Essay
Response Variables for Evaluation of the Effectiveness of Conservation Corridors ANDREW J. GREGORY∗ AND PAUL BEIER† ∗
School of the Earth, Environment and Society, 190 Overman Hall, Bowling Green State University, Bowling Green, OH 45403-0211, U.S.A., email [email protected] †School of Forestry, Northern Arizona University, Flagstaff, AZ 86011-5018, U.S.A.
Abstract: Many studies have evaluated effectiveness of corridors by measuring species presence in and movement through small structural corridors. However, few studies have assessed whether these response variables are adequate for assessing whether the conservation goals of the corridors have been achieved or considered the costs or lag times involved in measuring the response variables. We examined 4 response variables—presence of the focal species in the corridor, interpatch movement via the corridor, gene flow, and patch occupancy—with respect to 3 criteria—relevance to conservation goals, lag time (fewest generations at which a positive response to the corridor might be evident with a particular variable), and the cost of a study when applying a particular variable. The presence variable had the least relevance to conservation goals, no lag time advantage compared with interpatch movement, and only a moderate cost advantage over interpatch movement or gene flow. Movement of individual animals between patches was the most appropriate response variable for a corridor intended to provide seasonal migration, but it was not an appropriate response variable for corridor dwellers, and for passage species it was only moderately relevant to the goals of gene flow, demographic rescue, and recolonization. Response variables related to gene flow provided a good trade-off among cost, relevance to conservation goals, and lag time. Nonetheless, the lag time of 10–20 generations means that evaluation of conservation corridors cannot occur until a few decades after a corridor has been established. Response variables related to occupancy were most relevant to conservation goals, but the lag time and costs to detect corridor effects on occupancy were much greater than the lag time and costs to detect corridor effects on gene flow. Keywords: animal movement, corridor evaluation, fragmentation, gene flow, occupancy Variables de Respuesta para la Evaluaci´ on de la Efectividad de los Corredores de Conservaci´ on
Resumen: Muchos estudios han evaluado la efectividad de los corredores midiendo la presencia de especies y el movimiento en y a trav´es de corredores estructurales peque˜ nos. Sin embargo, pocos estudios han evaluado si estas variables de respuesta son adecuadas para estimar si los objetivos de conservaci´ on de los corredores se han logrado o si se han considerado los costos o tiempos de retraso involucrados en la medida de las variables de respuesta. Examinamos 4 variables de respuesta: la presencia de una especie focal en el corredor, el movimiento entre fragmentos por medio del corredor, el flujo g´enico y la ocupaci´ on de fragmentos. Estas variables se examinaron con respecto a 3 criterios: la relevancia para los objetivos de conservaci´ on, el tiempo de retraso (el menor n´ umero de generaciones en el que una respuesta positiva al corredor puede ser evidente con una variable particular) y el costo de un estudio al aplicar una variable particular. La variable de presencia tuvo la menor relevancia para los objetivos de conservaci´ on, ninguna ventaja en el tiempo de retraso en comparaci´ on con el movimiento entre fragmentos y solamente una moderada ventaja de costos sobre el movimiento entre fragmentos y el flujo g´enico. El movimiento de animales individuales entre los fragmentos fue la variable de respuesta m´ as apropiada para un corredor destinado a proporcionar migraci´ on estacional, pero no fue una variable de respuesta apropiada para los habitantes de los corredores, y para el paso de especies s´ olo fue moderadamente relevante para los objetivos del flujo g´enico, el rescate demogr´ afico
Paper submitted August 24, 2013; revised manuscript accepted November 2, 2013.
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y la recolonizaci´ on. Las variables de respuesta relacionadas con el flujo g´enico proporcionaron un buen trade-off entre el costo, la relevancia para los objetivos de conservaci´ on y el tiempo de retraso. Sin embargo, el tiempo de retraso de 10-20 generaciones significa que la evaluaci´ on de los corredores de conservaci´ on no puede darse hasta despu´es de unas d´ecadas de que se estableci´ o. Las variables de respuesta relacionadas con la ocupaci´ on fueron m´ as relevantes para los objetivos de conservaci´ on, pero el tiempo de retraso y los costos para detectar los efectos de los corredores sobre la ocupaci´ on fueron mucho m´ as grandes que el tiempo de retraso y los costos para detectar los efectos de los corredores sobre el flujo g´enico.
Palabras Clave: Evaluaci´on de corredor, flujo g´enico, fragmentaci´on, movimiento animal, ocupaci´on
Introduction In the most general sense, a corridor is a continuous remnant of habitat between otherwise isolated habitat patches (Inglis & Underwood 1992; Beier & Noss 1998). This definition covers a broad range of spatial extents and contexts, from corridors a few centimeters in length and width in laboratory microcosms (Forney & Gilpin 1989; Gilbert et al. 1998), to small, experimentally created grassland corridors 150 m long and 50 m wide within a forested matrix (Haddad et al. 2011), and to much larger corridors embedded in a matrix of humancentered land uses incompatible with movement or longterm occupancy by the focal species. Most conservation corridors are at the latter end of the spectrum. In particular, a conservation corridor is a relatively constricted area that is protected and managed to connect parks or other substantial habitat patches (Beier et al. 2011). Thus, a corridor is not merely an animal movement path, or a place where animals move, but also a conservation intervention (e.g., land protection, restoration, and management) applied to a portion of the potential movement area between habitat patches to achieve specific connectivity goals (Table 1) in landscapes that would otherwise be fragmented by urban, agricultural, or industrial land uses. Of the 7 goals listed in Table 1, we focused specifically on the ability of corridors to conserve seasonal migration (goal 2), maintain or restore gene flow (goal 3), promote demographic rescue (goal 4), and promote recolonization (goal 5) because all conservation corridors reviewed by Beier et al. (2008a, 2011) explicitly pursue some combination of these 4 goals. During 1977–2008, at least 110 studies measured the effectiveness of corridors in the broad sense (32 reviewed by Beier & Noss [1998] and 78 reviewed by Gilbert-Norton et al. [2010]; no study was considered in both reviews). These studies overwhelmingly showed that corridors promote interpatch movement of animals. However, only one of these studies involved a conservation corridor and fewer than 15 involved long corridors in a matrix of industrial, urban, or agricultural land uses. Ninety-five of these 110 studies assessed corridor effectiveness in terms of animal presence in or movement
