Soil and Climate Characterization to Define Environments for Summer Crops in Senegal

Carlos Manuel Hernández,P V Vara Prasad,Mamadou Ousseynou Ly,Luciana Nieto,Zachary P Stewart,Ignacio Antonio Ciampitti,Ana J P Carcedo,Leonardo Mendes Bastos,Aliou Faye

doi:10.3390/su132111739

Abstract

Investigating soil and climate variability is critical to defining environments for field crops, understanding yield-limiting factors, and contributing to the sustainability and resilience of agro-ecosystems. Following this rationale, the aim of this study was to develop a soil–climate characterization to describe environmental constraints in the Senegal summer-crops region. For the soil database, 825 soil samples were collected characterizing pH, electrical conductivity (EC), phosphorus (P), potassium (K), cation exchange capacity (CEC), and total carbon (C) and nitrogen (N). For the climate, monthly temperature, precipitation, and evapotranspiration layers were retrieved from WorldClim 2.1, CHIRPS and TERRACLIMATE. The same analysis was applied individually to both databases. Briefly, a principal component analysis (PCA) was executed to summarize the spatial variability. The outcomes from the PCA were subjected to a spatial fuzzy c-means algorithm, delineating five soil and three climate homogeneous areas, accounting for 73% of the soil and 88% of the climate variation. To our knowledge, no previous studies were done with large soil databases since availability field data is often limited. The use of soil and climate data allowed the characterization of different areas and their main drivers. The use of this classification will assist in developing strategic planning for future land use and capability classifications.

Highlights

This is especially relevant to smallholder farmers based on their specific environments due to a lack of access to timely information and limited resources to adapt to climate variability
Positive values of the MI verify the presence of spatial autocorrelation, showing the degree of similarity of a value in a given site with respect to the surrounding data neighborhood
Our main findings were that (i) from the soils perspective, delineating five homogeneous areas with cluster analysis for the soil dataset accounted for roughly 73% of the variation in the spatial scale, with most relevant variables as Ctot, Ntot, cation exchange capacity (CEC), electrical conductivity (EC), pH, and

Summary

Introduction

Senegal current population of 17.2 million [1] is projected to double by 2050, requiring greater food production to meet the increasing demand [2] In this context, improving our understanding of the impact of climate drivers on the crop production and their effects on food security [3,4,5], especially in the developing countries in the West Africa region [2] is a critical need. Food security has been a top priority over the last several decades, even more due to the reported variability in precipitation distribution and its seasonal patterns [7] Climate drivers such as erratic precipitation and more extreme events represent a serious threat to food security [8]. This is especially relevant to smallholder farmers based on their specific environments due to a lack of access to timely information and limited resources to adapt to climate variability

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Discussion

Conclusion