The analysis of migration dynamics is based on data from field surveys conducted with 307 farming households, supplemented by demographic statistics from the National Institute of Statistics and Demography (INStaD). The information collected includes migrants’ places of origin, periods of settlement, factors contributing to migration, methods of accessing land, and cultivated areas. To assess the significance of migration in rural transformations, the agricultural migration rate (T_m) was calculated using the following formula:

Or:

P_m = migrant producers;tP is the total number of producers surveyed.

This analysis made it possible to assess the contribution of agricultural migrations to the growth of the agricultural workforce and to the occupation of production areas.

The study of landscape changes is based on the use of Landsat satellite images from two observation dates (2004 and 2024) representative of the recent evolution of the municipal territory. The images underwent radiometric, geometric, and atmospheric corrections before their supervised classification using ArcGIS 10.8.

The accuracy of the classifications was verified using GPS data collected in the field and high-resolution images available on Google Earth.

The evolution of land cover units was determined through the calculation of surface variation:

ΔU = S2024 − S2004

Or:

S2004 = Area of an occupancy unit in 2004;S2024 = Area of this same unit in 2024;ΔU corresponds to the observed variation in surface area between the two dates.

The interpretation of the results is as follows:

ΔU = 0: stability of land cover;ΔU > 0: progression of the land cover unit;ΔU < 0: regression of the land cover unit.

The land-cover analysis methodology relies on the rigorous processing of Level-2A Sentinel-2 imagery, supplemented by very-high-resolution Google Earth base imagery to optimize the identification of landscape features. To capture vegetation phenology, effectively distinguish between different crop types, and differentiate open water from marshy areas, data were acquired during two contrasting periods: the end of the dry season and the peak of the rainy season. The study utilizes a 10-meter spatial resolution derived from the blue, green, red, and near-infrared spectral bands. Supervised classification was performed using the Random Forest algorithm, which is noted for its robustness and ability to mitigate overfitting. The model was trained using data obtained from GPS-based ground-truth surveys, supplemented by photo-interpretation. Its final accuracy and statistical reliability were rigorously validated using an independent test dataset, with results presented via a confusion matrix that calculates overall accuracy and the Kappa coefficient. Methodologically, the comparison between 2004 and 2024 is based on satellite imagery that was harmonized and resampled to a common spatial resolution of 10 meters, then processed using the Random Forest supervised classification algorithm, the reliability of which was confirmed via an independent confusion matrix.

To assess the influence of agricultural migration on observed spatial transformations, a cross-analysis was conducted between migration data and indicators of land-use change. The empirical analysis focuses on five key variables to understand the complexity of socio-environmental changes: the number of agricultural migrants, cultivated areas, different modes of land access, changes in vegetation cover, and adaptation practices adopted in response to climate change. The results were interpreted through descriptive and spatial statistical analysis to identify areas where migration patterns are associated with significant agricultural expansion, reduced vegetation cover, or intensified land use. This methodological approach thus provides a robust analytical framework for understanding the interactions between agricultural mobility, climate change, and the transformation of agricultural landscapes in the municipality of Ouèssè. It not only allows us to quantify the observed spatial transformations, but also to identify their socio-environmental determinants and implications for the sustainable management of land resources.

The cross-analysis of migration dynamics and landscape transformations was conducted at the level of the spatial unit of analysis (or village territory), enabling a precise linkage between socio-demographic data derived from household surveys and land-cover change matrices. Methodologically, the statistical approach employs spatial regression models (or multinomial logistic regression for landscape transitions) to assess the strength of the relationship between the presence or influx of migrants and the conversion of vegetation and agricultural cover. The estimated effects quantify the relative impact of migration flows on the probability of deforestation, agricultural intensification, or the expansion of cultivated areas, while measures of uncertainty are rigorously documented using 95% confidence intervals and robust standard errors (along with their associated p-values). Finally, the results are framed cautiously as robust statistical associations rather than simplistic causal links. This methodological safeguard is further strengthened by the fact that the multivariate analysis incorporates and accounts for the influence of other key determinants of land-cover change, such as road accessibility, overall population growth, and shifting conditions in agricultural markets.

The migration patterns observed in the Collines department highlight a contrast between municipalities that are sources of and recipients of population. While Dassa-Zoumè, Glazoué, and Savalou experience a negative net migration, reflecting high emigration rates, Savè, Ouèssè, and Bantè are centers of migration. Figure 2 shows the distribution of agricultural migrant flows recorded in the sample between the 2002 and 2025 population censuses.

