468 Landscape Corridors Better Worse (a) (b) (c) Figure Some of the better and worse reserve designs proposed by Wilson and Willis (1975): (a) larger patches are better than smaller patches, (b) patches closer together are better than those farther apart, and (c) patches connected by corridors are better than isolated patches Separating Connectivity Effects from Confounding Factors Corridor effects can arise from one of three mechanisms: (1) connectivity, whereby corridors increase movement between connected patches; (2) area, because corridors also increase the amount of suitable habitat any increase in movement, population sizes, or diversity could be due to the availability of additional habitat rather than because of a connection per se; and (3) patch shape, because corridors change the shape of a habitat patch by increasing the amount of edge habitat relative to core habitat, responses could be due to patch-shape effects rather than connectivity Observational studies of existing landscapes are often unable to control for these three separate factors However, some experiments have explicitly manipulated these factors so that the mechanisms underpinning corridor responses can be deciphered Measuring Corridor Responses The effectiveness of corridors can be evaluated using a variety of metrics The most commonly measured response is the movement of individuals among habitat patches This can be done in a variety of ways, including creating mathematical or simulation models, marking and recapturing organisms, conducting real-time follows of organisms as they move, using dyes to trace movement patterns, or determining genetic similarities to infer movement over time A less commonly measured response is the effect of corridors on population sizes In large part, this is because tracking populations requires long-term demographic data, which are difficult to obtain at large spatial scales Similarly, studies of community-level processes (e.g., predator–prey dynamics, species diversity) are also less frequent because they can require the identification of large numbers of organisms often over multiple years The latter two types of studies (population and community levels) are important to tackle because they are often the ultimate goal of corridor implementation: to prevent species declines and extinctions and to increase biodiversity Evidence from Models Theoretical and simulation models exploring the impact of corridors and connectivity on ecological processes can illuminate new avenues for research, tackle empirically challenging questions, and provide predictive power One of the most informative uses of simulation models in corridor research has been to determine how species will respond to various habitat configurations in conjunction with actual conservation decisions Paul Beier and colleagues have developed such models using geographic information systems (GIS) to illuminate pathways of least resistance or cost to organisms (e.g., Beier et al., 2009; McRae et al., 2008) These models have helped identify habitat connections and prioritize conservation efforts (Beier et al., 2008) For example, the South Coast Missing Linkages project in Southern California utilized this approach for identifying key habitat corridors amid an urban matrix (Beier, 2006) Simulation models have also been especially useful for evaluating the potential outcomes of negative corridor effects, which may pose special ethical challenges for testing in the field and for considering evolutionary effects that are unable to be tested over short time scales For example, Hess (1994) determined how corridors might affect the spread of disease