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Predicting effects of future development on a territorial forest songbird: methodology matters
Authors:Michelle L Brown  Therese M Donovan  Ruth M Mickey  Gregory S Warrington  W Scott Schwenk  David M Theobald
Institution:1.Vermont Cooperative Fish and Wildlife Research Unit, Rubenstein School of Environment and?Natural Resources,University of Vermont,Burlington,USA;2.U. S. Geological Survey, Vermont Cooperative Fish and Wildlife Research Unit, Rubenstein School of Environment and?Natural Resources,University of Vermont,Burlington,USA;3.Department of Mathematics and Statistics,University of Vermont,Burlington,USA;4.Department of Fish, Wildlife, and Conservation Biology,Colorado State University,Fort Collins,USA;5.The Nature Conservancy,Keene Valley,USA;6.North Atlantic Landscape Conservation Cooperative,Hadley,USA;7.Conservation Science Partners, Inc,Fort Collins,USA
Abstract:

Context

Projected increases in human population size are expected to increase forest loss and fragmentation in the next century at the expense of forest-dwelling species.

Objectives

We estimated landscape carrying capacity (N k) for Ovenbirds in urban, suburban, exurban, and rural areas for the years 2000 and 2050, and compared changes in N k with changes in occupancy probability.

Methods

Maximum clique analysis, a branch of mathematical graph theory, was used to estimate landscape carrying capacity, the maximum potential number of territories a given landscape is capable of supporting (N k). We used occupancy probability maps as inputs for calculating Ovenbird N k in the northeastern USA and a spatially explicit growth model to forecast future development patterns in 2050. We compared occupancy probability with estimates of N k for urban, suburban, exurban, and rural areas for the years 2000 and 2050.

Results

In response to human population growth and development, Ovenbird N k was predicted to decrease 23% in urban landscapes, 28% in suburban landscapes, 43% in exurban landscapes, and 20% in rural landscapes. These decreases far exceeded decreases in mean occupancy probabilities that ranged between 2 and 5% across the same development categories. Thus, small decreases in occupancy probability between 2000 and 2050 translated to much larger decreases in N k.

Conclusions

For the first time, our study compares occupancy probability with a species population metric, N k, to assess the impact of future development. Maximum clique analysis is a tool that can be used to estimate N k and inform landscape management and communication with stakeholders.
Keywords:
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