Role of agroforestry parklands in livelihood supports in the rural area of the Sahelo-Sudanian zone in Niger

doi:10.21203/rs.3.rs-2064706/v1

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Role of agroforestry parklands in livelihood supports in the rural area of the Sahelo-Sudanian zone in Niger

https://doi.org/10.21203/rs.3.rs-2064706/v1

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Several studies were made in Niger, but there is little data on agroforestry studies in two relatively different ecosystems. Therefore, the aim is to determine the services provided by agroforestry parklands and carbon stock estimation in the two villages. Firstly, a survey was carried out to highlight the benefits derived from agroforestry parklands to rural populations. Secondly, a forest inventory was used based on a systematic random sampling approach by transect. Finally, the Normalized Difference Vegetation Index (NDVI) was used. The study recorded 25 woody species in Dan Saga and 24 in Sekoukou village where there is more dominance of the Fabaceae family species (43.48% in Dan Saga and 58.34% in Sekoukou) followed respectively by Anacardiaceae and Combretaceae (8.7% and 12.5%). Dendrometric surveys showed relative low tree density (23 stems/ha at Dan Saga and 14 stem/ha at Sekoukou), a bell-shaped diameter structure showing a strong dominance of intermediate diameter trees ([20 cm; 30 cm [) and a low representativeness tree with extreme diameters ([0; 10 cm and [70 cm; → [), The soil cover (more than 50%) and the regeneration rate are more than 80% in both localities. The analysis of variances gives a significant difference (P-value < 0.05) in all dendrometric parameters as well as the carbon content, except for the density and the diameter of the trees. Shannon-Wiener index (intra-ecosystem diversity) and the Pielou equitability index are relatively low but similar to the mean Sørensen index. The estimated carbon stock rises to 5.67 t/ha in Dan Saga and 7.02 t/ha in Sekoukou. The NDVI of the two areas varies from]0; 1 [from 2001 to 2013, thus showing evolutionary vegetation (biomass) dynamic characterized by low vegetation cover in 2001 but increased in 2013 in both villages.

Agroforestry

woody species

biomass

carbon sequestration

livelihoods

NDVI

Never before in the development of human civilization have environmental concerns gained such a level of global importance. Almost seldom a day goes by without some part of it making news (Ramachandran Nair et al., 2009). Indeed, throughout the past ten years, the world's attention has been focused on the critical environmental issue of climate change. There have been and are still huge global efforts being undertaken at many levels and stages of magnitude to comprehend the intricacies and severity of human-induced climate change, as well as how to adapt to the changes and lessen their negative impacts (Kumar and Showalter., 2010). Given that agriculture constitutes the primary means of subsistence for the vast majority of rural areas, the potential effects of climate change on farm productivity are of great concern (Reppin et al., 2019). Furthermore, climate change will hurt all four aspects of food security, including food availability, food access, food supply stability, and food utilization, making agricultural systems more vulnerable. These impacts are linked to past and present greenhouse gas emissions (GHG) with different global warming potentials, specifically, carbon dioxide (CO₂) methane (CH₄) and nitrous oxide (N₂O) (Mosquera et al., 2017). Climate change is the most prevalent environmental and developmental concern, affecting natural resources and humans worldwide (Murthy et al., 2016). The degradation and conversion of several forest areas to other land use types are typically associated with a high population growth rate and agricultural expansion weakened by the climate change effect (Meragiaw, 2017).

Therefore, the current global environmental crisis is prompting requests for new techniques to sustainably manage agricultural landscapes or climate-wise agriculture to provide a more balanced combination of providing, regulating, supporting, and cultural ecosystem services. Land-use systems that promote multi-functionality, such as agroforestry, are seen as potential vehicles to deliver resilience at a landscape scale and play an important role in the socio-economic and ecological restoration of degraded land (Dumont et al., 2017). Agriculture, rural livelihoods, sustainable natural resource management, and food security are intricately tied to the twenty-first century's development and climate change challenges. Indeed, not only is food security an explicit concern under climate change; successful adaptation and mitigation responses in agriculture can only be achieved within the ecologic, economic, and social sustainability goals set forth by the World Food Summit, the Millennium Development Goals, and the United Nations Framework Convention on Climate Change (UNFCCC) (Tubiello, 2012).

