Connecting models to movements: testing connectivity model predictions against empirical migration and dispersal data

McClure, Meredith L.; Hansen, Andrew J.; Inman, Robert M.

doi:10.1007/s10980-016-0347-0

Cited by 146 publications

(151 citation statements)

References 36 publications

Supporting

Mentioning

129

Contrasting

Unclassified

Order By: Relevance

“…We then created landscape resistance maps by calculating the inverse of the 275 habitat suitability and scaling so that each cell in the grid was assigned a value from 1 to 1000, indicating the 'cost' (e.g., energy expenditure, mortality risk, or habitat avoidance) for the animals to move across it (Pullinger and Johnson 2010;McClure et al 2016). …”

Section: Landscape Resistancementioning

confidence: 99%

“…Both cost-distance and circuit theory use resistance maps to predict the relative value of cells in the landscape for movement between two endpoints (McClure et al 2016). We selected Manyara Ranch as the start point in the south and the shortgrass plains calving grounds on the Gelai Plains in the north as the end point (Fig.…”

Section: Migration Corridor Algorithmsmentioning

confidence: 99%

“…The linear shape of many corridors (Sawyer et al 2009) make migrations particularly sensitive to the effects of habitat loss and fragmentation, particularly in areas that act as natural bottlenecks such as valleys or passes (Morrison and Bolger 2014). Recent efforts to quantitatively delineate and validate 40 corridors to conserve migratory species and their associated ecological services have significantly improved the resolution and accuracy of corridor planning, but relatively little effort has been made to compare amongst the many types of data and analyses that form the basis of corridor prediction (Berger 2004;Sawyer et al 2009;Epps et al 2011;Poor et al 2012;McClure et al 2016). 45…”

mentioning

confidence: 99%

“…The use of resistance surfaces to represent the landscape between migratory endpoints and algorithms to delineate movement pathways has increased over the last decade (Sawyer et al 2009;Poor et al 2012;LaPoint et al 2013;Cushman et al 2013;McClure et al 2016). Beier et al (2008) described many of the steps, choices, and assumptions involved in corridor (or linkage) delineation and 55 design, and Zeller et al (2012) provided guidance for defining the resistance surface(s).…”

mentioning

confidence: 99%

“…We compared two cost-based corridor detection algorithms: cost distance and circuit theory, in delineating predictive corridors. Finally, we validated our predictive corridors with locational data and cross-validated with the other data type based on methods suggested by McClure et al (2016), by calculating whether corridors contained more or 100 fewer data points than expected relative to random. This multi-method framework provides a rigorous, formalized process for delineating and validating migration corridors using multiple data sources, which can be utilized in land-use plans to effectively conserve landscape connectivity for wildlife.…”

mentioning

confidence: 99%

See 4 more Smart Citations

A multi-method approach to delineate and validate migratory corridors

et al. 2017

View full text Add to dashboard Cite

A multi-method approach to delineate and validate migratory corridors. Landscape Ecology, 32(8), pp. 1705Ecology, 32(8), pp. -1721Ecology, 32(8), pp. . (doi:10.1007 This is the author's final accepted version.There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it.http://eprints.gla.ac.uk/143652/ Objectives We present a multi-method approach for delineating and validating wildlife corridors 5 using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.Methods We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and 10 Maxent), to generate resource selection functions and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.Results Both data types produced similar resource selection functions. Wildebeest consistently 15 selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with 20 highest probability of use.Conclusions The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.3

show abstract

Section: Landscape Resistancementioning

confidence: 99%

Section: Migration Corridor Algorithmsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

A multi-method approach to delineate and validate migratory corridors

et al. 2017

View full text Add to dashboard Cite

show abstract

Mapping potential effects of proposed roads on migratory connectivity for a highly mobile herbivore using circuit theory

Fullman¹,

Wilson²,

Joly

et al. 2020

Ecological Applications

View full text Add to dashboard Cite

Migration is common worldwide as species access spatiotemporally varying resources and avoid predators and parasites. However, long‐distance migrations are increasingly imperiled due to development and habitat fragmentation. Improved understanding of migratory behavior has implications for conservation and management of migratory species, allowing identification and protection of seasonal ranges and migration corridors. We present a technique that applies circuit theory to predict future effects of development by analyzing season‐specific resistance to movement from anthropogenic and natural environmental features across an entire migratory path. We demonstrate the utility of our approach by examining potential effects of a proposed road system on barren ground caribou (Rangifer tarandus granti) and subsistence hunters in northern Alaska. Resource selection functions revealed migratory selection by caribou. We tested five scenarios relating habitat selection to landscape resistance using Circuitscape and GPS telemetry data. To examine the effect of potential roads on connectivity of migrating animals and human hunters, we compared current flow values near communities in the presence of proposed roads. Caribou avoided dense vegetation, rugged terrain, major rivers, and existing roads in both spring and fall. A negative linear relationship between resource selection and landscape resistance was strongly supported for fall migration while spring migration featured a negative logarithmic relationship. Overall patterns of caribou connectivity remained similar in the presence of proposed roads, though reduced current flow was predicted for communities near the center of current migration areas. Such data can inform decisions to allow or disallow projects or to select among alternative development proposals and mitigation measures, though consideration of cumulative effects of development is needed. Our approach is flexible and can easily be adapted to other species, locations and development scenarios to expand understanding of movement behavior and to evaluate proposed developments. Such information is vital to inform policy decisions that balance new development, resource user needs, and preservation of ecosystem function.

show abstract

Prioritization of landscape connectivity for the conservation of Peary caribou

Mallory

Boyce

2019

Ecology and Evolution

View full text Add to dashboard Cite

Adequate connectivity between discontinuous habitat patches is crucial for the persistence of metapopulations across space and time. Loss of landscape connectivity is often a direct result of fragmentation caused by human activities but also can be caused indirectly through anthropogenic climate change. Peary caribou ( Rangifer tarandus pearyi ) are widely dispersed across the islands of the Canadian Arctic Archipelago and rely on sea ice to move seasonally between island habitats throughout their range. Seasonal connectivity provided by sea ice is necessary to maintain genetic diversity and to facilitate dispersal and recolonization of areas from which caribou have been extirpated. We used least‐cost path analysis and circuit theory to model connectivity across Peary caribou range, and future climate projections to investigate how this connectivity might be affected by a warming climate. Further, we used measures of current flow centrality to estimate the role of High Arctic islands in maintaining connectivity between Peary caribou populations and to identify and prioritize those islands and linkages most important for conservation. Our results suggest that the Bathurst Island complex plays a critical role in facilitating connectivity between Peary caribou populations. Large islands, including Banks, Victoria, and Ellesmere have limited roles in connecting Peary caribou. Without rigorous greenhouse gas emission reductions our projections indicate that by 2100 all connectivity between the more southern Peary caribou populations will be lost for important spring and early‐winter movement periods. Continued connectivity across the Canadian Arctic Archipelago, and possibly Peary caribou persistence, ultimately hinges on global commitments to limit climate change. Our research highlights priority areas where, in addition to emission reductions, conservation efforts to maintain connectivity would be most effective.

show abstract

Connecting models to movements: testing connectivity model predictions against empirical migration and dispersal data

Cited by 146 publications

References 36 publications

A multi-method approach to delineate and validate migratory corridors

A multi-method approach to delineate and validate migratory corridors

Mapping potential effects of proposed roads on migratory connectivity for a highly mobile herbivore using circuit theory

Prioritization of landscape connectivity for the conservation of Peary caribou

Contact Info

Product

Resources

About