Simulation-Based Analysis of Agroforestry Practices in Kisii County Kenya

Abstract

Agroforestry, the integration of trees into agricultural landscapes, is a sustainable practice that enhances biodiversity, improves soil health, and contributes to climate change mitigation. In Kisii County, agroforestry is particularly important due to the region’s reliance on agriculture and the challenges posed by climate change. This study focuses on simulating and analyzing the impact of common agroforestry tree species in Kisii County, including Grevillea robusta, Sesbania sesban, Casuarina equisetifolia, and Markhamia lutea. Using R programming, this study simulates data on tree density, crop yield, livestock density, soil health, biodiversity index, and carbon sequestration. Linear regression models revealed that tree density had a significant negative effect on crop yield (p < 0.001) but positive effects on soil health and carbon sequestration (p < 0.01). The findings suggest trade-offs between tree density and crop productivity that need careful management. This study provides data-driven insights for optimizing agroforestry practices in Kisii County to balance agricultural productivity with environmental benefits.