MAY 2023 
BASELINE REPORT
INRM Madagascar Nosy Manga 
Baseline Report
Document Title: INRM Madagascar Nosy Manga Baseline Report
Date of Publication: May 2023 
Author: Kimberlee Chang, Mike Duthie, Alexa Aziz
Front cover photo: Seaweed Farmers, Aurélia Frédérich Andriambololoniainjanahary, 2022
This document was produced for review by the United States Agency for International Development. It was 
prepared with support from the Integrated Natural Resource Management Task Order 7200AA18D00020, 
under the Strengthening Tenure and Resource Rights II (STARR II) IDIQ.
The authors’ views expressed in this publication do not necessarily reflect the views of the United States 
Agency for International Development or the United States Government.
Integrated Natural Resource Management (INRM)
Sound management of natural resources is central to long-term development and resilience. Faced 
with an urgent need to reduce environmental degradation while improving human well-being, 
solutions that effectively integrate investments in natural resource management with economic and 
social development are increasingly urgent. INRM promotes integrated programming across 
environment and non-environment sectors and across the Program Cycle. INRM supports USAID 
to amplify program impacts, strengthen gender equality and social inclusion, and identify best 
practices for integration.
For more information: 
https://land-links.org/project/integrated-natural-resource-management-inrm-activity/
INRM Madagascar Nosy Manga Baseline Report ii
Contents 
Acronyms .............................................................................................viii
Executive Summary .............................................................................. 1
Introduction ................................................................................................................................................................. 1
Findings......................................................................................................................................................................... 1
Conclusions................................................................................................................................................................. 4
Introduction ........................................................................................... 5
Baseline Design and Methodology .................................................... 7
Objectives.................................................................................................................................................................... 7
Geographic focus........................................................................................................................................................ 7
Sampling design........................................................................................................................................................... 8
Sample size and power calculation.......................................................................................................................10
Survey content..........................................................................................................................................................10
Fieldwork.............................................................................................. 12
Training and pilotingTraining ................................................................................................................................. 12
Data collection..........................................................................................................................................................12
Results................................................................................................... 14
Demographics & Background Characteristics...................................................................................................14
Dwelling characteristics, Assets and Land ownership.....................................................................................20
Group membership..................................................................................................................................................22
Food security and resilience..................................................................................................................................24
Agriculture, Livestock and Land clearing practices..........................................................................................41
Fishing and gleaning practices................................................................................................................................45
Perception of FISHERY and Environmental change .........................................................................................54
INRM Madagascar Nosy Manga Baseline Report iii
Aquaculture practices .............................................................................................................................................59
Attitude towards aquaculture ...............................................................................................................................60
Marine resource management decision-making and participation ...............................................................63
Attitude towards NRM rules................................................................................................................................. 67
Learning Questions..................................................................................................................................................76
APPENDIX A: Nosy Manga baseline survey instrument 
summary................................................................................................ 82
APPENDIX B: Summary Statistics for Key Outcome Areas..... 85
APPENDIX C: Nosy Manga Full Baseline Survey Instrument . 100
INRM Madagascar Nosy Manga Baseline Report iv
Tables 
Table 1. Number of villages in planned study population in each region............................................................. 9
Table 2. Surveys completed by district.......................................................................................................................13
Table 3. Summary statistics of household demographics by region....................................................................15
Table 4. Gendered household type by region ..........................................................................................................16
Table 5. Summary statistics of HH education and literacy by region ................................................................. 16
Table 6. Percentage of school-aged boys and girls in school per village by region..........................................17
Table 7. Percentage of school-aged children in school per HH by region ........................................................18
Table 8. Ethnicity composition by region...................................................................................................................18
Table 9. Percentage of HHs with activity as one of thier top three livelihood sources, by region.............25
Table 10. Percentage of HHs with activity as one of their top three livelihood sources, by gendered 
household type................................................................................................................................................................. 27
Table 11. Percentage of HHs with activity as one of thier top three livelihood sources, by ethnic 
category..............................................................................................................................................................................29
Table 12. Average income by region, with outliers and excluding outliers (greater than three standard 
deviations from mean) of total sample. ......................................................................................................................30
Table 13. Average income by seaweed farming and non-seaweed farming households (Menabe only), as 
well as gendered household head types, excluding outliers of total sample.....................................................30
Table 14. Average income by region, with outliers and excluding outliers of total sample..........................31
Table 15. Logistical regression result of socio-demographic and livelihood characteristics on poverty 
(odds-ratio) .......................................................................................................................................................................37
Table 16. Logistic regression result of household characteristics regressed on Land cleared and Intent to 
clear land (odds-ratio) ....................................................................................................................................................43
Table 17. CPUE calculates under different definitions of units of effort............................................................50
Table 18. Within household gendered behavior and decision-making of seaweed farming ..........................60
Table 19. Community survey responses of village relation with LMMA, by region ........................................63
Table 20. Difference between non-seaweed farming households with positive view of aquaculture and 
negative view of aquaculture.........................................................................................................................................72
Table 21. Linear regression of HH characteristic on Perception of aquaculture and Support for 
aquaculture closures.......................................................................................................................................................74
Table 22 Coefficient of Seaweed farming on models each regressing seaweed farming on key Nosy 
Manga outcomes of interest, controlling for HH demographics..........................................................................77
Table 23. Seaweed farming prevalence in villages in Menabe, as well as community leader survey 
responses of village engagement with marine governance, conservation initiative, and existence of marine 
conflicts..............................................................................................................................................................................79
INRM Madagascar Nosy Manga Baseline Report v
Figures 
Figure 1. Map of Nosy Manga program areas (Source: USAID MIKAJY Factsheet, 2019) .............................. 8
Figure 2 Migration responses by region .....................................................................................................................20
Figure 3. Dwelling characteristics by region..............................................................................................................21
Figure 4. Pirogue materials of HHs that own at least one pirogue, by region..................................................22
Figure 5. Percentage of HHs that participate in each group, by region..............................................................23
Figure 6. Main livelihoods by region............................................................................................................................26
Figure 7. Percent of income from main livelihoods by region ..............................................................................33
Figure 8. Income diversification. Percentage of income from primary, secondary and tertiary livelihood 
sources, by region............................................................................................................................................................34
Figure 9. Percent of HH income from seaweed farming........................................................................................35
Figure 10. Percentage of HHs below the poverty line, by region........................................................................36
Figure 11. Coefficient plots of logistical regression result of socio-demographic and livelihood 
characteristics on poverty, by region (odds-ratio), 95% confidence interval....................................................38
Figure 12. Access to electricity, cooking fuel, and water by region....................................................................39
Figure 13. Household mobile money usage prevalence and scope by region...................................................40
Figure 14. Self-reported land clearing practices by region ....................................................................................42
Figure 15. Region for land clearing, by region ..........................................................................................................43
Figure 16 Coefficient plot of logistic regression result, of household characteristics regressed on Land 
clearing and Intent to clear land (odds-ratio). 95% confidence intervals...........................................................45
Figure 17. Fishery asset ownership and lending by region.....................................................................................46
Figure 18. Fishery asset lending, by region ................................................................................................................47
Figure 19. Fishing method by region ...........................................................................................................................48
Figure 20. Percentage of households that fishing HHs mainly catch in each fish species group, by region
..............................................................................................................................................................................................49
Figure 21. Fishing catch decision and use, by region...............................................................................................51
Figure 22. Fishing site tenure security ........................................................................................................................52
Figure 23. Fishing site conflicts by region .................................................................................................................53
Figure 24. Perception of CPUE change by region....................................................................................................55
Figure 25. Perception of environmental change by region ....................................................................................56
Figure 26. Perception of environmental degradation by region ...........................................................................58
Figure 27. Perceived threats to the environment....................................................................................................59
Figure 27: Attitude towards aquaculture ...................................................................................................................61
Figure 28. Reasons given for the positive and negative perception of aquaculture.........................................62
Figure 29. LMMA existence and participation rates, region..................................................................................64
Figure 30. NRM decision-making actors, by region................................................................................................. 65
Figure 31. Village governance by region.....................................................................................................................66
Figure 32. NRM monitoring activities by region ......................................................................................................67
Figure 33. Existence of NRM rules..............................................................................................................................68
Figure 34. General attitude towards NRM rules .....................................................................................................68
Figure 36. Preference for change in NRM rules.......................................................................................................70
INRM Madagascar Nosy Manga Baseline Report vi
Figure 37. Preference for NRM rules .........................................................................................................................71
Figure 38 Coefficient plot of regression on perception of aquaculture. 95% confidence interval...............75
INRM Madagascar Nosy Manga Baseline Report vii
Acronyms
ARSSI Ability to Recover from Shocks and Stresses Index
BV Blue Venture
COBA Community-Based Associations
CPUE Catch Per Unit of Effort
FIES Food Insecurity Experience Scale
HH Household 
INRM Integrated Natural Resource Management 
IP Implementing Partner
LMMA Locally Managed Marine Area
NRM Natural Resource Management
OF Ocean Farmers
USAID United States Agency for International Development
VOI Vondron'Olona Ifotony
VSLA Village Savings and Loan Association
WCS World Conservation Society
WWF World Wildlife Fund 
INRM Madagascar Nosy Manga Baseline Report viii
Executive Summary 
INTRODUCTION
The purpose of the USAID/Madagascar Nosy Manga Baseline Survey and Report is to provide the 
United States Agency for International Development (USAID), USAID/Madagascar, and Nosy Manga 
implementing partners (IPs) with baseline estimates across a range of social indicators, as well as 
background information on target communities to aid IPs in implementation and participant selection.
The Nosy Manga activity will focus on promoting sustainable seaweed and sea cucumber farming in the 
Menabe region and the MaMaBay seascape in the Sava region, including Makira protected areas, Masoala 
National Park, and Antongil Bay, with plans for expansion of the sea cucumber farms into Atsimo 
Andrefana and Anosy. 
USAID/Madagascar is conducting this baseline through a buy-in to the USAID Integrated Natural 
Resource Management (INRM) contract. The survey team includes INRM, two in-country consultants, 
and the in-country data collection firm, CAETIC. The survey team carried out community surveys and 
household surveys in all 16 villages across Sava and Menabe, identified by Nosy Manga IPs to roll out
sustainable seaweed and sea cucumber farming programs. The household surveys conducted are
representative of the targeted villages but are not necessarily representative of the regions. Following 
this baseline study, the survey team will also develop a simplified social monitoring tool to hand over to 
the IPs as they roll out in other villages in the future.
The surveys include standard modules on household (HH) demographics, livelihood sources, HH assets,
food security and resilience, savings and borrowing, and access to basic services. The surveys also
include fishery and gleaning modules on fishing practices at fishing sites, fishery assets, group
participation and governance, natural resource use, and participation and attitudes towards natural 
resource management (NRM) (See details in Annex A).
FINDINGS 
DEMOGRAPHICS 
The research team completed 312 household surveys across five villages in the Sava region, 262 surveys
in the Morondava district of Menabe across six villages, and 210 surveys in the Manja district of Menabe 
across five villages, supplemented by three community surveys in each village. The households in Menabe
are slightly larger than Sava by one-to-two people, are more likely to have more children over five years
old, and are more likely to have more youth and more females of reproductive age. About 58 percent of 
HHs in both regions are headed by a male household head with a female spouse, and 21 percent are
headed by a female household head alone with no spouse. Adults and household heads in the surveyed
HHs tend to be more educated and literate in Sava than Menabe, with no difference between genders.
Adults are 15 to 25 percent less likely to be literate in Menabe than in Sava.
INRM Madagascar Nosy Manga Baseline Report 1 
POVERTY AND FOOD SECURITY
Poverty and food insecurity are much more prevalent in the study villages in Menabe than 
in Sava. On average, HHs in Menabe earn 82 percent of what is earned in Sava. The average HH 
monthly income without outliers in Sava is 233,108 Ariary (USD 53), and that in Menabe is 199,019 
Ariary (USD 45). In Sava, only 12 percent of HHs fall under the USD 1.90 per day poverty line, whereas
in Menabe, 44 percent of the HHs do. In Sava, 76 percent of HHs experience little or no food insecurity,
compared to only 28 percent in Menabe. Electricity and water access is a huge issue, particularly in
Menabe, where only 27 percent of HHs have access to electricity and only 18 percent of HHs have
water available in their HHs. In Sava, the lack of access is less severe but also significant. About 60 
percent of HHs in Sava and 44 percent of HHs in Menabe have savings. More than half of HHs in both 
regions that have savings mention saving for emergency cash, for food, and for health problems. For the
HHs who do not currently have savings, 48 percent in Sava and 28 percent in Menabe would use the 
savings for emergency cash for health, while 36 percent in Sava and 52 percent in Menabe would use it
to send kids to school, and 24 percent in Sava and 33 percent in Menabe would use it to buy a pirogue1.
In Sava, building a business (31 percent) was also a commonly mentioned use for savings.
LIVELIHOOD ACTIVITIES 
Fishing accounts for a major source of livelihood across the regions for 57 percent of the 
population, with 65 percent of HH incomes coming from fishing. Nearly all fishing HHs (90 
percent) use part of their catch for food – on average about 19 percent of their catch. Around 12
percent of HHs undertake gleaning as a main source of livelihood. Gleaning is a type of fishing method 
that involved gathering and collecting catch in the shallow water or exposed land in marine areas. For 
these HHs, gleaning accounts for 55 percent of their HH income in Sava and 37 percent in Menabe.
Seaweed farming currently only exists in program villages in Menabe, where 17 percent of HHs in 
Menabe are involved in seaweed farming, but only 13 percent do so as one of their main livelihoods. The
HHs with seaweed farming as a main activity earn, on average, 27 percent of their HH income from 
seaweed farming (but three percent of HHs with seaweed farming as their primary activity earn 52 
percent of their HH income from it). 
FISHING
Most fishing households across the region indicate a decrease in catch over the last ten 
years due to increased fishing competition and climate change. However, the majority of HHs
(73 percent in Sava and 87 percent in Menabe) perceive still having enough fish in the sea to provide
enough food for everyone who lives in the community. The most common fishing method employed in
both regions is net fishing, with 75 percent of fishing HHs in Sava and 87 percent of fishing HHs in 
Menabe employing net fishing. When eliminating outliers in catch size (larger than three standard 
deviations above the mean), the average catcher per unit effort (CPUE) in Sava is 20kg per person-day
and the average CPUE in Menabe is 17kg per person-day.
1 A pirogue is a traditional fishing canoe typically mad out of wood.
INRM Madagascar Nosy Manga Baseline Report 2 
Most fishing HHs feel confident or very confident that they can continue to access their
primary fishing sites, with a smaller percentage feeling so in Sava than in Menabe (68 percent
compared to 83 percent). In Sava, 21 percent of fishing HHs report disputes accessing fishing sites,
whereas in Menabe, only four percent of fishing households reported disputes. In Sava, the disputes,
which were sometimes with groups in the villages and with NGOs, tend to be about fishing gear, area 
access rules, and rule compliance and enforcement. In Menabe, disputes are about not having sufficient
areas and amounts of fish, mostly among groups in the village. 
FISHERY MANAGEMENT
Locally Managed Marine Areas (LMMAs) govern the marine areas of all study villages in
Sava, and gear restrictions, temporary closures, mangrove closures, and permanent
closures are reported by 90 to 100 percent of HHs. In Menabe, LMMAs govern the marine areas 
for nine out of the 11 villages. The survey asked HHs about the presence of a variety of resource
management rules in communes and about attitudes towards these rules. About 80 to 85 percent of
HHs in Menabe report the presence of gear restrictions, temporary closures, and mangrove closures in
their commune, while 46 percent of HHs report having permanent closures. Sixty percent of HHs in
Sava and 50 percent in Menabe would like the number of rules regarding marine and mangrove use to
stay the same. More than 90 percent of HHs do not currently have aquaculture closures in their
communes, and 64 percent in Sava and 82 percent in Menabe indicate that they would not like to have 
such a rule.
PERCEPTION OF SEAWEED AND SEA CUCUMBER FARMING
Seventy-five percent of HHs in Sava and 92 percent of HHs in Menabe think that seaweed 
and sea cucumber farming are good for the village. Commonly mentioned positive aspects of 
aquaculture are jobs and income provision, with some mentioning opportunities, particularly for women.
HHs who think aquaculture is bad for the village see the curbing of fishing activities as the primary harm
brought by aquaculture. In both regions, the loss of fishing livelihoods was the most mentioned reason 
among respondents who view aquaculture negatively, mentioned by 92 percent of negative respondents 
in Menabe and 76 percent of respondents in Sava. In Sava, 64 percent of respondents that think
negatively of aquaculture also mention aquaculture bringing social conflict to the village regarding marine 
area use. HHs who participate in seaweed farming or who have aquaculture closures in their commune
tend to have more positive attitudes towards aquaculture, while HHs that are more dependent on 
fishing for household consumption tend to view it more negatively.
LAND CLEARING 
A substantial 57 percent of surveyed HHs in Sava and 14 percent in Menabe indicate that
they intend to clear land in the next 12 months, while only 15 percent of HHs in Sava and four 
percent in Menabe indicate that they have cleared land in the past year. In Sava, the majority (63 
percent) of HHs who cleared land did so in forested land, and 34 percent in fallow agricultural land. The
reasons given are mostly to grow more crops to sell (75 percent).
INRM Madagascar Nosy Manga Baseline Report 3 
CONCLUSIONS
The proportion of HHs under the poverty line, facing moderate-to-severe food insecurity 
and lacking basic access to HH electricity and water is substantially higher in study villages
in Menabe than in Sava. Further analysis at lower administrative levels, coupled with community 
leader responses, can be used to provide a clearer picture of the concentration of poverty, public 
service access, and profiles of most vulnerable HHs within regions.
Land clearing and the intention of land clearing, mostly in forested land, widely exists in
Sava, motivated mainly by commercial agriculture. The practice and intention also exist in
Menabe, but they are less frequent.
Overall, in both regions, NGOs are mentioned as the most prominent actors in marine
management. LMMAs are more prevalent in Sava, but marine resource decision-making seems to be 
more decentralized to involve local leaders at the village, fokontany, and commune level in Menabe than 
in Sava. However, group decisions other than natural resource use, such as decisions on village social life
or government assistance/ material resource distribution, seem to be more decentralized at the village￾level in Sava than in Menabe.
There may be obstacles obtaining local buy-in on the Nosy Manga program in certain
areas, especially in Sava. The survey results indicate that a quarter of HHs in Sava view aquaculture 
negatively (compared to only eight percent in Menabe) and may be unwilling to engage with aquaculture 
programs. The HH surveys indicate that these HHs perceive aquaculture as in competition with 
fishing livelihoods, particularly for household consumption, which can create conflict on
marine use. The potential for aquaculture sites to be on their sacred land is another major reason of 
opposition to aquaculture gathered from qualitative data. 
Nuanced findings indicate the need to develop context-specific strategies for participant
recruitment and negotiation of marine sites for aquaculture and rules regarding site access 
for fishing. More detailed village-level and fishing site-level analysis can be used to identify whether
these sentiments and disputes are concentrated in particular fishing sites and villages to tailor localized 
approaches. 
On a more positive note, HHs who currently participate in seaweed farming and those who
currently have aquaculture closures in their community tend to view aquaculture more
positively, implying that the hurdle may exist largely in initial access.
Currently, only two percent of HHs overall connect aquaculture activities to marine and
fish population protection, mostly viewing it as an economic opportunity not connected to
or opposing fishing. However, there is local demand for conservation efforts, and there exists a 
perception of ecological degradation and threat among 50 to 60 percent of the population, attributing 
the threat mainly to climate change and some unsustainable fishing. There exists potential to use 
qualitative understanding of how local populations connect their environmental perception, demand for 
NRM rules, and HH economic motivations to fishing, to better align and frame the benefits of the Nosy
Manga program with the local population's motivations. 
INRM Madagascar Nosy Manga Baseline Report 4 
Introduction
Madagascar is one of the world’s highest-priority countries for biodiversity conservation.2 Madagascar 
has more than 5,000km of coastline with more than 250 islands, some of the world’s largest coral reef 
systems, and some of the most extensive mangrove areas in the western Indian Ocean.3 The richness of
Madagascar’s marine ecosystems is of invaluable importance to the country, sustaining much of its food 
stocks and livelihood resources.
However, increasing ocean temperatures brought on by climate change present a number of threats to 
Madagascar’s already-fragile marine environments. Some of these threats include the migration of marine 
organisms to more favorable temperatures, acidification, and bleaching of coral reefs. The effects of 
rising ocean temperatures are significantly exacerbated under stressors associated with overfishing,
coastal development, sedimentation, and pollution.4 A projected increase in the frequency and severity 
of extreme weather events, such as cyclones, are also of notable concern to cause further damage to 
coastal environments – especially reef surfaces.
Meanwhile, poverty rates in Madagascar are reaching new levels of severity, with an estimated 1.62 
million Malagasy facing acute food insecurity in 2022.5 Extreme poverty poses a significant challenge to 
Madagascar’s development, while high birth rates and unsustainable resource management worsens 
existing pressures on natural resources, resulting in resource overexploitation. The Malagasy population 
is particularly dependent on marine ecosystems, with approximately 50 percent of Malagasy residing 
near the coast and relying on coastal ecosystems as a source of food and livelihood.6 Madagascar’s 
population is at risk of becoming poorer as natural resource stocks are further depleted, prompting a 
significant need for sustainable agriculture to support at-risk communities.
The USAID/Madagascar Mission is supporting the Nosy Manga activity to help address the above issues, 
operating under the Health, Ecosystems and Agriculture for Resilient, Thriving Societies (HEARTH) 
program, within the Sustainable Environment and Economic Development (SEED) Office. Nosy Manga is
a five-year activity that will invest in sustainable aquaculture of seaweed and sea cucumber, targeting
both biophysical and livelihood outcomes. The activity includes an alliance of two aquaculture 
companies: Ocean Farmers (OF) and Indian Ocean Trepang, their international conservation NGO 
partners (including the World Conservation Society [WCS], Blue Venture [BV], and World Wildlife
Fund [WWF]), and the LMMA national network. Nosy Manga will scale up a business model that 
combines industrial and community-based farming, which was previously developed in the Atsimo￾Andrefana region to new landscapes in Mamabay and Menabe. The activity anticipates biophysical
2 Ecosystem Profile: Madagascar and Indian Ocean Islands. Final Version, December 2014.
3 Treasure Island: New biodiversity on Madagascar (1999 - 2010) 
4 Impacts of Climate Change on Coral Reefs and the Marine Environment | United Nations
5 Madagascar Overview: Development news, research, data | World Bank
6 Factsheet – An overview of the WCS Madagascar Marine Program 
INRM Madagascar Nosy Manga Baseline Report 5 
impacts related to climate change and habitat protection, in addition to livelihood improvements for 
Malagasy communities within and around the program’s geographical operating areas.
