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The Effects of Environmental Change on Food Webs and StructureEPA Grant Number: U916228
Title: The Effects of Environmental Change on Food Webs and Structure
Investigators: Sculley, Jack
Institution: University of California - Berkeley
EPA Project Officer: Jones, Brandon
Project Period: January 1, 2003 through January 1, 2006
Project Amount: $96,990
RFA: STAR Graduate Fellowships (2003) Recipients Lists
Research Category: Fellowship - Geography , Academic Fellowships , Ecological Indicators/Assessment/Restoration
The objective of this research project is to document the spatial and temporal responses of aquatic, marine, and terrestrial food webs across climate changes of differing temporal scales: a glacial-interglacial cycle, the Younger Dryas cold reversal, the millenial-scale Medieval Warm Period, a decadal PD cycle, and interannual variations such as the El Niño-Southern Oscillation. This research project will reconstruct food-web dynamics across these intervals to answer questions drawn from among the following:
1. Is the scale of climate change encompassed in this research project enough to appreciably disrupt food webs?
2. Which basic characteristics of aquatic and terrestrial food webs change through time and which remain stable?
3. How do climate changes influence the relative importance of top-down and bottom-up trophic interactions?
4. How do trophic properties change: homeostatically, gradually/linearly, or catastrophically/nonlinearly?
5. Which traits increase the resilience of food webs?
The importance of improving our understanding of the relationship between environmental change and responses at the community and ecosystem level is hard to overstate. Communities already are changing in response to global warming (McCarty, 2001), yet current food-web theory is inadequate to make even simple predictions about which responses to expect (Yodzis, 1993; Scheffer, et al., 2001). We need to understand both the mechanisms that stabilize ecosystems across environmental change and mechanisms that destabilize them so that major shifts can occur with little or no perceptible change in the environment (Scheffer, et al., 2001).
The method includes developing an archival and research spatial and temporal database in a geographic information system (GIS) from published data addressing the appropriate time slices. This includes datasets such as the Global Pollen Database, which documents Quaternary plant distributions, and FAUNMAP, which documents Quaternary mammal distributions. Other published data will be acquired that extends into the last interglacial, and published studies on aquatic food webs that have developed high-resolution, integrated data such as pollen, diatoms, lake pigments, and plant and animal macrofossils. The published food web data on 113 modern communities of Briand and Cohen (1987) and more recent updates will be included. These data will be supplemented with fieldwork to obtain supplementary higher resolution data as needed.
Size distribution, diversity, and relative abundance will be analyzed and entered into the GIS. Gross trophic levels will be reconstructed at selected localities from biomass/body size spectra (supplemented by ISN data, where available) and grouped into guilds based on trophic habit (herbivore, frugivore, omnivore, carnivore, insectivore, detritovore, etc.), and separately based on responses to climate variables, and vegetation will be grouped into functional types (submersed aquatics, shallow water emergents, herb, shrub, tree) where possible. Care will be taken to distinguish between migration and in situ change using the spatial GIS data. Comparisons will be made between terrestrial mammal, aquatic and marine food webs, vegetation assemblages, and climatic changes. Changes in the size distribution of faunas over these five time intervals will be evaluated using data entered into the GIS. Concurrent changes in trophic and guild structure will be compared, along with changes in floral and geologic indicators. Statistical analyses will be used to detect patterns of change and correlations or lags between biotic groupings and climate data. By understanding the feedbacks between climate and ecosystems, policymakers will make more informed decisions about conservation and environmental regulation.