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through the corridor. As we argue below, presence or movement are less closely related to conservation goals (Table 1) than the response variables in the other studies, such as species richness, patch occupancy, demographic performance, genetic distance, and colonization rate. Only 8 of the 110 studies assessed corridors that resembled conservation corridors in size and context and used variables that measured achievement of conservation goals. The goal of experiments on model systems is to develop theories and identify patterns that can be tested in other contexts (Gardner et al. 2001). By that standard, the studies published to date have been highly successful. By studying corridors in microcosms and mesocosms, it has been demonstrated that corridors promote movement by diverse species and that the potential negative effects of corridors are highly unlikely to occur (Haddad et al. 2003, 2011; Gilbert-Norton et al. 2010). Eventually the results of experiments on model systems must be tested in realworld contexts. Progress in learning whether or not conservation corridors achieve their goals will require studies of large corridors in landscapes where the matrix is dominated by urban, industrial, or agricultural uses (hereafter conservation corridor regardless of whether the corridor was designed for conservation purposes), and the use of response variables that reliably indicate whether a corridor is promoting seasonal migration, gene flow, demographic stability, or recolonization. We addressed the second of these issues. Specifically, we evaluated 4 response variables— presence of the focal species in the corridor, interpatch movement via the corridor, gene flow, and patch occupancy—with respect to 3 criteria, relevance to conservation goals, lag time (fewest number of generations at which a positive response to the corridor might be evident using that type of variable), and the cost of carrying out a study with a particular variable. Our goal was to help conservation scientists select response variables that support strong scientific inferences and sound conservation decisions. Conservation corridors are usually planned when a landscape is losing connectivity but when there are still several potential connective areas between large natural areas. In the process of corridor design, a subset of these areas, comprising one or more swaths, are selected
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Table 1. Seven goals of conservation corridors and response variables that could be used to assess whether a conservation corridor meets the goal.a Goal 1. Promote regular access to resources in 2 or more patches within an individual home rangeb 2. Conserve seasonal migration between patches 3. Maintain or restore gene flow between patches 4. Promote demographic rescue of a population in one or more patches
5. Promote recolonization of a patch after local extirpation
6. Promote range expansion in response to climate change or other environmental change 7. Conserve ecological and evolutionary processes, such as interspecific interactions, propagation of disturbance (e.g., fire), or movement of nutrients, water, or soil
Potential response variable: type of response that indicates corridor is effective individual movement: travel from patch to patch via the corridor individual performance: vital rates in a connected patch are better than those in a similar-sized isolated patch individual movement: travel between seasonal ranges via the corridor gene flow: corridor success index (see text) significantly >0 and not significantly different from 1 patch occupancy or species richness: higher occupancy or richness in patches connected by corridors than in isolated patches gene flow: corridor success index (see text) significantly >0 or assignment tests demonstrate successful dispersal between patches individual movement and reproduction: travel from patch to patch via the corridor, followed by reproductive contribution to the recipient patch individual movement: travel from patch to patch via the corridor (even if local extirpation has not occurred) patch occupancy: higher rate of patch occupancy or greater species richness in patches connected by corridors than in isolated patches gene flow: corridor success index (see text) significantly >0 and sex-linked markers indicate both sexes have contributed genes to a corridor-linked patch gene flow: genetic patterns suggest that the focal patch was recolonized by individuals from a patch connected to the focal patch by a corridor range shift: observed range expansion via the corridor during periods of environmental change conservation of ecological and evolutionary processes an underlying goal but rarely explicitly stated goal or a driver of design and management of the corridor variables that indicate success or failure with respect to this goal not developed
a The term patch refers to a park or other significant habitat area connected by the corridor to b Because resources are rarely invested in efforts to improve a single home range, this is rarely
for protection and management to serve the needs of multiple focal species (Beier et al. 2008a). Focal species usually include both passage species, individuals that can traverse the length of a corridor in a discrete movement event (e.g., juvenile dispersal or seasonal migration) and corridor dwellers, species that need >1 generation to achieve connectivity via the corridor (Beier & Loe 1992). Thus, most conservation corridors are designed to promote not only dispersal by passage species, but also occupancy and metapopulation connectivity for corridor dwellers. A corridor design embodies the hypothesis that these swaths will provide genetic and demographic connectivity after the landscape has reached a stable configuration of patches, corridors, and adjacent urban, agricultural, and industrial land uses, a condition referred to as build-out of the human footprint. Evaluation of this hypothesis can occur only after build-out has occurred.
another patch. the goal of a conservation corridor.
For instance, the Sierra Estrella and Sonoran Desert National Monument (Arizona, U.S.A.) are 2 protected areas separated by approximately 12 km of unprotected land with no human residents and no paved roads. After massive urban development was proposed for this area, a conservation corridor with 3 strands, each about 1.5 km wide, was designed to serve 7 focal species (Beier et al. 2008b). After build-out, the corridor strands will be a constricted remnant of present-day connectivity and will be subject to edge effects (e.g., light, noise, subsidized predators, and urban water runoff) and human activities. None of the response variables measured before buildout would be reliable indicators of corridor utility after build-out. Furthermore, after build-out there will be a time lag before the response variable will reflect the longterm utility of the corridor, as reflected in our lag time criterion.
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Potential Response Variables
year effort may be required if the first year yields no presences.