Nosy Manga
Nosy Manga is a five-year activity that will invest in sustainable aquaculture of seaweed and sea 
cucumber, targeting both biophysical and livelihood outcomes. The activity includes an alliance of two
aquaculture companies: Ocean Farmers (OF) and Indian Ocean Trepang, their international conservation 
NGO partners (including WCS, BV, and WWF), and the LMMA national network. Nosy Manga will scale
up a business model that combines industrial and community-based farming, which was previously 
developed in the Atsimo-Andrefana region to new landscapes in Mamabay and Menabe. The main 
Strategic Approach includes the following: 
• SA #1: Strengthening and expanding sustainable industrial sea cucumber enterprises;
• SA #2: Expansion and strengthening of sea cucumber and seaweed community-based farming as
sustainable alternative livelihoods;
• SA #3: Empowerment and engagement of civil society and communities for local governance
and management of areas surrounding community farms; and
• SA #4: Enhance research and information available for sustainable aquaculture practices.
The supporting Strategic Approach includes the following: 
• SA #5: Improved harmonization, coordination, and access to information and data for decision￾making;
• SA #6: Strengthened national governance and legal framework for sustainable aquaculture; and
• SA #7: Provide supporting services (health care, education, mobile money) for communities for
greater buy-in for sustainable aquaculture enterprises.
The activity anticipates biophysical impacts related to climate change, in addition to livelihood 
improvements for Malagasy communities within and around the program’s geographical operating areas. 
The primary goals for Nosy Manga under HEARTH are to: 
1. Reduce the pressure on coastal and marine resources through a sustainable market-based
aquaculture model that is scaled up with the coastal communities;
2. Alleviate poverty of targeted coastal communities through new income-generating
opportunities; and
3. Support the community-based sustainable management of marine resources in targeted areas.
INRM Madagascar Nosy Manga Baseline Report 6 
Baseline Design and 
Methodology
OBJECTIVES 
The USAID/Madagascar Nosy Manga baseline survey was designed to provide baseline measurements 
for activity indicators, and to provide baseline information on communities’ well-being, fishing practices, 
and marine area use and management that will inform activity implementation surrounding each SA 
outlined above. The Nosy Manga baseline social survey may be followed by midline and endline surveys,
at the discretion of USAID/Madagascar and OF. 
OF will begin participant selection only after program start-up and on a rolling basis each year.
Therefore, INRM, along with OF and USAID, decided to conduct the baseline survey with a random 
sample of households in each targeted village (since activity participants had not yet been identified).
This survey provides important context about the community, supplemented through surveys with 
community leaders, and information to inform Nosy Manga targeting and implementation. INRM will
create a condensed version of the surveys to serve as a monitoring tool for OF as they roll out the 
program in other locations, which can be used with project beneficiaries as they are identified.
GEOGRAPHIC FOCUS
The geographic focus on the Nosy Manga baseline survey data collection covers the Menabe region on
the west coast, and MaMaBay in the Sava region of the east coast of Madagascar. The whole activity will
focus on promoting sustainable seaweed and sea cucumber farming in the Menabe and MaMaBay 
seascapes, including the Makira protected areas, Masoala National Park, and Antongil Bay, with plans for
expansion of sea cucumber farms in other villages. The baseline survey will only cover Menabe and Sava 
since target villages have not yet been identified in the Atsimo Andrefana and Anosy regions. INRM will 
develop a simplified social monitoring tool to hand over to OF for use in their roll-out in those regions 
in the future. Figure 1 shows the two focus seascapes that encompass critical coastal zones, including 
southern regions of Madagascar most affected by prolonged drought and food insecurity,7 as well as
high-priority conservation areas for marine biodiversity in the northeast. Table 1 lists the region,
districts, and commune names of the study villages.
7 Drought in Madagascar (nasa.gov)
INRM Madagascar Nosy Manga Baseline Report 7 
Figure 1: Map of Nosy Manga program areas (Source: USAID MIKAJY Factsheet, 2019)
SAMPLING DESIGN 
The Nosy Baseline survey was conducted among a representative, random sample of the entire 
population of HHs of each study village in the Menabe and Sava regions where Nosy Manga activities will 
take place, amounting to 16 villages in total.8 The survey team conducted a HH listing of each village, 
from which the study team intended to randomly select 50 households in each village (the first 42 are 
sampled households with the remaining eight as replacements). The team chose to not sample through 
the official government listing of HHs due to concerns of excluding minority ethnic groups. OF 
experience suggests that the official listings often exclude certain disadvantaged groups that OF views as 
part of the village and would like to target as potential program participants and indirect beneficiaries. 
As Table 1 shows, the total study population includes six villages in the Sava region, Antalaha district, 
and 11 villages in the Menabe region, Morondava, and Manja districts.
8 This number of villages and associated Fokontany is slightly different than the information listed in the inception report. 
During fieldwork, upon clarification with local authorities as well as local NGO partners, we found that there was one duplicate 
village in the original list of villages. There were also some villages that were listed under the incorrect Fokontany. This revised 
list reflects the corrected information of the study villages after ground-truthing. 
INRM Madagascar Nosy Manga Baseline Report 8 
Table 1: Number of villages in planned study population in each region
Region District Commune Fokontany Number of 
program villages
Number of 
completed 
surveys per
village
SAVA Antalaha
Vinanivao Anovandrano 1 54
Vinanivao Vinanivao 2 18; 78
Vinanivao Beankora 1 0 
Vinanivao Masoala 2 90
MENABE 
Morondava
Belo sur mer Belo sur Mer 3 42; 42; 42
Belo sur mer Marovitike 1 39
Bemanonga Lovobe 1 55
Belo sur mer Ankilifolo 1 42
Manja
Andranopasy Ankoba 2 47; 32
Andranopasy Andranompasy I 1 42; 47
Andranopasy Andranompasy II 2 42
During fieldwork, the field teams were unable to access two villages in Commune Vinanivao due to 
refusal of the local population to partake in the study (See section Fieldwork for more detail). The study 
team adjusted their sampling strategy accordingly to preserve the sample size of 294 HHs in Sava and 
462 HHs in Menabe to reach a total sample size of around 750 HHs overall. The research team also had 
limited information on the size of the program villages prior to fieldwork. During HH listing, CAETIC 
found that certain villages had less than the target number of HHs to be sampled. In these cases, 
CAETIC attempted to survey the whole village. Where the target number was not met, CAETIC added 
the remaining surveys to the target sample number of a nearby larger village. In the analysis, the 
research team applied sampling weights at the village level accordingly, so the statistics reflect the 
general population of study villages per region adjusted for the different proportion of populations 
sampled in each village. 
For the community survey, CAETIC field teams were instructed to survey the authority most 
knowledgeable about local marine governance to complete the long community survey. In most villages, 
this person is the local Vondron'Olona Ifotony (VOI, or COBA, meaning community-based associations) 
or fishery group president. The CAETIC field teams were then instructed to identify two leaders of 
different local ethnic groups to complete the short community leader survey.
INRM Madagascar Nosy Manga Baseline Report 9 
SAMPLE SIZE AND POWER CALCULATION 
The aim of the Nosy Manga baseline survey is to produce estimates of indicators, including their
standard errors and confidence intervals, and to enable a statistical test of differences to detect changes 
in indicators over time. Power calculations based on relevant outcome indicators are presented below,
based on a target sample size of 750 HHs. 
For the power calculations, the team used total HH daily expenditure (in USD) as a rough proxy for 
income from seaweed and sea cucumber (as discussed). OF provided a rough estimate, based on an 
expected 20 percent increase in income over the life of the activity. Thus, the INRM team estimated the 
power of the sample to detect a 10 percentage point (pp), 15pp, and 20pp anticipated change in daily
HH expenditures with an alpha level of 0.95. Using data of HH expenditure in coastal regions of 
Madagascar as a proxy,
9 mean baseline expenditure is assumed to be 1.63 with a standard deviation of 
1.80.
The study team estimated the power of the sample of 750 HHs per wave to detect anticipated changes 
with a two-sided test, using the “sampsi” command in Stata. The team also assumed that 15 percent of 
the variance will be explained by other predictors. With these assumptions, the estimates of the power
to detect a 20pp, 15pp, and 10pp change are 94 percent, 75 percent and 42 percent, respectively, where
the standard acceptable statistical power level is 80 percent. This result means that the sample size has
enough power to detect a change in outcome of less than a 20pp, consistent with OF expectations. 
SURVEY CONTENT
INRM developed six major documents associated with the survey: (1) the long community survey 
instrument, (2) the short community survey instrument, (3) the HH survey instrument, (4) the 
Interviewer’s Manual, (5) the Supervisor’s Manual, and (6) the Field Staff Training Manual. A short 
version of the surveys will also be developed for OF to serve as a monitoring tool as they expand to 
more program areas. 
The survey instruments were developed based on existing, validated tools wherever possible, including 
the USAID HEARTH Global Monitoring Toolkit.10 Many of the modules are also adapted from BV’s
social baseline survey tool, which they shared with the study team. BV uses these tools in coastal villages
in the MaMaBay landscape, including questions related to HH wealth indicators, fishery assets, gendered 
livelihood practices and relevant local associations, natural resource use and NRM attitudes. The study
team also included standard Poverty Probability Index (PPI), food security, and resilience indicators that 
are comparable to the TSIRO Alliance HEARTH activity in Madagascar, drawing from the HEARTH
monitoring toolkit and FTF indicators. 
9 We used the 2015 Baseline Study of Food for Peace Development Food Assistance Projects in Madagascar to obtain this 
statistic. We only use the coastal regions for the mean and standard deviation assumptions of the power calculation. However, 
these estimates are more than five years old and are not direct estimates from the Nosy Manga implementation area.
10 Source: https://www.climatelinks.org/sites/default/files/asset/document/2022-
07/USAID%20HEARTH%20Monitoring%20and%20Evaluation%20Toolkit%202022-4.pdf
INRM Madagascar Nosy Manga Baseline Report 10
The Nosy Manga Baseline Survey Instrument includes the following survey modules. (Please see 
Appendix A for a detailed list of information captured under each module, and Appendix C for the full 
survey modules.) 
Long and Short Community Leader Survey:
• Module 1: Respondent details (In short survey)
• Module 2: Village infrastructure
• Module 3: Village livelihoods and marine access rights (in short survey)
• Module 4: Governance of marine areas:
• Module 5: Local conservation initiatives:
• Module 6: Perception of natural resource management (in short survey)
• Module 7: Ethnic Relations (in short survey)
Household Survey: 
• Module 1: Respondent details
• Module 2: HH Roster
• Module 3: HH assets
• Module 4: Livelihood
• Module 5: Fishery
• Module 6: Gleaning
• Module 7: Seaweed and sea cucumber farming
• Module 8: Savings, lending, and borrowing
• Module 9: Food security and coping strategies
• Module 10: Participation in groups and associations
• Module 11: Participation and attitudes towards resource management
• Module 12: Energy use, mangrove use, and land clearing
INRM Madagascar Nosy Manga Baseline Report 11
Fieldwork 
TRAINING AND PILOTING 
CAETIC hosted a six-day training workshop between October 10 –15, 2022 at its training center in 
Ambatolampy Tsimahafotsy, followed by a pilot in the coastal district Vatomandry, a day trip away from 
Antananarivo. The training consisted of four supervisors and 23 enumerator trainees, of which 16 were 
selected for the pilot, and 12 were selected from the fieldwork based on their familiarity with the survey 
post training, and performance at the pilot. The training, conducted with guidance and oversight from 
INRM remotely as well as the INRM’s in-country Aquaculture Expert (Mamy Andriantsoa) and Data 
Quality Specialist (Aurélia Frédérich Andriambololoniainjanahary) covered the following material: 
introduction to the survey, conducting the interview, questionnaire content, fieldwork procedures,
entering and managing data on the tablet, and completing survey modules. One day of training was 
dedicated also to household listing procedures. Hands-on training and practice sessions covered the use
of all technical equipment required for survey implementation, including tablet computers with
applications for data entry. 
At the conclusion of training, pilot surveys were carried out for both the HH and community surveys in
the coastal district Vatomandry in Fokontany Maintinandry, a day trip away from Antananarivo. The area 
purported to have similar characteristics to the Nosy Manga baseline survey population, with a large 
population reliant on fisheries for their livelihoods.
The pilot survey took place from October 18th –22nd, 2022 for 27 individuals, including: 16
enumerators, four field supervisors, two CAETIC staff, including the field manager, as well as the INRM
Aquaculture Expert and Data Quality Specialist. A total of 80 HH pilot surveys and four community 
leader long surveys were completed. The team also piloted HHs listing, accompaniments, co￾enumeration, and back-checks. The team refined the survey questions and translations according to 
feedback from the pilot. 
DATA COLLECTION 
Four field teams of enumerators and field supervisors as well as CAETIC management were deployed to
the field from October 26th – December 2nd, 2022, for a total of 36 days of field work. The timing was 
decided based on considerations of OF’s rollout timeline in Q1 2023, as well as travel conditions, as
influenced by the rainy season. Upon arrival in each commune, CAETIC conducted courtesy visits with
each mayor before beginning interviews in the selected fokontany. Representatives from the local office
of OF and local NGOs in each region were also contacted at the beginning of fieldwork to ensure that 
they were aware of the expected dates of data collection in each commune, and to assist with the 
introduction and access to villages as needed. The INRM Data Quality Specialist also conducted 
supervisory visits to each of the field teams and carried out additional back-check surveys in the first
three weeks of field collection.
INRM Madagascar Nosy Manga Baseline Report 12
Upon arrival at each fokontany, CAETIC conducted a courtesy visit to the local chief to explain the 
purpose of the survey. This was also an opportunity to inquire about information related to the survey, 
such as the name of hamlets in the fokontany, lodging for field teams, and any local considerations to 
keep in mind. The support given by the local authorities (fokontany chiefs, elders, and those responsible
for local security) was essential to identifying the correct respondents listed in the sample. Based on
information received from these visits, CAETIC was able to correct the location of two villages in Sava 
and identify a duplicate.
Table 2: Surveys completed by district
Region District
Villages 
listed and 
surveyed
# Survey 
attempts
# Surveys 
completed
# of 
surveys 
targeted
% of 
target 
achieved
# refusals/ 
non￾response
Sava Antalaha 5 out of 6* 574 312 294 106 30
Menabe
Morondava 6 out of 6 333 262 252 104 29
Manja 5 out of 5 229 210 210 100 7 
Total 1136 784 756 104 66
*HHs in two villages refused to be surveyed, but one village of the two was listed.
HH listings as well as community and HH interviews were carried out using tablets and SurveyCTO. 
Across the three districts included in the survey, a total of 784 interviews were fully completed out of 
the 756 targeted. There were no incomplete surveys. In a couple of cases, the field teams followed up 
with the same HHs that were unable to complete the survey on another day to complete it. In many 
villages, the field team intentionally scheduled and re-visited the HHs according to village event and 
farming activity schedules. The 66 HHs that declined to participate or were unable to be located were 
replaced using the replacement HH list in the random sample for each village. In all villages where HH
listing was completed (all except one), one long community leader survey and two short community 
leader surveys were completed. 
Two villages in Antalaha refused the field team entry due to negative perceptions of existing aquaculture 
projects reducing fishing areas, as well as rumors of the Nosy Manga project. With the negotiation of 
the local VOI president and WCS representative, the field team were ultimately able to complete the 
HH listing for one of the two villages and surveyed 18 non-randomly selected HHs identified by the VOI 
to be supportive of aquaculture thus willing to be surveyed by the field team. These Hhs are excluded 
from this analysis due to their non-random selection. This resulted in 312 surveys completed in Antalaha 
district, more than the targeted 294. The 10 extra surveys in Morondava district were in a village where 
local OF technician indicated the possibility of extending the intervention zone into two hamlets instead 
of one. Thus, INRM decided to expand the sample size in this area to randomly sample both hamlets. 
The full sample in this village is included in the analysis. 
INRM Madagascar Nosy Manga Baseline Report 13
Throughout data collection, field supervisors performed quality control in the form of accompaniment, 
co-enumeration, and back-checks. A total of 72 of the surveys received an accompaniment, while 30
HHs were co-enumerated by the interviewer and supervisor, and 79 of the surveyed HHs were 
contacted for a short back-check survey to verify key responses. Each team organized a daily debriefing 
to discuss the work progress, to review any challenges faced, clarify questions related to the survey 
protocol, and solve any problems encountered.
Results 
The Nosy Manga baseline survey findings are organized into the following categories: 1)demographics 
and background characteristics; 2) dwelling characteristics, assets, and land ownership; 3) food security 
and resilience; 4) livelihoods, access to basic services and savings and borrowing behavior; 5) group 
membership; 6) agriculture, livestock, and land clearing practices; fishery and gleaning practices 7)
perception of fishery and environmental change; 8) aquaculture practices and attitudes towards 
aquaculture; 9) marine resource management decision-making and participation; and 10) attitudes 
towards NRM rules. 
The study team focuses on the result from the HH surveys and presents inferences made regarding the
population of study villages at the regional level. In each of the subsections, the team presents results
from key HH-level indicators as well as statistical tests of differences across the region and other 
relevant disaggregation, such as gender and ethnic categories. Appendix B contains additional tables with 
summary statistics of indicators described for key outcome areas. To account for the different
proportions of populations sampled in each village, the team applied village-level sample weights, so the 
statistics are representative of the study areas at each regional level. 
DEMOGRAPHICS & BACKGROUND CHARACTERISTICS
HOUSEHOLD SIZE AND COMPOSITION 
Table 3 presents the summary statistics on size and composition of the HHs. Across the regions, the 
average HH has between four to five members, with HHs in Menabe having about one to two more 
members than Sava. The mean number of adults (HH members over 18 years of age) per household is
2.14, with roughly equal number of adult females and adult males. There is about one female of 
reproductive age (female HH members between age 15 and 49) and one youth (HH members between
15 and 29) in each HH. The mean number of children over five years of age is 1.156 and the mean 
number of children under five years of age is 0.71 per HH. The HHs in Menabe are slightly larger than 
Sava, with a mean of 4.61 compared to 3.44. An average HH in Menabe have more female adults (1.12
compared to 0.92), more females of reproductive age (0.95 compared to 0.74), more youth (1.08 
compared to 0.74) and more children over five years of age (1.70 compared to 0.89).
INRM Madagascar Nosy Manga Baseline Report 14
Table 3: Summary statistics of household demographics by region
All Sava Menabe
N Mean 
(SD) N Mean 
(SD) N Mean 
(SD) Diff. p-val
Household size 764 4.40
(2.80) 294 3.44
(1.67) 470 4.61
(2.95) -1.17 0.0
Number of adults (>18) 764 2.14
(1.28) 294 1.83
(0.65) 470 2.21
(1.37) -0.38 0.0
Number of adult males (>18) 764 1.06
(1.03) 294 0.91
(0.50) 470 1.09
(1.11) -0.18 0.1
Number of adult females (>18) 764 1.08
(0.64) 294 0.92
(0.51) 470 1.12
(0.66) -0.20 0 
Number of females of 
reproductive age (15-49) 764 0.91
(0.81) 294 0.74
(0.61) 470 0.95
(0.84) -0.21 0.01
Number of youth (15-29) 764 1.02
(1.10) 294 0.74
(0.76) 470 1.08
(1.15) -0.34 0.00
Number of children over five 
years of age 764 1.56
(1.77) 294 0.89
(1.13) 470 1.70
(1.85) -0.81 0.00
Number of children under five 
years of age 764 0.71
(0.81) 294 0.72
(0.76) 470 0.70
(0.81) 0.02 0.78
GENDERED HOUSEHOLD TYPE 
Table 4 presents the percentage of households that fall within each gendered household type across the 
regions. Across the regions, 58 percent of the households are headed by a married male adult, 21 
percent are headed by a single male adult, and an equal 21 percent are headed by a single female adult. 
There were no statistically significant differences in HH head type across the regions.
INRM Madagascar Nosy Manga Baseline Report 15
Table 4: Gendered household type by region
All Sava Menabe
N Percentage N Percentage N Percentage Diff. p-val
Female HHH, 
no spouse
764.00 20.78 294.00 18.58 470.00 21.26 -0.03 0.54
Male HHH, no 
spouse
764.00 20.99 294.00 17.18 470.00 21.81 -0.05 0.27
Male HHH, w/ 
spouse
764 58.23 294 64.25 470 56.92 0.07 0.15
EDUCATION, LITERACY, AND CHILDREN’S SCHOOL ATTENDANCE
Table 5 reports the education and literacy of the HH heads across regions. There are no statistically 
significant differences between the education level of female and male HH heads overall and within 
regions; thus, those statistics are not reported. However, across the regions, male HH head and male 
adult education is lower in Menabe than in Sava. An average male HH head in Sava has completed 
primary school education and 79 percent are literate, whereas an average male HH head in Menabe has 
an education level of between preschool completion and primary school completion, with only 53 
percent being literate. An average female HH head across regions is between preschool completion and 
primary school completion, with about 64 percent being literate.
When looking at all adults in the population, both the average male adult and female adult have a higher 
education in Sava than Menabe. In Sava, an average female has an education of between preschool 
completion primary school completion with 75 percent being literate. In Menabe, the average female 
also has an education of between preschool completion and primary school completion but with more 
females only completing preschool, and with only 52 percent of adult females being literate. Similarly for 
male adults, in Sava, an average male adult has an education of between primary school completion and 
secondary school first cycle completion with 79 percent being literate. In Menabe, the average male also 
has an education of between preschool completion primary school completion like female adults in 
Menabe, and with only 53 percent of adult females being literate. 