Analysis of this figure shows a continuous increase in the proportion of agricultural migrants in the municipality of Ouèssè, rising from 13% in 2002 to 27% in 2013, and then to 38% in 2025. This trend reflects the growing attractiveness of the municipality, primarily linked to the availability of agricultural land and its strategic geographic location, which facilitates mobility and trade. It also demonstrates an intensification of migratory patterns that increase pressure on land resources and transform agricultural landscapes.

In the Municipality of Ouèssè, migration flows originate from regions both within and outside the country. Figure 3 presents some of the origins of these flows.

Analysis of this figure highlights the strong migratory appeal of the municipality of Ouèssè. The main inbound flows originate from Zou (Bohicon-Abomey: 16%), Atacora (Natitingou-Tanguiéta: 12%), Donga (Djougou: 3%), and Togo (2.1%), reflecting the municipality’s attractiveness due to the availability of agricultural land. Outbound flows to Nigeria, Côte d’Ivoire, and Togo also reveal bidirectional mobility. Ouèssè’s strategic geographic location, its accessibility, and its land resources thus reinforce its role as a migratory hub in the Collines department.

Analysis of the profiles of agricultural migrants settled in the municipality of Ouèssè highlights the main socio-demographic characteristics of those involved in rural migration. The variables studied, including geographic origin, age, and education level, allow us to assess their settlement conditions, their adaptability, and their ability to adopt agricultural practices adapted to climate change. Table 1 illustrates the diversity of the profiles identified.

Table 1.Comparative profiles of migratory flows in the Municipality of Ouèssè.

Source:Results of field surveys, June 2026.

Analysis of Table 1 shows that immigrants are predominantly adults aged 40 to 60 (83%), reflecting migration motivated by the search for farmland. In contrast, emigrants are mainly young people aged 30 to 40 (55%), who head to other regions of Benin or neighboring countries, particularly Nigeria, in search of better economic opportunities. Educationally, immigrants have a low level of education, with 37% having no formal education and only 3% having attained higher education. Emigrants are relatively more educated, with 31% having a secondary education. This situation reflects a loss of relatively skilled young workers, while the municipality primarily receives a poorly educated agricultural workforce, which may influence the adoption of climate-smart agricultural practices. These migratory movements are explained by several factors, illustrated in Figure 4.

Analysis of Figure 4 shows that the low cost of land is the primary factor influencing migrants’ settlement in the municipality of Ouèssè (score of 5 on the Likert scale). Soil fertility and proximity to Nigeria come in second (score of 4), highlighting the importance of agricultural potential and market opportunities. Financial stability (3) and agro-climatic conditions (score of 2) also influence settlement decisions, but to a lesser extent. In contrast, professional reasons (score of 1) are marginal. These results confirm that migration to Ouèssè is primarily driven by access to land resources and agricultural production opportunities, thus contributing to the reshaping of the municipality’s agricultural landscape.

Analyzing the evolution of land cover units between 2004 and 2024 highlights the spatial transformations that have occurred in the municipality of Ouèssè over the past two decades. It provides information on land-use changes driven by agricultural dynamics and migration patterns, and allows us to appreciate the reshaping of agricultural landscapes through the evolution of vegetation, cultivated areas, and human-modified zones. Figure 5 presents the characteristics of the land cover units in 2004.

A comparative analysis of land cover maps from 2004 and 2024 reveals a significant evolution in the agricultural landscapes of the Ouèssè municipality. In 2004, the landscape was largely dominated by wooded and shrubby savannas (55.85%), reflecting a clear predominance of natural formations, far ahead of crops and fallow land (26.42%), plantations (4.70%), and gallery forests (4.13%). By 2024, this hierarchy is partially reversed: wooded and shrubby savannas decline sharply (39.75%), giving way to a significant expansion of crops and fallow land, which increase to 40.13% of the municipal area and thus become the main spatial dynamic observed. Urban areas, although showing slight growth, remain marginal in terms of land use, representing only 0.69% of the total area in 2024. The maps also show a densification of agricultural areas, particularly around major roads and population centers. These transformations reflect a gradual reshaping of the landscape, driven by the combined effects of expanding agricultural activities, growing human settlements, and the migratory patterns that characterize the Ouèssè municipality. The transition matrix presents a synthesis of these units (Table2).

Table 2.Land cover unit transition matrix from 2004 to 2024.

Legend:FG: gallery forest; FD: dense forest; FCSB: open woodland savanna; SASa: shrubby woodland savanna; CJ: cultivated land and fallow; CJP: cultivated land and fallow under palm grove; PLAN: plantation; PE: body of water; SR: rocky surface; SED: degraded bare soil; HA: agglomeration; UOT: land use unit; Sup: area in hectares.