Animal Presence in Corridor Because animal presence is weakly related to the primary goals of conservation corridors (Table 1), animal absence from a corridor does not indicate corridor failure, and animal presence in a corridor does not indicate corridor success. Absence does not indicate failure because some species (e.g., highly mobile species that live at low density) need only rare corridor movements to provide gene flow and demographic rescue (Beier 1993; Haddad & Tewksbury 2005). Rigorous surveys lasting 1–2 years could yield no detections in a corridor that does support such movements. For corridor dwellers, presence in a corridor is a necessary but not sufficient condition for corridor success. In particular, if a corridor is occupied by a population that does not interact with the populations in the patches or if the corridor is solely a sink for surplus individuals from those patches, animal presence in the corridor would not achieve the corridor’s conservation goal. For example, Horskins et al. (2006) reported that 2 small mammals occurred throughout a 70-year-old, 7-kmlong corridor, but genetic evidence suggested that no gene flow, recolonization, or demographic rescue had occurred between the 2 patches connected by the corridor. Similarly, Leidner and Haddad (2010) documented that human-caused habitat barriers and the configuration of a habitat mosaic prevented a linear strip of occupied habitat from providing connectivity. The lag time for animal presence to reflect long-term animal response to the corridor is probably no more than 2–3 generations of the focal species. Animal presence immediately after build-out could be positively biased (because site fidelity may cause older animals to continue to use a corridor that will be avoided by future generations) or negatively biased (because it takes time for animals to habituate to new landscape features or for dispersing animals to explore the new features). As an example of the latter phenomenon, very few wolves (Canis lupus), moose (Alces alces), or grizzly bears (Ursus arctos) used highway crossing structures on the TransCanada Highway through Banff National Park during the first 3 years after the structures were built, such that the animal presence response variable could have led to the conclusion that the connective structures were failures. Presence of these species in crossing structures increased dramatically 5 years after build-out and has remained high since (Clevenger et al. 2009). Documenting animal presence or absence can involve livetrapping, camera traps, sign surveys, visual observations, or other methods. The study could begin during the second generation after build-out (for a passage species) or after 2–3 generations (for a corridor dweller) and might be completed in 1 year. Because it is more difficult to infer absence than presence, a more intensive second
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Individual Movement between Patches via the Corridor For corridor dwellers, individual movement between patches is not an appropriate response variable because these species do not move between patches in discrete observable events. For passage species, animal movement through a corridor after build-out provides stronger evidence than animal presence provides for corridor effectiveness. Documentation of movement between seasonal ranges is sufficient to demonstrate success of a conservation corridor established to support seasonal migration (Table 1, goal 2), and lack of such movement reliably indicates the corridor has failed. For the other conservation goals in Table 1, interpatch movement is necessary but documenting such movement is not sufficient to infer corridor success because some interpatch movements do not improve demographic performance or increase genetic diversity (King & With 2002; Fischer & Lindenmayer 2007). For example, although most dispersing pumas in 1 study used corridors, almost all corridor users died before they became breeders in the recipient population (Beier 1995). Similarly, Riley et al. (2006) documented frequent interpatch movements by bobcats (Lynx rufus) and coyotes (Canis latrans) that did not contribute to the recipient populations. The lag time required to document interpatch movement is the same as that for presence, and for the same reasons. Greater effort is required because individually recognized animals must be detected moving between patches, either by monitoring radio-tagged animals or other expensive field efforts. For some focal species only dispersing juveniles are likely to move between patches, and dispersers experience high mortality, adding to the time and expense of studying interpatch movement. Compared with animal presence, movement between patches offers much improved relevance to conservation goals for passage species with little or no increase in lag time and a moderate increase in the cost of study (Fig. 1). Moreover, observations of movement provide a useful complement to genetic or occupancy data because interpatch movements are the mechanistic link between the landscape and the demographic and genetic effects of conservation interest. Gene Flow Variables related to gene flow (Wright 1969; Hampton et al. 2004; Balkenhol et al. 2009), dispersal rates inferred from genetic assignment tests (Berry et al. 2004), and barriers inferred from Bayesian clustering algorithms (Pritchard et al. 2000) directly measure conservation goals 3, 4, and 5 (Table 1) and are markedly superior to animal presence or interpatch movement in this regard.
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Cost
Occupancy
Movement (2)
Movement (3,4,5)
Gene flow
Presence 0
10
Lag time (generations)
20
30
Figure 1. Relevance to conservation goal (indicated by size of circle) of 4 response variables (animal presence, individual movement between patches via a corridor, gene flow, and patch occupancy) in relation to the cost of a study using that variable and lag time from build-out until a positive response to a corridor might be evident. The size of each symbol represents our qualitative assessment of how directly each variable measures achievement of the conservation goals.
Collection and analysis of genetic material from the corridor-connected patches alone can support qualitative inferences about corridor effectiveness (i.e., that flow has or has not occurred) (Dixon et al. 2006). Genetic similarity can also quantitatively measure success when GScorridor (genetic similarity between corridor-connected patches) is compared with GSisolates (genetic distance between isolated patches), and with GScontinuous (genetic distance between sampling locations in a large intact habitat area) (Mech & Hallett 2001; Horskins et al. 2006; Beier & Gregory 2012). Formally, the corridor success index, CSI = (GScorridor − GSisolates )/(GScontinuous − GSisolates ), with values close to 0 indicating failure, values close to 1 indicating a corridor that provides as much gene flow as an intact landscape, and intermediate values indicating relative success of the corridor. Because sensible or credible confidence intervals can readily be calculated from the underlying allele frequencies, CSI values can be compared not only to the reference values of 0 and 1, but can also be compared between corridors to yield inferences about variables that affect corridor success. The time lag required for genetic divergence between isolated patches increases in a predictable, quantifiable way as effective population size increases (Wright 1943). More specifically, genetic divergence should be evident after 10 generations for effective population sizes of approximately 60 per patch and after 20 generations for effective population sizes of approximately 100 individ-
uals. Because effective population size may be 5–15% of census population size (Hare et al. 2011), genetic divergence should be evident within 10–20 generations for populations of 400–2000 individuals per patch. If gene flow variables are measured before genetic divergence between isolated patches can occur, one could falsely conclude that the corridor works. Thus, use of genetic distance as a response variable requires acceptance of a lag time of 10–20 generations for small to moderately sized populations. For example, Mech and Hallett (2001) documented that interpatch genetic distances for redbacked voles (Clethrionomys gapperi) in patches that had been isolated for only 12 years were significantly higher than the genetic distances between patches connected by corridors. Sharma et al. (2013) documented that over the last century, loss of corridors diminished interpatch gene flow for tigers, whereas tiger gene flow between patches with intact corridors has remained high. It may be impossible to use gene flow as a response variable for species with large effective population sizes, but such species are unlikely to be a focus for conservation goals 3, 4, or 5. Using genetic variables as response variables involves the cost of genetic analyses and the cost of obtaining genetic samples from individuals in at least 2 corridorlinked patches. Use of CSI requires 2 additional pairs of locations (2 isolated patches and 2 sampling locations within intact habitat). The main factors affecting these costs are the difficulty of obtaining tissues from the focal species and whether genetic markers must be developed for the species. The cost of a study in which gene flow is used to measure corridor success is likely less than or similar to the cost of documenting animal movement. Gene flow also can be used to quantify corridor utility for corridor dwellers for which discrete interpatch movement is irrelevant (Waples & Gaggiotti 2006). Moreover, the same genetic data also can be used to estimate 2 other conservation-relevant variables, namely effective population size and census population size (Luikart et al. 2010). Compared with interpatch movement as a response variable, gene flow is vastly more relevant to conservation goals 3, 4, and 5, at the expense of an increase in lag time, but there is little or no increase in the cost of study (Fig. 1). Genetic data can also be used to monitor use of seasonal migratory corridors (conservation goal 2). For example, genetic sampling of polar bears (Ursus maritimus) in a nonbreeding area shared by 2 disjunct breeding populations confirmed the continued use of seasonal migratory corridors (Paetkau et al. 2008). In the near future, next generation sequence-based techniques such as RadS (Landguth & Balkenhol 2012; Davey & Blaxter 2013), and advanced Bayesian genetic clustering and other landscape genetic approaches (Balkenhol et al. 2009; Blair et al. 2012) will reduce the time lag needed to infer corridor utility from genetic data.