Table 5: Summary statistics of HH education and literacy by region
Sava Menabe
N Mean N Mean p-val.
HHH education (All) 293.00 2.04 457.00 1.59 0.00
HHH education (Female) 47.00 1.81 59.00 1.80 0.98
HHH education (Male) 246.00 2.09 398.00 1.53 0.00
INRM Madagascar Nosy Manga Baseline Report 16
INRM Madagascar Nosy Manga Baseline Report 17
Sava Menabe
N Mean N Mean p-val.
HHH literacy (All) 294.00 0.79 468.00 0.55 0.00
HHH literacy (Female) 47.00 0.77 59.00 0.62 0.16
HHH literacy (Male) 247.00 0.79 409.00 0.53 0.00
Average female adult education 231.00 1.90 344.00 1.48 0.00
Average male adult education 252.00 2.13 406.00 1.62 0.00
Average female adult literacy 231.00 0.75 351.00 0.52 0.00
Average male adult literacy 253.00 0.79 416.00 0.53 0.00
Tables 6 and 7 report school attendance of school-aged children (between five and 18 years old) across 
gender at the village and household levels. An average study village contains about 34 girls and 38 boys. 
School attendance is more prevalent in Sava (66 percent of the villages’ school aged children attend 
school) compared to Menabe (only 43 percent). The team found no statistically significant difference in 
school attendance between boys and girls. 
The reasons given by respondents for lack of school attendance include access (distance to school and 
money for tuition), provision (no teachers in schools), children wanting or needing to work, children 
being sick, and marriage or pregnancy for girls. In Sava, the most mentioned reason for non-attendance 
was lack of money for tuition. In Menabe, the most frequently mentioned reason was distance to school. 
Having no money for tuition and no teachers in schools were also prevalent reasons mentioned. 
Table 6: Percentage of school-aged boys and girls in school per village by region
All Sava Menabe
N Percentage N Percentage N Percentage Diff.
Percentage of village 
school-aged boys in school 15 47.07 7 66.23 11 42.93 23.30
Percentage of village 
school-aged girls in school 15 50.83 7 70.29 11 46.63 23.66
Percentage of village 
school-aged children in the 
village in school
15 49.46 7 68.59 11 45.32 23.27
Table 7: Percentage of school-aged children in school per HH by region
# of HHs 
with 
children
Percent of girls 
in school
Percent of 
boys in school p-val.
Percentage of HH school-aged 
children in school (All) 199.00 34.21 45.86 0.07
Percentage of HH School-aged 
children in school (Sava) 44.00 65.90 73.80 0.25
Percentage of HH School-aged 
children in school (Menabe) 155.00 30.95 42.99 0.09
ETHNICITY 
Table 8 presents the respondent ethnicity breakdown across the two regions. The ethnic composition 
of each region is widely different. A total of 84.4 percent of HHs in Sava are Betsimisaraka, whereas 
Antaimoro, Merina, and Betsileo mainly compose the other minority groups. In Menabe, Vezo compose 
the majority (70.6 percent) of HHs, with Sakalava being the second largest group (24.9 percent), with 
Betsileo, Mahafaly, and Antandroy mainly composing the other minority groups. For subsequent analysis
of ethnic group comparisons, the team created five categories of Betsimisaraka, Sava minority groups, 
Vezo, Sakalava and other Menabe minority groups. 
Table 8: Ethnicity composition by region
Region
Ethnicity Sava
(percentage)
Menabe
(percentage)
Total
(percentage)
Bara 0.0 0.2 0.1
Mahafaly 0.0 0.9 0.5
Antandroy 0.3 0.9 0.7
Vezo 0.7 70.6 43.7
Sihanaka 0.3 0.2 0.3
Sakalava 0.0 24.9 15.3
Antaifasy 0.7 0.0 0.3
Antambahoaka 0.7 0.0 0.3
Antaimoro 4.8 0.0 1.8
INRM Madagascar Nosy Manga Baseline Report 18
INRM Madagascar Nosy Manga Baseline Report 19
Region
Ethnicity Sava
(percentage)
Menabe
(percentage)
Total
(percentage)
Antanosy 0.7 0.4 0.5
Betsimisaraka 84.4 0.0 32.5
Merina 2.4 0.4 1.2
Tsimihety 1.0 0.0 0.4
Tanala 0.0 0.2 0.1
Betsileo 2.7 1.3 1.8
Foreigner 0.7 0.0 0.3
Other 0.7 0.0 0.3
Total 100.0 100.0 100.0
N 294 470 764
Pearson chi2(16)= 724.833
p-value= 0.000
MIGRATION 
Figure 2 presents the percentage of HHs in which the respondent was born in the village, as well as 
reasons for migration, if they are not native to the village. The team assumes that the migration status of 
the respondent reflects that of the HH. Across the regions, about 54 percent of HHs are native to the 
village, with no significant differences across regions. Out of the non-native HHs, 73.5 percent migrated 
for economic reasons across the regions. In Menabe, 15.4 percent of HHs migrated because of conflict, 
whereas only 2.6 percent in Sava migrated because of conflict. In Sava, 17 percent of HHs migrated 
because of marriage, whereas only 6.2 percent in Menabe migrated for marriage. Very few HHs across 
the regions (zero to one percent) attribute climate change as their reason for migration. 
Figure 2: Migration responses by region
DWELLING CHARACTERISTICS, ASSETS AND LAND 
OWNERSHIP
DWELLING CHARACTERISTICS
Figure 3 describes the dwelling characteristics across regions. The main wall materials are similar across 
the regions, with 62 percent of households using cement and 31 percent using thatch/palm/leaves. The 
main material of the roof is also similar across regions, with 72 percent of HHs using thatch/palm/leaves 
and 27 using sheet metal. The main material of the floor differs substantially between regions. In Sava, 30 
percent of HHs use wooden boards and 30 percent use palm/bamboo/tree trunks. In Menabe, 54 
percent of HHs use woven mats, and 11 percent have bare ground. 
0
10
20
30
40
50
60
70
80
90
Raised in village since
childhood
Migration reason -
Economic
Migration reason -
Marriage
Migration reason -
Conflict
Migration reason -
Other
Migration
Total Sava Menabe
INRM Madagascar Nosy Manga Baseline Report 20
Figure 3: Dwelling characteristics by region
HOUSEHOLD TRANSPORTATION ASSETS
In both regions, 99 percent of HHs do not own any land-based motorized vehicles, including 
motorcycles/scooters, tractors, and cars. Only 1.4 percent of HHs own a bicycle. However, the majority 
of HHs in both regions (69 percent in Sava and 83 percent in Menabe) own at least one pirogue. HHs 
own on average 0.8 pirogues in Sava and 1.1 pirogues in Menabe. 
Figure 4 presents characteristics of the pirogues that HHs own in the sample. All of the pirogues that 
the sampled HHs own are wood. While the majority have no motor, five percent of pirogues in Sava 
and one percent in Menabe have a motor. The average carrying capacity of the pirogue is four people, 
but ranges from one person to 30 people. The average age of the pirogues is two years old in Sava and 
0%
10%
20%
30%
40%
50%
60%
70%
80%
Metal
Cement
Vondro/Ravina/ Palme/Zozoro/ Falafa
Wood
Other
Metal
Vondro/Ravina/ Bozaka
Other
Ciment
Planche
Palme/ Bambou/ Rapaka
Ground
Woven mat
Other
Main material of the walls Main material of the
roof
Main material of the floor
Dwelling Characteristics
All Sava Menabe
INRM Madagascar Nosy Manga Baseline Report 21
one year on in Menabe, ranging from zero to ten years. A total of 64 percent of the pirogues in 
Menabe have a sail, compared to 19 percent in Sava. 
Figure 4: Pirogue materials of HHs that own at least one pirogue, by region
LAND OWNERSHIP
Most (85 percent) of the HHs in both regions own their house, and 68 percent of HHs in Sava and 84 
percent of HHs in Menabe own the land on which the HHs live. Of the HHs that own their land, 45.2 
percent are not recognized by the state (formal land title deed from the office of Service Foncier 
Domanial et Topographique) nor by the head of the fokontany (customary recognition). In Sava, 11 
percent are recognized by both the state and fokontany, 21 percent recognized only by the state and 25 
percent only recognized by the fokontany. In Menabe, 45.5 percent of the land ownership is recognized 
by the state only, nine percent by the fokontany only, and none are reported to be recognized by both. 
Independent of house ownership, 51 percent of HHs across the region own land elsewhere for building 
a house.
GROUP MEMBERSHIP
Respondents were asked whether eight types of groups or associations existed in their community. 
Figure 5 shows the percentage of HHs in each region that indicated that the group type exists in their 
community, and Figure 3 shows the percentage of HHs of only the villages where at least one HH 
indicated that the group type exists in each region, that also have at least one HH member who 
participates in the group. 
The most prevalent groups in both regions are agriculture/livestock/fisheries producer groups (95 
percent in Sava and 83 percent in Menabe), local government (100 percent in both regions), and 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Pirogue material: Wood Motorized pirogue Whether pirogue has a sail
Pirogue Material
Total Sava Menabe
INRM Madagascar Nosy Manga Baseline Report 22
religious groups (98 percent in Sava and 85 percent in Menabe). In Sava, credit or microfinance groups 
are also prevalent, with 83 percent of HHs reporting having one in their community. In Menabe, only 
36 percent of HHs reported having a credit or microfinance group, with one village having no HHs that 
reported having a microfinance group in their community. 
To understand the prevalence of group participation, the study team looked at the percentage of HHs 
that indicate that they have HH members who participate in the group type. In the calculation of 
percentages for each group type, the team excluded villages where no HHs indicate the group type 
exists in their community. The groups that have the most participation across the regions are religious 
groups. About 64 percent of HHs in both regions participate in a religious group. The second most 
prevalent participation is in agriculture/ livestock/ fisheries producer groups, where 55 percent of HHs 
in Sava and 32 percent in Menabe have HH members that participate. In Sava, where microfinance 
groups are more prevalent than in Menabe, 44 percent of HHs participate in a microfinance group, 
whereas in Menabe only 14 percent of HHs participate. 
While local government exists across the villages, only about three percent of HHs across the regions 
reported having HH members who participate in it. Only 2.4 percent of HHs reported having civic 
groups in their community, and no HHs in Sava and only one HH in Menabe in our sample participated 
in it. 
Figure 5: Percentage of HHs that participate in each group, by region
0% 25% 50% 75% 100%
Agricultural/ livestock/ fisheries producer’s group
Water users'
Credit microfinance
Mutal help of insurance group
Trade and business association
Civics group
Local government
Religious group
Active Membership in Groups
Total Menabe Sava
INRM Madagascar Nosy Manga Baseline Report 23
FOOD SECURITY AND RESILIENCE 
The study used the Food Insecurity Experience Scale (FIES) to measure food security, and the Ability to 
Recover from Shocks and Stresses Index (ARSSI) to capture the ability to recover from shocks. The 
team modified the standard ARSSI module that asks about shock experience on 16 types of shocks to 
condense it to general shock and modified the shock-exposure correction procedure accordingly. The 
social capital indicator is a Feed the Future (FTF) standard indicator. 
FOOD INSECURITY 
FIES captures the level of food insecurity that a HH experiences during the 12 months prior to data 
collection. The module asks whether the HH experienced eight dimensions of food security in the past 
12 months. Based on their response, each HH is assigned to a category of food insecurity severity (little 
or no, moderate, or severe insecurity). Consistent with the PPI, households in Sava are a lot more food 
secure than HHs in Menabe. In Sava, 76 percent of HHs experience little or no food insecurity, 23 
percent experience moderate food insecurity, and only one percent experience severe insecurity. In 
Menabe, only 28 percent of HHs experience little or no food insecurity, while 56 percent of HHs 
experience moderate insecurity, and 16 percent experience severe food insecurity. 
RESILIENCE - ABILITY TO RECOVER FROM SHOCKS 
The ARSSI is an indicator that measures the ability to recover from shocks by asking about a HH’s ability 
to currently meet food needs and future needs after experiencing a major shock in the past 12 months. 
These questions result in an index that ranges from two-to-six, where higher values indicate more 
resiliency. The response to ability to meet food needs is then corrected with the level of shock 
experience, where the ability to recover is adjusted downward if a HH’s level of shock exposure is 
below the mean of the population, and adjusted upward if a HH’s level of shock exposure is above the 
mean of the population. 
Around 29 percent of HHs in Sava and 37 percent of HHs in Menabe self-reported having experienced 
difficult times in the past 12 months. These shocks seriously impacted the HH’s economic situation. 
After adjusting for level of shock exposure, of the households that experienced shocks, the overall 
ARSSI score is 3.38 on a scale of two-to-six. The score is not statistically different between the two 
regions. 
RESILIENCE - SOCIAL CAPITAL 
Another dimension of HH resilience is social capital. This indicator measures the ability of HHs to rely 
on and support people within their own community (bonding social capital) and on HHs outside of their 
own community (bridging social capital) “during difficult times.” The definition of community is 
interpreted by the respondent. Each indicator ranges from zero to four. Overall, Sava has slightly 
stronger social capital than Menabe (3.14 compared to 2.81), and in both regions, bonding capital is 
stronger than bridging social capital. The study villages in Sava scored 3.48 out of four for bonding social 
capital and 2.81 out of four for bridging social capital. In Menabe, the study villages scored 3.25 out of 
four for bonding social capital and 2.37 out of four for bridging social capital. 
INRM Madagascar Nosy Manga Baseline Report 24
LIVELIHOODS 
This section presents an overview of the livelihoods of HHs across villages in both regions. The team 
first describes the main livelihood activities of households in each region, as well as average income and 
percentage of income from the main livelihoods. Then, using the PII created for the TSIRO baseline 
survey (TSIRO Baseline Survey, 2021), the team predict whether a HH falls below the USD 1.90 per day 
poverty line based on a series of HH consumption/expenditure and composition indicators. Due to the 
choice to use FIES and exclude the food consumption module in the survey, the team adjusted the 
TSIRO PII index and categorization accordingly. The team also describes access to electricity and water, 
borrowing, lending and mobile money use, and savings in each region. 
The study asked each respondent, “What is the most important, the second most important, and third 
most important activity your household relies on to meet food and income needs?”. Table 9 presents 
the percentage of HHs that reported each livelihood type as one of their top three main livelihoods. 
Figure 6 presents this information in graph form for the main livelihoods of each region as well as fishery 
or aquaculture livelihoods of interest. 
Table 9: Percentage of HHs with activity as one of their top three livelihood sources, by region 
MAIN LIVELIHOOD ACTIVITIES AND HOUSEHOLD MONTHLY INCOME 
Sava
(percentage)
Menabe
(percentage)
Total
(percentage)
Signif. of difference 
between regions
Crop farmer 86.3 24.3 35.3 ***
Animal farmer 15.3 11.1 11.8
Forest exploitation 0.7 2.9 2.5
Seaweed farmer 0.0 12.9 10.6 **
Sea cucumber farmer 0.2 0.8 0.7
Fisher 51.3 58.0 56.8
Diver 0.9 5.1 4.4 **
Gleaner 9.2 12.9 12.3
Teacher 3.4 5.4 5.0
Seasonal labor 17.0 14.8 15.2
Non-fish retailer 21.9 26.1 25.3
Fish retailor 4.5 1.4 1.9
Other: unskilled 3.5 8.2 7.4 * 
INRM Madagascar Nosy Manga Baseline Report 25
INRM Madagascar Nosy Manga Baseline Report 26
Sava
(percentage)
Menabe
(percentage)
Total
(percentage)
Signif. of difference 
between regions
Other: skilled 6.5 9.0 8.5
Fishing, crop farming, and non-fish retail are the main livelihoods in both regions, with crop farming 
being much more important in Sava than Menabe. In Sava, 86 percent of HHs rely on crop farming, 51
percent of HHs rely on fishing, and 22 percent of HHs rely on non-fish retail, while 17 percent also rely 
on seasonal labor and 15 percent on animal farming. In Menabe, 58 percent of HHs rely on fishing, 26 
percent on non-fish retail, 24 percent on crop farming, while 15 percent rely on seasonal labor, 13 
percent on gleaning, and 13 percent on seaweed farming. There are no seaweed farmers in the sample 
of HHs in Sava (although community leader surveys indicate that there are seaweed farmers in Sava. 
More details are included in the seaweed farming and Learning Questions section). Across both regions, 
only two HHs reported relying on sea cucumber harvesting as one of their main livelihoods, although 
the none of the community leaders reported any sea cucumber farming activities in their villages. 
Figure 6: Main livelihoods by region
The study also broke down main livelihoods by gendered HH types and HH ethnicity. However, these 
statistics should be interpreted with caution, as the sampling design does not allow sufficient statistical 
power to make claims regarding sub-group populations, especially for the less common livelihood types 
where the sample is scarce. 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Main Livelihood
Total Sava Menabe
Table 10 presents the livelihood breakdown by gendered HH types. The reliance of most livelihoods 
does not differ between HH types, except for forest exploitation, fishing, and non-fish retail. Forest 
exploitation is almost only reported by single male-headed HHs. Single female-headed HHs rely on 
fishing less than others (only 23 percent of single female-headed HH), whereas the majority of married 
male-headed HHs (71 percent) and the majority of single male-headed HHs (53 percent) rely on fishing. 
The most popular livelihood of single female-headed HHs is non-fish retail (45 percent), whereas a 
smaller percentage of married male-headed HHs and single male-headed HHs rely on non-fish retail (21 
percent and 18 percent, respectively). 
Table 10: Percentage of HHs with activity as one of their top three livelihood sources, by gendered household type 
Single male 
headed 
households
(percentage)
Married 
male headed 
households
(percentage)
Single 
female 
headed 
households
(percentage)
Total
(percentage)
Signif. Of 
difference 
between 
household 
types
Crop farmer 44.0 36.4 23.6 35.3
Animal farmer 7.4 13.4 12.0 11.8
Forest exploitation 11.6 0.1 0.0 2.5 ***
Seaweed farmer 5.1 10.7 15.6 10.6
Sea cucumber farmer 0.0 0.1 3.3 0.7
Fisher 52.4 70.5 22.9 56.8 ***
Diver 3.9 6.1 0.0 4.4
Gleaner 10.6 14.0 9.1 12.3
Teacher 6.9 4.9 3.3 5.0
Seasonal labor 16.6 13.9 17.4 15.2
Non-fish retailer 17.6 21.1 45.0 25.3 **
Fish retailor 4.8 1.1 1.2 1.9
Other: unskilled 10.2 5.9 8.6 7.4
Other: skilled 6.5 10.3 5.5 8.5
Table 11 presents the livelihood breakdown by the major ethnic categories in each region. There are 
statistically significant differences in main livelihoods between ethnic categories in Menabe in crop 
farming, forest exploitation, seaweed farming, and other skilled activities. HHs of the Sakalava ethnic 
group rely more on crop farming (65 percent of Sakalava households) than Veza and other numerical 
minority ethnic groups (18 percent and one percent, respectively). Forest exploitation is also mainly 
INRM Madagascar Nosy Manga Baseline Report 27
undertaken by Sakalava HHs, with no other ethnic categories being reliant on forest exploitation. Both 
HHs of the Sakalava and Veza ethnic groups rely more on fishing (60 and 62 percent), seaweed farming 
(15 and 10 percent), and gleaning (13 and 18 percent) than HHs of other ethnic groups. HHs of other 
ethnic groups in Menabe rely mainly on fishing (32 percent), but also on animal farming (24 percent) 
and teaching (22 percent), seasonal labor (23 percent), and other skilled activities (25 percent). HHs of 
the Betsimisaraka ethnic group and other numerical minority groups rely on mostly the same 
livelihoods, except more HHs of minority ethnic groups rely on other skilled activities (15 percent) than 
Betsimisaraka HHs (five percent). 
INRM Madagascar Nosy Manga Baseline Report 28
Table 11: Percentage of HHs with activity as one of their top three livelihood sources, by ethnic category
Menabe￾Veza
(percentage)
Menabe￾Sakalava
(percentage)
Menabe￾Other
(percentage)
Sava￾Betsimisaraka
(percentage)
Sava- Other
(percentage)
Signif. of 
difference 
between 
ethnic 
categories
Crop 
farmer 17.6 64.7 1.2 85.6 91.0 ***
Animal 
farmer 8.7 15.6 23.8 14.6 19.2
Forest 
exploitation 0.0 16.7 0.0 0.9 0.0 ***
Seaweed 
farmer 14.6 10.3 2.6 0.0 0.0 ***
Sea 
cucumber 
farmer
1.1 0.0 0.0 0.3 0.0
Fisher 59.9 61.7 32.3 50.7 55.4
Diver 6.8 0.4 0.0 1.0 0.0
Gleaner 13.2 17.5 0.6 9.3 8.8
Teacher 3.7 4.9 21.8 3.3 4.0
Seasonal 
labor 14.6 12.0 23.0 17.1 16.2
Non-fish 
retailer 28.3 21.4 16.0 21.7 22.8
Fish 
retailor 1.8 0.0 0.0 4.5 4.2
Other: 
unskilled 8.0 12.5 1.3 3.8 1.7
Other: 
skilled 9.0 1.6 24.7 5.1 15.4 * 
HH MONTHLY INCOME AND INCOME FROM MAIN LIVELIHOODS AND 
AQUACULTURE
The average HH monthly income is 420,928 Ariary (USD 95.72), with similar income across regions. 
Since the distribution of HH monthly income is heavily right skewed, to better represent the average 
HH, the team also calculated population statistics excluding outliers, defined as greater than three
standard deviations from the mean. Excluding outliers (HHs that earn much higher incomes than the 
rest), the average HH monthly income is 207,465 Ariary (USD 47.18) across the regions. Table 12 
presents the HH income by region, including and excluding outliers. On average, HHs in Menabe earn 
slightly less income than HHs in Sava (82 percent that of Sava). Table 12 presents the average monthly 
INRM Madagascar Nosy Manga Baseline Report 29
HH income by region with and without outliers. The average HH monthly income without outliers in 
Sava is 233,108 Ariary (USD 53), and that in Menabe is 199,019 Ariary (USD 45.26). 