However, by resolving definitively this crucial problem of agricultural systems vulnerability and living organism protection; agroforestry is increasingly recognized as a land management system that can serve as a response option for both climate change adaptation and mitigation while addressing many of the challenges that smallholder farmers are facing. Agroforestry can provide numerous livelihood and environmental benefits by helping to reduce climate change and assisting farmers in adapting to intense and changeable weather (IPCC., 2019). Moreover, Introduction in the West African Sahelian and Sudanian agroecological zones, parkland agroforests are economical and socio-ecological systems that integrate trees, crops, and livestock in the same unit of space. They play key roles in the functioning of agroecological landscapes, delivering essential goods and many ecosystem services that sustain smallholder farmers and pastoralist livelihoods. Delivery of provisioning ecosystem services, including food, fodder, and fuelwood, contributes greatly to rural communities’ daily needs. Income from these products helps to improve livelihoods and build resilient economies and socio-ecological systems in the face of ongoing climate change and variability (Dimobe et al., 2018).

The aim was to determine the structure and ecosystem services provided by the agroforestry systems of Dan Saga and Sekoukou villages in Niger. The climatic condition of the two villages is similar but has different ecosystems. Dan Saga village is a dry land area and Sekoukou village is located on the bank of river Niger. Moreover, more than twenty (20) years ago, the population of Dan Saga village practised farmer manage assisted natural regeneration which is a biodiversity conservation technique for woody plants in the agroforestry parklands (Morou et al., 2016). In the same vein, the population of Sekoukou village practised this technic but not longer than Dan Saga village because this population are more interested in rice production than rainfed farming.

2.1. The Study Area

This study was carried out in a rural area of Sekoukou and Dan Saga villages where the choice is based on the different eco-systemic variability. Sekoukou is located in the Tillaberi region, district of Kollo with 466 inhabitants (INS, 2014) and is distant around 41 km from the capital “Niamey”. Dan Saga is located in the Maradi region, district of Aguié with a population of 5000 inhabitants and distant at 661 km from Niamey. The area is characterized by a Sahelo-Sudanian climate with an average annual rainfall of 648.75 mm at Dan Saga and 400 mm at Sekoukou. The forest type in the community can be classified as Sudanian savannah in both. the average duration of the rainy season is 4 to 5 months (from June to September) and a dry season (October to May). temperature generally varies from 17°C to 43°C. Two types of soil characterize the two villages clay and sandy soils.

2.2. Sampling technique of forest inventory

Data collection was carried out during the start of the rainy season (June). However, to determine the ecosystem services, the estimation of the carbon stock through the diversity of the woody stand in the fields and characterization of woody vegetation on the one hand; systematic random sampling by transects were carried out on a total of 72 plots equidistant one after the other of at least 200 m (40 plots in Dan Saga and 32 plots in Sekoukou) (Saigle et al., 2016). The sampling unit is a rectangular plot of 50 m x 50 m, (2500 m²) on two east-west and north-south direction transects (Lawali et al., 2018). Each goes from the large central square of the village (Dan Saga and Sekoukou village) towards the limit of the land or a natural barrier. In each survey, an exhaustive census of the ligneous plants was carried out. For the installation of plots, the right triangle method (Pythagorean Theorem) or the 3-4-5 method considered was used. The measurements carried out focused on the dendrometry characteristics, namely: the diameter at 1.30 m (for trees) and 20 cm above the ground (for multi-stemmed shrubs), the height of the trees and the circumference at the base of the trunk. Concerning woody regeneration, the size of the plots also varies according to the types of vegetation; Five (5) meter plots were carried out in each plot to measure individuals with a circumference less than 10 cm (20 cm above the ground) are considered as suckers (young shoot or juvenile) (Thiombiano et al., 2016). The measurements were made using a flexible tape measure, GPS, Suunto clinometer, stakes, inventory cards, pencils, etc... (Saigle et al., 2016).