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Occupancy Rates and Species Richness of Patches Patch occupancy is the most conservation-relevant response variable for goals 4 and 5, which are arguably the most important conservation goals for corridors. Ultimately, a corridor is successful to the extent that it promotes demographic rescue and recolonization and is at best partially successful otherwise. Over the long term, this means that patches linked by successful corridors will be more frequently occupied than patches that are isolated from each other by the matrix (Inglis & Underwood 1992) and across multiple species, patches connected by successful corridors will have higher species richness than isolated patches (Collinge 2000). For conservation corridors and patches of the size served by larger conservation corridors, the lag time for observing changes in patch occupancy or species richness is much longer than for gene flow because extinctions (required for changes in occupancy) occur more slowly than genetic divergence. For example, Florida panthers (Puma concolor coryi) experienced marked genetic divergence from neighboring populations and lost most of their genetic diversity by 1960 (Culver et al. 2000), 35 years before genetic augmentation was undertaken to avert extinction. This time lag (identical to “relaxation time” [Diamond 1972]) gives rise to an extinction debt, whereby doomed species may persist for 50–400 or more years after habitat loss and fragmentation have ensured their demise (Tilman et al. 1994). The cost of using patch occupancy rates and species richness as a response variable for conservation corridors is probably an order of magnitude larger than for studies using other types of response variables. Although CSI for a single corridor can be statistically different from 1 or 0, an occupancy rate of 0% for a single isolated patch is not statistically different from an occupancy rate of 100% for a single corridor-connected patch. Because replication is needed to detect statistically significant differences in occupancy rates, costs increase enormously. The long lag time and the need for costly replication may preclude the use of patch occupancy rates and species richness as response variables for conservation corridors. Most studies using these response variables have been microcosm studies (e.g., Gilbert et al. 1998; Collinge 2000; Rantalainen et al. 2004) that have inexpensive replicates and short lag times (due to very small effective population sizes). Damschen et al. (2006) documented that 5-year-old corridors significantly increased plant species richness in a mesocosm study, showing that a rapid response can occur outside microcosms. But it would be more difficult to achieve sufficient replication to detect differences in richness or occupancy in large patches embedded in agricultural and urban land uses. In most microcosm studies in which occupancy or richness was a response variable, the experimenter caused extinctions in patches to further reduce lag time and
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to allow direct observation of recolonization (goal 5). As investigators scale up from microcosms, 2 ethically acceptable ways to reduce the time required to observe colonization would be to use habitat restoration to link unoccupied patches to occupied ones or to find a landscape and species for which fire or other disturbance regularly creates new patches and corridors. We conclude that response variables related to patch occupancy rates are most relevant to conservation goals, but the extremely long lag time and high costs of such studies severely limit their application to conservation corridors. We found little reason to use presence in the corridor as a response variable because it has the least relevance to conservation goals, no lag time advantage compared with interpatch movement, and only moderate cost advantage. Movement of individual animals between patches is clearly the most appropriate response variable for a corridor intended to provide seasonal migration, but it is not an appropriate response variable for corridor dwellers, and is only moderately relevant to goals 3, 4, and 5 for passage species. Response variables related to gene flow provide a good trade-off among cost, relevance to conservation goals, and lag time (Fig. 1). Nonetheless, the lag time of 10–20 generations means that evaluation of conservation corridors cannot occur until at least 10–50 years after build-out (depending on the generation time and population sizes of the focal species). Perhaps the best way to provide a useful assessment of conservation corridors would be to measure gene flow, patch occupancy, and species richness in a large number of corridor-connected and isolated patches that have been embedded in human dominated landscapes for >50 years, regardless of whether the corridors were originally designed for conservation purposes. Such an analysis would require careful controlling for the disparate circumstances of the study landscapes.