Table 12: Average income by region, with outliers and excluding outliers (greater than three standard deviations from mean) of total 
sample. 
Mean Std. Err. 95 percent Conf. Interval
HH monthly income (Ariary)
Sava 459,246 29,357 401,614 516,878
Menabe 412,648 49,873 314,742 510,555
HH monthly income, excluding outliers (Ariary)
Sava 243,260 10,344 222,948 263,572
Menabe 200,162 13,365 173,918 226,407
The study also disaggregated HH monthly income by gendered HH type as well as seaweed farming and 
non-seaweed farming HHs (Table 13). The income of seaweed farming and non-seaweed farming HHs 
are not statistically significantly different from each other. HHs headed by a single female earn less than 
HHs with a married male HH head. Single male and single female-headed HH income, as well as single 
and married male-headed HH income, are not significantly different from each other. 
Table 13: Average income by seaweed farming and non-seaweed farming households (Menabe only), as well as gendered household 
head types, excluding outliers of total sample. 
Mean Std. Err. 95 percent Conf. Interval
HH monthly income, excluding outliers (Ariary), Menabe only
Non-seaweed farming HHs 212,726 17,449 178,430 247,023
Seaweed farming HHs 233,170 23,245 187,481 278,860
HH monthly income, excluding outliers (Ariary)
Female HHH, no spouse 107,746 16,285 75,766 139,725
Male HHH, no spouse 185,048 26,167 133,664 236,433
Male HHH, w/ spouse 258,662 12,176 234,752 282,572
Table 14 presents the average HH monthly income from livelihood activities, excluding the income
outliers. The study only presents the statistics for the more common livelihood activities (crop farming, 
INRM Madagascar Nosy Manga Baseline Report 30
fishing, non-fish retail, and in Menabe, seaweed farming), as there are not enough observations of income 
from less common livelihood sources to make claims for the population of HHs in each region that rely 
on those livelihoods. In Sava, a HH with crop farming as one of their main livelihoods makes about 
71,557 Ariary (USD 16.27) from crop farming, whereas in Menabe HHs that crop farm make only 
31,612 Ariary (USD 7.19) from crop farming. For fishing, HHs that fish as one of their main livelihoods 
make about 165,322 Ariary (USD 37.59) in Sava and 95,413 Ariary (USD 21.70) in Menabe. Likewise, for 
non-fish retail, HHs that engage in non-fish retail as one of their main livelihoods make about 165,322 
Ariary (USD 37.59) in Sava and 95,413 Ariary (USD 21.70) in Menabe, with no statistically significant 
difference between the regions. HHs that depend on seaweed farming as one of their main livelihoods 
(only in Menabe) make on average 45,064 Ariary (USD 10.25) from seaweed farming. 
Table 14: Average income by region, with outliers and excluding outliers of total sample. 
Average monthly income from each main livelihood activity (Ariary)
Region Mean 95 percent Conf. Interval
Crop farmer
Sava 245,758 222,933 268,583 
Menabe 161,450 125,590 197,310 
Fisher 
Sava 299,236 271,710 326,763 
Menabe 238,311 210,447 266,175 
Non-fish retailer 
Sava 282,163 233,080 331,246 
Menabe 204,503 154,818 254,187 
Seaweed farmer 
Menabe 181,933 160,892 202,975 
INRM Madagascar Nosy Manga Baseline Report 31
RELIANCE AND INCOME DIVERSIFICATION 
The study presents the percentage of HH income from each major livelihood activity to demonstrate 
the level of reliance of HHs on each major livelihood. Figure 7 shows the percentage of HH income 
from fishing, gleaning, crop farming, and non-fish retail among the HHs that rely on the activity as one of 
their main livelihood activities. Fishing composes an average of 65 percent of HH incomes across both 
regions, with fishing as one of the top three livelihood activities. (HHs that rely on fishing as their 
primary livelihood earn 76 percent of their HH income from fishing.) The average percentage of HH 
income from gleaning among HHs with gleaning as a main activity is 55 percent in Sava and 37 percent in 
Menabe. The average percentage of HH income from crop farming among HHs with crop farming as a 
main activity is 34 percent in Sava and 22 percent in Menabe. The average percentage of HH income 
from non-fish retail among HHs with it as a main activity is 57 percent in Sava and 51 percent in Menabe.
INRM Madagascar Nosy Manga Baseline Report 32
Figure 7: Percent of income from main livelihoods by region N= 553 N= 132
N= 364
N=156
N= 164
N= 33
N= 255
N=54
N= 389
N= 99
N= 109
N=102
0%
10%
20%
30%
40%
50%
60%
70%
% of income from fishing
among fishing HHs
% of income from
gleaning among gleaning
HHs
% of income from crop
farming among crop
farming HHs
% of income from non￾fish retail
Percent of Income from Primary Livelihood Activity
Total Sava Menabe
INRM Madagascar Nosy Manga Baseline Report 33
68.58%
23.91%
5.48%
73.72%
20.83%
4.74%
67.48%
24.58%
5.63%
0%
10%
20%
30%
40%
50%
60%
70%
80%
% of income from primary livelihood % of income from secondary
livelihood
% of income from tertiary livelihood
Income Diversification 
Total Sava Menabe
Figure 8: Income diversification. Percentage of income from primary, secondary and tertiary livelihood sources, by region
To illustrate the extent of livelihood diversification, irrespective of livelihood source, the study looked at 
the percentage of HH income from HHs’ primary livelihoods, secondary livelihoods, and tertiary 
livelihoods, respectively, in Figure 8. It shows that the majority of HHs rely on their primary livelihood 
for about 67 percent of their income, with secondary livelihoods earning them about 25 percent and 
tertiary livelihoods five percent, with little difference across the regions.
Next, the study looked at the role of seaweed farming in livelihood diversification in Menabe. Figure 9 
shows the percentage of income from seaweed farming among all HHs that undertake any seaweed 
farming activity (even if not as one of their top three livelihoods), as well as those that rely on it as their 
primary, secondary, and tertiary livelihoods, respectively. The three percent of HHs in Menabe that 
undertake it as their primary activity earn 52 percent of their HH income from it. Those that rely on it 
as a secondary activity (seven percent of all HHs in Menabe) earn on average 26 percent of their HH 
income from it, and those that rely on it as a tertiary activity (three percent of all HHs in Menabe) earn 
about seven percent of their HH incomes from seaweed farming. HHs that have at least one HH 
INRM Madagascar Nosy Manga Baseline Report 34
member involved in seaweed farming, regardless of it being their main source of livelihood or not (35 
percent of HHs in Menabe), earn on average 20 percent of their HH income from seaweed farming.
N=758
N=10
N=68
N=45
0%
10%
20%
30%
40%
50%
60%
% of income from
seaweed farming among all
seaweed farming HHs
% of income from
seaweed farming as
primary activity
% of income from
seaweed farming as
secondary activity
% of income from
seaweed farming as
tertiary activity
Percent of HH Income from Seaweed Farming
Figure 9: Percent of HH income from seaweed farming
PREVALENCE OF POVERTY
Figure 10 shows the distribution of HHs below the poverty line across regions. On average, 38 percent 
of HHs fall below the USD 1.90 per day poverty line, but the percentage differs significantly across the 
two regions. Only 12 percent of HHs in Sava, compared to a substantial 44 percent of HHs in Menabe 
fall below the poverty line. 
INRM Madagascar Nosy Manga Baseline Report 35
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Total Sava Menabe
Households Below USD 1.90/day Poverty Line (Predicted)
Figure 10: Percentage of HHs below the poverty line, by region
To look at the HH characteristics that are associated with poverty, Table 15 presents the multivariate 
logistic regression results comparing the association between poverty status and a range of socio￾demographic and livelihood characteristics, and Figure 11 plots out the coefficients with confidence 
intervals. The study first tested the association of HH characteristics with poverty while controlling for 
regional effects.11 To test the association of regional ethnic groups with poverty, the study also 
conducted subpopulation analysis using only the sample in each region and added the ethnic categories 
relevant to each region as an explanatory variable. The result table is presented in odds ratios. 
Unsurprisingly, lower educated HHHs and larger HHs are more likely to fall below the poverty line. 
Model 1 results show that with each increase in education level of the HH head (for example from 
preschool education completion to primary school education completion), the household is 54 percent
less likely to be under the poverty line. The subpopulation analysis indicates that other characteristics 
associated with poverty may be different in each region. A HH that is larger and native to the village is 
more likely to be under the poverty line in Menabe, with those who are native 2.54 times more likely, 
and the addition of a HH member 1.25 more likely to fall under the poverty line. In Sava, being a HH 
with at least one HH member who fishes decreases the odds of being under the poverty line by 61 
percent. Controlling for these HH characteristics, ethnic group categories are not associated with 
poverty. 
11 We used regional-level fixed effects. Doing so eliminates any regional differences that might influence a household’s poverty 
status, including ethnic groups which have distinct regional dynamics. 
INRM Madagascar Nosy Manga Baseline Report 36
Table 15: Logistical regression result of socio-demographic and livelihood characteristics on poverty (odds-ratio)
Model 1:
All
(HHs below $1.90/day 
poverty line)
Model 2:
Sava
(HHs below $1.90/day 
poverty line)
Model 3: 
Menabe
(HHs below $1.90/day 
poverty line)
Coefficient (SE) Coefficient (SE) Coefficient (SE)
MHHH w/ spouse 1.17
(0.36)
0.52
(-1.35)
1.32
(0.57)
FHHH only 2.66
(1.71)
0.75
(-0.46)
3.79
(1.93)
HHH education (category) 0.46***
(-5.39)
0.45***
(-4.01)
0.45***
(-5.23)
How many people are in your 
household? (include you, and 
babies/children)
1.21* 
(2.19)
1.04
(0.31)
1.25* 
(2.17)
Were you raised in this village 
since childhood?
1.93*
(1.97)
0.56
(-1.41)
2.54*
(2.56)
Fishing HH 0.65
(-0.94)
0.39*
(-2.18)
0.76
(-0.50)
Gleaning HH 1.46
(0.88)
1.14
(0.24)
1.81
(1.21)
Seaweed farming HH 0.98
(-0.05)
0.95
(-0.13)
Menabe 4.87***
(4.73)
Sava - other 0.33
(-1.66)
Menabe - Sakalava 1.45
(0.89)
Menabe - other 3.48
(1.58)
N 750 293 457
INRM Madagascar Nosy Manga Baseline Report 37
Figure 11: Coefficient plots of logistical regression result of socio-demographic and livelihood characteristics on poverty, by region (odds￾ratio), 95 percent confidence interval
ACCESS TO ELECTRICITY, COOKING FUEL AND WATER
Figure 12 shows the level and method of HH access to electricity, cooking fuel, and water across the 
region. Electricity access differs substantially and significantly across the two regions, though sources of 
electricity are similar. In Sava, 76 percent of HHs have electricity access, whereas in Menabe, only 27 
percent do. Out of the HHs that have access to electricity, 90 percent use solar panels as their main 
INRM Madagascar Nosy Manga Baseline Report 38
source of electricity, eight percent use batteries as their main source, and two percent use the electrical 
grid. 
With regards to cooking fuel, across regions, 64 percent of HHs use a wood stove only, 21 percent of 
HHs use a charcoal stove only, and 15 percent of HHs use both wood and charcoal. No HHs in the 
sample reported using a kerosene or clean energy stove. 
Very few HHs have their main source of drinking water within the HH; 85 percent of HHs across the 
regions rely on village wells as their primary source of drinking water. About 10 percent of HHs have 
their own well in the HH. For HHs where enumerators were able to observe the place where HH 
members most often wash their hands, 40 percent in Sava and 82 percent in Menabe did not have water 
available, and 72 percent in Sava and 98 percent in Menabe did not have soap. 40% 2% 90% 8% 0%0% 10% 85% 0%
4%
21%
64%
15%
76%
0%
91%
8%
1%
2%
8%
88%
1%
2%
14%
66%
19%
27%
3%
89%
8%
0%
0%
11%
84%
0%
5%
22%
64%
14%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Access to electricity
Electrical grid
Solar panels
Batteries
Other
Tap of the village
Well of the household
Well of the village
Spring
River/ surface water
Charcoal
Wood
Both
Main source of electricity Main source of drinking water Main cooking fuel
Access to Electricity, Cooking Fuel and Water
Total Sava Menabe
Figure 12: Access to electricity, cooking fuel, and water by region
INRM Madagascar Nosy Manga Baseline Report 39
BORROWING & LENDING AND MOBILE MONEY USE 
Across the regions, 61 percent of HHs did not borrow any money from others in the past year, and 36 
percent borrowed once or twice. Of those that borrowed money once or more, about 91 percent of 
HHs only borrow from one source: 56 percent borrowed from family, and 38 from a local business￾person or shop owner (23 in Sava and 40 in Menabe). No HHs in Sava and only 0.2 percent in Menabe 
borrowed from NGOs, but 14 percent of HHs across regions borrowed from other entities, including 
local Village Savings and Loan Associations (VSLAs), friends in the community, and mobile money 
advances. About 52 percent of HHs across the regions were not asked to lend money in the past year, 
while 25 percent of HHs were asked by one-to-two people, and 17 percent of HHs were asked by 
three-to-five people. 
Figure 13 presents mobile money services usage prevalence and scope by region. A total of 32 percent 
of HHs use mobile money, of which, 93 percent report being able to withdraw all their money from 
their mobile devices, and 93 percent also report being able to use their money on their mobile devices 
to trade or send to individuals. Only nine percent of those that use mobile money services report being 
able to trade with shops using mobile devices. 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Members of household
using mobile money
Ability of household
members to withdraw
mobile money
Ability of household to
use mobile money at local
shops
Ability of household to
use mobile money to
trade/send money to
individuals
Household Mobile Money Usage
Total Sava Menabe
Figure 13: Household mobile money usage prevalence and scope by region
INRM Madagascar Nosy Manga Baseline Report 40
SAVING 
With regards to saving practices, 60 percent of HHs in Sava and 47 percent in Menabe have savings. 
The main reasons HHs reported saving money are for emergency cash for food (61 percent) and 
emergency cash for health problems (49 percent). Other reasons mentioned in both regions include for 
funeral costs (23 percent), to build a retail business (19 percent), and for clothes (11 percent). In Sava, 
house building (29 percent) and children’s schooling (19 percent) were also mentioned as major reasons 
for saving. In Menabe, HHs also mentioned buying fishing equipment for HH use (13 percent) and buying 
a pirogue (12 percent) as reasons for saving. Other reasons respondents frequently mentioned in Sava 
are buying farmland and paying land labor for crop farming. 
AGRICULTURE, LIVESTOCK AND LAND CLEARING 
PRACTICES 
This section summarizes agricultural land tenure, livestock ownership, and land clearing practices across 
the sampled villages in both regions. 
AGRICULTURAL LAND TENURE 
HHs were asked whether any members of their HH farmland and the size of the farm that they 
cultivate. HHs that farmland were then asked what percent of their farmed land they also own. If HHs 
do not own any of the land they farm, they were asked about the contractual arrangement to farm the 
land. HHs that do not farmland were asked whether they own land that is farmed by someone else. 
In Sava, 92 percent of the HHs engage in crop farming, whereas in Menabe only 27 percent do. Out of 
the farming HHs, the area of land farmed by HHs in Sava is statistically significantly larger than in 
Menabe. Farming HHs in Sava farm on average 176 ares (1.76 hectares) of land compared to 123 ares 
(1.23 hectares) in Menabe. In both regions, around 84 percent of the HHs farm own their land, and 
each HH owns on average 95 percent of the land on which they farm. 
Aside from owning farmland, in Sava, 23 percent of HH who farm use common land, and around eight 
percent rent private land. In Menabe, 25 percent of HHs who farm rent private land to do so, and 
almost no HHs use common land. 
In both regions, about 19 percent of HHs own farmland that is not farmed by HH members, of which 35 
percent of HHs have other relatives (not from their HH) who farm the land. About 60 percent of HHs 
own farmland that is fallowed, with some citing reasons for its lack of use as drought and waiting to use 
it as children's inheritance. 
LIVESTOCK OWNERSHIP 
About 75 percent of HHs in Sava and 53 percent in Menabe own livestock. In Sava, the predominant 
livestock is poultry (72 percent of HHs) with 14 percent of HHs also owning zebus. Out of the HHs 
who own livestock, each HH owns an average of 10 poultry and 0.56 zebu in Sava. In Menabe, 42 
percent of HHs own poultry, 13 percent own pigs, 10 percent own goats, and only 5 percent of HHs 
INRM Madagascar Nosy Manga Baseline Report 41
own zebus. Out of the HHs who own livestock, each HH owns an average of six poultry, three goats, 
one pig, and one zebu.
12
LAND CLEARING PRACTICES 
The study asked respondents whether anyone in the HH cleared land to allow more cultivation or 
livestock rearing in the past year, as well as if they intend to clear land in the next 12 months. Figures 14 
and 15 show the responses by region. Fifteen percent of HHs in Sava and four percent of HHs in 
Menabe indicate that they have cleared land in the past year, and a substantial 57 percent in Sava and 14 
percent in Menabe indicate that they intend to clear land in the next 12 months. In Sava, the majority 
(63 percent) of HHs who cleared land did so in forested land, and 34 percent in fallow agricultural land. 
In Menabe, the majority (70 percent) of HHs who cleared land did so in fallow agricultural land, and only 
two percent cleared forested land. A few HHs also mentioned clearing land in rice fields. 
The HHs who intend to clear land were asked to list all the reasons for the intention. The most 
frequently mentioned reason (mentioned by 75 percent of HHs who intend to clear land) is to grow 
more crops to sell. Fifty percent of HHs also mentioned growing crops for HH consumption, and 47 
percent mentioned the reason being to grow different crop types. In Sava, 22 percent of HHs also 
mentioned acquiring their own land or more land as other reasons they cleared land. 
0%
20%
40%
60%
80%
100%
120%
No Yes No Yes Forested land Fallowed
agricultural land
Other
Over the last one year, did you or
anyone in your household clear
land to allow
Intent to clear land for cultivation
in the next 12 months
Where land was most recently cleared
Land Clearing Practices
Total Sava Menabe
Figure 14: Self-reported land clearing practices by region
12 Although zebus ownership in Menabe is less common, three zebus-owning HH own a large number of zebus. Excluding these
households, the average HH ownership of zebus in Menabe is 0.40. 
INRM Madagascar Nosy Manga Baseline Report 42
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
To grow more
crops to sell
To grow more
crops to consume
To grow different
crop types
(diversification)
To replace land
that is no longer
productive
To prevent
others from using
it
Other
Reason for planning to clear more land for cultivation/farming
Land Clearing Reason
Total Sava Menabe
Figure 15: Region for land clearing, by region
The study ran a multivariate logit regression to investigate the profiles of HHs that have cleared land in 
the past 12 months and intend to clear land in the next 12 months. The results are displayed in Table 16 
in odds ratio form and coefficient plots displayed in Figure 16. After accounting for regional factors 
related to land clearing, the percentage of income from crop farming and perception of the health of 
mangroves being healthier increases the odds of intending to clear land (1.02 and 1.98 more likely 
respectively). A HH below the poverty line is 82 percent less likely to have the intention to clear land. 
Table 16: Logistic regression result of household characteristics regressed on Land cleared and Intent to clear land (odds-ratio)
Model 1: 
Cleared land over the 
last 12 months
Model 2: 
Intend to clear land in the 
next 12 months
HH is below $1.90/day poverty line 0.40
(-1.53)
0.19***
(-4.87)
Percentage of HH income from crop farming 1.00
(0.53)
1.02* 
(2.07)
HH size 1.02
(0.38)
1.11
(1.85)
Attitude on NRM rules 1.06
(0.15)
1.32
(1.38)
INRM Madagascar Nosy Manga Baseline Report 43
INRM Madagascar Nosy Manga Baseline Report 44
Model 1: 
Cleared land over the 
last 12 months
Model 2: 
Intend to clear land in the 
next 12 months
Perception of ability to influence NRM 1.83
(1.76)
1.55
(1.36)
Perceives ecosystem in general is under threat 1.14
(0.14)
0.57
(-1.52)
Perception of health of mangroves (higher 
healthier)
0.81
(-0.36)
1.98* 
(2.31)
Has mangrove closures in community 2.78
(1.67)
1.13
(0.25)
Menabe 0.18*
(-2.28)
0.25***
(-3.48)
N 676 673
Figure 16: Coefficient plot of logistic regression result, of household characteristics regressed on Land clearing and Intent to clear land 
(odds-ratio). 95 percent confidence intervals
FISHING AND GLEANING PRACTICES
This section presents the result of the fishery module of the baseline survey. The survey first gathered
information on HH fishing asset ownership, as well as gear lending and borrowing behavior. Then, the 
survey asked respondents to list up to three most frequently used fishing sites, as well as the fishing 
method, labor, trip length, and catch associated with fishing activities the HH undertakes at each site. 
These HH survey questions intended to approximate CPUE that is usually more directly measured 
through catch surveys at fishing sites. The fishery module asked respondents about the use of catch at 
each site and decision-making regarding use of the catch. The module also asked about overall security 
of access rights and conflict surrounding fishing sites. This section first presents HH fishing assets and 
methods used by HHs across the population of sampled villages across regions. Then, information on 
fishing trips across the main three sites of each HH are presented. Lastly, the study presents HH 
perceptions of access right security and conflict around fishing sites at the HH level of analysis.
FISHERY ASSET OWNERSHIP, LENDING, AND BORROWING
Figure 16 presents the prevalence of fishing gear ownership and lending, and Figure 17 presents 
prevalence of gear borrowing by region. Most HHs (96 percent) across both regions own fishing gear 
purchased with HH savings. Lending and borrowing are more frequent in Sava than in Menabe: 52 
percent of HHs in Sava lend fishing equipment to others, of which 55 percent is in exchange for fish and 
41 percent without exchange; 36 percent of HHs regularly borrow from others, of which 66 percent is 
in exchange for fish and 31 percent in exchange for nothing. In Menabe, only 36 percent of HHs lend 
INRM Madagascar Nosy Manga Baseline Report 45
fishing equipment regularly, of which 48 is in exchange for nothing, 34 percent is in exchange for fish, 
and 14 percent is in exchange for money, and 25 percent of HHs regularly borrow fishing equipment 
in exchange for nothing or fish, and sometimes money. In Sava, 40 percent of HHs also buy other 
fishing materials needed for each trip, such as ice and light needed for night trips, whereas in Menabe, 
13 percent of HHs do so. Almost no HHs in the sample borrows other fishing trip materials. 
