Effects of anthropic dynamics on mangrove ecosystems’ degradation in Haiti

Efectos de la dinámica antrópica en la degradación de los ecosistemas de manglar en el Haití

Abstract

Anthropization process and climatic changes, mainly deforestation and sea level rise, are factors significantly contributing to the loss of mangrove ecosystems. The aim of our study is to analyze the effects of the dynamics of human activities closely associated with these ecosystems’ degradation. We identify and compare soil use and occupation variations based on information provided by 140 randomly chosen participants at the Caracol County - Haiti. The results analyzed through multivariate regression tests, the most significant exploratory variable for the mangroves’ degradation process was “mangrove occupation”, regardless of age, gender, schooling, time in the same residence, profession, home distance from the mangrove, landslide events, and risk of floods. We have concluded that distance from home, ecological function, intervention in biodiversity conservation, as well as water-climatic and geo-physical threats are factors closely correlated to mangroves’ environmental conservation and management.

Keywords:
Coastal occupation; environmental vulnerability; socioeconomic activity; The Caribbean; Mangrove

Resumo

O processo de antropização e as mudanças climáticas, principalmente o desmatamento e a elevação do nível do mar, são fatores que contribuem significativamente para a perda dos ecossistemas de mangue. A pesquisa analisou os efeitos da dinâmica das atividades humanas à degradação desses ecossistemas. Foram avaliadas as variações de uso e ocupação do solo com base em informações de 140 participantes escolhidos aleatoriamente no município de Caracol - Haiti. Os resultados mostraram que a variável mais significativa para a degradação dos manguezais foi a “ocupação do mangue”, independente de idade, gênero, escolaridade, tempo na mesma residência, profissão dos participantes, distância residência/mangue, eventos de deslizamento de terra e risco de inundações. Concluímos que a distância da residência para o mangue, função ecológica, intervenção na conservação da biodiversidade, ameaças hidroclimáticas e geofísicas são fatores correlacionados à conservação e ao manejo ambiental dos manguezais.

Palavras-chave:
Ocupação costeira; vulnerabilidade ambiental; atividade socioeconômica; Caribe; Mangue

Resumen

El proceso de antropización y el cambio climático, principalmente la deforestación y el aumento del nivel del mar, son factores que contribuyen significativamente a la pérdida de los ecosistemas de manglares. La investigación analizó los efectos de la dinámica de las actividades humanas en la degradación de estos ecosistemas. Nosotros identificamos y comparamos las variaciones en el uso y ocupación del suelo a partir de información de 140 participantes elegidos al azar en el Municipio de Caracol - Haiti. Los resultados indicó eso la variable más significativa para la degradación del manglar fue la “ocupación del manglar”, independientemente de la edad, genero, escolaridad, tiempo en la misma residencia, profesión de los participantes, distancia residencia/manglar, eventos de deslizamiento y riesgo de inundación. Concluimos que la distancia de la residencia, la función ecológica, la intervención en la conservación de la biodiversidad, las amenazas hidroclimáticas y geofísicas son factores correlacionados con la conservación y manejo ambiental de los manglares.

Palabras-clave:
Ocupación costera; vulnerabilidad ambiental; actividad socioeconómica; El Caribe; Manglar

Introduction

Mangroves are a group of trees and shrubs that live in the coastal intertidal zone (NOOA, 2017). Mangrove forests are among the most productive and biologically relevant ecosystems in the world; they form essential habitats for fish and crustaceans, which account for several ecosystem services (MAURICIO et al., 2019). Furthermore, they provide important assets and services that give support to coastal lines’ physical stability. Mangrove forests also represent habitats for refuge and nursery of several endemic marine species, as they absorb significant amount of atmospheric Carbon and, to reduce the negative effects of climatic changes (MAARTJE et al., 2018).

The mangrove is a vegetation of first occupation of edaphic character, which occupies lands rejuvenated by the repeated deposition of fluvio-marine alluvium at the mouths of rivers. For this reason, it belongs to the complex edaphic vegetation of first occupation (IBGE, 2012). The mangroves are the only tall tree forest on the Earth where land, freshwater and sea mix together. They are also known as ‘tidal forests’ or ‘coastal woodlands’, specially adapted to survive in harsh interface between land and sea and in conditions of high salinity, extreme tides, strong winds, high temperatures, low oxygen, and muddy soil (QASIM, 2010).

In this regard, the Caribbean Islands are among the ten main biodiversity hotspots; nowadays, they keep some of the highest endemism levels in the world. Especially in Haiti, in the municipality of Caracol, is one of most productive coastal and marine areas, although it still has more than 5,000 ha of mangrove forest (WIENER et al., 2013).

This region houses important habitats for several endangered species (TIMYAN; HILAIRE, 2011; KRAMER et al., 2016; LUNA et al., 2018). Furthermore, its geographic position in the Caribbean and geomorphological profile, with relatively plane relief, expose the soil and habitats to the risk of floods, and make them vulnerable to natural hazardous such as sea level rise and extreme climatic events. Despite the natural richness represented by its biodiversity, nowadays, Caracol County has been facing the fast degradation of these ecosystems due to bad soil use and occupation, which are associated with inappropriate geographic space. Environmental dynamics in Caracol’s coastal bay is truly catastrophic, given the solid waste discarded by the population in both coastal lines and forests (WHITCHLER-JUNIOR; ROLDOLF; DIEUDONNÉ, 2019).

Population vulnerability conditions in Latin America and in the Caribbean, for example, and its socioeconomic activities are associated, among other factors, with historical territorial occupation processes, as well as with the existing high population density areas, which result in disordered growth, poverty and social inequality. The political situation in Haiti and its socioeconomic vulnerability conditions are well-known (SZLAFSZTEIN, 2020), because they worsen and increase the deforestation threat degree. This scenario tends to worsen poverty indices, for they are not associated with the high rates of exposure to climatic risks, as well as with lack of land use planning, misery and with low population schooling indices (SINGH; COHEN, 2014).

These are alarming numbers, as only 31% of Haiti’s population has access to basic sanitation. This number drops to 16% in the countryside. Income inequality is also stagnated based on its Gini coefficient (0.61, since 2001). Thus, the 20% richest individuals hold more than 64% of the country’s total income, whereas the 20% poorest individuals only account for 1% of it. These inequality levels place Haiti among the most unequal countries in Latin America (LOZANO-GRACIA; LOZANO, 2017).

