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Harvard Forest Research Project 2024
- Title: Collaborative proposal: Combining NEON and remotely sensed habitats to determine climate impacts on community dynamics
- Principal investigator: James Clark (jimclark@duke.edu)
- Institution: Duke University
- Primary contact: Jordan Siminitz (jordan.siminitz@duke.edu)
- Team members: Roland Kays
Arielle Parsons - Abstract:
The impact of climate change on biological communities will depend on interactions involving the local habitat and the species that interact with one another. As each species responds directly to climate, it indirectly affects all of the species with which it interacts. These species interactions complicate our ability to predict climate effects, because each species experiences habitat complexity at a different scale ”from flightless insects to large vertebrates." Not surprisingly, current species distribution models (SDMs) used to anticipate community responses to climate change are too imperfect to provide much guidance. This study combines data from the National Ecological Observation Network (NEON) with new data collection and a new modeling approach that analyzes the combined responses of species to climate, habitat and one another. This study will determine how diverse communities of species monitored in NEON (ground beetles, vascular plants, small mammals, birds) respond together with food supply, in the form of masting shrubs and trees, and large mammal surveys. A focus on the mast system of pulsed seed and fruit production from trees, includes vertebrate consumers, and indirect interactions with arthropod competitors and vertebrate predators. Remotely-sensed imagery and the NEON airborne observatory will be used to characterize habitat diversity. Results of this analysis will be used to forecast community change and reorganization, including prediction and attribution of climate risk by species and habitat and how it is shared across species groups. Together these results will extend ecological forecasting to include how communities respond to climate change. The study offers a framework for synthesizing environmental and biological data across the NEON network, one that can be exploited by the scientific community for integration with their own analyses. New data on large mammals and seed production from NEON sites will be made available to the community. The study will engage the public through citizen assisted identification of animal images. Forecasts of community responses to climate will be made available through a web site. A workshop will be offered for training of advanced PhDs, postdocs, and academic and agency scientists in the use of our modeling tools and NEON data. The study will train two graduate students, including a program in science communication, and involve four undergraduates in fieldwork.
