Modeling Climate-Induced Range Shifts with Bioclimatic Predictors
DOI:
https://doi.org/10.61978/sativa.v1i4.1428Keywords:
Climate Change, Pest Distribution, Species Distribution Modeling, Growing Degree Days, Extreme Weather, Agricultural Resilience, SPIAbstract
Climate change is accelerating shifts in the distribution and intensity of agricultural pests and diseases, threatening global food security and crop resilience. This study investigates the role of climate variables including temperature, moisture, and extreme events in shaping pest dynamics using biologically relevant climate indicators. Historical and projected climate data (ERA5, WorldClim v2.1) were combined with pest occurrence records (GBIF) and cropping system data to build species distribution models (SDMs) under multiple Shared Socioeconomic Pathways (SSPs). Derived climate indicators such as Growing Degree Days (GDD), Standardized Precipitation Index (SPI), and heatwave duration were found to be more predictive of pest suitability than raw climate variables. Results reveal significant historical range expansions for pests like Spodoptera frugiperda, correlated with increased thermal accumulation. Future projections under high-emission scenarios (e.g., SSP585) indicate up to a 42% increase in pest-suitable areas by 2041–2060. Overlaying pest risk maps with cropping system changes highlights regions with heightened exposure risk due to cropland expansion and altered planting calendars. Climate extremes, particularly droughts and heatwaves, emerged as key modulators of pest reproduction and outbreak frequency. The study underscores the value of integrating climate indicators into spatial pest risk assessments and supports the development of early warning systems for climate-resilient agriculture. It also identifies critical modeling limitations, including data gaps and ecological oversimplifications, while recommending interdisciplinary collaboration and real-time data integration for future model improvements.
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