Human development and the Anthropocene push Haiti down to the 170th position among the 189 countries and territories in the world category of “low human development” - its HDI is 0.510 (PNUD, 2020). These indices are closely correlated to over-exploration of natural resources, which tend to quickly get exhausted, and it would limit any current and future possibility of having communities in these environments to accomplish sustainable development (HAUGE, 2018). Accordingly, Communities in Caracol County - Haiti significantly depend on coastal and marine ecosystems’ resources, with emphasis on artisanal and subsistence fishing. These ecosystems are bond to transition ecosystems, with emphasis on forest resources, mainly on vulnerable and explored mangroves for coal production (GLOBAL ALLIANCE FOR CLEAN COOKSTOVES, 2017).

Somehow, communities’ socioeconomic vulnerability derives from the worsening of demographic issues (urban and rural migration), mainly from poverty. There are other aggravating factors, such as the population’s trend to mainly leave on mangroves’ coastal shores (close to food), a fact that accounts for increasing coastal silting rates. This process seems to be affecting the environment’s weak resilience ability due to climatic change effects (PIERRE, 2019). Surface water flow at elevated sites in the urban zone transport solid waste and a significant fraction of sediments generated by soil misuse, exposure, and occupation (GARCIA; MIRALLES-WILHELM, 2017).

Accordingly, we have tested the hypotheses that the degradation of mangroves in Caracol County (Haiti) can be explained either by socio-environmental (anthropic) or natural variables (existing and remaining natural resources). Among the problems of occupation and degradation of mangroves, woody resources have been used as the main source of energy (charcoal production) that deplete and threaten the conservation of these natural resources. The hypotheses are substantiated by the fact that families’ main power generation source lies on wood resources combustion; therefore, stopping deforestation under such conditions becomes a crucial matter and great challenge in Haiti (JOSEPH; SAFFACHE, 2018).

The population growth in Haiti and the ratio of people living in vulnerable urban areas led to substantial increase in the demand for wood and coal. The Ministry of the Environment has estimated that 85% of the Haitian population depended on biomass energy for domestic use - 3.3 million m3 year-1 of wood. The conversion of native forests for domestic use has been causing deforestation, soil loss, water quality degradation, and socioeconomic instability (CHURCHES et al., 2014).

Simultaneously, there is a lack of action by the government to deal with the coal issue in local communities (BLANC et al., 2019). The excessive cutting of native trees and unsustainable agriculture (maize, pea, potatoes, yam, cassava, banana cultures) have been leading to high deforestation rates, to erosion and vegetal biomass losses Thus, these factors have also remarkable effect on hazardous flood events (PAULEUS; AIDE, 2020).

The goal of this study is statistically analyzing locally measured socioeconomic parameters to explain the reasons why populations have occupied and destroyed mangrove forests in Caracol County - Haiti.

Materials and Methods

Study Site

The research was carried out in Caracol County - Haiti (Figure 1), which is located within a 75.74 Km² area; its local population comprises 7,714 inhabitants. The Caracol County constitutes one of Haiti’s counties and is an important wetland in the country. The area of vegetation cover of mangroves in Haiti is not precisely defined. However, the numbers commonly presented in official documents indicate a forest cover of the order of 1 to 2%. A 1990 World Bank report on the management of natural resources in Haiti suggests that the area of natural forests represented 200,000 ha (nearly 7% of the total area of the country). In 1995, the Food and Agriculture Organization of the United Nations estimated these natural forest areas at 107,000 ha. That is, almost 4% of the total area of the country. In 2005, he estimated the forested area at 105,000 ha, showing a significant reduction in forest cover. On the other hand, including tree growing areas, forest cover in the country is estimated at around 500,000 ha, or 18% of the country’s total area. But field observations suggest that the areas of tree systems have changed little. However, this regression has caused anthropic and physical impacts to the coastal strip, where one of the most important marine stretches in Haiti occurs in the design of the Biological Corridor of the Caribbean. In general, human presence in mangroves is very intense in Haiti, especially in the mangroves of the municipality of Caracol, which has an impact on aquatic species (MDE, 2015). And for this reason, this municipality was chosen as the object of this research.

Figure 1
Central America, Haiti and Caracol County.

In summary, Caracol mangroves are very fragile and are gradually disappearing, subject to use that no longer meets the traditional needs of local populations. However, the population increasingly conforms to the characteristics of the market economy imposed on the country. For example, while the latter occupy an area of 180 km² in Haitian territory, they occupy respectively 4,000 and 4,860 km² in Cuban and Panamanian territory. In recent decades, Caribbean mangroves have suffered particularly uncontrolled exploitation and almost irreversible degradation. Although these coastal forests have a significant capacity for natural regeneration, it seems important to support this process by establishing appropriate procedures and dialogue with the local population (SAFFACHE, 2006).

With regard to soil use and occupation features, landcover in Caracol County counts on dense agricultural crops, medium-density agricultural crops, on ecosystem of mangrove, beaches and dunes, savanna, savanna with other vegetation types, dense agroforestry systems, urban areas and saline areas (Figure 2).

Figure 2
Main vegetation cover in Caracol County.

Data collection

The assessed population comprises all mangrove users and local authorities. Information about mangroves’ disturbances encompass either mangroves’ users or local authorities in Caracol County. Users forming the valid sample are the ones who explore at least one of the resources associated with mangrove forest. Local authorities are the ones who account for the proper management of mangroves’ ecosystems. The socioeconomic and environmental profiles include fishermen and loggers, saline site explorers, and local autarchies in the municipal administration council (DESTRO; MARCO; TERRIBILE, 2020).

We defined the samples based on the actions of each assessed actor; it was done to assess topics concerning mangrove sites’ reduction in comparison to the dynamics of human activities. The method adopted to survey mangrove users and local authorities was based on a random sampling process (TAHERDOOST, 2016). Questionnaires were locally applied by mangrove users, based on the population sample, which totaled 140 valid respondents in Caracol County - local agents were trained to this research stage. However, interviewees (saline site explorers and local authorities) were randomly picked.

Interviews were carried out from March to November 2020 - interviewees were informed about research aims and identity secrecy, so they could feel safe to share their opinions about mangrove use and management profile in Caracol County. The research project and the format were submitted to and approved by the UNIFAP’s Ethics Committee (Plataforma Brasil, number 4.203.511).