2.3. Survey

To determine the livelihoods of rural populations who live from the benefits offered by agroforestry parks, a survey concerned 131 people (68 in Dan Saga and 63 in Sekoukou). These 131 people surveyed constitute the representative sample (sample size) of the population obtained from the use of (Surveymonkey, 2014) method which has a parameter such as the size of the target population, default proportion of 0.5, sampling confidence interval (90%) and a 5% margin of error. The advantage of this method for quantitative surveys is that it allows a large population to indicate the size of the sample to obtain survey results representative of the entire population. The sample size is calculated with the following formula:

\(\text{n}=\frac{{\text{t}}_{\text{p}}^{2}⨯\text{p} \left(1-\text{p}\right)⨯\text{N}}{{\text{T}}_{\text{P}}^{2}⨯\text{P} \left(1-\text{P}\right)+ \left(\text{N}-1\right) \times {\text{Y}}^{2}}\) source (Surveymonkey., 2014)

n = Sample size

N = Total number of populations

P = proportion = 0.5

tp = confidence interval (for 90%, tp = 1.96)

Y = Margin of error (between 5 to10%)

2.4. Dendrometry parameters

Dendrometric parameters can be generated by plot or by plant community. They generally make it possible to appreciate species populations' Spatiotemporal dynamics and identify those that present conservation difficulties for appropriate action through figures or statistical tests. It is about: trees density (total number of trees in the plot/total area of the plot), trees diameter (at 1.30 m from the ground or at chest height were taken with a pi tape), regeneration rate (total number of young plants/ total population size source) (Morou et al., 2016). The tree's cover area (R (%) = π (Dm)² with D_m = average crown diameter and π = 3.14) is defined as the percentage of the ground surface that would be covered if the aerial parts of the species were projected vertically onto the ground (Saadou et al., 1997).

2.5. Diversity Index

Diversity indices are used for a better understanding of the structure and composition of plant communities. They take into account the relative abundances of different species. Species richness is often not sufficient to compare two communities because it does not take into account the relative dominance of each species (Mahamane et al., 1999).

Shannon index: H’= \(-\sum _{i=1}^{s}Pi.\frac{lnPi}{{ln}_{2}}.pi\) where

i = relative abundance of a species i

S = maximum number of species. Varies between [0; 5[ Source (Francour, 2000).

The Pielou regularity index: E=\(\frac{Hʹ}{{log}_{2}}\) source (Rocklin, 2003).

Where H' = Shannon's index and varies between [0; 1[

Sørensen index: Cs= \(\frac{2j}{2j+a+b}\) source (Mahamane et al., 2016), where:

J = number of common species

A = number of species found only in site A.

B = number of species found in site B. and varying between [0; 1[

Analyze of variance (ANOVA) in Dan Saga and Sekoukou

Calculations of the probabilities related to the testing of the different factors were made from the variances in the R-studio of the different terms in the ANOVA model. However, when normality is not verified, the Kruskal Wallis test is used. Furthermore, if the calculated probability value is ≤ at risk α (α = 0.05), one would conclude that there is a significant difference in the means of the character in the populations considered. In this case, the "provenance" factor is said to be significant and if the probability value is ≥ 0.05, then the difference is not significant.

2.6. Floristic wealth

Floristic richness is assessed from the number of families, gender, and species. Thus, the floristic list was established based on the APG III classification (2016) or phylogenetic classification, which is the fourth version of the botanical classification of angiosperms established by the Angiosperm Phylogeny Group. Thus, all the individuals encountered during the inventory are grouped by family, genus, and species.

2.7. List of inventoried species

An exhaustive list of species has been established to determine the number of individuals per species and to calculate the relative frequency of the species. Only the woody species including trees (height > 7 m), shrubs (height < 7 m) and natural regeneration of woody species were considered and their local and scientific names.

2.8. biomass and carbon stock estimation

Three techniques can be used to measure biomass and carbon in forests; field measurements, remote sensing-GIS (monitoring of field verification), and modeling. Thus, forest inventory was considered to estimate the total biomass (aboveground and underground) in the two villages. On the other hand, \({\text{C}\text{O}}_{2}\) is the unit of measurement used by international emission reduction organizations. Thus, for the total carbon stock in the two villages we had chosen Chave et al., (2014), modeling which takes into account the most used allometric equations in West Africa (Saigle et al., 2016). The amount of carbon for each carbon pool in each stratum is determined by multiplying the fresh biomass by the fraction of carbon in the dry biomass (0.47) and it is converted to tonnes of carbon per hectare (C/ha) (Saigle et al., 2016). Because dry wood contains about 50% carbon, this means that almost 25% of a living tree is made up of carbon, as the fraction commonly applied by default is 0.47 between dry biomass and living biomass (IPCC, 2006).

a. Aboveground biomass

AGB (kg) = 0. 0673 (ρ × D^2×H) ^0.976 Where ρ (g/cm^3) = wood density was obtained from ICRAF wood density Database (Ketterings et al., 2001).

