@article {685,
	title = {Connectivity of core habitat in the Northeastern United States: Parks and protected areas in a landscape context},
	journal = {Remote Sensing of Environment},
	volume = {113},
	year = {2009},
	month = {2009},
	pages = {1421-1429},
	abstract = {The exurbanization process, particularly rural residential development, is reducing the amount of roadless areas and remote habitat across the nation, with implications for biodiversity and ecosystem integrity of parks and protected areas. The need for connecting protected areas via existing habitat centers, or relatively undisturbed core areas, is greater than ever as exurbanization expands. Our objective was to make use of nationally available data sets on roads as well as information derived from satellite imagery, including impervious cover of the built environment and forest canopy density, to identify core habitat of the northeastern and mid-Atlantic USA. The identified core habitat areas, which covered 73,730 km(2) across 1177 discrete units, were stratified in terms of land ownership and management, and then analyzed in a landscape context using connectivity metrics derived from graph theory. The connectivity analysis made use of a suitability surface, derived from the land cover information, which approximated the costs incurred by hypothetical animals traversing the landscape. We show that protected areas are frequently identified as core habitat but are typically isolated, albeit sometimes buffered by adjacent multi-use lands (such as state or national forests). Over one third of the core habitat we identified has no protection, and another 42\% is subject to motorized recreation or timber extraction. We provide maps showing the relative importance of core habitat areas for potentially connecting existing protected areas, and also provide an example of the vulnerability of connectivity to projected future residential development around one greater park ecosystem.},
	keywords = {connectivity, Conservation, Graph theory, impervious cover, Land cover change, Landscape ecology, Management, Protected areas, Roadless areas},
	url = {http://www.sciencedirect.com/science?_ob=ArticleURL\&_udi=B6V6V-4VXJW0M-2\&_user=112642\&_coverDate=07\%2F15\%2F2009\&_alid=1020426547\&_rdoc=1\&_fmt=high\&_orig=search\&_cdi=5824\&_sort=r\&_docanchor=\&view=c\&_ct=1\&_acct=C000059608\&_version=1\&_urlVersion=0\&_userid=11},
	author = {Goetz, S. J. and Jantz, P. and Jantz, C. A.}
}
@article {833,
	title = {Planning for climate change: Identifying minimum-dispersal corridors for the Cape proteaceae},
	journal = {Conservation Biology},
	volume = {19},
	year = {2005},
	month = {2005},
	pages = {1063-1074},
	abstract = {Climate change poses a challenge to the conventional approach to biodiversity conservation, which relies on fixed protected areas, because the changing climate is expected to shift the distribution of suitable areas for many species. Some species will persist only if they can colonize new areas, although in some cases their dispersal abilities may be very limited. To address this problem we devised a quantitative method for identifying multiple corridors of connectivity through shifting habitat suitabilities that seeks to minimize dispersal demands first and then the area of land required. We applied the method to Proteaceae mapped on a 1-minute grid for the western part of the Cape Floristic Region of South Africa, to supplement the existing protected areas using Worldmap software. Our goal was to represent each species in at least 35 grid cells (approximately 100 km(2)) at all times between 2000 and 2050 despite climate change. Although it was possible to achieve the goal at reasonable cost, caution will be needed in applying our method to reserves or other conservation investments until there is further information to support or refine the climate-change models and the species{\textquoteright} habitat-suitability and dispersal models.},
	keywords = {area-selection algorithms, bioclimatic modeling, biodiversity, biodiversity conservation, connectivity, Conservation, distance, distribution models, distributions, floristic region, habitat suitability, plant migration, Protected areas, reserve selection algorithms, south-africa, species persistence},
	url = {<Go to ISI>://000231118600013},
	author = {Williams, P. and Hannah, L. and Andelman, S. and Midgley, G. and Araujo, M. and Hughes, G. and Manne, L. and Martinez-Meyer, E. and Pearson, R.}
}