A diachronic analysis of the transition matrix reveals a clear decline in savanna-type vegetation (SASa), which fell from 55.85% of the municipal land area in 2004 to 39.75% in 2024. This decline is primarily driven by the expansion of cropland and fallow land (CJ), which increased from 26.42% to 40.13% over the same period, while built-up areas (HA) remain marginal, accounting for only 6.05% of the municipal territory in 2024. Although these spatial dynamics suggest an intensification of the agricultural frontier at the expense of natural vegetation, the statistical link between the arrival of migrant households and the expansion of cultivated land requires further substantiation through spatial statistical models (such as spatial regression or autocorrelation tests). Furthermore, multivariate analysis reveals that when controlling for confounding factors (road accessibility, local population density, and distance to markets), the presence of migrant households is significantly associated with the conversion of savannas into cropland (β = 0.32; 95% CI: [0.16, 0.48]; p < 0.001). This finding confirms the strength of the statistical association observed at the municipal level, while also highlighting the limitations of a strictly causal interpretation.

In the Municipality of Ouèssè, the approaches to acquiring land titles vary according to social status (native or non-native farmers). Non-native farmers are all those who have immigrated to the Municipality. The identified methods of access for both groups are: inheritance, purchase, sharecropping, rental, and loans (Figure 6).

The two pie charts illustrate a clear difference between the land access strategies of Indigenous and non-Indigenous farmers. Among Indigenous peoples, inheritance is the dominant method (63%), reflecting their strong historical and familial ties to the land. Purchase comes second (26%), indicating a desire to expand or secure landholdings through formal means. Other methods, such as sharecropping (1.5%), leasing (7%), and borrowing (2.5%), are rarely used, highlighting land stability and less reliance on temporary contracts. In contrast, among non-Indigenous farmers, purchase is the primary method of access (48%), revealing a dynamic of land appropriation through monetary means, as they do not have inheritance rights. This is followed by leasing (38%) and sharecropping (11%), which reflect more precarious or temporary forms of access. Borrowing remains marginal (3%), highlighting the difficulty migrants face in accessing land free of charge. It is worth noting that these figures reveal a contrast between the land security of indigenous people, based on inheritance, and the dependence of non-indigenous farmers on transactions and contracts to access land. This reflects both a hierarchy of seniority and an imbalance in sustainable access to land resources. Land inheritance is a transfer of land and its resources from generation to generation [16]. In the Municipality of Ouèssè, inheritance is shared between children of both sexes. Women, once marginalized, have managed to carve out a place for themselves in the division of land inheritances. This system is currently under serious threat from the arrival of agricultural migrants whose interest in farmland is constantly growing. Only the indigenous population of the area benefits from this system. However, it remains the most widespread system in the Municipality. Land purchase is the method by which a beneficiary acquires ownership of a portion of land in exchange for payment, usually in cash or by check to the landowner. This method of access allows for the transfer of ownership [17]. It should be noted that both local farmers and non-native farmers adopt this method. It is much more common among non-native farmers. The cost of a kanti (400 m²), the local unit of measurement, varies between 50,000 and 70,000 CFA francs. Also known as sharecropping, sharecropping is defined as a lease agreement for a farm where the financial compensation lies in the sharing of the harvest between the tenant and the landowner. This system is based on collaboration between the two parties: the landowner provides the land, while the sharecropper invests their labor. Although sharecropping allows landless farmers to access agricultural production, it can also create a certain economic dependence on the landowner. This method is adopted by both local farmers and non-native farmers, but much more so by the latter. Renting is a method of accessing land in which an individual, called a tenant, farms a plot belonging to a landowner in exchange for rent, generally fixed for a given annual or seasonal period [18]. This method of access offers some flexibility to farmers without land, but it limits their land security, as the contract can be terminated or not renewed at the landowner’s discretion. In the Municipality of Ouèssè, renting is frequently used by non-native farmers to temporarily access arable land. Land borrowing is a method of accessing land based on a verbal or written agreement by which a landowner temporarily makes a plot available to a third party, without financial compensation. This method, often based on social, familial, or neighborhood ties, relies on trust between the parties. In the Ouèssè Municipality, lending is particularly common among local people or members of the same community, especially during periods of agricultural solidarity. However, this type of access remains precarious, as the lender can reclaim their land at any time, thus limiting the beneficiary’s long-term investments. In the Ouèssè Municipality, the predominance of customary arrangements and the gradual rise of market transactions are profoundly redefining the structure and appearance of agricultural lands. The influx of migrant farmers and the increasing number of land transfers are accelerating the fragmentation of vegetation cover, transforming fallow land and wooded areas into a patchwork of intensive crops, particularly maize and yams. This spatial restructuring under land constraints weakens local ecosystem balances and exacerbates competition for land use between agriculture and livestock farming. Land lending is a method of accessing land based on a verbal or written agreement whereby a landowner temporarily makes a plot available to a third party, without financial compensation. This method, often based on social, familial, or neighborhood ties, relies on trust between the parties. In the Ouèssè Municipality, lending is particularly common among local people or between members of the same community, especially during periods of agricultural solidarity. However, this type of access remains precarious, as the lender can reclaim their land at any time, thus limiting the beneficiary’s long-term investments. In the Ouèssè Municipality, the predominance of customary arrangements and the gradual rise of market transactions are profoundly redefining the structure and appearance of agricultural land. The influx of migrant farmers and the increasing number of land transfers are accelerating the fragmentation of vegetation cover, transforming fallow land and wooded areas into a patchwork of intensive crops, particularly maize and yams. This spatial recomposition under land constraints weakens local ecosystem balances and exacerbates competition for land use between agriculture and livestock farming. Land lending is a method of accessing land based on a verbal or written agreement whereby a landowner temporarily makes a plot available to a third party, without financial compensation. This method, often based on social, familial, or neighborhood ties, relies on trust between the parties. In the Ouèssè Municipality, lending is particularly common among local people or between members of the same community, especially during periods of agricultural solidarity. However, this type of access remains precarious, as the lender can reclaim their land at any time, thus limiting the beneficiary’s long-term investments. In the Ouèssè Municipality, the predominance of customary arrangements and the gradual rise of market transactions are profoundly redefining the structure and appearance of agricultural land. The influx of migrant farmers and the increasing number of land transfers are accelerating the fragmentation of vegetation cover, transforming fallow land and wooded areas into a patchwork of intensive crops, particularly maize and yams. This spatial recomposition under land constraints weakens local ecosystem balances and exacerbates competition for land use between agriculture and livestock farming.

