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Brown, M. L., T. M. Donovan, R. M. Mickey, G. S. Warrington, W. S. Schwenk, and D. S. Theobald. 2017. Predicting effects of future development on a territorial forest songbird: methodology matters. Landscape Ecology 33:93-108. DOI 10.1007/s10980-017-0586-8


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.

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

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 (Nk). We used occupancy probability maps as inputs for calculating Ovenbird Nk in the northeastern USA and a spatially explicit growth model to forecast future development patterns in 2050. We compared occupancy probability with estimates of
Nk for urban, suburban, exurban, and rural areas for the
years 2000 and 2050.

In response to human population growth and development, Ovenbird Nk was predicted to decrease23% 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 Nk.

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


Current Staff

Federal Staff: 2

Masters Students: 2

Phd Students: 4

Post Docs: 0

University Staff: 3

5 Year Summary

Students graduated: 5

Scientific Publications: 24

Presentations: 35



October (4th Quarter/Autumn) 2017


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Unit Authors

Vermont Cooperative Fish and Wildlife Research Unit Cooperators

  1. U.S. Geological Survey
  2. University of Vermont
  3. Vermont Fish and Wildlife Department
  4. Wildlife Management Institute