Research description

The questionnaire counted on 28 questions, 25 of them were closed and 3 were open; the open questions regarded the participant’s general opinion (contributions to and perspectives for mangroves’ shared management). Table 1 describes the questionnaire variables; it was divided into four sections, namely: 1) primary information, regarding residence neighborhood, age, gender, schooling, family origin and income. Monthly family income estimate was reported in “Haitian gourdes” (HTG $) and converted into American dollars (US $) based on the following Exchange rate 1 USD = 95.0358 HTG (on December 31st, 2019); 2) anthropogenic factors degrading the mangroves; 3) natural factors that have contributed to degrade the mangroves and that are a threat to them in the assessed county, as individuals live far from mangroves; and 4) identification of local actors who play some role in the county’s management and in mangroves’ protection.

Statistical analysis

We used the following analyzes to evaluate the research hypotheses: a) simple regression, with the objective of individually testing the explanatory variables and independent factors on the occupation of mangrove areas (Mangrove occupation) (Table 1). b) the Kruskal-Wallis test was applied to test the influence of independent variables and factors on the reasons for the degradation of mangroves (Mangroves’ degradation factors) (Table 2).

In the case of the Kruskal-Wallis method, non-parametric tests have the advantage of allowing the study (α < 0,05) of data that are inherently classified (nominal scale) or presented in ranks (ordinal scale). This occurs when the assumptions of normality and homoscedasticity are violated significantly (CRAWLEY, 2007), or when it is not possible to trust the result of a traditional analysis of variance (probability of committing a Type I error departs markedly from significance α < 0.05). That is, the Kruskal-Wallis method is a non-parametric alternative to one-way ANOVA criterion. The Kruskal-Wallis test is a non-parametric test used to compare three or more independent samples, which indicates the existence or not of differences between at least two of them. The application of the test uses numerical values transformed into ranks and grouped into a single data set. Comparison of groups is performed using the average of ranks (average rank).

Tabulation process and descriptive statistical analysis were carried out in Microsoft Excel. Hypotheses’ comparative tests were conducted in the R-Project tool (data frame of Excel file in “txt”), which generated the data matrix (Non-parametric multi-comparative tests - Kruskal-Wallis) to be subsequently processed at significance level of α < 0.05 (R CORE TEAM, 2018).

Results

The results showed “reasons” why populations occupy mangrove forest zones (“Mangrove occupation”) (Table 1). Variables that stood out as explanatory for mangroves’ occupation, in separate were “Slope landslide events” (36%), “Profession or occupation” (28%), “Threats due to floods” (16%) and “Monthly family income” (16%). “Slope landslide events” and “Threats due to floods” are related to populations’ concern with copping with floods and flash floods caused by climatic events that could harm their activities in degraded (or not) mangrove areas. Different professions and/or occupations, as well as the respective income levels (job opportunities and income variations) are relevant additional attractions for mangroves’ occupation nowadays and, assumingly, it will be the same, in the future.

Socio-environmental variables “Age” and “Time in the residence” presented positive contribution concerning mangroves’ occupation; therefore, they were significant (p<0.05). In other words, they only explain 4.80% and 4.38% of the influence, respectively. “Gender” and “Schooling” recorded low significance, with explicability of 2.5% and 2.03%, respectively; these numbers are close to the significance limit (p ≈ 0.05) or have positive contribution. However, they do not satisfactorily explain mangroves’ occupation level. The other variables were not significant (NS or p>0.05).

Among all variables related to mangroves’ degradation factors, there are the significant ones (p<0.05), such as “Distance from the mangrove”. However, the distance does not explain much about the mangroves’ occupation variation (2.36%). Other natural and anthropic factors, such as coastal erosion and drought, have been contributing much more to mangroves’ occupation and degradation (“Anthropic activities in the mangrove”). “Slope landslide events”, as well as “Threats due to floods”, and “Challenges users and local authorities have to face for mangroves’ environmental management” emerged as evident threats, as they help explaining mangroves’ occupation.

Variables close to the significant ones (p=0.03) regarding mean “Monthly family income”, can be related to mangroves’ degradation, because it is influenced by individuals’ paid and economic activities (“Activities that affect the mangrove”); furthermore, it can be associated with flood and flash “Flood events”. The other variables were not significant (p>0.05). Based on the slope coefficient column (parameter “b”), the only negative values were the ones related to “Distance from the mangrove”, “Threats due to floods” and “Flood events”. Table 1 lists the significant variables that mostly represented the Variables in bold highlight the significance of mangroves’ occupation significance.

Table 1
Simple regression tests to quantify parameters’ variations in mangrove deforestation based on anthropogenic and natural factors in Caracol County - Haiti.

Parameters (x)	Regression Tests (Y = Mangrove occupation) Y = a + bx
	a	b	R2 ad (F,DF)	p-value
Age	0.16	0.01	0.048	0.0083 (**)
Gender	0.45	0.24	0.021	0.0599 (.)
Schooling year	0.90	-0.04	0.025	0.0613 (.)
Schooling	----	Variant	0.031	NS
Origin	0.61	-0.06	-0.08	NS
Time in the residence	0.25	0.01	0.044	0.0112 (*)
Profession or occupation	0.75	Variant	0.28	< 0.0001 (***)
Paid activity	0.47	0.11	-0.005	NS
Monthly family income	0.21	0.002	0.162	< 0.0001 (***)
Mangrove occupation	------	------	------	------
Distance from the mangrove	0.78	-0.001	0.0236	0.0487 (*)
Mangroves’ environmental condition	------	Variant	------	NS
Activities that affect the mangrove	0.51	0.096	-0.003	NS
Anthropic activities in the mangrove	------	Variant	0.032	NS
Extinction of animal and plant species due to exploration	0.56	Variant	0.005	NS
Species’ migration phenomenon	0.64	-0.0946	-0.005	NS
Flood events	1.11	-0.57	0.044	0.0114 (*)
Slope landslide events	0.42	1.30	0.364	< 0.0001 (***)
Threats due to floods	1.25	-0.79	0.17	< 0.0001 (***)
Local actors’ functions	0.41	0.38	0.006	NS
Behaviors related to mangroves’ degradation	0.58	-0.03	-0.01	NS
Challenges users and local authorities have to face for mangroves’ environmental management	0.82	Variant	-0.02	NS
Measures for mangroves’ protection	0.47	Variant	0.004	NS
Conservation of mangroves in Caracol’s protection area	1.00	Variant	0.012	NS
Protecting mangroves, among other natural and anthropogenic factors	0.53	Variant	-0.013	NS

• NS = non-significant; if p<0.05 - or close to it -, then, it is not significant (in bold).
• Font: Authors, 2021.