0%
20%
40%
60%
80%
100%
120%
No
Yes
Given by a family member
Given by client(s)
Thanks to savings
Borrowed from clients
Borrowed money from someone
No
Yes
Gets nothing
Gets fish
Gets money
Gets fish and money
Fishing gear
ownership
Source of money for fishing gear Regularly lend
fishing
Arrangement for lending fishing
equipment
Fishery Asset Ownership and Lending 
Total Sava Menabe
Figure 17. Fishery asset ownership and lending by region
INRM Madagascar Nosy Manga Baseline Report 46
0%
20%
40%
60%
80%
100%
120%
No Yes Pays
nothing
Pays fish Pays
money
Pays fish
and
money
No Yes No Yes
Regularly borrow
fishing equipment
from others
Arrangement for borrowing fishing
equipment
Buys other materials
needed for the fishing
trip (such as ice and
light)
Borrows other
materials needed for
the fishing trip (such
as ice and light)
Fishery Asset Borrowing
Total Sava Menabe
Figure 18: Fishery asset lending, by region
FISHING METHODS
Figure 19 presents the percentage of HHs that use each fishing method by region. In Sava, fishing HHs 
mainly use net fishing (i.e., Jarifa, ZZ, beach seine, mosquito net, purse seine, and gillnets), harpoons, line 
fishing (i.e., hook and line, handline, trolling line, and drift line), and diving. In Menabe, fishing HHs mainly 
use net fishing and line fishing. The most common fishing method employed across regions is net fishing, 
with 75 percent of fishing HHs in Sava and 87 percent of fishing HHs in Menabe employing this method. 
The second most common method in Sava is harpoons (45 percent), whereas in Menabe significantly 
fewer (five percent) use harpoons. The second most common method in Menabe is line fishing (40 
percent), which is also used frequently in Sava (21 percent). In Sava, 15 percent of HHs undertake diving, 
and eight percent use fish/shrimp/lobster traps. 
INRM Madagascar Nosy Manga Baseline Report 47
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Diving Long line
Fishing
Net Fishing Line Fishing Fish / shrimp
/ lobster
traps
Fixed traps Rifles Harpoons
Fishing Method
Sava Menabe Total
Figure 19: Fishing method by region
As for the use of pirogues, time of day, and season of fishing, in Sava, almost all HHs engage in fishing by 
pirogue, and in Menabe, 90 percent of fishing HHs fish by pirogue. In Sava, 10 percent of HHs also fish 
by foot, compared to 21 percent in Menabe. Across the region, most fishing HHs (98 percent) fish 
during the day, with 30 percent in Sava and 10 percent in Menabe also fishing at night. There are no HHs 
that only fish at night. 
CATCH, LABOR, AND CPUE
Figure 20 presents the percentage of fishing HHs in each region that that self-reported catching each fish 
species group on their regular fishing trips. The catch species differs significantly across regions. In Sava, 
71 percent of fishing HHs mainly catch big reef fish (groupers, jacks, barracudas, and big snappers), 46 
percent catch small reef fish, 35 percent catch octopus, and 29 percent catch large pelagics, including 
tuna/bonito, marlin/sailboats, dolphinfish, king mackerel, and small pelagics across their main fishing sites. 
In Menabe, small pelagics comprise the main catch of 74 percent of fishing HHs, followed by large 
pelagics, at 34 percent. Small reef fish (28 percent), large reef fish (18 percent), and shrimp (16 percent)
are also important catch species for a smaller percentage of fishing HHs in Menabe. 
INRM Madagascar Nosy Manga Baseline Report 48
0%
10%
20%
30%
40%
50%
60%
70%
80%
Fishing Species
Total Sava Menabe
Figure 20: Percentage of households that fishing HHs mainly catch in each fish species group, by region
The study asked each HH the labor (number of people), catch (kg), and length of trip (hours) of a typical 
fishing trip at the three most frequented sites to capture catch per unit of effort (CPUE) data for each 
site. Respondents were asked, “In general, how many kilos of fish do you catch per trip?”. The study 
team then took the average of each HH and reported the CPUE (kg per person per day)averaged across 
the most frequented fishing sites. 
In general, fishing HHs in Sava go on 2.16-person and 5.41-hour trips (0.5 person-days on average), 
whereas fishing HHs in Menabe go on 1.81 person and 7.4-hour trips (0.6 person-days on average). HHs 
report an average of 14.25kg of catch per trip, similar across the regions. The average CPUE of a HH is 
similar across the regions at about 31.79 kg per person-day. However, when eliminating the outliers in 
catch size (larger than three standard deviations above the mean), the average CPUE in Sava is 20kg per 
person-day and the average CPUE in Menabe is 17kg per person-day. 
This number is still higher than the CPUE documented by NGOs, WWF and BV, in Belo sur Mer in 
Menabe through participatory catch surveys, which documents a CPUE of between 8.9 to 12.7kg per 
fisher-day between 2017 and 2022 between their project baseline and endline.13 However, these catch 
surveys directly observed the catch and trip information at marine areas. Fishers may consistently over￾or under-estimate the catch size, labor, and trip length during recall through HH surveys. An 
investigation of the fisheries of the Menabe region, produced during the Plan d’Aménagement des 
Pêcheries (PAP), or Fisheries Management Plan, process for USAID Mikajy project team14 uses farmer 
recall to estimate the regional CPUE as well. They estimate a 31.04 kg per pirogue-day for small pelagic
13 Source: Monitoring data shared by WWF with INRM
14 Source: "Diagnostic Global de la Pecherie Region Menabe", shared by USAID Hay Tao team with INRM
INRM Madagascar Nosy Manga Baseline Report 49
fish and 26.54 kg per pirogue-day for large pelagic fish. This number is more consistent with this study’s 
estimates. If an average trip is taken by about two fishers in both regions, the CPUE converts to 
15.02kg per fisher-day and 13.27kg per fisher-day, which is more consistent with estimates that also rely 
on recall. For comparability with other monitoring efforts, below in Table 17, the study reports CPUE 
at the unit of kg per person-per day by converting reported trip hours to days, as well as kg per person￾trip, to kg per pirogue-trip, with and without accounting for outliers. 
Table 17: CPUE calculates under different definitions of units of effort. 
With outliers Without outliers
Mean Std. 
Err.
95
percent 
Conf.
Interval Mean Std. 
Err.
95
percent
Conf.
Interval
Kg per person-day
Sava 35.98 2.86 30.36 41.60 20.78 1.03 18.76 22.80
Menabe 31.66 5.16 21.52 41.80 16.99 0.99 15.05 18.92
Kg per person-trip
Sava 5.15 0.34 4.47 5.83 4.25 0.20 3.85 4.65
Menabe 9.15 1.55 6.11 12.18 4.90 0.28 4.35 5.46
Kg per pirogue-trip
Sava 10.32 0.69 8.95 11.68 9.10 0.57 7.98 10.22
Menabe 15.70 4.37 7.12 24.28 8.34 0.49 7.37 9.30
CATCH USE AND DECISION-MAKING
Figure 21 presents fishing HHs’ fishing catch use by region if the HH has the autonomy to make such 
decisions. Around two percent of fishing HHs in Sava and 88 percent in Menabe’s use some (on average, 
19 percent) of their catch for food. About 68 percent of fishing HHs in Sava and 48 percent in Menabe 
sell the majority (83 percent) of their catch to intermediary collectors, 29 percent of fishing HHs in Sava 
and 31 percent in Menabe sell the majority (76 percent) of their catch to the local market seller, 
whereas 29 percent of fishing HHs in Sava and 39 percent in Menabe sell most (70 percent) of their 
catch to some other person. A total of 97 percent of fishing HHs in Menabe report having a say in who 
to sell/give their catch to and how much to sell for, whereas in Sava only 84 percent report having a say. 
INRM Madagascar Nosy Manga Baseline Report 50
INRM Madagascar Nosy Manga Baseline Report 51
Figure 21: Fishing catch decision and use, by region
In general, about one-to-two persons per HH fish in both regions, and similarly, about one-to-two 
people make the decision about what to do with the catch. In Sava, about 87 percent of fishing HHs only 
have men who fish, and about 12 percent of fishing HHs have both men and women who fish, and 15 
percent of fishing HHs do not make decisions about catch sales. About 18 percent make decisions by 
men only, 28 percent make decisions by women only, and 38 percent make decisions jointly by men and 
women. In Menabe, about 64 percent of fishing HHs only have men who fish, and about 36 percent of 
fishing HHs have both men and women who fish—more common than in Sava. Only four percent of 
fishing HHs do not make decisions about catch sales. About 66 percent make decisions by men only, 14
percent make decisions by women only, and 24 percent make decisions jointly by men and women.
ACCESS RIGHTS SECURITY AND CONFLICT
Figure 22 presents HH responses to perception of access rights security and reasons for feeling secure. 
Across sites per HH, 55 percent of HHs feel confident that they can continue to access their main 
fishing sites in the future. In Sava, more HHs (15 and 17 percent) feel not confident at all or only 
somewhat confident, respectively, compared to eight and nine percent, respectively, in Menabe. The 
most prevalent reason for confidence is lack of conflict in the area, and in Menabe about 30 percent of 
the reason for confidence is having formal access rights. 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
HH decides
catch use
Sell to local
market seller
Sell to
intermediary
collector
Sell to anyone
else
Use as bait Use as HH
food
Gift to family
Fishing Catch Use
Total Sava Menabe
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Not confident at all
Somewhat confident
Confident
Very confident
Have formal rights
Have within village governance
Have between village governance
Have local village conservation initiatives
Have external conservation initiatives
There is no conflict in access and use of this
area
Confidence that the household can
continue to access this area for fishing in
the future
Reason for confidence
Fishing Site Tenure Security
Total Sava Menabe
Figure 22: Fishing site tenure security
Figure 23 presents HH responses regarding disputes at their most frequented fishing sites. Twenty-one 
percent of fishing HHs report disputes related to accessing fishing sites, whereas in Menabe only four
percent of fishing HHs reported disputes. In Sava, disputes related to rule compliance and enforcement, 
as well as fishing gear use rules, and 44 percent of HHs indicate that these disputes are between groups 
in the village, while 15 percent indicate that they are with groups in the village as well as an NGO. In 
Menabe, instead of disagreements regarding marine management rules, 51 percent of the disputes are
about not having sufficient area to fish and 44 percent about not having a sufficient amount of fish. Forty￾four percent of the disputes are among groups in the village. 
INRM Madagascar Nosy Manga Baseline Report 52
INRM Madagascar Nosy Manga Baseline Report 53
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
No
Yes
Groups in the village
Groups in the village and migrants
Groups in the village and NGO
Groups in the village and other
Groups outside the village
Migrants
NGO
Private companies
Other
No sufficient area to fish for villagers
No sufficient amount fish for villagers
No sufficient area and amount fish for villagers
No sufficient area to fish for villagers and other reasons
Other
Are there
any disputes
regarding
access to
fishing sites
in the
village?
Who is the dispute with? What is the dispute?
Fishing Site Conflicts
Total Sava Menabe
Figure 23: Fishing site conflicts by region
INRM Madagascar Nosy Manga Baseline Report 54
PERCEPTION OF FISHERY AND ENVIRONMENTAL 
CHANGE 
The study asked fishing HHs their perceptions of change in fishing catch in the last five years, and about 
their perceptions of mangrove and fish stock changes between now and when they were a child, as well 
as the overall state of coral, mangroves and lagoons, and general environmental degradation. 
FISHERY CPUE CHANGE 
Figure 24 presents the perception of CPUE changes by fishing HHs by region. On a scale of one-to-five, 
(one being much easier, three being the same, and five being much harder), fishing HHs in Menabe 
report that fishing has become between much harder and harder (4.14), and fishing HHs in Sava 
reported it being the same and harder (both 3.8). In other words, 84 percent of HHs in Sava and 92 
percent of HHs thought it was harder or much harder to catch the same amount of fish as five years 
ago, and only 6.4 percent in Sava and 0.6 percent in Menabe thought it was easier. When probed about 
reasons for their answers, for those that think it is harder, 68 percent in Sava mentioned increases in 
local fishermen competition (only 15 percent mentioned outside fishermen competition), 32.7 percent 
mentioned general climate change.
15 For those who thought it is harder, 14 percent attribute the 
decrease in CPUE to the increase in effort from environmental regulations, and eight percent thought 
decreases in environmental regulation were the reason for the decrease in catch per effort; in Menabe, 
similarly 64 percent mentioned climate change as the reason for CPUE decrease, while 43 percent cited 
an increases in local fishermen competition (16 percent outside fishermen competition). 
15 We did not ask to clarify what part of climate change they perceive to be the driver.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Easier
Same
Harder
Much harder
Decrease in industrial fishing
Climate change
Decrease in local fisherman competition
Increase in environmental regulation
Decrease in environmental regulation
Increase in industrial fishing activities
Climate Change
Increase in local fisherman competition
Increase in outside fisherman competition
Increase in environmental regulation
Decrease in environmental regulation
In general, has it gotten
easier ot harder to catch the
same amount of fish as y
Reason if easier Reason if harder
Perception of CPUE Change
Total Sava Menabe
Figure 24: Perception of CPUE change by region
PERCEPTION OF ENVIRONMENTAL CHANGE 
To gauge perceptions of change in natural resource availability, the study asked whether there is enough 
mangrove wood in the forest and fish in the sea to provide for the needs of everyone who lives in the 
community, both currently and when the respondent was a child. Results are presented in Figure 25. 
More respondents perceive mangrove wood provision to be enough in Sava than in Menabe. In Sava, 31 
percent of HHs perceive it as not being enough in the past and not being enough now, while 32 percent 
perceive it to be enough in the past and not enough now. In Menabe, most HHs (65 percent) believe
mangrove wood to be enough in the past and now, while 22 percent perceived enough in the past but 
not enough now, and 12 percent perceived it to be not enough in the past and not enough now. For the 
HHs that perceived there to be enough in the past but not enough now, the survey asked why. The 
majority of these HHs (52 percent in Sava and 69 percent in Menabe) attributed it to cutting mangroves 
INRM Madagascar Nosy Manga Baseline Report 55
to build houses. In Sava, respondents reported that more people in the village and cutting mangroves to 
make lime16 to strengthen house durability are also major reasons. In Menabe, making sokay and building 
fences are also major reasons, while 36 percent of HHs in both regions also mentioned using mangrove 
wood for fuel as a reason. 
With regards to fish stock in the sea, the majority of HHs (73 percent in Sava and 87 percent in 
Menabe) perceive having enough fish in the sea to provide enough food for everyone who lives in the 
community; 26.8 percent in Sava and 10.5 percent in Menabe perceive having enough in the past but 
not enough now. Among the respondents that perceive fish stock to have declined, 59.3 percent in Sava 
and 39 percent in Menabe attribute the decline to an increase in the number of fishermen in the village. 
About 22 percent across the regions attribute the decline to the use of destructive fishing gear and 
methods. In Menabe, 21 percent also note the increase in village population as a cause. Some HHs also 
mention environmental reasons, including climate change, the lack of rain, and degradation of coral. 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Enough in
the past,
enough now
Not enough
in the past,
enough now
Enough in
the past, not
enough now
Not enough
in the past,
not enough
now
Enough in
the past,
enough now
Not enough
in the past,
enough now
Enough in
the past, not
enough now
Not enough
in the past,
not enough
now
Mangrove wood provision past and now Fish stock provision past and now
Perception of Environmental Change
Total Sava Menabe
Figure 25: Perception of environmental change by region
16 The material locally known as sokay is a “sea-shell based lime produced in mangrove wood kilns and used as a render on 
houses.” It is considered a status symbol and is often related to rise in household income (Scales et a., 2017). 
INRM Madagascar Nosy Manga Baseline Report 56
PERCEPTION OF ENVIRONMENTAL DEGRADATION 
The study asked each respondent whether they think the natural environment is healthy or degraded 
on a scale of one-to-four (one being very degraded and four being very healthy). Responses are 
presented in Figure 26. 
About 56 percent of respondents across regions think the overall state of the natural environment is 
degraded or very degraded (average score of 2.3 across regions). When asked about the overall state of 
coral, about 44 percent of HHs answered that it was degraded or very degraded (average score of 2.5 
across regions). With regards to mangroves, more HHs in Menabe perceive it to be degraded or very 
degraded (34 percent, an average score of 2.6) than in Sava (20 percent, an average score of 3). Similarly 
for lagoon health, 44 percent of HHs in Menabe perceive the state of lagoons to be degraded or very 
degraded (average score of 2.5) compared to 31 percent of HHs in Sava (an average score of 2.7). 
When asked about threats to these ecosystems, about 65 percent of HHs across the region perceive 
that there are threats, with most respondents mentioning multiple threats. Out of the respondents that 
perceive threats to local ecosystems, climate change is most mentioned as a threat in both regions (58 
percent). Illegal/ unsustainable logging is also mentioned often (31 percent across regions) as well as 
illegal/unsustainable fishing (25 percent across regions). In Sava, unsustainable farming is also mentioned 
by 18 percent of respondents. Some other responses mentioned are land clearing in Menabe, and fire, 
drought, cyclones, and climate change in Sava. Figure 27 presents the major threats mentioned in each 
region. 
INRM Madagascar Nosy Manga Baseline Report 57
4%
53%
42%
1% 2%
44%
52%
2% 4%
58%
37%
1% 3%
40%
56%
1% 3%
52%
43%
1% 2%
45%
51%
3%
0%
10%
20%
30%
40%
50%
60%
70%
Very
degraded
Degraded Healthy Very healthy Very
degraded
Degraded Healthy Very healthy
Perception of the overall state of natural
environment
Perception of the overall state of corals
Perception of Environmental Degradation 1
Total Sava Menabe
6%
31%
57%
6% 4%
38%
58%
1% 1%
20%
59%
20%
2%
30%
67%
1%
7%
34%
57%
3% 4%
40%
56%
0%
0%
10%
20%
30%
40%
50%
60%
70%
Very
degraded
Degraded Healthy Very healthy Very
degraded
Degraded Healthy Very healthy
Perception of the overall state of mangroves Perception of the overall state of lagoon
Perception of environmental degradation 2
Total Sava Menabe
Figure 26: Perception of environmental degradation by region
INRM Madagascar Nosy Manga Baseline Report 58
30.00%
38.20%
7.30%
32.70%
49.80%
18.60%
6.20%
10.40%
31.20%
17.30%
0.40%
22.70%
58.30%
0.20%
13.60%
5.40%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
Illegal/unsustainable logging
Slash-and-burn agriculture
Poaching/hunting for
consumption
Illegal/unsustainable fishing
Climate change impacts
Unsustainable farming
Pollution
Other
Percieved Human-Caused Threats to the Environment
Sava Menabe
Figure 27: Perceived threats to the environment
AQUACULTURE PRACTICES 
The study also asked seaweed farming HHs about decision-making on seaweed sales, and gender 
dynamics in seaweed farming and decision-making. Seaweed farming is only undertaken by HHs in 
Menabe in the sample (18 percent of HHs in Menabe). About 88 percent of seaweed farming HHs say 
that they sell the produce to someone in particular, and of these HHs, 78 percent sell to intermediary 
collectors. In the 22.4 percent that mention selling to other actors, when asked to elaborate, 31 percent 
mentioned selling to the person who trained them and gave them seaweed to farm. Some specifically
mention BV, OF, and WWF. 
Across Menabe, HHs report, on average, an equal number of female and male HH members farming 
seaweed. Table 18 displays the average intra-HH gender breakdown of seaweed farming and decision￾making on seaweed sales. About 41 percent of seaweed farming HHs have only male HH members 
farming seaweed, 45 percent have only female members farming it, and 15 percent have both male and 
female engaged in it. HHs report more female HH members making decisions about seaweed sales than 
male HH members, with 15 percent of HHs reporting only male members makings decisions, 50 percent 
reporting only females making decisions, and 36 percent reporting both female and male members 
making decisions. 
INRM Madagascar Nosy Manga Baseline Report 59
Table 18: Within household gendered behavior and decision-making of seaweed farming
Percent of seaweed 
farming HHs
HH members who farms seaweed
male only 40.5
female only 44.5
both male and female 15.0
Total 100.0
HH members who makes decisions about seaweed sales
male only 14.5
female only 49.5
both male and female 36.0
Total 100.0
ATTITUDE TOWARDS AQUACULTURE
The study asked respondents if they thought seaweed and sea cucumber farming is good or bad for the 
village. The respondents answered on a scale of one-to-four, where one is very bad and four is very 
good. The results are presented in Figure 27. Although most respondents have a positive attitude 
toward aquaculture, HHs in Menabe have a better perception of aquaculture than those in Sava. On 
average, HHs in Menabe said seaweed and sea cucumber farming is good and very good (average score 
of 3.18), whereas HHs in Sava on average answered that it is either bad or good (an average score of 
2.78). In other words, only seven percent of HHs in Menabe answered that it is very bad or bad; 66 
percent answered that it is good, and 26 percent answered that it is very good. In Sava, 25 percent 
answered that it is very bad or bad; 71 percent answered that it is good and only four percent answered 
that it is very good. 
When probed about the reason behind their answer (Figure 28), most respondents had more than one 
reason. For the HHs with positive views, 96 percent mentioned jobs and income provision (18 percent
of women respondents mentioned this). About 16 percent also mentioned raising the status of the 
village. Very few (2.4 percent) mentioned protecting marine areas as a benefit of aquaculture. In Sava, 
INRM Madagascar Nosy Manga Baseline Report 60
some households (3.5 percent) mentioned ethnic groups working together as a benefit, whereas in 
Menabe this reason was barely raised. 