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Haddad, N. M., and J. J. Tewksbury. 2005. Low-quality habitat corridors as movement conduits for butterflies. Ecological Applications 15:250–257. Hampton, J. O., P. Spencer, D. Alpers, L. Twigg, A. Woolnough, J. Doust, T. Higgs, and J. Pluske. 2004. Molecular techniques, wildlife management and the importance of genetic population structure and dispersal: a case study with feral pigs. Journal of Applied Ecology 41:735–743. Hare, M. P., L. Nunney, M. K. Shwartz, D. E. Ruzzante, M. Burford, R. S. Waples, K. Ruegg, and F. Palstra. 2011. Understanding and estimating effective population size for practical application in marine species management. Conservation Biology 25:438–449. Horskins, K., P. B. Mather, and J. C. Wilson. 2006. Corridors and connectivity: when use and function do not equate. Landscape Ecology 21:641–655. Inglis, G., and A. Underwood. 1992. Comments on some designs proposed for experiments on the biological importance of corridors. Conservation Biology 4:581–586. King, A. W. and K. With. 2002. Dispersal success on spatially structured landscapes: When do spatial pattern and dispersal behavior really matter? Ecological Modeling 147:23–39. Landguth, E., and N. Balkenhol. 2012. Relative sensitivity of neutral versus adaptive genetic data for assessing popualtion differentiation. Conservation Genetics 13:1421–1426. Leidner, A., and N. Haddad. 2010. Natural, not urban, barriers define population structure for a coastal endemic butterfly. Conservation Genetics 11:2311–2320. Luikart, G., N. Ryman, D. A. Tallmon, M. K. Schwartz, and F. W. Allendorf. 2010. Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches. Conservation Genetics 11:355–373. Mech, S. G., and J. G. Hallett. 2001. Evaluating the effectiveness of corridors: a genetic approach. Conservation Biology 5:467–474. Paetkau, D., W. Calvert, I. Stirling, and C. Strobek. 2008. Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology 4:347–354. Pritchard, J., M. Stephens, and P. Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155:945– 955. Rantalainen, M. L., J. Haimi, and H. Set¨al¨a. 2004. Testing the usefulness of habitat corridors in mitigating the negative effects of fragmentation: the soil faunal community as a model system. Applied Soil Ecology 25:267–274. Riley, S., J. Pollinger, R. Sauvajot, E. York, C. Bromley, T. K. Fuller, and R. K. Wayne. 2006. A southern California freeway is a physical and social barrier to gene flow in carnivores. Molecular Ecology 15:1733–1741. Sharma, S., T. Dutta, J. E. Maldonado, T. C. Wood, H. S. Panwar, and J. Seidensticker. 2013. Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India. Proceedings of the Royal Society B 280. DOI: 10.1098/rspb.2013.1506. Tilman, D., R. M. May, C. Lehman, and M. Nowak. 1994. Habitat destruction and the extinction debt. Nature 371:65–66. Waples, R., and O. Gaggiotti. 2006. What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Molecular Ecology 15:1419–1439. Wright, S. 1943. Isolation by distance. Genetics 28:114–138. Wright, S. 1969. Evolution and the genetics of populations: volume 2. The theory of gene frequencies. University of Chicago Press, Illinois.
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Response Variables for Evaluation of the Effectiveness of Conservation Corridors ANDREW J. GREGORY∗ AND PAUL BEIER† ∗
School of the Earth, Environment and Society, 190 Overman Hall, Bowling Green State University, Bowling Green, OH 45403-0211, U.S.A., email [email protected] †School of Forestry, Northern Arizona University, Flagstaff, AZ 86011-5018, U.S.A.
Abstract: Many studies have evaluated effectiveness of corridors by measuring species presence in and movement through small structural corridors. However, few studies have assessed whether these response variables are adequate for assessing whether the conservation goals of the corridors have been achieved or considered the costs or lag times involved in measuring the response variables. We examined 4 response variables—presence of the focal species in the corridor, interpatch movement via the corridor, gene flow, and patch occupancy—with respect to 3 criteria—relevance to conservation goals, lag time (fewest generations at which a positive response to the corridor might be evident with a particular variable), and the cost of a study when applying a particular variable. The presence variable had the least relevance to conservation goals, no lag time advantage compared with interpatch movement, and only a moderate cost advantage over interpatch movement or gene flow. Movement of individual animals between patches was the most appropriate response variable for a corridor intended to provide seasonal migration, but it was not an appropriate response variable for corridor dwellers, and for passage species it was only moderately relevant to the goals of gene flow, demographic rescue, and recolonization. Response variables related to gene flow provided a good trade-off among cost, relevance to conservation goals, and lag time. Nonetheless, the lag time of 10–20 generations means that evaluation of conservation corridors cannot occur until a few decades after a corridor has been established. Response variables related to occupancy were most relevant to conservation goals, but the lag time and costs to detect corridor effects on occupancy were much greater than the lag time and costs to detect corridor effects on gene flow. Keywords: animal movement, corridor evaluation, fragmentation, gene flow, occupancy Variables de Respuesta para la Evaluaci´ on de la Efectividad de los Corredores de Conservaci´ on
Resumen: Muchos estudios han evaluado la efectividad de los corredores midiendo la presencia de especies y el movimiento en y a trav´es de corredores estructurales peque˜ nos. Sin embargo, pocos estudios han evaluado si estas variables de respuesta son adecuadas para estimar si los objetivos de conservaci´ on de los corredores se han logrado o si se han considerado los costos o tiempos de retraso involucrados en la medida de las variables de respuesta. Examinamos 4 variables de respuesta: la presencia de una especie focal en el corredor, el movimiento entre fragmentos por medio del corredor, el flujo g´enico y la ocupaci´ on de fragmentos. Estas variables se examinaron con respecto a 3 criterios: la relevancia para los objetivos de conservaci´ on, el tiempo de retraso (el menor n´ umero de generaciones en el que una respuesta positiva al corredor puede ser evidente con una variable particular) y el costo de un estudio al aplicar una variable particular. La variable de presencia tuvo la menor relevancia para los objetivos de conservaci´ on, ninguna ventaja en el tiempo de retraso en comparaci´ on con el movimiento entre fragmentos y solamente una moderada ventaja de costos sobre el movimiento entre fragmentos y el flujo g´enico. El movimiento de animales individuales entre los fragmentos fue la variable de respuesta m´ as apropiada para un corredor destinado a proporcionar migraci´ on estacional, pero no fue una variable de respuesta apropiada para los habitantes de los corredores, y para el paso de especies s´ olo fue moderadamente relevante para los objetivos del flujo g´enico, el rescate demogr´ afico
Paper submitted August 24, 2013; revised manuscript accepted November 2, 2013.
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y la recolonizaci´ on. Las variables de respuesta relacionadas con el flujo g´enico proporcionaron un buen trade-off entre el costo, la relevancia para los objetivos de conservaci´ on y el tiempo de retraso. Sin embargo, el tiempo de retraso de 10-20 generaciones significa que la evaluaci´ on de los corredores de conservaci´ on no puede darse hasta despu´es de unas d´ecadas de que se estableci´ o. Las variables de respuesta relacionadas con la ocupaci´ on fueron m´ as relevantes para los objetivos de conservaci´ on, pero el tiempo de retraso y los costos para detectar los efectos de los corredores sobre la ocupaci´ on fueron mucho m´ as grandes que el tiempo de retraso y los costos para detectar los efectos de los corredores sobre el flujo g´enico.
