Species Distribution Modeling

Species Distribution Modeling (SDM) is a quantitative approach that uses the relationship between observed species occurrences and environmental conditions to predict the geographic distribution of species across landscapes, regions, or the globe. SDMs are among the most widely used tools in ecology and conservation biology, providing spatially explicit predictions of where environmental conditions are suitable for a species, even in areas that have never been surveyed. Modeling Approaches and DataSDMs relate georeferenced species occurrence records to environmental predictor variables that represent the ecological niche of the species. Common predictors include bioclimatic variables derived from temperature and precipitation records, terrain variables from digital elevation models, land cover classifications from satellite imagerySatellite ImagerySatellite imagery consists of photographs and data captured by Earth observation satellites orbiting the planet. Thes..., soil properties, and proximity to water features. Presence-only methods like MaxEnt model the environmental conditions at known occurrence locations relative to the background environment. Presence-absence methods like generalized linear models and random forests use both presence and confirmed absence data to model habitat suitability. Ensemble modeling combines predictions from multiple algorithms to reduce model-specific uncertainty and produce more robust distribution estimates. Applications and ChallengesRange mapping produces comprehensive distribution maps for species that have been only partially surveyed, filling knowledge gaps for conservation assessment. Climate change impact projection models how species ranges will shift as temperatures and precipitation patterns change, identifying potential refugia and areas of future range loss. Conservation gap analysis compares predicted species distributions with existing protected area networks to identify gaps in protection. Biosecurity screening predicts where invasive species could establish if introduced to new regions. Key challenges include spatial bias in occurrence records toward accessible and well-surveyed areas, the difficulty of accounting for biotic interactions like competition and predation, the assumption that species are in equilibrium with current environmental conditions, and transferring models to novel environmental conditions that species have not yet experienced.