AGB = aboveground biomass

H (m) = trees height (cm)

D (cm) = diameter in cm at breast height (1.3 m)

However, this formula (Chave et al., 2014) is only valid for trees with a diameter ≥ 5 cm.

b. underground biomass

If underground biomass is considered a carbon store, it can be calculated using the root-shoot ratio, which is the ratio of underground biomass to above-ground biomass.

UGB (kg) = AGB×R Where R = root growth ratio = 0. 25 developed by Saigle et al., (2016).

c. Total biomass

The total biomass of the tree in each village is the sum of the above-ground biomass plus the below-ground biomass with the formula:

TB (kg) = AGB + UGB where TB = Total biomass

2.9. Normalized Difference Vegetation Index (NDVI)

NDVI was used for the Spatiotemporal analysis to see and analyzed the dynamic of vegetation in Sekoukou and Dan Saga villages from 2001 to 2013. Thus, the NDVI vegetation Index, varying between − 1 and 1, is a normalized ratio between near-infrared and Red with the formula: NDVI= (PIR-R)/(PIR + R) Where PIR = reflectance in the near-infrared. R = reflectance in the red. The interval is comprised within]-1; 1[

3.1. Agroforestry services

Table 1

Contribution of agroforestry to the improvement of rural livelihoods
Villages	Dan Saga		Sekoukou
Variables	Frequency (f)	Percentages (%)	Frequency (f)	Percentages (%)
Products obtained from agroforestry trees
Fodder	49	72.05	40	63.49
Fire hood	67	98.52	62	98.41
Fruits	42	61.76	48	76.19
Medicine	61	89.70	43	68.25
Services obtained from agroforestry trees
Soil improvement	58	85.29	53	84.12
Water retention and conservation	47	69.11	49	77.77
Biodiversity conservation	31	45.58	33	52.38
Impact of agroforestry adoption on livelihoods
Increase in income	59	86.76	44	69.84
Improved health and nutrition	67	98.52	60	95.23
Increased crop yield	66	97.05	61	96.82
Shade	27	39.70	23	36.50

The contribution of agroforestry practice to improved rural livelihoods is presented in Table 1 which showed that the rural populations identified the following products as agroforestry tree products such as firewood/energy (98%), fruits (76%), medicines (89%), and fodder (72%). For environmental protection, the majority (85%) of respondents indicated that agroforestry improved soil fertility, (69%) increased soil humidity and (52%) mentioned it conserved biodiversity. For the socio-economic activities, (86%) mentioned that agroforestry practice increases incomes, (98%) increases crop yields and (97%) improves human health and food security. However, this result showed how rural population are more interested in agroforestry practice where all their daily demand or resources comes from the agroforest. Furthermore, their socio-economic activities, income and food come from these agroforest parks.

3.2. The woody species’ floristic composition

The proportions of woody species are distributed (Fig. 1 and Fig. 2) in the different families. 25 woody species in Dan Saga and 24 in Sekoukou village are listed successively into 13 genera and 12 families and 12 genera and 9 families. Therefore, the research was conducted in two different ecosystems (Sekoukou wetland on the river's edge and Dan Saga dryland) and some trees family’s species are different (proportion and type) such as Sapotaceae, Annonaceae, Euphorbiaceae, Loganiaceae and Gramineae are present in Dan Saga but not in Sekoukou village. In the same vein, the proportion of trees family’s species is different but the best-represented families are Fabaceae (43.48%) in Dan Saga village and (58.34) in Sekoukou followed by Anacardiaceae, Palmae and Combretaceae (8.7%), Annonaceae, Balanitaceae, Gramineae, Euphorbiaceae, Meliaceae, Rhamnaceae, Loganiaceae, Sapotaceae with (4.35%) in both villages which showed that there is an inter-similarity in some plant composition in the two zones. The reason why some species are found in Sekoukou village (wetland) without appearing in Dan Saga village is because in Niger some tree species can only thrive perfectly in humid environments (eg: Sekoukou village). In addition, the high dominance of some family species (eg: Fabaceae) is mostly related to the climate condition as they are drier tolerate species and soil types. These leguminous plants are mainly used for feeding animals sometimes feeding ourselves when the agricultural harvesting was not good. Thus, the two villages have both a good proportion of leguminous species which can be an alternative to improve food security and livestock.

