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Data from: Incorporating existing thermal tolerance into projections of compositional turnover under climate change

Citation

Bush, Alex et al. (2019), Data from: Incorporating existing thermal tolerance into projections of compositional turnover under climate change, Dryad, Dataset, https://doi.org/10.5061/dryad.jg1bn4s

Abstract

Aim: Observed, realized niche space often underestimates species’ physiological tolerances due to interactions with other species, dispersal constraints, and because some combinations of influential environmental factors do not currently exist in the real world. Conversely, correlative ecological niche models rely on the assumption that the range of environmental conditions encompassed by a species’ geographic distribution accurately reflects their environmental tolerances, including community-level approaches like Generalised Dissimilarity Modelling (GDM). We extend GDM to better understand what effect broader environmental tolerances could have on compositional turnover under climate change. Innovation: We show how GDM can be adjusted as a function of best-available estimates of the average ratio between realized and potential niche widths to modify projected temporal turnover. We demonstrate this approach by using the estimated niche ratios of Australian plant species (n=7184) relative to thermal extremes, and the rate at which this ratio varied with temperature. The modified GDMs showed existing thermal tolerance could reduce the turnover predicted by standard models under climate change by up to 11%. We further show how the reduction in expected turnover by 2090 will influence where a greater proportion of the current community will persist in a region. Main conclusions: We suggest that standard spatial GDMs and their modified versions represent the extremes of ecological niche perspectives (i.e. realized and potential) and the range of tolerance communities may have when responding to environmental change. GDM projections therefore identify the range of uncertainty associated with a critical model assumption, and as climate change continues, ongoing community monitoring could be used to validate the balance between the two possibilities.

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