Using housing growth to estimate habitat change: detecting Ovenbird response in a rapidly growing New England State

作者:Lepczyk Christopher A*; Wunnicke Aaron; Radeloff Volker C; Flather Curtis H; Pidgeon Anna M; Hammer Roger B
来源:Urban Ecosystems, 2013, 16(3): 499-510.
DOI:10.1007/s11252-013-0290-7

摘要

Numerous measures of human influence on the environment exist, but one that is of particular importance is houses as they can impact the environment from species through the landscape level. Furthermore, because the addition of houses represents an important component of landscape change, housing information could be used to assess ecological responses (e.g., decline in wildlife habitat) to that change. Recently developed housing density data represents a potential source of information to assess landscape and habitat change over long periods of time and at broad spatial extents, which is critically needed for conservation and management. Considering the potential value of housing data, our goal was to demonstrate how changes in the number of houses leads to changes in the amount of habitat across the landscape, and in-turn, how these habitat changes are likely to influence the distribution and abundance for a species of conservation concern, the Ovenbird (Seiurus aurocapillus). Using a relationship between Ovenbird abundance and housing density, we predict suitable habitat in the forests of Massachusetts (USA) from 1970 to 2030. Over this 60-year period, the number of houses was projected to increase from 1.84 to 3.32 million. This magnitude of housing growth translates into a 57 % decline in Ovenbird habitat (6,002 km(2) to 2,616 km(2)), a minimum decline of similar to 850,000 (48 %) Ovenbirds, and an increase in the number of subpopulations across the landscape. Overall, housing data provide important information to robustly measure landscape and habitat change, and hence predict population change of a species. We suggest that time series of housing data linked to ecological responses (e.g., Ovenbird abundance) offers a novel and underutilized approach to estimating long-term and spatially broad predictions of ecosystem response to landscape change, which in turn can inform conservation and management.

  • 出版日期2013-9