Palabras Clave: Evaluaci´on de corredor, flujo g´enico, fragmentaci´on, movimiento animal, ocupaci´on
Introduction In the most general sense, a corridor is a continuous remnant of habitat between otherwise isolated habitat patches (Inglis & Underwood 1992; Beier & Noss 1998). This definition covers a broad range of spatial extents and contexts, from corridors a few centimeters in length and width in laboratory microcosms (Forney & Gilpin 1989; Gilbert et al. 1998), to small, experimentally created grassland corridors 150 m long and 50 m wide within a forested matrix (Haddad et al. 2011), and to much larger corridors embedded in a matrix of humancentered land uses incompatible with movement or longterm occupancy by the focal species. Most conservation corridors are at the latter end of the spectrum. In particular, a conservation corridor is a relatively constricted area that is protected and managed to connect parks or other substantial habitat patches (Beier et al. 2011). Thus, a corridor is not merely an animal movement path, or a place where animals move, but also a conservation intervention (e.g., land protection, restoration, and management) applied to a portion of the potential movement area between habitat patches to achieve specific connectivity goals (Table 1) in landscapes that would otherwise be fragmented by urban, agricultural, or industrial land uses. Of the 7 goals listed in Table 1, we focused specifically on the ability of corridors to conserve seasonal migration (goal 2), maintain or restore gene flow (goal 3), promote demographic rescue (goal 4), and promote recolonization (goal 5) because all conservation corridors reviewed by Beier et al. (2008a, 2011) explicitly pursue some combination of these 4 goals. During 1977–2008, at least 110 studies measured the effectiveness of corridors in the broad sense (32 reviewed by Beier & Noss [1998] and 78 reviewed by Gilbert-Norton et al. [2010]; no study was considered in both reviews). These studies overwhelmingly showed that corridors promote interpatch movement of animals. However, only one of these studies involved a conservation corridor and fewer than 15 involved long corridors in a matrix of industrial, urban, or agricultural land uses. Ninety-five of these 110 studies assessed corridor effectiveness in terms of animal presence in or movement
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through the corridor. As we argue below, presence or movement are less closely related to conservation goals (Table 1) than the response variables in the other studies, such as species richness, patch occupancy, demographic performance, genetic distance, and colonization rate. Only 8 of the 110 studies assessed corridors that resembled conservation corridors in size and context and used variables that measured achievement of conservation goals. The goal of experiments on model systems is to develop theories and identify patterns that can be tested in other contexts (Gardner et al. 2001). By that standard, the studies published to date have been highly successful. By studying corridors in microcosms and mesocosms, it has been demonstrated that corridors promote movement by diverse species and that the potential negative effects of corridors are highly unlikely to occur (Haddad et al. 2003, 2011; Gilbert-Norton et al. 2010). Eventually the results of experiments on model systems must be tested in realworld contexts. Progress in learning whether or not conservation corridors achieve their goals will require studies of large corridors in landscapes where the matrix is dominated by urban, industrial, or agricultural uses (hereafter conservation corridor regardless of whether the corridor was designed for conservation purposes), and the use of response variables that reliably indicate whether a corridor is promoting seasonal migration, gene flow, demographic stability, or recolonization. We addressed the second of these issues. Specifically, we evaluated 4 response variables— presence of the focal species in the corridor, interpatch movement via the corridor, gene flow, and patch occupancy—with respect to 3 criteria, relevance to conservation goals, lag time (fewest number of generations at which a positive response to the corridor might be evident using that type of variable), and the cost of carrying out a study with a particular variable. Our goal was to help conservation scientists select response variables that support strong scientific inferences and sound conservation decisions. Conservation corridors are usually planned when a landscape is losing connectivity but when there are still several potential connective areas between large natural areas. In the process of corridor design, a subset of these areas, comprising one or more swaths, are selected
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Table 1. Seven goals of conservation corridors and response variables that could be used to assess whether a conservation corridor meets the goal.a Goal 1. Promote regular access to resources in 2 or more patches within an individual home rangeb 2. Conserve seasonal migration between patches 3. Maintain or restore gene flow between patches 4. Promote demographic rescue of a population in one or more patches
5. Promote recolonization of a patch after local extirpation
6. Promote range expansion in response to climate change or other environmental change 7. Conserve ecological and evolutionary processes, such as interspecific interactions, propagation of disturbance (e.g., fire), or movement of nutrients, water, or soil
Potential response variable: type of response that indicates corridor is effective individual movement: travel from patch to patch via the corridor individual performance: vital rates in a connected patch are better than those in a similar-sized isolated patch individual movement: travel between seasonal ranges via the corridor gene flow: corridor success index (see text) significantly >0 and not significantly different from 1 patch occupancy or species richness: higher occupancy or richness in patches connected by corridors than in isolated patches gene flow: corridor success index (see text) significantly >0 or assignment tests demonstrate successful dispersal between patches individual movement and reproduction: travel from patch to patch via the corridor, followed by reproductive contribution to the recipient patch individual movement: travel from patch to patch via the corridor (even if local extirpation has not occurred) patch occupancy: higher rate of patch occupancy or greater species richness in patches connected by corridors than in isolated patches gene flow: corridor success index (see text) significantly >0 and sex-linked markers indicate both sexes have contributed genes to a corridor-linked patch gene flow: genetic patterns suggest that the focal patch was recolonized by individuals from a patch connected to the focal patch by a corridor range shift: observed range expansion via the corridor during periods of environmental change conservation of ecological and evolutionary processes an underlying goal but rarely explicitly stated goal or a driver of design and management of the corridor variables that indicate success or failure with respect to this goal not developed
a The term patch refers to a park or other significant habitat area connected by the corridor to b Because resources are rarely invested in efforts to improve a single home range, this is rarely
for protection and management to serve the needs of multiple focal species (Beier et al. 2008a). Focal species usually include both passage species, individuals that can traverse the length of a corridor in a discrete movement event (e.g., juvenile dispersal or seasonal migration) and corridor dwellers, species that need >1 generation to achieve connectivity via the corridor (Beier & Loe 1992). Thus, most conservation corridors are designed to promote not only dispersal by passage species, but also occupancy and metapopulation connectivity for corridor dwellers. A corridor design embodies the hypothesis that these swaths will provide genetic and demographic connectivity after the landscape has reached a stable configuration of patches, corridors, and adjacent urban, agricultural, and industrial land uses, a condition referred to as build-out of the human footprint. Evaluation of this hypothesis can occur only after build-out has occurred.
another patch. the goal of a conservation corridor.
