- Related Research Areas
- Carbon Cycle & Ecosystems, Climate Variability & Change
We seek to test the hypothesis that recent advances in remotely sensed technologies can significantly improve our ability to measure the impacts of land-cover and evaluate the role of climate change on biodiversity. We propose to investigate the effects of climate change and landcover change on shifting patterns of biodiversity during two decades of observational data and, through model development we will forecast vegetation, climate and biodiversity into the future. Our measure of biodiversity will be songbirds. Songbird communities offer an excellent taxon for examining changes in biodiversity because they tend to be sensitive to environmental change and can be monitored using regional surveys such as atlases. As such, the New York State Breeding Bird Atlas is a unique survey documenting distribution of ~250 species across the entire state in 1980-1985, and was repeated in 2000-2005. Based on this atlas, we recently found strong evidence of northward range shifts for many species, and that the two likely drivers of these shifts have been regional climatic changes and large-scale afforestation from agricultural abandonment. A principal limitation, however, is the current inability to characterize, at landscape scales, early-successional communities that provide critical habitat to many of the bird species experiencing range shifts. In this research, we propose to acquire LIDAR data to identify these transitional covertypes and other vegetation structure indicators at landscape scales. Climatic change during this period will be evaluated using spatially interpolated historical records (PRISM data). Results from both climatic and land-cover change analyses will be aggregated at the BBA block resolution for statistical modeling. We will model observed range shifts in NYS based on observed changes in climate and modeled changes in vegetation structure from 1980-2005. We will develop a forest succession model based on LIDAR measurements of several chronosequences of old-field communities to derive vegetation structure (e.g., height, canopy architecture), across sites varying in prior land use (e.g., crops, pasture). Our model will hindcast from present day (2010) to the vegetation structure during the first BBA survey (1980) and then forecast to 2030 and beyond. We will use an information-theoretic approach to test competing hypotheses pertaining to the roles of climate and land use change in shifting bird species distributions. The proposed work is relevant to NASA’s priorities and has significant societal value because it seeks to address needs for: (1) rigorous measures of the influence of climate change on biodiversity that can provide leaders in government and business with better information to make policy decisions - our work is a significant step toward assessment of the biodiversity at the species and ecosystems levels; (2) new scientific knowledge through development of models that improve predictive capabilities based on data from NASA satellite missions; (3) proof that LIDAR can complement existing NASA spaceborne sensors to assess biodiversity patterns and processes - our efforts will provide concrete evidence for launching LIDAR technology into orbit; (4) support of the transition between research and operations by providing an assessment of the influence of existing and novel three-dimensional statistics extracted from LIDAR waveform for biodiversity applications allowing development of a common framework for data processing and distribution beyond the LIDAR scientific community - critical as new missions (e.g. DESDynI) are around the corner; (5) showcasing of the scientific value of the unique multi-temporal NY statewide Breeding Bird Survey and provide suggestions for implementations at other sites; (6) reaching out to relevant scientific communities and the general public and inform them of novel data, model and results (e.g. through our own courses and workshops).
Project PI: Giorgos Mountrakis/The State University of New York
SUNY-ESF 419 Baker Lab 1 Forestry Dr. Syracuse, New York 13210-2778
Phone: (315) 470-4824
Fax: (315) 470-6958
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