Methodologies for Extrapolating from Local to Regional Ecosystem Scales: Scaling Functions and Thresholds in Animal Responses to Landscape Pattern and Land Use

EPA Grant Number: R826764
Title: Methodologies for Extrapolating from Local to Regional Ecosystem Scales: Scaling Functions and Thresholds in Animal Responses to Landscape Pattern and Land Use
Investigators: Wiens, John A. , Horne, Beatrice Van
Institution: Colorado State University
EPA Project Officer: Hahn, Intaek
Project Period: October 1, 1998 through September 30, 2001 (Extended to December 31, 2002)
Project Amount: $581,519
RFA: Regional Scale Analysis and Assessment (1998) RFA Text |  Recipients Lists
Research Category: Ecosystems , Ecological Indicators/Assessment/Restoration

Description:

The objective of this research is to develop and test new concepts and methodologies for evaluating how changes in scale and scale-dependent thresholds in system processes are expressed in ecological landscapes. We will derive scaling functions and GIS-based spatial models to assess how information gathered at fine scales in intensive studies can be extrapolated to the broad scales of ecological monitoring and environmental risk assessment. Such models will be used to predict the effects of landscape change associated with anthropogenic activities on animal distributions and community biodiversity and functional organization at multiple scales of resolution.

Approach:

Our approach is based upon combining inventories of the occurrence and abundance of species with specifications of the ecological and life-history attributes of these species to define suites of species that share functional properties and respond to environmental variation on similar scales. This information will be linked with multiscale analyses of landscape composition and structure, using GIS modeling and spatial modeling. The mathematical functions derived from these models will be used to predict changes in species occurrences, functional group composition, and biodiversity at broader scales and to identify scaling thresholds at which community organization changes. The models will be validated and their predictions tested in direct field applications.

Expected Results:

We will develop specific models and a methodological structure for determining how the results of local, intensive studies and regional monitoring programs (i.e. species inventories and landscape maps) and remote sensing can be linked together.

The methodology will provide a way of defining the limits of scaling extrapolation functions based on functional (process) attributes of species, and of assessing the impacts of anthropogenic stresses on biological communities. The approach will not require detailed, situation-specific information and will be applicable in a wide range of ecosystems and landscapes.

Publications and Presentations:

Publications have been submitted on this project: View all 38 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 5 journal articles for this project

Supplemental Keywords:

terrestrial ecosystems, animals, indicators, scaling, habitat assessment, grazing, conservation, EMAP, Great Plains, CO, NM, ID, land management,, RFA, Scientific Discipline, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, Ecosystem/Assessment/Indicators, Ecosystem Protection, State, climate change, Ecological Effects - Environmental Exposure & Risk, Monitoring/Modeling, Environmental Monitoring, Regional/Scaling, Ecological Risk Assessment, Ecological Indicators, Agricultural Engineering, ecological exposure, EMAP, scaling, landscapes, risk assessment, extrapolation methods, biodiversity, ecosystem assessment, landscape context, Idaho (ID), terrestrial ecosystems, animal responses, spatial scale, New Mexico (NM), conservation, land use change, regional scale impacts, GIS, conservation , landscape patterns, grazing, indicators, land use, land management, Environmental Monitoring & Assessment Program

Progress and Final Reports:

  • 1999 Progress Report
  • 2000 Progress Report
  • 2001 Progress Report
  • 2002
  • Final Report