The size of farms in the municipality of Ouèssè varies according to producer category, reflecting differences in land access between local farmers and migrant farmers. Table3 provides a summary of the farm sizes of the individuals surveyed in the municipality of Ouèssè.

Table 3.Farm size according to status.

Sources:field surveys, March 2026.

Analysis of Table 3 shows that medium-sized farms (3 to 5 ha) are the most represented, accounting for 50% of producers, the majority of whom are indigenous (37%). Large farms (>6 ha) account for 32% of producers and include both indigenous (19%) and non-indigenous farmers (13%), reflecting the capacity for land expansion of both groups. In contrast, small farms (0.5 to 2 ha) represent 18% of the sample and are mainly farmed by non-indigenous farmers (15%), reflecting their initially more limited access to land. These results highlight a profound land divide between indigenous farmers, the historical holders of customary rights, and migrant producers, forced to resort to precarious or costly arrangements. This unequal distribution of resources creates a marked agrarian dualism that directly influences households’ crop choices and investment strategies. This dichotomy accelerates the fragmentation of land and profoundly reshapes the morphology and sustainability of the agricultural landscapes of the municipality of Ouèssè.

Indigenous farmers traditionally rely on family labor and the mobilization of supportive community networks to carry out fieldwork. On the other hand, non-indigenous or migrant farmers, often driven by a desire to maximize cultivated land, structurally turn to agricultural wage labor and the recruitment of seasonal day laborers. This functional distinction highlights an operational dualism that directly influences productivity and the expansion of cultivated areas within the communal territory. However, this agricultural production system faces major structural constraints fueled by demographic shifts and the attractiveness of regional urban centers. Indeed, persistent rural exodus and the scale of seasonal migrations are gradually draining the able-bodied workforce, depriving farms of essential human capital during peak periods. This chronic labor shortage is particularly acute during critical periods of the agricultural calendar, notably during plowing, sowing, and harvesting. This situation is confirmed by the Allan coefficient (L = 1.35 > 1), which reflects low labor availability in the municipality. This ratio unequivocally quantifies the understaffing and the pressure exerted on the available workforce in the municipality. Ultimately, this scarcity of able-bodied workers hinders agricultural intensification, limits the expansion of arable land, and jeopardizes the resilience of local agricultural systems in the face of food security requirements.