Adaptation Atlas Pest and Disease Yield Impacts

This dataset contains spatially explicit projections of climate-driven changes in crop pest and pathogen performance and their implications for global crop yields. It includes modeled shifts in relative pest and pathogen performance under multiple future climate scenarios, derived from experimentally based thermal performance relationships and projected growing-season temperatures.
The dataset also provides estimates of the indirect effects of climate change on maize, rice, soybean, and wheat yields mediated by changes in pest and pathogen performance, expressed as proportional changes in yield loss relative to current conditions.
In addition, the dataset integrates these indirect effects with existing projections of the direct impacts of climate change on crop yields to produce estimates of net yield change under future climates. Together, these outputs enable assessment of how biological responses of crop pests and pathogens may alter the magnitude, direction, and spatial distribution of climate change impacts on global food production.

Methodology:Temperature‐dependent performance data for crop pests and pathogens (P&Ps) were synthesized using a systematic Web of Science search and screened to include measured performance across at least four temperatures. Asymmetric thermal performance curves (TPCs) were fit to each experiment using Brière functions; time‐series measurements were summarized using spline-based area under the curve estimates. Curves lacking unimodal responses or known geographic origins were excluded.
This yielded 285 TPCs across 128 P&P species or strains, from which optimum temperatures and thermal breadths were derived. Present day and future growing-season mean temperatures were taken from five CMIP6 global climate models under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, SSP5-8.5). Changes in proportional P&P performance under future climates were calculated relative to current conditions and analyzed using linear mixed-effects models. Spatial projections of P&P performance change were generated using mixed-effects models for all GCM × SSP combinations. Indirect effects of climate change on crop yields were estimated by translating projected changes in P&P performance into changes in yield loss using published global loss estimates. These indirect effects were combined with direct climate impacts on crop yields from ISIMIP3b to estimate net climate change effects across crops, scenarios, and model ensembles. (2026-01)