Zhenghua Lian, Juan Wang, Chunyu Zhang, Xiuhai Zhao, Klaus von Gadow. Mismatch between species distribution and climatic niche optima in relation to functional traits[J]. Forest Ecosystems, 2022, 9(1): 100077. DOI: 10.1016/j.fecs.2022.100077
Citation: Zhenghua Lian, Juan Wang, Chunyu Zhang, Xiuhai Zhao, Klaus von Gadow. Mismatch between species distribution and climatic niche optima in relation to functional traits[J]. Forest Ecosystems, 2022, 9(1): 100077. DOI: 10.1016/j.fecs.2022.100077

Mismatch between species distribution and climatic niche optima in relation to functional traits

  •   Background  Forecasts of climate change impacts on biodiversity often assume that the current geographical distributions of species match their niche optima. However, empirical evidence has challenged this assumption, suggesting a mismatch. We examine whether the mismatch is related to functional traits along temperature or precipitation gradients.
      Methods  The observed distributions of 32 tree species in northeast China were evaluated to test this mismatch. Bayesian models were used to estimate the climatic niche optima, i.e. the habitats where the highest species growth and density can be expected. The mismatch is defined as the difference between the actual species occurrence in an assumed niche optimum and the habitat with the highest probability of species occurrence. Species' functional traits were used to explore the mechanisms that may have caused the mismatches.
      Results  Contrasting these climatic niche optima with the observed species distributions, we found that the distribution-niche optima mismatch had high variability among species based on temperature and precipitation gradients. However, these mismatches depended on functional traits associated with competition and migration lags only in temperature gradients.
      Conclusions  We conclude that more relevant research is needed in the future to quantify the mismatch between species distribution and climatic niche optima, which may be crucial for future designs of forested landscapes, species conservation and dynamic forecasting of biodiversity under expected climate change.
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