A second analysis was carried out to interpret the variables explaining the “Mangroves’ degradation factors”. Kruskal-Wallis hypotheses’ tests worked and complementary analysis in the current evaluation, rather than just mangroves’ occupation (Table 2).

The best interpretations of these tests results were: a) “Distance from the mangrove” and biodiversity conservation intervention level (“Anthropic activities in the mangrove”) are relevant for avoiding mangroves’ degradation, as they explain their potential impacts, as well as occupation (interpreted through linear regression based on distance); b) it depends on water-climatic and geophysical factors and threats (climate, time, earthquakes, floods, flash floods, sea level rise, among others). “Slope landslide events” and “Threats due to floods” were also significant in simple linear regression analyses; and c) ecological and managerial functions related to the importance of NGOs and public institutions concerning mangroves’ environmental conservation and management were relevant for Kruskal-Wallis tests (p<0.05).

Table 2
Kruskal-Wallis test to assess significant variations in and influence of independent variables on “Mangroves’ degradation factors”.

Parameters Factor (Fi)	Kruskal - Wallis (Y = Mangroves’ degradation factors)(Fi)
	Df	X2	p-value
Age	51	51.95	0.44 (NS)
Gender	1	1.55	0.22 (NS)
Schooling year	15	22.20	0.10 (.)
Schooling	5	6.50	0.26 (NS)
Origin	1	0.35	0.55 (NS)
Time in the residence	50	46.21	0.62 (NS)
Profession or occupation	12	14.04	0.29 (NS)
Paid activity	1	0.01	0.93(NS)
Monthly family income	43	56.56	0.08 (.)
Mangrove occupation	3	0.50	0.92 (NS)
Distance from the mangrove	8	20.04	0.012 (*)
Mangroves’ environmental condition	4	2.22	0.69 (NS)
Activities that affect the mangrove	1	2.77	0.09 (.)
Anthropic activities in the mangrove	4	16.25	0.003
Extinction of animal and plant species due to exploration	8	4.03	0.85 (NS)
Species’ migration phenomenon	1	0.45	0.46 (NS)
Flood events	1	2.86	0.09 (.)
Slope landslide events	1	15.04	0.0001 (***)
Threats due to floods	2	20.21	< 0.0001 (***)
Local actors’ functions	4	11.11	0.025 (**)
Behaviors related to mangroves’ degradation	1	0.011	0.91(NS)
Challenges users and local authorities have to face for mangroves’ environmental management	8	20.03	0.01 (**)
Measures for mangroves’ protection	3	2.33	0.51 (NS)
Conservation of mangroves in Caracol’s protection area	7	7.62	0.37 (NS)
Protecting mangroves, among other natural and anthropogenic factors	3	0.09	0.99 (NS)

• Significant (p<0.05) or close to it (^.), and/or highlighted in bold). NS = Non-significant
• Font: Authors, 2021.

Statistics Analysis

Tables 1 and 2, respectively, are significant for the following variable: “Time in the residence” 4.38% and 61.60%. Different scenarios in time living in the same residence variation are showed in Table 1: “Flood events” explains 11.4%, “Slope landslide events” explain 0.01%; such as for Table 2: “Flood events” explains 9.06%, and “Slope landslide events” explains 0.01% of variations in the impact increased accountability rate recorded for flood events in the most frequent slopes. In other words, they can change mangroves’ vegetation areas due to changes in either anthropogenic or natural factors.

Consequently, “Profession or occupation”, in Table 1, explain 28.56% of mangroves’ degradation variation. But, if one takes into consideration the current approach about the socioeconomic costs and multiple uses of mangroves’ ecosystems, profession or occupation emerged as irrelevant variables for mangroves’ degradation (Table 2). Nevertheless, whenever there is categorization (classes - Kruskal-Wallis test), such a significance becomes relevant.

“Monthly family income” only explained 8% of the degradation (Table 1). With respect to residences’ rate and alternatives to migration, these variables only take into account lack of local socioeconomic opportunities to young individuals; and it forces some inhabitants to claim for mangroves’ commercial exploration.

When it comes to governance by environmental bureaus given the challenges posed to mangroves’ ecosystems management in Caracol County, this factor explains 20% of influence on mangroves’ degradation variation (Table 2, p<0.01). In this case, we have identified that the 1st most relevant dependent variable is “Mangroves’ occupation” (Table 1), and the 2nd most relevant dependent variable is the “Mangroves’ degradation factor”.

It is important highlighting that 24% of participants have revealed that mangroves are visibly degraded, but that such a degradation change depending on the location of their residences (urban area). According to 22% of participants, assumingly, salts’ exploration is the main mangroves’ environmental degradation factor. In total, 29% of interviewees believe that solid waste pollutes the ecosystems, and this rate changes depending on the place of their residence. However, the worst environmental degradation scenario is explained by the uncontrolled use of wood as natural fuel (charcoal production) (Table 2).

Discussion

Factors related to natural hazardous, socio-economy and the environment

Natural hazardous and other anthropic factors have been stopping Haiti from changing its economic and human development potential. High and steep mountains cover 63% of the country’s surface, with 20% slope (or more) and with only 3% forest coverage; Haiti is one of the most devastated countries in the world. Besides, this country is located in the area of hurricanes, not mentioning the swell caused by storms and floods (GLAS et al., 2020).

Based on the Global Climatic Change Index, published in 2016 by Germanwatch, Haiti is the third country mostly affected by climatic events. Among all Caribbean countries, Haiti is the one suffering with the largest number of hazards per Km² (based on data by EM-DAT of OFDA/CRED). Therefore, based on the aforementioned numbers, the country has been facing an environmental crisis that is quite worrisome for its citizens. Given its geographic position, the country gets very exposed to such types of climate-related hazardous events, a fact that would have led to annual estimated damages and losses close to 2% of its GDP from 1975 to 2016. Tropical storms and hurricanes back in 2008 have caused losses estimated in 15% of the country’s GDP. The hurricane recorded on January 12th, 2010, killed 220,000 people, and it forced the displacement of 1.5 million people and caused destruction equivalent to 120% of its GDP. Back in October 2016, Matthew Hurricane (category 4 in the Saphir-Simson scale) accounted for wind at speed ranging from 200 to 250 km h-1 and caused considerable damage to the Caribbean countries (AZAR, 2017).