3.3. Vegetation dynamic

The structure and vegetation dynamic are key parameters to assess the agroforestry parkland in Niger. the establishment and interpretation of diameter structures are essential for decision-making in forest management The shape of the diameter structure of forest stands varies according to the type of natural formation present (Saigle et al., 2016). Therefore, Fig. 3 and Fig. 4 showed the distribution of these species’ diameters presented a bell-shaped structure, characterized by a fairly low distribution of individuals of small and large diameters in the two villages. For all species, the largest numbers are in the intermediate diameter classes while the extreme classes have the lowest numbers. Such observations showed extinction of stress is caused by anthropogenic and natural factors.

3.4. Diversity indices of Dan Saga and Sekoukou

Table 2

Diversity index
Index	villages			Specific purpose	General-purpose
Shannon-Wiener index (H’) (Alpha diversity)	Dan Saga	Sekoukou		To measure intra-ecosystem diversity (range [0; 5]).	A better understanding of the structure and composition of plant communities
Shannon-Wiener index (H’) (Alpha diversity)	0.34	0.47		To measure intra-ecosystem diversity (range [0; 5]).
Sørensen index (Beta diversity)	0.489			To assess the similarity between two communities (varying between [0; 1]).
Pielou index of Equitability (E)	0.07		0.10	Equitability within the two communities (varying between [0; 1]).

The diversity index represents the amount of information provided by a sample about the structure of the stand from which the sample was taken and how individuals are distributed among the various species. Hence, Shannon's index is the most commonly used diversity index. Pielou's index of regularity “equitable index”, reflects the quality of the organization of a community. It is equal to 0 when only one species is present and 1 when all species have the same abundance. To evaluate -diversity (similarity between two communities), the Sørensen similarity index can be calculated. The Sørensen similarity index is calculated based on the absence/presence of species (Rocklin, 2003). Thus, for this study, these indices were calculated in Table 2, presenting respectively a very low diversity index of Shannon in the two villages (0.34 in Dan Saga and 0.47 in Sekoukou). The same for Pielou's equitability index of 0.07 in Dan Saga and 0.10 in Sekoukou. On the other hand, the Sørensen similarity index between the two communities or ecosystems is moderately low (0.489), reflecting a less acceptable similarity between Dan Saga and Sekoukou.

3.5. Biomass and the estimation of carbon stock

Table 3

The carbon stock estimation
Villages	Land surface (ha)	aboveground biomass BA (Kg)	underground biomass BS (Kg)	Total biomass (Kg)	Total carbon C		otal\({{C}{O}}_{2}\)
Villages	Land surface (ha)	aboveground biomass BA (Kg)	underground biomass BS (Kg)	Total biomass (Kg)	Kg	tC/ha	Kg	t/ha
Dan Saga	10	96589.23	24147.30	120736.54	56746.17	5.67	208088.22	20.80
Sekoukou	8	95712.81	23928.20	119641.01	56231.27	7.02	206200.09	25.77
P-value				0.001 ***	0.000 ***		0.001 ***
Code: ***= highly significant difference.

Carbon sequestration (CS) is the process of removing carbon (C) from the atmosphere and depositing it in a reservoir. Hence, compared to the global average or even other parts of Africa, the C storage potential in Sahelian agroecosystems is relatively low (Batjes, 2001). However, Table 3 presented a very low carbon stock potential (5.67 t / ha in Dan Saga and 7.02 t / ha in Sekoukou) similar to Hanan et al., (1998) research conducted on photosynthesis and carbon balance of a Sahelian fallow savanna in West Africa and especially in Niger. On the other hand, compared to the two villages the result showed Sekoukou have more biomass than Dan Saga so more carbon stock than Dan Saga. Therefore, the low carbon stock in this particular zone is mostly related to the climatic condition where the total annual rainfall is less than 700 mm. The population growth exacerbated the pressure on vegetation and increased deforestation, desertification and soil degradation. In addition, climate change emphasized forest degradation in Niger, we observed this last year’s high increase in air temperature which stresses trees. All these effects led to reduced vegetation cover and carbon sequestration in Niger.