The majority of respondents with negative attitudes towards aquaculture see the curbing of fishing 
activities as a harm to the community brought by aquaculture. In both regions, the loss of fishing 
livelihoods was the most mentioned reason among respondents that view aquaculture negatively, 
mentioned by 92 percent of negative respondents in Menabe and 76 percent of respondents in Sava. In 
Sava, 64 percent of respondents also thought that aquaculture could bring social conflict to the village 
regarding marine area use, and 21 percent mention that it brings social conflict regarding who gets 
selected as a farmer. Other reasons mentioned in Sava include wrath from farming on sacred land, 
seaweed farmers not being able to practice other marine-based subsistence activities, and the 
disturbance to fishing activities in the village for subsistence. In Menabe, aside from the loss of fishing as 
a livelihood, 14.7 percent of respondents that view aquaculture negatively also mentioned social conflict 
regarding marine area use as a reason. In Menabe, a number of respondents also noted disturbance of 
water flow and the site in the village not being suitable for seaweed farming. 
2%
23%
71%
4%
Perception of seaweed and sea 
cucumber farming on the village 
(Sava)
Very bad Bad Good Very good
1% 6%
66%
26%
Perception of seaweed and sea 
cucumber farming on the village 
(Menabe)
Very bad Bad Good Very good
Figure 28: Attitude towards aquaculture
INRM Madagascar Nosy Manga Baseline Report 61
93%
3%
16%
4%
13% 14%
0%
21%
65%
1%
76%
23%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Provides jobs and income for
more people in the village
Protects marine areas
Provides jobs and income for
women
Ethnic groups work together
Raise status of village
Other
Social conflict from who gets
selected as farmer
Social conflict regarding marine
area use
Loss of ethnic identity
Loss of fishing as livelihood
Other
Perceived benefits Perceived harms
Attitude Towards Aquaculture (Sava)
96%
2%
19%
0%
16%
2% 0% 0%
15%
0%
92%
9%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Provides jobs and income for
more people in the village
Protects marine areas
Provides jobs and income for
women
Ethnic groups work together
Raise status of village
Other
Social conflict from who gets
selected as farmer
Social conflict regarding marine
area use
Loss of ethnic identity
Loss of fishing as livelihood
Other
Perceived benefits Perceived harms
Attitude Towards Aquaculture (Menabe)
Figure 29: Reasons given for the positive and negative perception of aquaculture.
INRM Madagascar Nosy Manga Baseline Report 62
MARINE RESOURCE MANAGEMENT DECISION-MAKING 
AND PARTICIPATION 
The study asked about the existence and participation in LMMA, as well as decision-making power and 
local participation in marine management in general. Figure 29 presents the results. This section also 
incorporates results from the long community survey with local fishery leaders regarding village 
participation in LMMAs. 
Seventy-one percent of HHs in Sava have heard of LMMA compared to 57 percent in Menabe. The 
community leader long surveys indicate that all of the Sava’s six study villages have LMMAs, and nine out 
of 11 of the study villages in Menabe have them. About 41 percent of HHs in Sava and 24 percent in 
Menabe attend LMMA meetings. According to community leaders, except for one village in Sava, all 
villages are part of the LMMA if there is an LMMA that governs their marine area. Of the villages that 
are part of an LMMA, all villages have a representative that attends the LMMA meetings. 
However, their perception of the ability of village leaders to influence decisions of the LMMA varies. 
Village fishery leaders were asked if they agreed with the statement: "If the LMMA makes a decision or 
acts in a way that the village leader disagree with, there are ways for the village to express disagreement 
and influence the decision of the LMMA" (Table 19). Four out of nine leaders in Menabe disagree (four 
agree) and three out of five leaders disagree (one agrees and one strongly agrees). When asked whether 
the people in the village are generally satisfied with the decisions of the LMMA, the response is mostly 
satisfied or very satisfied in Menabe (five said satisfied and two said very satisfied), and mostly dissatisfied 
in Sava (three dissatisfied). 
Table 19: Community survey responses of village relation with LMMA, by region 
MARINE RESOURCE DECISION-MAKING AND VILLAGE GOVERNANCE 
Do you agree with the following statement" "If the 
LMMA makes a decision or acts in a way that the village 
leader disagree with, there are ways for the village to 
express disagreement and influence the decision of the 
LMMA."
Are people in the village generally satisfied with the 
decisions of the LMMA?
Menabe Sava Total Menabe Sava Total
Disagree 4 3 7 Dissatisfied 1 3 4
Neither agree nor 
disagree
1 0 1 Neither satisfied 
nor satisfied
1 1 2
Agree 4 1 5 Satisfied 5 1 6
Strongly agree 0 1 1 Very satisfied 2 0 2
Total 9 5 14 Total 9 5 14
When asked about how important marine resource decisions are made (Figure 30), while most HHs 
mention multiple sources of decision-making, 28 percent mention NGOs as the only or main decision￾INRM Madagascar Nosy Manga Baseline Report 63
maker. In Sava, the actors most mentioned are NGOs (61 percent) and LMMAs (55 percent), while 27 
percent of HHs mentioned COBA/VOI (community-based organizations). Only a minority of HHs 
mentioned village president (seven percent), fokontany (nine percent), and communes (seven percent). 
In Menabe, LMMAs take a smaller role and local decision-makers take a larger role. Households mention 
marine decision-makers to be mainly NGOs (46 percent), communes (33 percent), village presidents (25 
percent), COBA/VOI (23 percent), government ministries (21 percent), and fokontany committees (10 
percent), while only seven percent mention LMMAs. Few in either region mention regional/district 
government (eight percent). 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
No Yes No Yes
Heard about locally managed marine areas (LMMAs)
before today
Have you or any family members participated in
LMMA meetings?
LMMA Existence and Participation Rates
Total Sava Menabe
Figure 30: LMMA existence and participation rates, region 
INRM Madagascar Nosy Manga Baseline Report 64
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Village president
Fokontany committee
Commune
Region/district
Government ministry
COBA/VOI
NGO
Private sector
LMMA
Other
How important decisions about marine resources are made in village
Natural Resource Decision-Making
Total Sava Menabe
Figure 31: NRM decision-making actors, by region
Figure 31 presents HH responses for questions regarding general village governance, not necessarily 
related to resource management. Village decision-making is more participatory in Sava, with 68 percent 
of HHs indicating that group decisions are made by the whole villages instead of by the president (48 
percent). Village meetings are held more often and attended more often. In Menabe, most village 
decisions are made by the village president (51 percent), and village meetings are held less frequently 
and attended less often.
INRM Madagascar Nosy Manga Baseline Report 65
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
By the village president
The most respected elders in the
village
By the whole village, at a meeting
Other
Once a year or less
A few times a year
Every month
Every few weeks
Every week
Never
only certain meetings
The majority of meetings
For all meetings
Not confident at all
Somewhat condifent
Confident
Very confident
How group decisions
are usually made in the
village
How often public village
meetings are held
How often household
attends these village
meetings
Confidence about
speaking at public
meetings
Village Governance
Total Sava Menabe
Figure 32: Village governance by region
RESOURCE MONITORING PARTICIPATION 
Figure 32 presents the prevalence and type of participatory resource monitoring efforts by region. With 
regards to participation in resource monitoring efforts, more HHs in Sava (29 percent) participate than 
in Menabe (15 percent). In Menabe, the monitors tend to be compensated in cash (43 percent of 
monitoring HHs were compensated), and in Sava only eight percent of monitoring HHs were 
compensated. However, participating HHs across regions mostly perceive no benefits from participating 
(56 percent of participating HHs). Across regions, more males participate in monitoring, with 27 percent 
and 14 percent of HHs having a male member participating in resource monitoring in Sava and Menabe, 
respectively, compared to two percent of households having a female HH member participating in both 
regions. In Sava, the monitoring activities include fish catch size tracking (58 percent), control of 
protected areas (52 percent), assessment of catches (37 percent), and some ecological monitoring (11 
percent). In Menabe, the monitoring activities include control of protected areas (56 percent), fish catch 
size tracking (31 percent), and ecological monitoring (23 percent). Across regions, HHs also mention 
frequent participation in fish gear and nets monitoring, as well as night diving and fishing monitoring in 
Sava. 
INRM Madagascar Nosy Manga Baseline Report 66
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
No
Yes
No
Yes
No
Yes
In cash
In kind
Both
Assessment on catches
Catch fish size tracking
Ecological monitoring
Mapping of village boundaries
Control of protected areas
Other
Household
participation
in resource
monitoring
efforts
Has your
household
benefited
from
participating
in this
activity?
Are they
compensated
for it?
How? What do they do?
NRM Monitoring Activities
Total Sava Menabe
Figure 33: NRM monitoring activities by region
ATTITUDE TOWARDS NRM RULES
The study asked about the existence of a range of resource management rule types, including long-term 
closures, temporary closures, fishing gear restrictions, community aquaculture project closures, 
mangrove access restrictions in respondents’ commune. The responses are presented in Figure 33. For 
those that answered that a rule-type exists, the study asked if the respondent would like more or less of 
the rule (Figure 36). For those that answered that a rule does not currently exist, the study asked
whether respondents would like that type of rule in their commune (Figure 37). 
Unsurprisingly, due to the prevalence of LMMAs, in Sava, almost all HHs report there to be fishing gear 
restrictions (100 percent), temporary closures (99 percent), mangrove closures (90 percent), and 
permanent closures (87 percent). Only 4.2 percent of HHs report there being aquaculture closures. 
Menabe HHs report fishing gear restrictions (86 percent), mangrove closures (81 percent), temporary 
closures (79 percent), permanent closures (46 percent), and aquaculture closures (9.2 percent). 
INRM Madagascar Nosy Manga Baseline Report 67
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Prohobit fishing in
certain areas for
the long term (Yes)
Close off areas
temporarily (usually
3 months) and
prohibit fishing
(Yes)
Close off areas for
community
seaweed or sea
cucumber farming
(Yes)
Restrict the type of
fishing gear you can
use when you go
fishing (Yes)
Restrict areas of
mangroves where
people cannot go
to collect wood
(Yes)
Do rules like these exist in your commune?
Existence of NRM Rules 
Total Sava Menabe
Figure 34: Existence of NRM rules 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Big reduction Small reduction Stay the same A little more Much more
In general, would you like greater or fewer rules surround marine and mangrove use?
General Attitude Towards NRM Rules
Total Sava Menabe
Figure 35: General attitude towards NRM rules
INRM Madagascar Nosy Manga Baseline Report 68
When asked about their preference for more or less rules, the HHs gave divided answers, especially in 
Menabe. When asked about marine and mangrove use rules in general, 60 percent of HHs in Sava and 
50 percent of HHs in Menabe want the number of rules to stay the same. In Sava, 24 percent of HHs 
want more rules and 16 percent want less rules. In Menabe, 31 percent of HHs want more rules and 18 
want less rules. Figure 26 shows the breakdown of the attitude towards NRM rules by type of rules. 
The majority of HHs do not have aquaculture closures in their communes (96 percent in Sava and 91 
percent in Menabe). In Sava, out of the HHs that do not currently have aquaculture closures, 64 
percent would not like to have aquaculture closures. Their attitudes on mangrove and temporary 
closures are more positive, with 88 percent wanting mangrove closures and 77 percent wanting 
permanent closures for the extreme minority of HHs not having them. In Menabe, 83 percent of HHs 
without aquaculture closures in their commune do not want them. In general, HHs in Menabe that do 
not report NRM rules in their commune do not want new rules. 
Of the minority of HHs that have aquaculture closures in their commune in Sava, 27 percent would like 
a small reduction, 21 percent would like a little more, and 52 percent would like it to stay the same. In 
Menabe the attitude is even more divided, where of the minority of HHs that have aquaculture closures 
in their commune, 37 percent want much more, 11 percent want a little more, 32 percent want either a 
big or small reduction, and only 20 percent want it to say the same. 
INRM Madagascar Nosy Manga Baseline Report 69
2%
21%
57%
16%
5% 1% 7%
69%
19%
4% 0%
27%
52%
21%
0% 1%
13%
69%
11% 6% 4%
64%
30%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Big reduction
Small reduction
Stay the same
A little more
Much more
Big reduction
Small reduction
Stay the same
A little more
Much more
Big reduction
Small reduction
Stay the same
A little more
Much more
Big reduction
Small reduction
Stay the same
A little more
Much more
Decrease
Stay the same
Increase
Preference for change
in longterm closures
Preference for change
in temporary closures
Preference for change
in aquaculture
closures
Preference for change
in gear restriction
rules
Preference
for change in
mangrove
closures
Preference for Change in NRM Rules 
(Among HHs who report no current existence of rule type in commune)
Sava
3%
16%
31%24%27%
6%
21%
47%
15%11%11%
22%20%
11%
37%
11%
19%
34%
22%
14%18%
43%40%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Big reduction
Small reduction
Stay the same
A little more
Much more
Big reduction
Small reduction
Stay the same
A little more
Much more
Big reduction
Small reduction
Stay the same
A little more
Much more
Big reduction
Small reduction
Stay the same
A little more
Much more
Decrease
Stay the same
Increase
Preference for change
in longterm closures
Preference for change
in temporary closures
Preference for change
in aquaculture
closures
Preference for change
in gear restriction
rules
Preference
for change in
mangrove
closures
Preference for Change in NRM Rules 
(Among HHs who report no current existence of rule type in commune)
Menabe
Figure 36: Preference for change in NRM rules
INRM Madagascar Nosy Manga Baseline Report 70
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Yes Yes Yes Yes Yes
Preference for
longterm closures
Preference fo
temporary closures
Preference for
aquaculture closures
Preference for gear
restriction rules
Preference for
mangrove closures
Preference for NRM Rules 
(Among HHs who report no current existence of rule type in commune)
Total Sava Menabe
Figure 37: Preference for NRM rules
The study ran bivariate and multivariate regressions to investigate which HH characteristics are most 
associated with more positive attitudes towards aquaculture and aquaculture closures. These 
characteristics included those related to commercial and subsistence use of fish catches, poverty, 
experience with aquaculture closures, experience with aquaculture, attitudes on temporary closures in 
general, attitudes on NRM rules in general, and perceived ability to influence NRM rules. For the 
bivariate regression, the study team excluded seaweed farming HHs from the sample after learning from 
the multivariate regression that seaweed farming is highly correlated with positive aquaculture views. 
Table 20 displays the bivariate regression results. HHs with positive views on aquaculture tend to have a 
HH size about one person larger, are less likely to be a fishing HH, earn a lower percentage of their HH
income from fishing, and also use a lower percentage of their fishing catch for HH consumption. In other 
words, HHs with positive views of aquaculture rely on fishing less for commercial and subsistence use. 
None of the NRM participation and environmental perception indicators are statistically significantly 
correlated with aquaculture views in a bivariate analysis. 
INRM Madagascar Nosy Manga Baseline Report 71
Table 20: Difference between non-seaweed farming households with positive view of aquaculture and negative view of aquaculture.
Non-seaweed
farming HHs only
Positive views of 
aquaculture
Negative views of 
aquaculture Difference
N Mean (SD) N Mean (SD) Diff. p-val
HH demographics
HHH education 
(category) 104.00 2.00 414.00 1.72 0.28 0.30
Household size 106.00 3.61 422.00 4.40 -0.79 0.05* 
Native to the village 106.00 0.57 422.00 0.49 0.07 0.46
Fishing HH 106.00 0.74 422.00 0.52 0.22 0.01**
Gleaning HH 106.00 0.31 422.00 0.15 0.15 0.14
Monthly HH income 106.00 628,047.12 422.00 432,866.25 195,180.87 0.32
Poverty status (below 
$1.90/day poverty line) 106.00 0.17 422.00 0.36 -0.19 0.00***
Fishing reliance
Income from fishing 106.00 251,349.54 422.00 152,688.87 98,660.67 0.26
Percentage of HH 
income from fishing 106.00 49.81 422.00 35.04 14.76 0.07+ 
Percentage of catch used 
for HH consumption 76.00 21.60 283.00 15.35 6.24 0.02* 
Land clearing practices
Cleared land in the past 
year 
106.00 0.09 422.00 0.05 0.04 0.27
Intend to clear land in 
the next 12 months 105.00 0.31 422.00 0.24 0.08 0.38
NRM participation
Participate in LMMA 
meeting 
67.00 0.50 274.00 0.45 0.05 0.67
Preference for more 
NRM rules 105.00 0.37 411.00 0.20 0.17 0.41
Perception of having 
influence over NRM 
decisions
106.00 1.46 419.00 1.34 0.12 0.41
INRM Madagascar Nosy Manga Baseline Report 72
INRM Madagascar Nosy Manga Baseline Report 73
Non-seaweed
farming HHs only
Positive views of 
aquaculture
Negative views of 
aquaculture Difference
N Mean (SD) N Mean (SD) Diff. p-val
Environmental Perception
Perceived fishing catch 
increase/decrease in the 
past 5 years
82.00 3.99 303.00 4.10 -0.11 0.12
Perceived health of 
overall state of the 
natural environment 
106.00 2.33 419.00 2.37 -0.04 0.79
Perceived existence of 
threats to local 
ecosystems 
104.00 0.65 417.00 0.61 0.05 0.64
Perceived health of 
corals 100.00 2.68 391.00 2.49 0.19 0.06+ 
Perceived health of 
mangroves 
82.00 2.72 404.00 2.61 0.11 0.56
Perceived health of 
lagoon 93.00 2.65 386.00 2.51 0.14 0.40
Table 21 and Figure 38 displays the results of the multivariate regressions, where the team looked at 
association of each variable while controlling for the association of other characteristics. For attitudes 
on the benefits or harm of aquaculture for the village (Model 1), after controlling for the more positive 
attitude in Menabe that may be due to regional differences aside from HH characteristics, seaweed 
farming HHs tend to view aquaculture 0.31 points more positively on a scale of one-to-four. Two 
characteristics negatively associate with aquaculture attitudes. All else equal, a HH that uses more of its 
fishing catch for HH consumption tends to think of aquaculture more negatively. The perception of a 
higher ability to influence NRM decisions also negatively influences aquaculture attitudes. Other 
characteristics are not statistically significantly associated with attitudes towards aquaculture. 
The study also estimated a model adding perception of fishing CPUE change in the past five years as an 
explanatory variable, and only estimating the model with the fishing households as our sample. 
Controlling for all other variables, the perception of CPUE change has no statistically significant effect on 
perception of aquaculture and the coefficient size is also close to zero. The team also looked at pair￾wise correlations between the perception of fishery CPUE change and perception of aquaculture, and 
the result shows that the two characteristics are not correlated with each other (0.06 with p=0.13).
Regarding support for closing marine sites for aquaculture, having a positive attitude towards temporary 
closures in general is associated with an increase in support for closures for aquaculture. However, 
being a seaweed farming HH decreases support for closures for aquaculture by about the same 
magnitude. Percentage of income from fishing is also associated with support for aquaculture closure, 
but not by a substantively meaningful magnitude. 
Table 21: Linear regression of HH characteristic on perception of aquaculture and support for aquaculture closures
Model 1:
Do you think
seaweed and sea 
cucumber farming 
is good or bad for 
the village?
Model 2:
Would you like a rule like 
[aquaculture closures] in your 
[commune name] or no?
b/t b/t
HH is below $1.90/day poverty line 0.10
(1.12) 
-0.08
(-1.32)
Percentage of fishing catch used for HH food -0.01*
(-2.55)
0.00
(0.45) 
Percentage of HH income from fishing 0.00
(1.23) 
0.00
(1.59) 
Seaweed farming HH 0.31**
(3.08)
-0.21***
(-3.59)
Have existing closures for aquaculture in commune 0.08
(0.30) 
Support for longer temporary marine closures -0.04
(-0.66)
0.05
(1.34) 
General support for more NRM rules 0.13
(1.86) 
0.08*
(2.10) 
Perceived ease of influencing village NRM decisions -0.10**
(-3.15) 
0.05*
(2.02) 
Menabe 0.36***
(4.46)
-0.09
(-1.57)
N 551 506
r2 0.21 0.19
INRM Madagascar Nosy Manga Baseline Report 74
Figure 38: Coefficient plot of regression on perception of aquaculture. 95% confidence interval
INRM Madagascar Nosy Manga Baseline Report 75
LEARNING QUESTIONS 
The Nosy Manga MEL framework contains two learning questions (LQs) regarding the potential impact 
of seaweed farming which the HH baseline survey can inform. The study investigated the difference in 
expected HH and village-level outcomes between existing seaweed farming HHs and non-seaweed 
farming HHs, as well as the different proportion of seaweed farming HHs in the village. However, it is 
important to keep in mind that the baseline data can only provide information on the association of key 
characteristics and behavior with seaweed farming but cannot attribute the cause of the difference to 
seaweed farming. 
The study was unable to make causal claims attributing seaweed farming to the differences observed 
between HHs because of possible selection bias. Whether a HH farms seaweed, and whether a village 
has more seaweed farming activities, are not due to random decisions. It is very plausible that HHs and 
villages with certain pre-existing characteristics are more likely to adopt seaweed farming. Thus, the 
study cannot rule out the possibility that differences observed between seaweed farming HHs and non￾seaweed farming HHs, as well as differences between villages with lots of seaweed farming activities and 
villages with no seaweed farming, are due to pre-existing differences in HHs and villages that are more 
prone to adopt seaweed farming activities, instead of due to changes from seaweed farming. 
LEARNING QUESTION 1 
How farmer recruitment criteria (as well as the technical support to farmers) can influence final results in terms 
of substitution of unsustainable practices, poverty reduction (most vulnerable) and community engagement (buy￾in from community leadership and willingness to engage into project activities)? 
For LQ1, investigating the association between seaweed farming and HH resource use behavior, well￾being and engagement in resource governance can shed light on the possibility that selection of farmers 
can maximize impact. The study looked at differences in key outcome characteristics between existing 
seaweed farming and non-seaweed farming HHs in villages with seaweed farming, while controlling for 
other HH characteristics. 