Nevertheless, hurricanes and climatic changes also affect the degradation of both mangroves’ ecosystems and the environment, as well as biodiversity losses in Caracol County - Haiti, Table 1: “Flood events”, “Slope landslide events”, “Threats due to floods”, “Distance from the mangrove”, “Age”, “Time in the residence”, “Profession or occupation”, “Monthly family income” and Table 2: “Slope landslide events”, “Threats due to floods”, “Local actors’ functions”, “Anthropic activities in the mangrove”, “Distance from the mangrove”, “Challenges users and local authorities have to face for mangrove’ environmental management”; however, in more general terms, they also affect the rest of the Caribbean. Damage extension is also explained by anthropogenic and natural factors that worsen the conditions in the Caribbean territory (BRL INGÉNIERIE, 2021).

There are approximately 20 swamps in Haiti. They are composed of fresh and salty water, and are mostly interconnected by lakes, lagoons and rivers (NDOUTOUM, 2021). Thus, the current financial support granted to energy and climate-related projects is focused on three priorities set by the government to fight climatic changes: 1) food security, 2) renewable energy sources, and 3) integrated water resources’ management. Therefore, hazardous’ risk reduction is favored by significant funding, which is directly linked to climatic changes, including agricultural adjustment, reforestation, agroforestry, coastal zone management, training, bio-economy development, institutional reinforcement, mangroves’ management, waste protection and management (GALLAGHER et al., 2019).

According to UN’s estimates, and the Worldmeters’ growth model, Haitian population was 10,950,361 inhabitants in April 3rd, 2017 and it will reach 12,578,313 by 2030; and it means increase by 15% within the estimated time interval. Nowadays, up to 50% of agro-food products in Haiti are imported, mainly from the Dominican Republic and from the United States (USAID, 2016). The United Nations Organization for Food and Agriculture (FAO) estimates that the global agro-food production must rise by 70% until 2050. The aim is to fulfil the need of the world’s population, which has been growing fast, as well as to restore forest landscapes for ecological purposes and ecosystems’ yield (SPRENKLE-HYPPOLITE et al., 2016). Thus, FAO (2015) estimated that restoring tropical forests, other forests, and mangroves costs US $ 3,450 ha-1, US $ 2,390 and US $ 2.880 ha-1, respectively, on average. It represents the cost-effective relation of 37.3, 10.3, and 26.4 (WALTER, 2015).

In hierarchical terms, the main deforestation and soil degradation causes in Haiti are 1) forest and agricultural resources’ unsustainable management and exploration, including unsustainable wood extraction (wood biomass for power production), as it is the main power source for cooking; and 2) the precariousness of Haitian communities that still face the absurd of having farmers cutting fruit trees to sell its wood. Accordingly, forest ecosystems, mangroves, and coastal and marine ecosystems might be in danger for future generations (NADEAU et al., 2018). Forest loss is one of the main causes of subsistence means for these populations, as they depend on them - this process can be somehow locally explained, as shown by data in Tables 1 “Age”, “Time in the residence”, “Profession or occupation”, “Monthly family income” and 2 “Distance from the mangrove”, “Anthropic activities in the mangrove”, “Local actors’ functions”.

Although urbanization in Haiti is the man factor accounting for biodiversity loss, proper projects for, and management of, urban green areas can help keeping significant and valuable biodiversity levels (EXANTUS; BEAUNE; CÉZILLY, 2021). Mangroves’ management is essential, as evidenced by Haiti’s contribution at national policy level. This policy can be applied to our Case Study about Caracol County - Haiti, which has shown the need of reaching climate targets and sustainable development targets at several dimensions (KUHL, 2019). General targets for Haiti should be a) integrated water resources and watersheds’ management; b) integrated coastal zones’ management and infrastructural rehabilitation; c) food security conservation and reinforcement, mainly through bioeconomy development; d) energy transition to reduce the dependence on fossil fuel; and e) information, education and awareness (PIERRE, 2015). This context can be explained by variable “Challenges users and local authorities have to face for mangroves’ environmental management” (Table 2).

The vulnerability of coastal zones and mean sea level in Haiti have been increasing by 1.8 mm year-1 (MDE, 2015). Just for comparison, Maimi City (USA) must become one of the metropolis mostly exposed to marine submersion events in years to come, as the combination of tides and swell events mainly contribute to coastal floods. Sea level rise in Miami will lead to great population displacement and migration, as well as to significant damage to properties, infrastructure and the environment. According to the World Resources Institute, local sea level rose 12 inches and it will rise approximately 2 feet (≈ 60 cm) by 2060 (ISLAM; NESHKOVA, 2017). It is expected that approximately 2 million people will be affected by sea level rise of 1.8 m by 2100, in Miami (HAUER; EVANS; MISHRA, 2016). Thus, it is possible assuming that such a threat will be similar in the Caribbean as a whole. For instance, Caracol County has presented significance influence for some variables associated with the climate (Table 1: “Flood events”, ”Slope landslide events”, “Threats due to floods”).

There are several obvious reasons to protect these ecosystems, among them one finds: a) guarantee of proper functioning, as the destruction of a given species can weaken the whole ecosystem; b) keeping its economic relevance (wood, food and medication). Therefore, the ecosystem contributes to the maintenance of the specific diversity composing it, besides being source of coastal stability; c) keeping its role as “carbon absorption pump”, which acts as fortification against climatic change impacts (hurricanes, tsunamis). Furthermore, it avoids water elevation, which is key element against coil salinization (CALIL et al., 2017).

Based on results in Tables 1 and 2, it is possible observing significant variables that locally explain, for example, perceptions about simultaneous mangroves’ occupation and/or degradation. It is so, because the mangrove area is featured by particular vocation to conserve ecosystems’ integrity and environmental services (SARDESHPANDE; SHACKLETON, 2020).