For instance, the Sierra Estrella and Sonoran Desert National Monument (Arizona, U.S.A.) are 2 protected areas separated by approximately 12 km of unprotected land with no human residents and no paved roads. After massive urban development was proposed for this area, a conservation corridor with 3 strands, each about 1.5 km wide, was designed to serve 7 focal species (Beier et al. 2008b). After build-out, the corridor strands will be a constricted remnant of present-day connectivity and will be subject to edge effects (e.g., light, noise, subsidized predators, and urban water runoff) and human activities. None of the response variables measured before buildout would be reliable indicators of corridor utility after build-out. Furthermore, after build-out there will be a time lag before the response variable will reflect the longterm utility of the corridor, as reflected in our lag time criterion.
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Potential Response Variables
year effort may be required if the first year yields no presences.
Animal Presence in Corridor Because animal presence is weakly related to the primary goals of conservation corridors (Table 1), animal absence from a corridor does not indicate corridor failure, and animal presence in a corridor does not indicate corridor success. Absence does not indicate failure because some species (e.g., highly mobile species that live at low density) need only rare corridor movements to provide gene flow and demographic rescue (Beier 1993; Haddad & Tewksbury 2005). Rigorous surveys lasting 1–2 years could yield no detections in a corridor that does support such movements. For corridor dwellers, presence in a corridor is a necessary but not sufficient condition for corridor success. In particular, if a corridor is occupied by a population that does not interact with the populations in the patches or if the corridor is solely a sink for surplus individuals from those patches, animal presence in the corridor would not achieve the corridor’s conservation goal. For example, Horskins et al. (2006) reported that 2 small mammals occurred throughout a 70-year-old, 7-kmlong corridor, but genetic evidence suggested that no gene flow, recolonization, or demographic rescue had occurred between the 2 patches connected by the corridor. Similarly, Leidner and Haddad (2010) documented that human-caused habitat barriers and the configuration of a habitat mosaic prevented a linear strip of occupied habitat from providing connectivity. The lag time for animal presence to reflect long-term animal response to the corridor is probably no more than 2–3 generations of the focal species. Animal presence immediately after build-out could be positively biased (because site fidelity may cause older animals to continue to use a corridor that will be avoided by future generations) or negatively biased (because it takes time for animals to habituate to new landscape features or for dispersing animals to explore the new features). As an example of the latter phenomenon, very few wolves (Canis lupus), moose (Alces alces), or grizzly bears (Ursus arctos) used highway crossing structures on the TransCanada Highway through Banff National Park during the first 3 years after the structures were built, such that the animal presence response variable could have led to the conclusion that the connective structures were failures. Presence of these species in crossing structures increased dramatically 5 years after build-out and has remained high since (Clevenger et al. 2009). Documenting animal presence or absence can involve livetrapping, camera traps, sign surveys, visual observations, or other methods. The study could begin during the second generation after build-out (for a passage species) or after 2–3 generations (for a corridor dweller) and might be completed in 1 year. Because it is more difficult to infer absence than presence, a more intensive second
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Individual Movement between Patches via the Corridor For corridor dwellers, individual movement between patches is not an appropriate response variable because these species do not move between patches in discrete observable events. For passage species, animal movement through a corridor after build-out provides stronger evidence than animal presence provides for corridor effectiveness. Documentation of movement between seasonal ranges is sufficient to demonstrate success of a conservation corridor established to support seasonal migration (Table 1, goal 2), and lack of such movement reliably indicates the corridor has failed. For the other conservation goals in Table 1, interpatch movement is necessary but documenting such movement is not sufficient to infer corridor success because some interpatch movements do not improve demographic performance or increase genetic diversity (King & With 2002; Fischer & Lindenmayer 2007). For example, although most dispersing pumas in 1 study used corridors, almost all corridor users died before they became breeders in the recipient population (Beier 1995). Similarly, Riley et al. (2006) documented frequent interpatch movements by bobcats (Lynx rufus) and coyotes (Canis latrans) that did not contribute to the recipient populations. The lag time required to document interpatch movement is the same as that for presence, and for the same reasons. Greater effort is required because individually recognized animals must be detected moving between patches, either by monitoring radio-tagged animals or other expensive field efforts. For some focal species only dispersing juveniles are likely to move between patches, and dispersers experience high mortality, adding to the time and expense of studying interpatch movement. Compared with animal presence, movement between patches offers much improved relevance to conservation goals for passage species with little or no increase in lag time and a moderate increase in the cost of study (Fig. 1). Moreover, observations of movement provide a useful complement to genetic or occupancy data because interpatch movements are the mechanistic link between the landscape and the demographic and genetic effects of conservation interest. Gene Flow Variables related to gene flow (Wright 1969; Hampton et al. 2004; Balkenhol et al. 2009), dispersal rates inferred from genetic assignment tests (Berry et al. 2004), and barriers inferred from Bayesian clustering algorithms (Pritchard et al. 2000) directly measure conservation goals 3, 4, and 5 (Table 1) and are markedly superior to animal presence or interpatch movement in this regard.
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Cost
Occupancy
Movement (2)
Movement (3,4,5)
Gene flow
Presence 0
10
Lag time (generations)
20
30
Figure 1. Relevance to conservation goal (indicated by size of circle) of 4 response variables (animal presence, individual movement between patches via a corridor, gene flow, and patch occupancy) in relation to the cost of a study using that variable and lag time from build-out until a positive response to a corridor might be evident. The size of each symbol represents our qualitative assessment of how directly each variable measures achievement of the conservation goals.