The study regressed whether a HH undertakes seaweed farming on several outcomes: unsustainable 
practices (over-fishing captured through income from fishing, average catch amount per trip, as well as 
land clearing behavior and intention), engagement with LMMA (participating in LMMA or local 
government), and perception of environmental degradation and environmental threat. The coefficient of 
seaweed farming from the multivariate analysis are displayed in Table 22. The HH demographics 
controlled for include gendered household head type, HH head education, HH size, native or immigrant, 
fishing HH, gleaning HH, HH ethnic category, and HH monthly income. Through a comparison of 
difference test (pair-wise t-test), the study learned that seaweed farming HHs tend to be less educated, 
more likely to be native to the villages, and more likely to be a fishing HH. HH size, gleaning practice, 
monthly income, and poverty status are not statistically significant between the two groups (Result 
provided in Appendix B). 
After controlling for these HH characteristics, including HH monthly income, the result shows that 
seaweed farming HHs earn 60,367 Ariary (USD 13.73) less income from fishing and rely about eight 
INRM Madagascar Nosy Manga Baseline Report 76
percent less on fishing for monthly income (statistically significant at the p<0.10 level). This shows that 
seaweed farming HHs rely less on fishing for their livelihood, thus may be less prone to engage in 
overfishing. Seaweed farming is not statistically correlated with land clearing behavior and intention to 
clear land. However, the existing seaweed farming HHs in the sample are located in Menabe where land 
clearing behavior is less prominent. 
Seaweed farming is not statistically correlated with any of the participation outcome variables in the 
multivariate analysis, including participating in LMMA, being an active member of the local government, 
attending village meetings and confidence to speak at public meetings. With regard to environmental 
perception, seaweed farming HHs view that the state of the mangroves are healthier, and they perceive 
a greater decline in fishing catches in the past five years (significant at the p<0.10 level). However, being 
a seaweed farming HH has no effect on perception of the health of other resources, nor impression of 
threat to the environment. 
Table 22: Coefficient of Seaweed farming on models each regressing seaweed farming on key Nosy Manga outcomes of interest, 
controlling for HH demographics
Outcome (Dependent variable)
Coefficient of 
Seaweed farming 
HH
p-value of coefficient
Poverty
households below $1.90/day poverty line 
(Predicted) -0.01 0.93
Fishing reliance
Income from fishing -60,367.02 0.03 * 
Percentage of HH income from fishing -8.14 0.07 + 
Percentage of HH income from gleaning 5.05 0.03 * 
Land clearing practices
Cleared land in the past year 0.03 0.63
Intend to clear land in the next 12 months -0.05 0.35
NRM participation
Participate in LMMA meeting 0.06 0.59
Preference for more/less NRM rules 0.09 0.75
Environmental Perception
INRM Madagascar Nosy Manga Baseline Report 77
INRM Madagascar Nosy Manga Baseline Report 78
Outcome (Dependent variable)
Coefficient of 
Seaweed farming 
HH
p-value of coefficient
Perceived health of overall state of the natural 
environment 
0.14 0.20
Perceived existence of threats to local ecosystems 0.11 0.21
Perceived health of corals 0.11 0.39
Perceived health of mangroves 0.28 0.02 * 
Perceived health of lagoon 0.14 0.23
Perceived fishing catch increase/decrease in the 
past 5 years 0.18 0.10 + 
LEARNING QUESTION 2
How does integrating sustainable aquaculture and creation of new livelihood opportunity in a landscape, facilitate 
local conservation initiatives and objectives and help reach improved environmental protection consensus among 
space users?
The study looked at the correlation between the proportion of village HHs that farm seaweed, and local 
conservation initiatives, local monitoring participation, and consensus on environmental protection on 
the village level. Table 23 displays the responses from community leaders of relevant questions. Among 
these villages, a higher proportion of village HHs farming seaweed are associated with greater 
satisfaction with LMMA (pairwise correlation coefficients of 0.45) and villages with conservation 
initiatives (0.55), but less village participation in resource monitoring (-0.53). Since the study had only 11
villages, no conclusions were made regarding the population of villages. This question at the village level 
is better answered by monitoring qualitative data. 
With the HH survey dataset, the study team also examined the correlation between viewing aquaculture 
positively for economic impact, and on views on health of the ecosystem, preference for more or less 
NRM rules, and engagement with village NRM decision-making. All the variables of interest are only 
weakly correlated with having a positive view of aquaculture for its economic impact (correlation 
coefficient smaller than 0.08, and not statistically significant).
Table 23: Seaweed farming prevalence in villages in Menabe, as well as community leader survey responses of village engagement with marine governance, conservation initiative, and 
existence of marine conflicts
Village
Total 
# of 
HHs
Percentag
es of HH 
that farms 
seaweed
"Are there 
any conflicts 
around 
[seaweed 
farmer's 
marine] 
access 
rights?"
"Is there 
an LMMA 
that 
governs 
the marine 
areas of 
the 
village?"
"Are people 
in the village 
generally 
satisfied 
with the 
decisions of 
the LMMA?"
"Are there 
any 
conservati
on 
initiatives 
or reserves 
in this 
village?"
"Do you feel like 
you or the village 
representative 
can influence 
important 
decisions about 
marine resource 
management?"
"Do village 
members 
participate 
in resource 
monitoring 
efforts?"
"What 
resource"?
Village 1
Under 
50 0 No No Yes Yes 
Marine, 
Forest
Village 2
Over 
500 4 No Yes 
Neither 
satisfied nor 
dissatisfied Yes Yes Yes 
Mangroves, 
Marine, 
Forest
Village 3
Over 
500 13 No Yes Satisfied Yes Yes Yes 
Mangroves, 
Marine
Village 4
50 to 
100 18 No Yes Dissatisfied No No Yes Mangroves
Village 5
50 to 
100 20 No Yes Very satisfied Yes Yes Yes 
Mangroves, 
Marine
Village 6
50 to 
100 23 No Yes Very satisfied Yes Yes Yes 
Mangroves, 
Marine
Village 7
50 to 
100 32 No Yes Satisfied Yes Yes Yes 
Mangroves, 
Marine
Village 8
50 to 
100 33 No No Yes Yes Yes Mangroves
Village 9
50 to 
100 50 No Yes Satisfied Yes Yes Yes 
Mangroves, 
Marine
Village 
10
50 to 
100 75 No Yes Satisfied Yes Yes Yes 
Mangroves, 
Marine
Village 
11
50 to 
100 93 Yes Yes Satisfied Yes Yes Yes 
Mangroves, 
Marine
INRM Madagascar Nosy Manga Baseline Report 79
Conclusions 
Several important conclusions emerge from these findings related to the difference in poverty level 
between regions, NRM governance decision-makers, drivers of opposition to aquaculture, and framing of 
restorative aquaculture programs to obtain local buy-in. 
The proportion of HHs under the poverty line, facing moderate to severe food insecurity 
and lacking basic access to electricity and water for household use is substantially higher in 
study villages in Menabe than in Sava. Excluding outliers, the average monthly income in Menabe is 
82 percent that of Sava. The HH characteristics associated with those under the poverty line are slightly 
different between Sava and Menabe. In Menabe, fishing HHs and HHs where the HH head or spouse was 
born in the village are more likely to be in poverty, compared to in Sava where HH education level is the 
HH characteristic most strongly associated with poverty. Further analysis at lower administrative levels, 
coupled with community leader responses, can be used to provide a clearer picture of the 
concentration of poverty, public service access, and profiles of the most vulnerable HHs within regions. 
Land clearing and the intention of land clearing, mostly in forested land, widely exists in 
Sava, motivated by commercial agriculture to grow more, and more diverse crops, and for 
household consumption. This practice and intention also exist in Menabe but it is less frequent. The 
percentage of income from crop farming and perception of health of mangroves, and not being under 
the poverty line, are closely associated with having the intention to clear land. 
Overall, LMMAs are more prevalent in Sava, but marine resource decision-making seems 
to be more decentralized to involve local leaders at the village, fokontany, and commune 
level in Menabe than Sava. This observation is puzzling as non-resource group decisions seem to be 
more decentralized at the village-level in Sava than in Menabe, where more group decisions are made at 
public village meetings (70 percent versus 39 percent) rather than by the village president, and where 
public village meetings are more often held and attended. However, in both regions, NGOs are 
mentioned as the most prominent actor in marine management. 
While most HHs in both regions views aquaculture positively, the results imply there may 
be some obstacles obtaining local buy-in on the Nosy Manga program in certain areas, 
especially in Sava. With regards to perception of aquaculture, the survey results indicate that the 
majority of HHs have a positive view of aquaculture (75 percent of HHs in Sava and 92 percent of HHs 
in Menabe think that seaweed and sea cucumber farming are good for the village). However, a quarter of 
HHs in Sava view aquaculture negatively in Sava compared to only eight percent in Menabe and may be 
unwilling to engage with aquaculture programs. The HH survey indicates that these HHs perceive 
aquaculture as in competition with fishing livelihoods and creating conflict on marine use. Thus, in Sava 
where HHs reported more existing conflicts around the use of marine areas for fishing, and internal 
disputes as well as disputes with NGOs regarding existing rules regulating fishing activities in marine 
areas, the support for aquaculture is lower. While most fishing HHs feel confident they can continue to 
access their fishing sites, a substantial proportion in Sava (32 percent) do not. Multivariate analysis also 
shows that after controlling for non-HH level regional differences, it is fishing for HH consumption, 
INRM Madagascar Nosy Manga Baseline Report 80
instead of for commercial exchange for income, that is associated with negative perceptions of 
aquaculture. 
Aside from competition with fishing interests, there is another reason for negative perceptions of 
aquaculture related to marine area use. For the two villages in Sava that refused to be surveyed, as well 
as indicated by some of the surveyed respondents in other villages, the local population opposes 
aquaculture programs because they perceive the identified aquaculture sites to be on their sacred land. 
Moreover, while the majority of HHs perceive aquaculture positively, there may be further obstacles 
when identifying farming sites and negotiating site access rules. When asked about the closing of marine 
areas for aquaculture as a rule, a large majority of HHs are against it (80 percent overall). 
These nuanced findings indicate the need to develop context-specific strategies for 
participant recruitment as well as negotiation of marine sites for aquaculture and rules 
regarding site access for fishing. More detailed village-level and fishing site-level analysis can be used 
to identify if these sentiments and disputes are concentrated in particular fishing sites and villages to 
tailor localized approaches. On a more positive note, HHs who currently participate in seaweed farming 
as well as those who currently have aquaculture closures in their community tend to view aquaculture 
more positively, implying that the hurdle may exist largely in initial access. 
The result also points to the need for a more qualitative understanding of how local populations connect 
their environmental perception, demand for NRM rules, and HH economic motivations connected to 
fishing. This knowledge can inform how the benefit of Nosy Manga aquaculture programs, as related to 
environmental protection and increasing fish diversity and abundance, can be better presented to local 
populations, in addition to presenting it as a viable economic and subsistence alternative to fishing 
instead of a competitor. 
Currently, only two percent of HHs overall connect aquaculture activities to marine and 
fish population protection, mostly viewing it as an economic opportunity unconnected or 
opposing fishery. However, there is local demand for conservation efforts. While most of the study 
population is opposed to marine closures for aquaculture, they are not opposed to other conservation 
initiatives. They are largely indifferent to current levels of marine and mangrove-use rules in their 
communities which are very widespread with the near-universal presence of LMMAs (with attitudes in 
Menabe being more divided). The study population does perceive their ecosystem to be degraded (57 
percent) and under threat (65 percent) by mainly climate change but also some unsustainable fishing. 
Though, despite the perception of environmental degradation and decreased fishing CPUE, the majority 
of HHs (73 percent in Sava and 87 percent in Menabe) still perceive having enough fish in the sea to 
provide enough food for everyone who lives in the community. 
INRM Madagascar Nosy Manga Baseline Report 81
APPENDIX A: Nosy Manga 
Baseline Survey Instrument 
Summary
HH Survey
• Module 1 Respondent details:
Gender, age, education, literacy, ethnicity, migration status (birthplace, time in current village,
migration reason), main occupation.
• Module 2 HH Roster:
Gender, age, education (school attendance status for under 18), literacy, main occupation.
• Module 3 HH Assets:
Household assets, transport/farm/livestock assets, pirogue ownership and borrowing/renting,
farmland ownership and rental, access to electricity, solar panel ownership. Other Poverty
Probability Index indicators.
• Module 4 Livelihood:
Three most important livelihoods for the household and proportion of income from each
source.
• Module 5 Fishery:
HH members who fish, HH monthly income from fishing activities, perceived change in CPUE,
fishery assets and its borrowing/lending:
o Per fishing site: technology used, effort, fish species, catch quantity, proportion of the
catch for selling and household consumption, who makes selling decisions, disputes
regarding site access.
• Module 6 Gleaning:
HH members who glean, HH monthly income from gleaning activities, perceived change in
CPUE:
o Per gleaning site: effort, species, catch quantity, proportion of the catch for selling and
household consumption, who makes selling decisions, disputes regarding site access.
• Module 7 Seaweed and Sea Cucumber Farming:
HH member that participates in aquaculture, HH monthly income from sea cucumber and
seaweed farming, who do they sell to, and which HH member makes selling decisions and
decisions about the use of aquaculture income (for HH’s that don’t participate in aquaculture,
we ask about awareness, attitude towards aquaculture, and perceived effect of aquaculture
activities in the village).
INRM Madagascar Nosy Manga Baseline Report 82
• Module 8 Savings, Lending, and Borrowing:
Have/does not have savings, use of savings, frequency and source of borrowing, household
income last month, mobile banking use.
• Module 9 Food Security and Coping Strategies:
HEARTH Toolkit household food security (past 12 months) and coping strategy modules.
• Module 10: Participation in Groups and Associations:
Who makes village decisions; HH participation in local groups and associations; confidence in
speaking in village meetings.
• Module 11 Participation and Attitudes Towards Resource Management:
Understanding of what resource management is, who makes village marine and mangrove
governance decisions, HH level of participation and perceived influence in meetings; LMMA
familiarity and participation; existence and attitudes towards different conservation rules, and
general attitude towards conservation and conservation rules; participation and attitudes
towards resource monitoring.
• Module 12 Energy Use and Mangrove Conservation:
Energy source, attitude towards mangrove conservation, and perception of mangrove and
marine fishery resource change; land cleaning for farming.
Community Survey (Long and Short)
• Module 1 Respondent Details (Included in Short Survey)
• Module 2 Village Infrastructure:
Primary and secondary school distance and fee, health center distance and level, market
distance, local shops supply level, existence of community center, dock, existence of active
mobile phone network and electricity supply, microfinance office, and access point distance.
• Module 3 Village Livelihoods and Marine Access Rights (in Short Survey):
Three most important village issues, village size, local ethnic groups, electricity and drinking
water access, main village livelihoods for each livelihood: # of households participating,
primarily done by women or men, primarily done by any particular ethnic group; main
fishing and gleaning practices, for each practice: # of households participating, primarily done
by women or men, primarily done by any particular ethnic group; sites for fishing and
gleaning, for each site: name, distance, user access rights, other village access, conflicts and
conflict details; seaweed and sea cucumber farming: # of households participating, primarily
done by women or men, primarily done by any particular ethnic group, marine access rights,
other village access, conflicts and conflict details.
• Module 4 Governance of Marine Areas:
LMMA existence, age, decision maker, existence of fisheries, corals and mangrove
management plans and regulations, existence of designated protected areas (where, access
INRM Madagascar Nosy Manga Baseline Report 83
rules), village membership, LMMA meeting frequency and village participation, perceived 
village influence, and satisfaction with LMMA. 
• Module 5 Local Conservation Initiatives:
Local resource management organizations, local conservation initiatives including marine
reserves, for each initiative/reserve: name, decision maker, rules, who monitors, rule
breaking, any problems.
• Module 6 Perception of Natural Resource Management (in Short Survey):
Existence and agreement regarding different resource management rules, perception of
seaweed and sea cucumber farming; for short survey, here we ask about local resource
decision making and influence; for long survey only: monitoring activities and participation.
• Module 7 Ethnic Relations (in Short Survey):
Main decision makers, perceived influence, who attends village meetings, most disadvantaged
ethnic groups, fishery dependent ethnic groups, ethnic groups’ primary fishing technology,
other non-village groups who use resource cooperative-conflictual ethnic relationship scale,
cooperative ethnic groups, ability to work together if paired.
INRM Madagascar Nosy Manga Baseline Report 84
APPENDIX B: Summary 
Statistics for Key Outcome 
Areas 
Table 12: Migration across regions
Sava Menabe Total
Percent SE Percent SE Percent SE Signif.
Raised in village since childhood
No 39.2 3.038 47.4 4.097 45.9 3.414 * 
Yes 60.8 3.038 52.6 4.097 54.1 3.414
Total 100 100 100
Migrated
Migration reason - Economic
No 22.2 4.074 27.3 5.521 26.5 4.732 * 
Yes 77.8 4.074 72.7 5.521 73.5 4.732
Total 100 100 100
Migration reason - Marriage
No 83 3.744 93.8 2.514 92.1 2.23 * 
Yes 17 3.744 6.2 2.514 7.9 2.23
Total 100 100 100
Migration reason - Conflict
No 97.4 1.31 84.6 4.666 86.5 3.99 ***
Yes 2.6 1.31 15.4 4.666 13.5 3.99
Total 100 100 100
Migration reason - Other
No 100 0 99 0.394 99.1 0.331 * 
Yes 0 0 1 0.394 0.9 0.331
Total 100 100 100
Table 13: Dwelling characteristics
Sava Menabe Total
Percent SE Percent SE Percent SE Signif.
Main material of the walls
Metal 0.5 0.33 4.5 1.94 3.8 1.6 **
Cement 0.2 0.24 2 1.24 1.7 1.02
Vondro/Ravina/ 
Palme/Zozoro/Falafa 72 2.89 60.1 4.15 62.2 3.48
INRM Madagascar Nosy Manga Baseline Report 85
INRM Madagascar Nosy Manga Baseline Report 86
Sava Menabe Total
Percent SE Percent SE Percent SE Signif.
Wood 27.3 2.87 31.9 4.06 31.1 3.38
Other 0 0 1.6 0.34 1.3 0.28
Main material of the roof
Metal 32.3 3 26.6 3.89 27.6 3.24 * 
Vondro/Ravina/ 
Bozaka 67.7 3 73.4 3.89 72.3 3.24
Other 0 0 0.1 0.06 0 0.05
Main material of the floor
Ciment 10.3 2.03 23.5 3.81 21.1 3.18 ***
Planche 30.6 2.85 8.8 2.3 12.7 1.99
Palme/ Bambou/ 
Rapaka 30.5 2.86 0.2 0.14 5.6 0.69
Ground 2.3 1.01 11.8 2.65 10.1 2.2
Woven mat 9.2 1.84 54.5 4.14 46.4 3.42
Other 17.1 2.45 1.2 0.94 4 0.92
Household access to electricity
No 23.7 2.61 72.8 3.9 64.1 3.25 ***
Yes 76.3 2.61 27.2 3.9 35.9 3.25
Table 14: Access to electricity, water, and cooking fuel 
Sava Menabe Overall
Percent SE Percent SE Percent SE Signif.
Main source of electricity
Electrical grid 0 0 3.4 3.38 2.1 2.11 . 
Solar panels 91.3 1.95 89.1 5.62 89.9 3.57
8 1.88 7.5 4.69 7.7 3 
Other 0.7 0.52 0 0 0.3 0.2
Main source of drinking water
Tap of the village 1.6 0.94 0 0 0.3 0.17 ***
Well of the 
household 7.6 1.41 10.8 2.83 10.3 2.34
Well of the village 88.2 1.82 84.4 2.86 85.1 2.37
Spring 1 0.5 0 0 0.2 0.09
River/ surface water 1.6 0.62 4.7 0.63 4.2 0.52
Main cooking fuel 
Charcoal 14.3 2.33 21.9 3.69 20.6 3.08 . 
Wood 66.4 3.03 63.7 4.13 64.2 3.44
Both 19.3 2.52 14.4 3.07 15.3 2.56
Table 15: Borrowing and lending 
Sava Menabe Total
Percent Percent Percent Signif.
Frequency of borrowing money from other people in the last year
Never 65.8 60.4 61.3 . 
Once or twice in the last year 33.8 36.2 35.8
Once per week 0.5 3 2.5
Every day, or almost every day 0 0.5 0.4
Who is borrowed from
Family 64.8 54.1 55.8
A local businessperson/shop owner 23.2 40.6 37.8
NGO 0 0.2 0.1
Other 18.9 13.1 14
In the last year, how many people have you been asked to lend money to?
None 56 50.8 51.7 . 
1-2 people 21.7 25.4 24.7
3-5 people 15.4 17.4 17.1
6-10 people 4 3.3 3.4
More than 10 people 2.9 3 3 
Table 16: Mobile money use 
Sava Menabe Total
Percent Percent Percent
Members of household using mobile money 29 32 32
Ability of household members to withdraw mobile money 93 93 93
Ability of household to use mobile money at local shops 6 9 9 
Ability of household to use mobile money to trade/send money 
to individuals 97 93 93
INRM Madagascar Nosy Manga Baseline Report 87
Table 17: Resilience – shock recovery 
All Sava Menabe
N Mean
(SD) N Mean
(SD) N Mean
(SD) Diff. p￾val
Shock severity 763 1.13 294 0.88 469 1.19 -0.31 0.06
Ability to 
recover from 
shock
222 3.07 86 2.79 136 3.12 -0.33 0.12
Corrected ARSII 
index 221 3.38 86 3.07 135 3.43 -0.36 0.09
Table 18: Resilience – social capital 
All Sava Menabe
N Mean
(SD) N Mean
(SD) N Mean
(SD) Diff. p-val
Bonding social 
capital 764 3.29 294 3.48 470 3.25 0.23 0.04
Bridging social 
capital 764 2.45 294 2.81 470 2.37 0.44 0 
General social 
capital 764 2.87 294 3.14 470 2.81 0.34 0 
Table 19: Resilience – food security (FIES)
Little or no Moderate Severe Moderate or 
severe
Percent Percent Percent Percent
Sava 76 23 1 24
Menabe 28 56 16 72
Total 35 51 14 65
Table 20: Land ownership
Sava Menabe Overall
Percent SE Percent SE Percent SE Signif.
Housing status
Owner 87.8 2.21 83.9 3.29 84.6 2.74 . 