Besides, some socioeconomic factors seem to worsen the degradation scenario in mangroves due to severe environmental consequences, to the hard time reestablishing them and to the regeneration limitations of neighbor ecosystems and habitats (PÉREZ-CEBALLOS et al., 2020). Decision-makers can use variable ‘profession’ to plan integrated management actions based on local initiatives to make the extraction of resources natural to mangroves’ ecosystems more effective and sustainable (CARVALHO et al., 2020). On the other hand, they can increase mangroves’ vulnerability because of actors’ interest in land use and occupation, although they are aware of their harming effect on the environment (ROBSON; KLOOSTER, 2018).

Among the aforementioned factors, distance between the residence and the mangrove explains 4.8% of degradation in mangrove areas (Table 2), with emphasis on solid waste generation. The so-called ‘garbage’ management has been ineffective and has been generating even more environmental pollution and demand for better management practices, as mangrove forest borders are also confronted by human presence, which indirectly affects forests and often causes their excessive exploration or even their extinction. The anthropogenic dynamics is, therefore, a challenging management element to avoid environmental degradation (ROBSON; KLOOSTER, 2018).

Forest fragmentation due to all sorts of anthropogenic disturbances is herein translated by socioeconomic parameters that can cause effective loss of mangroves because of demographic pressure influence. Despite the essential role played by mangroves in the health of the environment, approximately 0.55% of mangrove area - for each 1% increase in human population density - is lost for agricultural conversion in one of the biggest mangroves in the world (TURSCHWELL et al., 2020).

Therefore, forest losses due to anthropic action are a global threat to biodiversity, as they continuously reduce forest species populations. Almost 80% of primary energy supply in Haiti comes from this source. Accordingly, forests have been severely and dangerously degraded. It has been observed for a long time already, and frequent deforestation cases are induced by excessive wood consumption (GHILARDI; TARTER; BAILIS, 2018).

However, the extinction of some species is oftentimes delayed until the last habitat is gone. Mass extinction can be imminent in some tropical countries presenting low forest coverage. Haiti, which has less than 1% of its original primary forest, is experiencing the mass extinction of its biodiversity (HEDGES et al., 2018).

The herein assessed variables are also correlated to the likely concern by the population about natural water hydroclimatological events (be them extreme, or not), mainly in areas closer to the coast. The more these events happen, the lower is the trend of mangrove occupation (parameter ‘b’ negative - Tables 1 and 2). Variables “Age”, “Profession or occupation”, “Monthly family income” and “Slope landslide events” gave positive contribution to mangroves’ occupation level (parameter ‘b’ positive). It is important highlighting that, with respect to variable “Profession or occupation” variation”, based on the results, there are different professions influencing the way mangrove areas are occupied (they are related to liberal professionals, loggers, salt collectors, among others), which is a relevant explanatory factor. This outcome points out that the profession of different categories explains soil use and occupation by presenting different impact levels on mangrove occupation (variable “Profession or occupation” indicated in Table 1).

Mangrove vegetation in Caracol County - Haiti is threatened by significant changes in this ecosystem, to the extent of causing potential decline in sustainability and environmental quality due to vegetal cover suppression. This issue can be attributed to two socio-environmental impact typologies, namely: 1) negative impacts from population pressure, poverty and soil use and occupation; and 2) unsustainable use of natural resources, which is featured by anthropogenic actions associated with, and worsened by, extreme climatic events.

However, different socioeconomic and environmental factors tend to act differently towards impacts over mangrove ecosystems. If these actions remain inappropriate, mangroves tend to extinction, and it will lead to worsened socioeconomic and environmental conditions. Thus, if these actions are well-oriented, they can lead to integrated and sustainable management actions in Caracol County. Despite actors’ extreme poverty socioeconomic situation, it is possible culturally changing consolidated production methods and promoting sustainable mangrove production and protection systems, as well as overcoming pressures that lead to its shallow cut and to its potential extinction, a fact that poses risk to ecosystems and to populations depending on them.

Conclusions

Our hypothesis was confirmed. The degradation of Caracol’s mangroves, in Haiti, was explained either by socio-environmental or natural variables (or by their interaction). The degradation process experienced by their habitats happens based on the combination of (natural) socio-environmental variables and factors, as expressed by its own citizens.

Local policy-makers and decision-makers often face challengers to manage and avoid environmental impacts. Therefore, better political-managerial stability associated with educations actions and concrete awareness about the topic by the population, including proper socio-environmental economic propositions, are essential for this process. It is important shining light on sustainable alternatives that can contribute to mangroves’ conservation and benefit socially fairer development solutions. Thus, it is essential taking into account the current socio-environmental context and the population’s poverty and misery in the future, so that concrete actions can be put at practice to favor a whole set of actions focused on protecting the local environment, economy and quality of life.

Acknowledgements

We thank to the Universidade Federal do Amapá, to the Programa de Pós-Graduação em Biodiversidade Tropical - PPGBIO, to PROPESPG-UNIFAP, to CAPES for the granting of the first author’s scholarship. We are also grateful to CNPq for the granting (PQ2 # Process 309684/2018-8). We thank the participants and actors who provided us with information in the field. We thank the field assistants in Caracol, Adolphe Jeff, Nitchbenson Henry, Ocephine Francoeur, Cassandra François, Jude Desravines, Johnson Bassinet, Ferry Jean Valais, Joyce Junior Joseph, Fécu Métellus and Ilguentche Appolon.

