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Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using rangewide monitoring data.

Robert K ShriverCharles B YackulicDavid M BellJohn B Bradford
Published in: Ecology (2021)
Climate change is expected to alter the distribution and abundance of tree species, impacting ecosystem structure and function. Yet, anticipating where this will occur is often hampered by a lack of understanding of how demographic rates, most notably recruitment, vary in response to climate and competition across a species range. Using large-scale monitoring data on two dry woodland tree species (Pinus edulis and Juniperus osteosperma), we develop an approach to infer recruitment, survival, and growth of both species across their range. In doing so, we account for ecological and statistical dependencies inherent in large-scale monitoring data. We find that drying and warming conditions generally lead to declines in recruitment and survival, but the strength of responses varied between species. These climate conditions point to geographic regions of high vulnerability for particular species, such as Pinus edulis in northern Arizona, where both survival and recruitment are low. Our approach provides a path forward for leveraging emerging large-scale monitoring and remotely sensed data to anticipate the impacts of global change on species distributions.
Keyphrases
  • climate change
  • electronic health record
  • genetic diversity
  • human health
  • machine learning
  • free survival
  • deep learning
  • wastewater treatment