3.6. Determination of vegetation changes with the NDVI method

earth's ecosystem changed due to several anthropogenic and natural factors. This can be possible addressed by remote sensing, which has shown great potential analysis of earth surface observation in our study. Indeed, this NDVI method (band 3-4-5) was used to assess the spatiotemporal analysis of Dan Saga and Sekoukou vegetation cover from 2001 to 2013. Thus, Fig. 5 showed a very low spread of vegetation in 2001 than in 2013 in Dan Saga within an interval of [0; 1[, where the band with 0 (yellow colour) represented no vegetation but band 1 (green colour) showed a high density of vegetation. The year 2001 has fewer trees than the year 2013 in Dan Saga village and it's due to some measurement that has been taken by the local population, government and NGOs. Such practices of forest restoration, reforestation, afforestation, and assisted natural regeneration are the main activities developed in this area.

In the same vein, Fig. 6 showed the same improvement of vegetation dynamic from 2001 to 2013 in Sekoukou village but more concentrated on the bank of river Niger.

Agroforestry emerges as a robust farming practice addressing food security problems by making feeds for people, mitigating adverse effects of climate change by enhancing environmental quality, sustaining economic viability and enhancing livelihoods. Therefore, most of the farmers in Niger have mentioned several reasons why they are pruning and conserving trees in their farmland even though the practices differ from one village to another because of the culture and the climate conditions.

Thus, this study involves all the social classes in Dan Saga and Sekoukou villages (men, women and children) as they are the first to benefit from the advantages offer by these agroforestry parklands with the indigenous knowledge of farmers. Subsequently, the technique of Farmer Managed Natural Regeneration (FMNR) that existed about 20 years ago in Dan Saga showed that it is an effective support for strengthening climate resilience and improving basic socio-economic and environmental factors. Sekoukou village has an ecosystem appropriate to agroforestry practices because of its proximity to the bank of river Niger.

However, a good forest management policy in Sekoukou, such as the FMNR, planting trees, land restoration, etc... Could positively change the livelihoods of the population.

The dendrometric parameters, ground cover, regeneration rate, carbon stock and total biomass are significantly different from Sekoukou to Dan Sage villages. Furthermore, the way the population of Dan Saga village are well organized and have been started forest restoration more than 20 years ago, this community will ten have more biomass than Sekoukou village even though it has been considered a wetland (located on the bank of river Niger) but recorded less forest restoration activities in this area.

Agroforestry is recognized as a strategy to reduce greenhouse gases emission, enhance carbon budget, improve food security and build resilience to climate change to benefit from the carbon credit found. These adaptation strategies depend on the agroforestry systems applied in a different agroecological zone with an influence of the culture.

Acknowledgements

I acknowledge with thanks the scholarship and financial support provided by the Federal Ministry of Foreign affairs (BMBF), DAAD, the Centre for Development Research (ZEF) at the University of Bonn, Germany and the West African Centre for Sustainable Rural Transformation (WAC-SRT/Niamey-Niger).

Conflict of interest

All authors declare no conflict of interest in this paper.

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No competing interests reported.

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14 Sep, 2022

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Role of agroforestry parklands in livelihood supports in the rural area of the Sahelo-Sudanian zone in Niger

Status:

Version 1

Abstract

Figures

1. Introduction

2. Material And Methods

2.1. The Study Area

2.2. Sampling technique of forest inventory

2.3. Survey

2.4. Dendrometry parameters

2.5. Diversity Index

2.6. Floristic wealth

2.7. List of inventoried species

2.8. biomass and carbon stock estimation

2.9. Normalized Difference Vegetation Index (NDVI)

3. Results And Discussion

3.1. Agroforestry services

3.2. The woody species’ floristic composition

3.3. Vegetation dynamic

3.4. Diversity indices of Dan Saga and Sekoukou

3.5. Biomass and the estimation of carbon stock

3.6. Determination of vegetation changes with the NDVI method

4. Conclusions

Declarations

References

Additional Declarations

Status:

Version 1