References

• AZAR, M. S. Cadre de gestion environnementale et sociale (CGES). Ministère de l´Agriculture, des Ressources Naturelles et du Developpement Rural (MARNDR). 2017.
• BLANC, C. E.; IRA, J. P.; LOUIS, M.; JEAN-PAUL, D.; SALOMON, S. A.; MARIGO, M. Sixième rapport national sur la biodiversité d´Haiti. Ministère de l´Environnement, Haiti. 2019.
• BRL INGÉNIERIE. Etude d’Impact Environnemental et Social (EIES). Ministère des Travaux Publics, Transports et Communications (MTPTC). 2021.
• CALIL, J.; REGUERO, B. G.; ZAMORA, A. R.; LOSADA, I. J.; MENDEZ, F. J. Comparative Coastal Risk Index (CCRI): A multidisciplinary risk index for Latin America and the Caribbean. Plos One, 11, 1-24. 2017. doi:http://dx.doi.org/10.1371/journal.pone.0187011
  » http://dx.doi.org/10.1371/journal.pone.0187011
• CARVALHO, F.; BROWN, K. A.; GORDON, A. D.; YESUF, G. U.; RAHERILALAO, M. J.; RASELIMANANA, A. P.; GOODMAN, S. M. Methods for prioritizing protected areas using individual and aggregate rankings. Environmental Conservation, 47, 113-122. 2020. doi:https://doi.org/10.1017/S0376892920000090
  » https://doi.org/10.1017/S0376892920000090
• CHURCHES, C. E.; WAMPLER, P. J.; SUN, W.; SMITH, A. J. Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data. International Journal of Applied Earth Observation and Geoinformation, 30, 203-216. 2014. doi:http://dx.doi.org/10.1016/j.jag.2014.01.020
  » http://dx.doi.org/10.1016/j.jag.2014.01.020
• CRAWLEY, M. J. The R Book. New Jersey: John Wiley & Sons, LTDA. 2007.
• DESTRO, G. F. G.; MARCO, P.; TERRIBILE, L. C. Comparing environmental and socioeconomic drivers of illegal capture of wild birds in Brazil. Environmental Conservation, 47, 46-51. 2020. doi:10.1017/s0376892919000316
  » https://doi.org/10.1017/s0376892919000316
• EXANTUS, J. M.; BEAUNE, D.; CÉZILLY, F. The relevance of urban agroforestry and urban remnant forest for avian diversity in a densely-populated developing country: The case of Port-au-Prince, Haiti. Urban Forestry & Urban Greening, 63, 1-9. 2021. doi:https://doi.org/10.1016/j.ufug.2021.127217
  » https://doi.org/10.1016/j.ufug.2021.127217
• FAO. Global Forest Resources Assessment. 2^a edition. 2015.
• GALLAGHER, K. S.; PERRY, K.; WANSEM, M. V.; KUHL, L.; FRAPAISE, L. Analysis of International Funding for Haiti’s Climate Change Priorities. SSRN, 1-17. 2019. doi:http://dx.doi.org/10.2139/ssrn.3333173
  » http://dx.doi.org/10.2139/ssrn.3333173
• GARCIA, R.; MIRALLES-WILHELM, F. Advanced hydraulic and water quality modeling to asses flood and pollution impacts: A case study of the Caracol industrial park in Haiti. Aqua-LAC, 9, 1-14. 2017. doi:https://doi.org/10.29104/phi-aqualac/2017-v9-1-01
  » https://doi.org/10.29104/phi-aqualac/2017-v9-1-01
• GHILARDI, A.; TARTER, A.; BAILIS, R. Potential environmental benefits from woodfuel transitions in Haiti: Geospatial scenarios to 2027. Environmental Research Letters, 13, 1-12. 2018. doi:https://doi.org/10.1088/1748-9326/aaa846
  » https://doi.org/10.1088/1748-9326/aaa846
• GLAS, H.; MAEYER, D. P.; MERISIER, S.; DERUYTER, G. Development of a low-cost methodology for data acquisition and flood risk assessment in the floodplain of the river Moustiques in Haiti. Journal of Flood Risk Management, 13, 1-17. 2020. doi:https://doi.org/10.1111/jfr3.12608
  » https://doi.org/10.1111/jfr3.12608
• GLOBAL ALLIANCE FOR CLEAN COOKSTOVES. Haïti: plan d’action pour la transformation du marché des réchauds et des combustibles. 2017.
• HAUER, M. E.; EVANS, J. M.; MISHRA, D. R. Milions projected to be risk from sea-level rise in the continental United States. Nature Climate Change, v. 6, 2016.
• HAUGE, W. I. Haiti: A Political Economy Analysis. Norwegian Ministry of Foreign Affairs. 2018. https://www.prio.org/utility/DownloadFile.ashx?id=1606&type=publicationfile
  » https://www.prio.org/utility/DownloadFile.ashx?id=1606&type=publicationfile
• HEDGES, S. B.; COHEN, W. B.; TIMYAN, J.; YANG, Z. Haiti’s biodiversity threatened by nearly complete loss of primary forest. PNAS, 115, 1-6. 2018. doi:10.1073/pnas.1809753115
• IBGE. Manual técnico da vegetação brasileira; Sistema fitogeográfico, inventário das formações florestais e campestres, técnicas e manejo de coleções botânicas, procedimentos para mapeamentos. Fundação Instituto Brasileiro de Geografia e Estatística. Rio de Janeiro. 2012.
• ISLAM, M. T.; NESHKOVA, M. J. S. Sea level rise in Miami. Research on Policy Alternatives, 1-19. 2017. doi:10.13140/RG.2.2.32896.74241
  » https://doi.org/10.13140/RG.2.2.32896.74241
• JOSEPH, C.; SAFFACHE, P. L’importance des écosystèmes forestiers et les enjeux de la déforestation dans la lutte contre le changement climatique en Haïti: Cas des mangroves du Parc des Trois Baies, des forêts des massifs de la Selle et de la Hotte. Haïti Perspectives, 6, 21-31. 2018.
• KRAMER, P.; ATIS, M.; SCHILL, S.; WILLIAMS, S. M.; FREID, E.; MOORE, G.; MARTINEZ-SANCHEZ, J. C.; BENJAMIN, F.; CYPRIEN, L. S.; ALEXIS, J. R.; GRIZZLE, R.; WARD, K.; MARKS, K.; GRENDA, D. Baseline Ecological Inventory for Three Bays National Park. The Nature Conservancy: Report to the Inter-American. 2016.
• KUHL, L. Synergies between Climate Policies and the Sustainable Development Goals in Haiti. SSRN, 1-17. 2019. doi:https://dx.doi.org/10.2139/ssrn.3398352
  » https://dx.doi.org/10.2139/ssrn.3398352
• LOZANO-GRACIA, N.; LOZANO, M. G. Haitian cities: action for today with an eye on tomorrow. World Bank. 2017. https://openknowledge.worldbank.org/handle/10986/29202
  » https://openknowledge.worldbank.org/handle/10986/29202
