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

Abstract

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