Collection and analysis of genetic material from the corridor-connected patches alone can support qualitative inferences about corridor effectiveness (i.e., that flow has or has not occurred) (Dixon et al. 2006). Genetic similarity can also quantitatively measure success when GScorridor (genetic similarity between corridor-connected patches) is compared with GSisolates (genetic distance between isolated patches), and with GScontinuous (genetic distance between sampling locations in a large intact habitat area) (Mech & Hallett 2001; Horskins et al. 2006; Beier & Gregory 2012). Formally, the corridor success index, CSI = (GScorridor − GSisolates )/(GScontinuous − GSisolates ), with values close to 0 indicating failure, values close to 1 indicating a corridor that provides as much gene flow as an intact landscape, and intermediate values indicating relative success of the corridor. Because sensible or credible confidence intervals can readily be calculated from the underlying allele frequencies, CSI values can be compared not only to the reference values of 0 and 1, but can also be compared between corridors to yield inferences about variables that affect corridor success. The time lag required for genetic divergence between isolated patches increases in a predictable, quantifiable way as effective population size increases (Wright 1943). More specifically, genetic divergence should be evident after 10 generations for effective population sizes of approximately 60 per patch and after 20 generations for effective population sizes of approximately 100 individ-
uals. Because effective population size may be 5–15% of census population size (Hare et al. 2011), genetic divergence should be evident within 10–20 generations for populations of 400–2000 individuals per patch. If gene flow variables are measured before genetic divergence between isolated patches can occur, one could falsely conclude that the corridor works. Thus, use of genetic distance as a response variable requires acceptance of a lag time of 10–20 generations for small to moderately sized populations. For example, Mech and Hallett (2001) documented that interpatch genetic distances for redbacked voles (Clethrionomys gapperi) in patches that had been isolated for only 12 years were significantly higher than the genetic distances between patches connected by corridors. Sharma et al. (2013) documented that over the last century, loss of corridors diminished interpatch gene flow for tigers, whereas tiger gene flow between patches with intact corridors has remained high. It may be impossible to use gene flow as a response variable for species with large effective population sizes, but such species are unlikely to be a focus for conservation goals 3, 4, or 5. Using genetic variables as response variables involves the cost of genetic analyses and the cost of obtaining genetic samples from individuals in at least 2 corridorlinked patches. Use of CSI requires 2 additional pairs of locations (2 isolated patches and 2 sampling locations within intact habitat). The main factors affecting these costs are the difficulty of obtaining tissues from the focal species and whether genetic markers must be developed for the species. The cost of a study in which gene flow is used to measure corridor success is likely less than or similar to the cost of documenting animal movement. Gene flow also can be used to quantify corridor utility for corridor dwellers for which discrete interpatch movement is irrelevant (Waples & Gaggiotti 2006). Moreover, the same genetic data also can be used to estimate 2 other conservation-relevant variables, namely effective population size and census population size (Luikart et al. 2010). Compared with interpatch movement as a response variable, gene flow is vastly more relevant to conservation goals 3, 4, and 5, at the expense of an increase in lag time, but there is little or no increase in the cost of study (Fig. 1). Genetic data can also be used to monitor use of seasonal migratory corridors (conservation goal 2). For example, genetic sampling of polar bears (Ursus maritimus) in a nonbreeding area shared by 2 disjunct breeding populations confirmed the continued use of seasonal migratory corridors (Paetkau et al. 2008). In the near future, next generation sequence-based techniques such as RadS (Landguth & Balkenhol 2012; Davey & Blaxter 2013), and advanced Bayesian genetic clustering and other landscape genetic approaches (Balkenhol et al. 2009; Blair et al. 2012) will reduce the time lag needed to infer corridor utility from genetic data.
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Occupancy Rates and Species Richness of Patches Patch occupancy is the most conservation-relevant response variable for goals 4 and 5, which are arguably the most important conservation goals for corridors. Ultimately, a corridor is successful to the extent that it promotes demographic rescue and recolonization and is at best partially successful otherwise. Over the long term, this means that patches linked by successful corridors will be more frequently occupied than patches that are isolated from each other by the matrix (Inglis & Underwood 1992) and across multiple species, patches connected by successful corridors will have higher species richness than isolated patches (Collinge 2000). For conservation corridors and patches of the size served by larger conservation corridors, the lag time for observing changes in patch occupancy or species richness is much longer than for gene flow because extinctions (required for changes in occupancy) occur more slowly than genetic divergence. For example, Florida panthers (Puma concolor coryi) experienced marked genetic divergence from neighboring populations and lost most of their genetic diversity by 1960 (Culver et al. 2000), 35 years before genetic augmentation was undertaken to avert extinction. This time lag (identical to “relaxation time” [Diamond 1972]) gives rise to an extinction debt, whereby doomed species may persist for 50–400 or more years after habitat loss and fragmentation have ensured their demise (Tilman et al. 1994). The cost of using patch occupancy rates and species richness as a response variable for conservation corridors is probably an order of magnitude larger than for studies using other types of response variables. Although CSI for a single corridor can be statistically different from 1 or 0, an occupancy rate of 0% for a single isolated patch is not statistically different from an occupancy rate of 100% for a single corridor-connected patch. Because replication is needed to detect statistically significant differences in occupancy rates, costs increase enormously. The long lag time and the need for costly replication may preclude the use of patch occupancy rates and species richness as response variables for conservation corridors. Most studies using these response variables have been microcosm studies (e.g., Gilbert et al. 1998; Collinge 2000; Rantalainen et al. 2004) that have inexpensive replicates and short lag times (due to very small effective population sizes). Damschen et al. (2006) documented that 5-year-old corridors significantly increased plant species richness in a mesocosm study, showing that a rapid response can occur outside microcosms. But it would be more difficult to achieve sufficient replication to detect differences in richness or occupancy in large patches embedded in agricultural and urban land uses. In most microcosm studies in which occupancy or richness was a response variable, the experimenter caused extinctions in patches to further reduce lag time and
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to allow direct observation of recolonization (goal 5). As investigators scale up from microcosms, 2 ethically acceptable ways to reduce the time required to observe colonization would be to use habitat restoration to link unoccupied patches to occupied ones or to find a landscape and species for which fire or other disturbance regularly creates new patches and corridors. We conclude that response variables related to patch occupancy rates are most relevant to conservation goals, but the extremely long lag time and high costs of such studies severely limit their application to conservation corridors. We found little reason to use presence in the corridor as a response variable because it has the least relevance to conservation goals, no lag time advantage compared with interpatch movement, and only moderate cost advantage. Movement of individual animals between patches is clearly the most appropriate response variable for a corridor intended to provide seasonal migration, but it is not an appropriate response variable for corridor dwellers, and is only moderately relevant to goals 3, 4, and 5 for passage species. Response variables related to gene flow provide a good trade-off among cost, relevance to conservation goals, and lag time (Fig. 1). Nonetheless, the lag time of 10–20 generations means that evaluation of conservation corridors cannot occur until at least 10–50 years after build-out (depending on the generation time and population sizes of the focal species). Perhaps the best way to provide a useful assessment of conservation corridors would be to measure gene flow, patch occupancy, and species richness in a large number of corridor-connected and isolated patches that have been embedded in human dominated landscapes for >50 years, regardless of whether the corridors were originally designed for conservation purposes. Such an analysis would require careful controlling for the disparate circumstances of the study landscapes.
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