• LUNA, Á.; ROMERO-VIDAL, P.; HIRALDO, F.; TELLA, J. L. Cities may save some threatened species but not their ecological functions. PeerJ, 6, 1-22. 2018. doi:10.7717/peerj.4908
  » https://doi.org/10.7717/peerj.4908
• MAARTJE, O.; MARIA, J. S.; DENNIS, W.; JOS, V.; SONIA, S. Assessing rehabilitation of managed mangrove ecosystems using high. Estuarine, Coastal and Shelf Science, 211, 238-247. 2018. doi:https://doi.org/10.1016/j.ecss.2018.06.020
  » https://doi.org/10.1016/j.ecss.2018.06.020
• MAURICIO, C.-H.; NATALIE, B.; MARIO, R.; FRANCIS, J. The mangrove-fishery relationship: A local ecological knowledge perspective. Marine Policy, 1-11. 2019. doi:https://doi.org/10.1016/j.marpol.2019.103656
  » https://doi.org/10.1016/j.marpol.2019.103656
• MDE. Etat d’avancement en termes d’adaptation au changement climatique. Ministère de l’Environnement. 2015.
• NADEAU, M. B.; HENAULT-ETHIER, L.; RONY, F. J.; MICHEL, G.; MONETTE, M. Restauration des paysages forestiers et agroforestiers jumelée à la valorisation des déchets organiques en Haïti pour le développement durable d’une économie verte résiliente aux changements climatiques. Haïti Perspectives, 6, 1-42. 2018.
• National Geospatial Information Center (CNIGS). 2008.
• NDOUTOUM, J.-P. Écosystèmes et zones humides en Francophonie: Préservation, restauration et valorisation pour la survie de la biodiversité. Institut de la Francophonie pour le Developpement Durable. 2021.
• NOAA. What is a mangrove forest? https://oceanservice.noaa.gov/facts/mangroves.html 01/20/23.
  » https://oceanservice.noaa.gov/facts/mangroves.html
• PAULEUS, O.; AIDE, T. M. Haiti has more forest than previously reported: land change 2000-2015. Peerj, 1-20. 2020. doi:10.7717/peerj.9919
  » https://doi.org/10.7717/peerj.9919
• PÉREZ-CEBALLOS, R.; ZALDÍVAR-JIMÉNEZ, A.; CANALES-DELGADILLO, J.; LÓPEZ-ADAME, H.; LÓPEZ-PORTILLO, J.; MERINO-IBARRA, M. Determining hydrological flow paths to enhance restoration in impaired mangrove wetlands. Plos One, 15, 1-20. 2020. doi:https://doi.org/10.1371/journal.pone.0227665
  » https://doi.org/10.1371/journal.pone.0227665
• PIERRE, A. Analyse du plan de gestion du parc national des trois baies (Haiti). Université de Liège. 2019.
• PIERRE, D. Contribution Prévue Déterminée au niveau National. Ministère de l´Environnement. 2015.
• PNUD. Rapport sur le développement humain. 2020.
• QASIM, S. Z. Some environmental factors affecting coastal waters. Journal of Coastal Environment. 1. p. 1-10. 2010.
• R CORE TEAM. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2018.
• ROBSON, J. P.; KLOOSTER, D. J. Migration and a New Landscape of Forest Use and Conservation. Environmental Conservation, 46, 1-8. 2018. doi: 10.1017/S0376892918000218
  » https://doi.org/10.1017/S0376892918000218
• SAFFACHE, P. Le milieu marin haitien: chronique d’une catastrophe écologique. Études Caribéennes. 1-8. 2006. https://doi.org/10.4000/etudescaribeennes.267
  » https://doi.org/10.4000/etudescaribeennes.267
• SARDESHPANDE, M.; SHACKLETON, C. Urban foraging: Land management policy, perspectives, and potential. Plos One, 15, 1-26. 2020. doi:https://doi.org/10.1371/journal.pone.0230693
  » https://doi.org/10.1371/journal.pone.0230693
• SINGH, B.; COHEN, M. J. Climate Change Resilience: The case of Haiti. OXFAM. 2014.
• SPRENKLE-HYPPOLITE, S. D.; LATIMER, A. M.; YOUNG, T. P.; RICE, K. J. Landscape Factors and Restoration Practices Associated with Initial Reforestation Success in Haiti. Ecological Restoration, 34, 306-316. 2016. doi:10.3368/er.34.4.306
  » https://doi.org/10.3368/er.34.4.306
• SZLAFSZTEIN, C. F. Extreme Natural Events Mitigation: An Analysis of the National Disaster Funds in Latin America. Frontiers in Climate, 2, 1-12. 2020. doi:http://dx.doi.org/10.3389/fclim.2020.603176
  » http://dx.doi.org/10.3389/fclim.2020.603176
• TAHERDOOST, H. Sampling methods in research methodology; how to choose a sampling technique for research. International Journal of Academic Research in Management, v. 5, 2. 2016.
• TIMYAN, J. C.; HILAIRE, J. Les zones clés de la biodiversité d’Haiti. Comité Interministériel d’Aménagement du Territoire. 2011.
• TURSCHWELL, M. P.; TULLOCH, V. J. D.; SIEVERS, M.; PEARSON, R. M.; ANDRADI-BROWN, D. A.; AHMADIA, G. N.; CONNOLLY, R. M.; BRYAN-BROWN, D.; LOPEZ-MARCANO, S.; ADAME, M. F.; BROWN, C. J. Multi-scale estimation of the effects of pressures and drivers on mangrove forest loss globally. Biological Conservation, 247, 1-11. 2020. doi:https://doi.org/10.1016/j.biocon.2020.108637
  » https://doi.org/10.1016/j.biocon.2020.108637
• USAID. Food assistance fact sheet - Haiti. United States Agency for International Development. 2016. doi:https://www.usaid.gov/humanitarian-assistance/haiti
  » https://www.usaid.gov/humanitarian-assistance/haiti
• WALTER, S. Sustainable financing for forest and landscape restoration - key messages. Food and Agriculture Organization, Rome. 2015.
• WHITCHLER-JUNIOR, J.-P.; ROLDOLF, P. C.; DIEUDONNÉ, P.-L. Entre activités anthropiques et degradation du littoral haitien: le cas de Caracol. Le national. 2019. http://www.lenational.org/post_free.php?elif=1_CONTENUE%2Fsocietes&rebmun=3268
  » http://www.lenational.org/post_free.php?elif=1_CONTENUE%2Fsocietes&rebmun=3268
• WIENER, J.; GREGORY, C.; THOMAS, M.; DANIEL, D. Rapid Ecological Baseline Assessment Lower Trou du Nord River (Caracol Industrial Park). Fondation pour la Protection de la Biodiversité Marine FoProBiM. 2013.

Publication Dates

• Publication in this collection
  29 Nov 2024
• Date of issue
  2024

History

• Received
  22 May 2023
• Accepted
  16 Apr 2024