@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.}
}
@inbook {361,
	title = {Mapping and monitoring terrestrial biodiversity using geographic information systems},
	booktitle = {Biodiversity and Terrestrial Ecosystems},
	volume = {Monograph Series No. 14},
	year = {1994},
	pages = {461-471},
	publisher = {Institute of Botany, Academia Sinica},
	organization = {Institute of Botany, Academia Sinica},
	address = {Taipei},
	abstract = {Location in space and time are attributes of nearly all biodiversity data. Obvious examples include species{\textquoteright} collection localities, range maps and habitat maps. Geographic Information Systems for managing and analyzing spatial data are rapidly becoming an integral tool for scientists, resource managers and policy makers concerned with biodiversity conservation and ecosystem management. Database capabilities of GIS have extended the traditional map to a much more flexible and powerful representation of spatial information by allowing potentially large amounts of non-graphical information to be attached to each map unit. Biologists have yet to fully exploit this aspect of GIS in classification and mapping of biodiversity patterns. Some advantages of the GIS model over traditional maps are illustrated with a vegetation mapping project in southern California. In recent years GIS has been applied to a wide range of biodiversity issues, for example, modeling species distributions, Gap Analysis, population viability analysis, modeling ecosystem disturbance processes, and projecting the ecological impacts of global climate change. Specimen data can be of much greater use in conservation planning when coupled to predictive habitat relationship models and accurate habitat maps. The use of GIS to assemble multiple lines of evidence in modeling species{\textquoteright} distribution is illustrated for Cnemidophorus hyperythrus, an endangered lizard of coastal southern California. Lastly, an example is provided of the application of GIS modeling of habitat suitability and connectivity to conservation planning in southern California.},
	keywords = {biodiversity, connectivity, evidence, GIS, southern California, whiptail},
	author = {Davis, F. W.},
	editor = {Chou, C. I. Peng and C. H.}
}
