John D. Marshall College of Natural Resources University of Idaho Moscow, ID 83844-1133 jdm@uidaho.edu
John M. Blair Division of Biology Kansas State University Manhattan, KS 66506-4901
This NEON Research Design addresses the Grand Challenge of developing a predictive understanding of the responses of terrestrial and inland aquatic ecosystems to climate variability and climate change. We focus on the short- and long-term ecological consequences of drought, warming, snowpack disappearance, and changes in fire regime. We propose to quantify these effects using sites from the entire continental-scale network, recognizing that the domains were originally delineated, at least in part, based on climate variation. This approach will enable us to detect and quantify the ecological consequences of anticipated climatic changes at multiple scales. This approach will also enhance the probability of detecting the ecological consequences of extreme, stochastic events, such as droughts and fires, that occur locally but can interact with land-use variation to propagate to much larger areas. Coordinated and standardized measurement protocols across the network will enable comparisons of the relative sensitivities of different ecosystems to multiple climate change factors. The continental network will be augmented by intensively instrumented local elevational gradients, sited to detect responses to warming and snowpack disappearance. The snowpack gradients will be distributed broadly but placed at high densities in the headwaters of the Rio Grande and Columbia Rivers and above California’s Central Valley, allowing us to examine the regional ecological impacts of changing snowpack. Increased droughts, warming, and snowpack disappearance will all increase fire severity and frequency. These fire effects will be monitored by atmospheric measurements of combustion products at sites from across the network and by remote sensing between them. Our Research Design relies primarily on infrastructure from the Domain Toolboxes with additions from the Continental Toolbox, primarily to upgrade instrumentation at the snowpack gradient sites.
Observational data will be integrated with simulation models into a conceptual framework for understanding and predicting ecological responses to climate change at local to continental scales. Predictive models will be used to synthesize and integrate data collected across a range of scales and from different networks, to guide collection of additional data and development of new instrumentation, to generate testable hypotheses, and to forecast the ecological consequences of future climate changes. In addition, data from this Research Design can be combined with data from other Designs focusing on land-use, invasive species, lakes and streams to improve our ability to forecast ecological responses to multiple global change factors. To address these NEON challenges, it is critical that we partner with other existing and emerging observatory networks (e.g., Climate Reference Network, National Phenology Network, WATERS, AmeriFlux, National Atmospheric Deposition Program, LTER and others) to maximize the efficient deployment of NEON infrastructure and use of NEON data and models.
This NEON design will require cyberinfrastructure at both individual sites and the network level. Individual site data will be assembled, collected, stored, and transmitted as described in the NEON cyberinfrastructure document. CI needs at the network level will include reformatting and conversion of data required by the models as well as support for the modeling itself.
As climate changes and our understanding of its effects deepens over the next 30 years, NEON will provide important educational opportunities to a broad range of users. Ready access to continental-scale real-time data will inspire a new generation of scientists, particularly as they use these data to understand the dramatic effects of climate change on snowpack, drought, fire, and species shifts unfolding during their lifetimes. Integration and modeling of these data will lead to a host of practical applications, including forecasting the ecological effects of climate change. The forecasts will inform citizens and policymakers and lead to adaptive responses.