Using near‐ground leaf temperatures alters the projected climate change impacts on the historical range of a floristic biodiversity hotspot

Aim Species distribution models (SDMs) have been used widely to predict the responses of species climate change. However, data drive these typically represents ambient air temperatures, derived from measurements taken 1–2 m above ground. Most plant live near ground where temperatures can differ significantly, owing effects solar radiation and reduced wind speed. Here, we investigate differences in spatio-temporal patterns near-ground leaf implications this has on projected changes richness a suite Fynbos species. Location Biome, South Africa. Methods For each individual (n = 83), constructed two types SDMs: one using temperatures. Each was fitted occurrence for recent time period backwards into past. projections both periods were then binarized projections. Results We found that impact change – degree suitable lost historical range gained outside greater SDMs built with Independent validation hindcast revealed be more accurate. Main Conclusions Our study suggests are likely overestimating breadth species’ occupied thermal niche, thus underestimating change-driven risk particularly decoupled another. Additionally, may ex-situ refugial potential inland mountains. Ambient should not considered an effective surrogate investigating impacts living