UVM Theses and Dissertations
Format:
Print
Author:
Brown, Michelle Lynn
Dept./Program:
Natural Resources
Year:
2012
Degree:
MS
Abstract:
Forest loss and fragmentation are among the largest threats to forest-dwelling wildlife species today, and projected increases in human population growth are expected to increase forest loss and fragmentation in the next century. First, we combined spatially-explicit growth models with wildlife distribution models to predict the effects of human development on 5 forest-dependent bird species in Vermont, New Hampshife, and Massachusetts, USA. We used single-species occupancy models to derive the probability of occupancy for each species across the study area in the years 2000 and 2050. Second, we used maximum clique analysis to calculate the landscape carrying capacity, Nk, for the forest-dependent Ovenbird. We sampled four developed land cover classes: urban, suburban, exurban, and rural, and estimated Ovenbird Nk from occupancy probability maps for the years 2000 and 2050. Over half a million new housing units were predicted to be added to the landscape. The maximum human housing density grew from 517 housing units per hectare in the year 2000 to 530 housing units per hectare in the year 2050.
However, 30% of the towns in the study area were projected to add less than 1 housing unit per ha. In the face of this predicted human growth, the overall occupancy of each species decreased by as much as 38% in certain places in the study area in the year 2050. These declines were greater outside of protected areas than within protected lands. Nk was predicted to decrease 44% in the landscape classified as exurban development, 25% in urban and suburban development, and 14% in rural development. These decreases far exceeded the decreases in occupancy probabilities that ranged between 3% and 5% across the same sampled sites. This spatial approach to wildlife planning provides data to evaluate trade-offs between development scenarios and the viability of forest-dependent wildlife species. Specifically, maximum clique analysis is a tool that can be used to estimate a species population metric, Nk, and provide decision-makers with straightforward data to inform decisions and communicate with stakeholders.
However, 30% of the towns in the study area were projected to add less than 1 housing unit per ha. In the face of this predicted human growth, the overall occupancy of each species decreased by as much as 38% in certain places in the study area in the year 2050. These declines were greater outside of protected areas than within protected lands. Nk was predicted to decrease 44% in the landscape classified as exurban development, 25% in urban and suburban development, and 14% in rural development. These decreases far exceeded the decreases in occupancy probabilities that ranged between 3% and 5% across the same sampled sites. This spatial approach to wildlife planning provides data to evaluate trade-offs between development scenarios and the viability of forest-dependent wildlife species. Specifically, maximum clique analysis is a tool that can be used to estimate a species population metric, Nk, and provide decision-makers with straightforward data to inform decisions and communicate with stakeholders.