The increasing severity of Striga gesnerioides attacks on cowpea across West Africa has been related to its prolificity, seed mobility and longevity, and adaptation to aridity, in a context of agricultural intensification. To understand this fast extension, we analyzed (1) the distributions of the crop and the witchweed with ecological niche modeling and multivariate climate analysis, and (2) the chronological information available from collections and the literature. The ecoclimatic envelope of S. gesnerioides attacks on cowpea is the same as on wild hosts. Consistently, the modeled distribution of cowpea infestations is closely similar to the simple superposition of the parasite model (involving all hosts) and the crop model. Striga gesnerioides infestations are restricted to the driest component of the cultivated cowpea ecoclimatic niche, corresponding to the Sahelian and Sudano-Sahelian belts and the Dahomey gap. Thus, the parasite distribution, determined by its own requirements, does not constrain cowpea cultivation under Guinean climates. The spatial and temporal distributions of S. gesnerioides field infestations are consistent with an earlier impact on cowpea production in eastern West Africa, related itself to a similar trend in cowpea cultivation intensification from Niger, Nigeria and Benin to Burkina Faso and Ghana. Mali and Senegal were affected later, and literature reports of Senegalese strains of S. gesnerioides from the wild developing virulence on cowpea offer a model for the diffusion of witchweed parasitism by multilocal evolution, through host-driven selection, instead of epidemic diffusion. A contrario, in Côte d’Ivoire, cowpea is much less widespread, so the parasite has remained confined to the wild compartment. Thus, both historical and ecogeographic analyses refute the vision of S. gesnerioides as an invader. Instead, they point to the increasing importance and intensification of the crop, and the consequent loss of biodiversity, as the main drivers of the extension and diversification of its crop-specific strains.

Unplanned urban expansion poses significant challenges to environmental sustainability and urban planning. This study analyzes the spatiotemporal dynamics of Zinder’s urban landscape using Landsat satellite imagery from 1988, 2000, 2011, and 2022. The study applied remote sensing (RS), geographic information system (GIS) techniques, and urban growth models. The random forest classifier, a machine learning algorithm, was used to classify three land use/land cover categories: “vegetation”, “built-up”, and “others”. Zinder’s arid environment is characterized by sparse vegetation, which constitutes a limited but vital component of its landscape. Despite the already sparse vegetation in the area, the findings reveal a 3.5% reduction in vegetation cover between 1988 and 2022, alongside an 11.5% increase in “built-up” areas and an 8% decrease in the “others” category. This loss of already minimal vegetation raises significant concerns about environmental degradation and the exacerbation of desertification risks. Interestingly, urban expansion showed no significant correlation with population growth (r = 0.29, p > 0.5), suggesting that other factors, such as economic activities, infrastructure development, and land use policies, drive land conversion. Edge expansion emerged as the dominant growth type, with a significant directional preference (Chi-Square = 2334.41, p < 0.001) toward major roads and areas with higher accessibility to public services. These findings emphasize the need for strategic urban planning and land management policies to address the drivers of unplanned expansion. Prioritizing sustainable infrastructure development, enforcing land use regulations, and conserving natural landscapes are critical to balancing urban growth with environmental preservation, ensuring resilience and sustainability in Zinder.

The study aimed to analyze the process of Landuse/Landcover change of two rural communes (SaéSaboua and Chadakori) of Maradi region (Republic of Niger) over the past 28 years (1986 – 2014),through landscape structure analysis by diachronic cartographic approach and landscape indices. Mixedclassification of temporal series of Landsat images led to identifying six Landuse/Landcover (LULC)classes, namely ”cultivated land under shrubs and trees”, ”cultivated land under trees”, “continuouscropland”, ”fallow/pasture land”, ”forest reserve”, and ”settlement”. The composition and structure ofthe studied landscapes have greatly changed from 1986 to 2014. The class ”cultivated land under trees”was the landscape matrix in 1986 with 38.65% of landscape total area but in 2001 and 2014 the class”continuous cropland” became the landscape matrix. The changes also affected the ”forest reserve”which was transformed to smallholder agricultural land from 1986 to 2014. The area occupied byclasses ”cultivated land under trees” changed from 38.65% in 1986 to 8.78% in 2014; and from 1986to 2014, the area occupied by ”fallow/pasture land” has decreased of about 16%. The decrease in theseclasses was in favor of ¨continuous crop land¨, ¨settlement¨ and “cultivated land under shrubs and trees”which respectively gained 38%, 0.3% and 8.15% of their areas in 1986. The results of this study reflectthe problem of access to land and even land saturation in semi-arid region, a consequence of strongpopulation growth. They also contribute to a better rethinking of agricultural practices in order to initiateadaptation and resilience strategies for the population facing food insecurity and poverty.