Tenant 3.5 1.33 9.1 2.69 8.1 2.23
Lodger/friend 5.5 1.49 5.1 1.87 5.1 1.56
Other 3.2 1.19 1.9 1.24 2.1 1.04
Land ownership
No 32.1 3.12 12.5 2.78 16.1 2.37 ***
INRM Madagascar Nosy Manga Baseline Report 88
INRM Madagascar Nosy Manga Baseline Report 89
Sava Menabe Overall
Percent SE Percent SE Percent SE Signif.
Yes 67.9 3.12 87.5 2.78 83.9 2.37
Land ownership recognition by state or head of fokontany 
Not officially recognized 42.5 4.01 45.6 4.57 45.2 3.93 ***
State 20.9 3.07 45.5 4.79 41.8 4.18
Fokontany 25.4 3.42 8.9 3.17 11.3 2.73
Both 11.2 2.84 0 0 1.7 0.46
Land ownership for building a house elsewhere
No 49.2 3.15 48.5 4.11 48.6 3.42 . 
Yes 50.8 3.15 51.5 4.11 51.4 3.42
Table 21: Agricultural land and livestock ownership 
All Sava Menabe
N Mean 
(SD) N Mean 
(SD) N Mean 
(SD) Diff. p-val
Area of land farmed by 
your household (in 
ares)
395 145.66 274 176.41 121 122.6 53.81 0.04
Percentage of farmed 
land owned by HH 394 0.8 273 0.78 121 0.82 -0.04 0.6
Area of farmland
owned by your 
household (in ares)
83 128.39 3 38.41 80 130.88 -92.47 0.03
Goats 485 2.1 226 0.03 259 2.73 -2.71 0 
Sheep 485 0.01 226 0.05 259 0 0.05 0.16
Chicken or duck (or 
other poultry) 485 6.59 226 9.77 259 5.61 4.16 0 
Pig 485 0.66 226 0.01 259 0.87 -0.86 0 
Zebu 485 1.16 226 0.56 259 1.34 -0.78 0.26
Table 22: Fishing method 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Fish by boat/foot
Foot 0.4 0.45 9.6 3.25 8.1 2.74 ***
Boat 92.7 2.04 89.2 3.26 89.7 2.76
Both 6.9 2 1.2 0.42 2.1 0.5
Fish in day/night
Day 70.7 3.67 90.5 3.24 87.3 2.78 **
Night 12.3 2.7 4.1 2.18 5.4 1.88
Both 17 2.95 5.4 2.54 7.3 2.18
Fish year round
Yes 9.2 2.25 5.8 2.23 6.3 1.9 .
INRM Madagascar Nosy Manga Baseline Report 90
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
No 90.8 2.25 94.2 2.23 93.7 1.9
Fish dry season only
No 31.8 9.1 27.1 9.94 27.9 8.37 . 
Yes 68.2 9.1 72.9 9.94 72.1 8.37
Fish wet season only
No 54.2 9.96 70.7 9.85 67.9 8.27 . 
Yes 45.8 9.96 29.3 9.85 32.1 8.27
Table 23: Fishing CPUE 
Total Sava Menabe
N Mean(SD) N Mean(SD) N Mean(SD) Diff. p-val.
Average 
length 
(hours) 
per trip
563 7.08 171 5.4 392 7.4 -2 0.01
Average 
number of 
people per 
trip
541 1.87 170 2.16 371 1.81 0.35 0.03
Average 
catch (kg) 
per trip
563 14.25 171 11.09 392 14.85 -3.76 0.36
Average 
response 
to change 
in catch 
per trip
562 -0.76 170 -0.75 392 -0.77 0.02 0.8
Average 
CPUE per 
trip
541 32.41 170 35.98 371 31.66 4.32 0.46
Table 24: Acquaculture attitudes 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Perception of seaweed and sea cucumber farming on the village
Very bad 1.7 1.01 1.2 0.89 1.3 0.77 ***
Bad 23.3 3.01 6.1 1.78 8.8 1.6
Good 70.7 3.23 66.3 3.97 67 3.39
Very good 4.3 1.4 26.3 3.78 22.9 3.21
Perceived benefits
Provides jobs and income 
for more people in the 
village
93 2.06 96.4 1.64 95.9 1.45
INRM Madagascar Nosy Manga Baseline Report 91
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Protects marine areas 2.5 1.36 2.3 1.43 2.4 1.26
Provides jobs and income 
for women 15.6 2.98 18.8 3.5 18.4 3.06
Ethnic groups work 
together 3.5 1.5 0.2 0.12 0.6 0.23
Raise status of village 13.4 2.85 15.9 3.44 15.6 3.01
Other 14.1 2.72 1.9 1.33 3.5 1.22
Perceived harms
Social conflict from who 
gets selected as farmer 21.4 5.98 0 0 8.3 2.83
Social conflict regarding 
marine area use 64.6 6.88 14.7 4.94 34.1 6.71
Loss of ethnic identity 1.4 1.4 0 0 0.5 0.55
Loss of fishing as livelihood 76 6.5 92.3 3.2 86 3.8
Other 23 6.62 8.8 3.54 14.3 3.9
Table 25: Perception of environmental change 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
In general, has it gotten easier or harder to catch the same amount of fish as 10 years ago?
Easier 6.4 1.69 0.6 0.26 1.5 0.36 ***
Same 9.8 2.51 7 2.92 7.5 2.49
Harder 77.6 3.39 70.1 4.53 71.3 3.85
Much harder 6.2 2.08 22.3 4.01 19.7 3.39
Reason if easier
Decrease in industrial fishing 7 6.97 0 0 4.8 4.81
Climate change 7 6.97 62.1 22.12 24.6 10.84
Decrease in local fisherman competition 13.4 9.11 0 0 9.1 6.37
Increase in environmental regulation 52.1 13.75 0 0 35.5 11.3
Decrease in environmental regulation 7 6.97 0 0 4.8 4.81
Reason if harder
Increase in industrial fishing activities 1.2 1.23 3.6 1.58 3.2 1.36
Climate Change 32.7 4.41 64.2 4.97 59.6 4.27
Increase in local fisherman competition 68 4.21 43.1 5 46.8 4.31
Increase in outside fisherman 
competition
14.7 3.51 15.8 3.63 15.6 3.14
Increase in environmental regulation 13.8 2.83 1.6 1.49 3.4 1.35
Decrease in environmental regulation 8 2.82 2 1.69 2.9 1.5
Table 26: Perception of resource change 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Mangrove wood provision past and now
Enough in the past, enough 
now
35 3.14 64.7 4.13 59.4 3.48 ***
Not enough in the past, 
enough now 2.3 0.93 1.1 0.92 1.3 0.78
Enough in the past, not 
enough now 31.6 3.21 22.1 3.66 23.7 3.07
Not enough in the past, not 
enough now 31.1 3.13 12.2 2.72 15.5 2.34
Fish stock provision past and now
Enough in the past, enough 
now
72.9 2.94 86.8 2.96 84.3 2.49 * 
Not enough in the past, 
enough now 0.3 0.29 0.9 0.86 0.8 0.71
Enough in the past, not 
enough now 26.8 2.93 10.5 2.66 13.4 2.26
Not enough in the past, not 
enough now 0 0 1.7 1.21 1.4 0.99
Perception of the overall state of natural environment 
Very degraded 4.2 1.39 3.3 1.64 3.5 1.37 . 
Degraded 57.8 3.09 52.1 4.1 53.1 3.41
Healthy 36.9 2.97 43.3 4.02 42.1 3.34
Very healthy 1.1 0.77 1.3 0.85 1.3 0.71
Perception of the overall state of corals
Very degraded 2.8 1.2 1.9 1.25 2 1.06 . 
Degraded 40.3 3.35 44.7 4.23 44 3.58
Healthy 55.7 3.39 50.9 4.22 51.7 3.58
Very healthy 1.2 0.77 2.5 1.34 2.3 1.13
Perception of the overall state of mangroves
Very degraded 0.8 0.63 6.5 2.28 5.5 1.88 ***
Degraded 19.8 2.66 33.8 4.03 31.3 3.37
Healthy 58.9 3.2 56.6 4.21 57 3.51
Very healthy 20.4 2.57 3.1 1.26 6.2 1.17
Perception of the overall state of lagoon
Very degraded 1.9 1.02 3.9 1.82 3.6 1.53 * 
Degraded 29.5 3.15 40.2 4.27 38.4 3.61
Healthy 67.3 3.24 55.6 4.3 57.5 3.65
Very healthy 1.3 0.79 0.3 0.15 0.5 0.19
Perception of current threats to these ecosystems in community
INRM Madagascar Nosy Manga Baseline Report 92
INRM Madagascar Nosy Manga Baseline Report 93
No 27.9 2.95 36.4 3.98 34.9 3.35 . 
Yes 72.1 2.95 63.6 3.98 65.1 3.35
Table 28: Village governance 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
How group decisions are usually made in the village
By the village president 48 3.16 53.5 4.05 52.5 3.39
The most respected 
elders in the village 41.3 3.14 20.8 2.94 24.5 2.55
By the whole village, at 
a meeting
68.7 2.97 38.9 4 44.2 3.36
Other 1.2 0.67 19.2 3.26 16 2.7
How often public village meetings are held
Once a year or less 3.2 0.96 19.6 3.5 16.5 2.85 ***
A few times a year 57.1 3.12 56.5 4.21 56.7 3.46
Every month 22.1 2.62 19.1 3.11 19.7 2.57
Every few weeks 16.2 2.22 0.2 0.12 3.3 0.51
Every week 1.4 0.73 4.5 1.63 3.9 1.32
How often household attends these village meetings
Never 9.3 1.88 44.4 4.15 38.1 3.52 ***
Only certain meetings 16.6 2.34 14.4 2.86 14.8 2.39
The majority of 
meetings 
14.6 2.4 4.1 1.38 6 1.23
For all meetings 59.5 3.14 37.1 3.87 41.1 3.27
Confidence about speaking at public meetings
Not confident at all 40.6 3.15 53.9 4.12 51.5 3.43 ***
Somewhat confident 30 2.91 12.4 2.42 15.6 2.09
Confident 21.7 2.48 20.4 3.43 20.7 2.85
Very confident 7.7 1.68 13.2 2.8 12.2 2.32
Table 29: Village governance by ethnic categories 
Menabe-Veza Menabe- Sakalava Menabe- Other Sava￾Betsimisaraka Sava- Other Total
Signif
Percent SE Percent SE Percent SE Percent SE Percent SE Percent SE
How group decisions are usually made in the village
By the 
village 
president
52.4 4.76 55.3 8.71 59.5 15.14 50.4 3.43 32.6 7.81 52.5 3.39
The most 
respected 
elders in 
the village
21.7 3.62 19.2 4.14 16.7 10.94 43.7 3.43 25.6 7.29 24.5 2.55
By the 
whole 
village, at a 
meeting
39.4 4.69 31.6 7.93 50.3 15.73 65.3 3.29 90.4 4.88 44.2 3.36
Other 19.9 3.8 14.8 6.78 21.8 13.46 0 0 9 4.72 16 2.7
How often public village meetings are held
Once a 
year or less 15.5 3.64 25.7 8.48 47.6 17.6 2.9 1.01 5.1 2.89 16.5 2.85 ***
A few 
times a 
year
57.2 4.93 57.5 8.73 46.8 17.47 57.5 3.39 54.8 7.83 56.7 3.46
Every 
month 22 4.01 13 3.16 4.6 2.99 21.4 2.82 26.5 6.99 19.7 2.57
Every few 
weeks 0.3 0.16 0 0 0 0 16.6 2.43 13.7 5.5 3.3 0.51
Every week 5 2.14 3.7 1.4 1 1.07 1.6 0.84 0 0 3.9 1.32
How often household attends these village meetings
Never 43.6 4.85 41.6 9.12 57.9 15.34 9.8 2.07 5.7 4.22 38.1 3.52 ***
Only 
certain 
meetings
10.8 2.89 25.3 8.17 23.8 13.48 17 2.59 13.8 4.98 14.8 2.39
The 
majority of 
meetings
3.9 1.37 7.2 5.28 0 0 16.5 2.73 2.1 2.09 6 1.23
INRM Madagascar Nosy Manga Baseline Report 94
INRM Madagascar Nosy Manga Baseline Report 95
Menabe-Veza Menabe- Sakalava Menabe- Other Sava￾Betsimisaraka Sava- Other Total
Signif
Percent SE Percent SE Percent SE Percent SE Percent SE Percent SE
For all 
meetings 41.8 4.7 25.9 6.09 18.3 11.01 56.6 3.43 78.3 6.38 41.1 3.27
Confidence about speaking at public meetings
Not 
confident 
at all
57.7 4.77 46.2 8.95 35.9 15.01 42.6 3.44 27.6 7.18 51.5 3.43 * 
Somewhat 
confident 10.5 2.5 16.4 5.65 21.8 13.46 32.1 3.22 16.9 5.34 15.6 2.09
Confident 17.7 3.81 29 8.56 26.4 14.01 21.3 2.68 24.5 6.59 20.7 2.85
Very 
confident 14.1 3.39 8.4 4.78 16 10.86 4.1 1.32 31 7.76 12.2 2.32
Table 30: NRM governance 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Heard about locally managed marine areas (LMMAs) before today
No 28.9 3.01 43.1 4.05 40.6 3.37 **
Yes 71.1 3.01 56.9 4.05 59.4 3.37
Have you or any family members participated in LMMA meetings?
No 43 3.6 58.1 5.4 54.8 4.34 * 
Yes 57 3.6 41.9 5.4 45.2 4.34
How important decisions about marine resources are made in village
Village president 7.1 1.45 24.8 3.54 21.7 2.93
Fokontany committee 1.8 0.77 10.2 2.21 8.7 1.82
Commune 6.8 1.36 32.7 4.01 28.1 3.37
Region/district 6.3 1.32 8.4 2.38 8 1.97
Government ministry 7.5 1.37 20.6 3.24 18.3 2.68
COBA/VOI 27.2 2.63 23.3 3.57 24 2.97
NGO 61.1 3.05 46.4 4.08 49 3.42
Private sector 0.6 0.4 0.8 0.83 0.8 0.68
LMMA 55.1 3.15 6.8 1.19 15.4 1.47
Other 1 0.63 1.1 0.83 1.1 0.69
How group decisions are usually made in the village
By the village president 48 3.16 53.5 4.05 52.5 3.39
The most respected elders in
the village 41.3 3.14 20.8 2.94 24.5 2.55
By the whole village, at a 
meeting 68.7 2.97 38.9 4 44.2 3.36
Other 1.2 0.67 19.2 3.26 16 2.7
How often public village meetings are held
Once a year or less 3.2 0.96 19.6 3.5 16.5 2.85 ***
A few times a year 57.1 3.12 56.5 4.21 56.7 3.46
Every month 22.1 2.62 19.1 3.11 19.7 2.57
Every few weeks 16.2 2.22 0.2 0.12 3.3 0.51
Every week 1.4 0.73 4.5 1.63 3.9 1.32
How often household attends these village meetings
Never 9.3 1.88 44.4 4.15 38.1 3.52 ***
Only certain meetings 16.6 2.34 14.4 2.86 14.8 2.39
The majority of meetings 14.6 2.4 4.1 1.38 6 1.23
For all meetings 59.5 3.14 37.1 3.87 41.1 3.27
Confidence about speaking at public meetings
Not confident at all 40.6 3.15 53.9 4.12 51.5 3.43 ***
Somewhat confident 30 2.91 12.4 2.42 15.6 2.09
Confident 21.7 2.48 20.4 3.43 20.7 2.85
Very confident 7.7 1.68 13.2 2.8 12.2 2.32
INRM Madagascar Nosy Manga Baseline Report 96
Table 31: Attitudes towards NRM rules 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Some places prohibit fishing in certain areas for the long term. Do rules like this exist in your 
commune?
No 13.5 1.94 53.9 4.13 46.6 3.49 ***
Yes 86.5 1.94 46.1 4.13 53.4 3.49
Some places close off areas temporarily (usually 3 months) and prohibit fishing and gleaning to 
increase growth of species such as octopus, shrimp and crabs. Do rules like this exist in your 
commune?
No 1 0.64 20.6 3.39 17 2.8 ***
Yes 99 0.64 79.4 3.39 83 2.8
Some places close off areas for community seaweed or sea cucumber farming. Do rules like this 
exist in your commune?
No 95.8 1.05 90.8 2.56 91.7 2.11 * 
Yes 4.2 1.05 9.2 2.56 8.3 2.11
Some places restrict the type of fishing gear you can use when you go fishing. Do rules like this exist 
in your commune?
No 0.2 0.23 13.8 3.01 11.3 2.48 ***
Yes 99.8 0.23 86.2 3.01 88.7 2.48
Some places restrict areas of mangroves where people cannot go to collect wood. Do rules like this 
exist in your commune?
No 9.6 1.94 18.7 3.55 17.1 2.94 * 
Yes 90.4 1.94 81.3 3.55 82.9 2.94
Would like more or fewer rules? (Permanent closures)
Big reduction 1.9 1.03 2.6 2.08 2.4 1.52 ***
Small reduction 20.6 2.89 15.9 4.65 17.2 3.44
Stay the same 57 3.52 30.6 5.46 38 4.13
A little more 15.5 2.45 24.1 5.08 21.7 3.73
Much more 4.9 1.61 26.8 5.18 20.7 3.79
Would you like to see an increase or a decrease in the length of time that the reserves are closed 
for?
Big reduction 1.4 0.73 5.5 2.47 4.6 1.94 ***
Small reduction 7.1 1.57 21.2 3.93 18.1 3.09
Stay the same 68.6 2.99 47.3 4.78 52 3.81
A little more 19.2 2.57 15.4 3.54 16.3 2.81
Much more 3.8 1.21 10.6 2.78 9 2.18
Would like to have more or fewer of these? (gear restrictions)
Big reduction 0 0 10.7 10.13 9.8 9.3 . 
Small reduction 27.2 11.78 21.6 12.16 22.1 11.17
Stay the same 51.6 13.16 20.4 12.13 23 11.18
A little more 21.2 10.98 10.7 9.15 11.6 8.43
Much more 0 0 36.6 13.91 33.5 12.71
Would you like greater or fewer restrictions on the type of fishing gear you can use?
Big reduction 1.1 0.67 10.8 3.13 8.8 2.51 ***
INRM Madagascar Nosy Manga Baseline Report 97
INRM Madagascar Nosy Manga Baseline Report 98
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Small reduction 13.3 2.17 19.4 3.5 18.2 2.81
Stay the same 68.7 2.94 33.8 4.04 41 3.41
A little more 11.2 1.92 21.6 3.94 19.5 3.17
Much more 5.7 1.46 14.3 3.26 12.6 2.62
Would you like to see an increase or a decrease in the area of mangroves that is protected (where 
wood cannot be removed)?
-1 3.6 1.28 18 3.73 15.2 3.03 ***
0 64 3.22 42.5 4.5 46.7 3.71
1 29.6 3.06 39.5 4.51 37.6 3.68
97 1.6 0.94 0 0 0.3 0.19
98 1.2 0.59 0 0 0.2 0.12
Would you like a rule like this in your commune or no? (Permanent closure)
No 50.1 7.65 80.5 4.58 78.9 4.37 ***
Yes 49.9 7.65 19.5 4.58 21.1 4.37
Would you like a rule like this in your commune or no? (Temporary closure)
No 22.6 22.13 71.2 8.91 70.6 8.81 . 
Yes 77.4 22.13 28.8 8.91 29.4 8.81
Would you like a rule like this in your commune or no? (Aquaculture closure)
No 63.7 3.69 82.3 3.34 79.5 2.9 ***
Yes 36.3 3.69 17.7 3.34 20.5 2.9
Would you like a rule like this in your commune or no? (Gear restriction)
No 100 0 77.9 9.88 78 9.84 . 
Yes 0 0 22.1 9.88 22 9.84
Would you like a rule like this in your commune or no? (Mangrove closure)
No 12.5 7.2 62.6 10.5 57.6 9.57 ***
Yes 87.5 7.2 37.4 10.5 42.4 9.57
Are there other rules about natural resource use that exists in your commune?
No 93 1.63 99.8 0.12 98.6 0.32 ***
Yes 7 1.63 0.2 0.12 1.4 0.32
In general, would you like greater or fewer rules surrounding marine and mangrove use?
Big reduction 1 0.65 7.8 2.52 6.6 2.08 **
Small reduction 14.9 2.23 10.6 2.58 11.4 2.15
Stay the same 60.4 3.11 50.3 4.19 52.2 3.49
A little more 17.7 2.44 17.4 3.3 17.4 2.74
Much more 5.9 1.44 13.9 2.96 12.4 2.44 0 
Table 32: NRM monitoring 
Sava Menabe Total
Signif Percent SE Percent SE Percent SE
Household participation in resource monitoring efforts
No 70.9 2.69 84.4 2.94 82 2.47 **
Yes 29.1 2.69 15.6 2.94 18 2.47
Has your household benefited from participating in this activity?
No 54 5.17 56.7 10.23 56 7.44 . 
Yes 46 5.17 43.3 10.23 44 7.44
Are they compensated for it?
No 92 2.59 60.6 10.2 69.6 7.58 ***
Yes 8 2.59 39.4 10.2 30.4 7.58
How?
In cash 90.2 9.54 85.5 12.67 85.9 11.75 . 
In kind 9.8 9.54 1 1.01 1.6 1.26
Both 0 0 13.5 12.66 12.5 11.74
What do they do?
Assessment on catches 37.3 5.22 6.9 5.21 15.6 4.28
Catch fish size tracking 57.8 5.17 30.8 9.92 38.5 7.22
Ecological monitoring 11.4 3.66 23 9.05 19.7 6.6
Mapping of village boundaries 2.6 1.48 8.2 5.83 6.6 4.19
Control of protected areas 51.7 5.25 55.7 10.27 54.6 7.47
Other 21 4.26 13.9 5.61 15.9 4.26
INRM Madagascar Nosy Manga Baseline Report 99
APPENDIX C: Nosy Manga Full 
Baseline Survey Instrument 
INRM Madagascar Nosy Manga Baseline Report 100