UCLA

Tropical dry forests have been estimated to comprise 42% of all tropical forested biomes and are believed to be one of the world’s most endangered ecosystems. There is a growing interest in identifying forest extent and forest change in tropical dry forest regions, especially to identify dry forest that deserve a high conservation priority at a global spatial scale. There is currently a debate concerning the classification and extent of tropical dry forest at the global scale. We identify the extent of tropical dry forest regions based on commonly used climatic definitions and datasets to improve global estimates of tropical dry forest extent. We compare climatic definitions of tropical dry forest (Murphy and Lugo, FAO, Dryflor, Aridity Index) using Worldclim, CHELSA, and Global Aridity and PET climatic datasets (1 km) and compare results to the World Wildlife Fund’s Terrestrial Ecoregions (Tropical and Subtropical Dry Broadleaf Forest), as well as 579 field plots identified as tropical dry forest. Understanding the best method to estimate global tropical dry forest extent gives both researchers and policy makers a vital tool to begin protecting this critically endangered and valuable resource. We identify methods that most accurately predicted tropical dry forest extent. The global extents of tropical dry forest regions varied significantly with the Aridity Index predicting the largest extent, Murphy and Lugo and FAO predicting similar extents, and DryFlor predicting the smallest extent regardless of climatic dataset used. Globally, there was low agreement between climatic definitions and WWF Ecoregions. FAO and the Aridity Index climate definitions had the highest agreement with WWF Tropical and Subtropical Dry Broadleaf Forest Ecoregions (57%) while FAO (76%) and Murphy and Lugo (69%) definitions had the highest agreement with field plots. However, extents and accuracy varied significantly by regions, biodiversity hotspots, and island archipelagos. Tropical dry forest region extent varies significantly based on climatic definition but not climatic datasets at a global spatial scale. Nearly half of all tropical dry forests will be missed when only analyzing WWF Ecoregion boundaries and climatic definitions will be needed to estimate dry forest cover and change. There was high heterogeneity among climatic definitions at a regional and local spatial scale suggesting that climate definition can only provide a first order hypothesis about the distribution of dry forests and data on phenology, forest structure, and composition are still needed to compare local tropical dry forest extent.