Frontiers in Ecology and Evolution (Jan 2024)
Comparative analysis of habitat suitability for a crop and its primary insect herbivore: providing insights for crop planting and pest management strategies
Abstract
Habitat suitability analysis using species distribution models (SDMs) presents a valuable approach for determining appropriate land utilization strategies and crop planting decisions, which are vital to achieve optimal agricultural productivity and ensure environmental sustainability in the context of rapid global change. Aside abiotic conditions, pests emerge as the most important biological factor affecting crop growth. It can be an effective avenue to comprehensively assess land use suitability by building and integrating SDMs for both crops and their pests. Using the MaxEnt model and a bivariate map, we predicted and integrated the habitat suitability of tea (Camellia sinensis) and its primary insect herbivore (Empoasca onukii) in China. Our study explicitly revealed spatial heterogeneity in suitability between the two species, despite finding that they shared common environmental predictors (i.e., temperature, elevation, and soil pH). Results support South China and Southwest China as the most favorable areas for tea cultivation, while highlighting the adverse climatic challenges on tea growth in the middle and lower reaches of the Yangtze River and in the northern regions of the Yangtze River. Meanwhile, analyses emphasize the necessity of sustainable leafhopper management strategies in the middle and lower reaches of the Yangtze River and in regions along the southeast coast. These findings demonstrate the significance of comparative analysis on the habitat suitability of both crops and insect herbivores, providing valuable insights for agricultural production planning and sustainable pest management. Furthermore, the methods employed in this study hold potential for the application in diverse context, ranging from the control of invasive species to the conservation of endangered biodiversity.
Keywords
