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Microclimate reveals the true thermal niche of forest plant species.

Stef HaesenJonathan LenoirEva GrilPieter De FrenneJonas J LembrechtsMartin KopeckýMartin MacekMatěj ManJan WildKoenraad Van Meerbeek
Published in: Ecology letters (2023)
Species distributions are conventionally modelled using coarse-grained macroclimate data measured in open areas, potentially leading to biased predictions since most terrestrial species reside in the shade of trees. For forest plant species across Europe, we compared conventional macroclimate-based species distribution models (SDMs) with models corrected for forest microclimate buffering. We show that microclimate-based SDMs at high spatial resolution outperformed models using macroclimate and microclimate data at coarser resolution. Additionally, macroclimate-based models introduced a systematic bias in modelled species response curves, which could result in erroneous range shift predictions. Critically important for conservation science, these models were unable to identify warm and cold refugia at the range edges of species distributions. Our study emphasizes the crucial role of microclimate data when SDMs are used to gain insights into biodiversity conservation in the face of climate change, particularly given the growing policy and management focus on the conservation of refugia worldwide.
Keyphrases
  • climate change
  • electronic health record
  • public health
  • big data
  • molecular dynamics
  • genetic diversity
  • machine learning
  • mental health
  • single molecule
  • data analysis