Extending isolation by resistance to predict genetic connectivity

Fletcher, Robert J.; Sefair, Jorge A.; Kortessis, Nicholas; Jaffé, Rodolfo; Holt, Robert D.; Robertson, Ellen P.; Duncan, Sarah I.; Marx, Andrew J.; Austin, James D.

doi:10.1111/2041-210x.13975

Cited by 9 publications

(8 citation statements)

References 52 publications

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“…S3 ). In this situation, net visitation rates quantify the expected net movement rates of dispersing individuals through a given pixel in a landscape based on specific starting and ending locations ( 34 ). Both mortality and conflict together reduced expected movement and connectivity between key populations, decreasing predicted net visitation rates ( SI Appendix , Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, we mapped the predicted movement and flow of elephants based under assumptions of no constraints regarding absorption from natural mortality or conflict relative to expectations of flow under human–elephant conflict. To do so, we calculated net visitation rates over space ( 34 ). Visitation rates are the

th element of F , which describe the total time a disperser spends at location

if starting in location

.…”

Section: Methodsmentioning

confidence: 99%

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Mapping the connectivity–conflict interface to inform conservation

Vasudev

Fletcher

Srinivas

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs for humans and animals and impeding connectivity. Thus, conflict mitigation and connectivity present an apparent dilemma for conservation. We present a framework to address this dilemma and disentangle the effects of barriers to animal movement and conflict-induced mortality of dispersers on connectivity. We extend random-walk theory to map the connectivity–conflict interface, or areas where frequent animal movement may lead to conflict and conflict in turn impedes connectivity. We illustrate this framework with the endangered Asian elephant Elephas maximus , a species that frequently disperses out of protected areas and comes into conflict with humans. We mapped expected movement across a human-dominated landscape over the short- and long-term, accounting for conflict mortality. Natural and conflict-induced mortality together reduced expected movement and connectivity among populations. Based on model validation, our conflict predictions that explicitly captured animal movement better explained observed conflict than a model that considered distribution alone. Our work highlights the interaction between connectivity and conflict and enables identification of location-specific conflict mitigation strategies that minimize losses to people, while ensuring critical wildlife movement between habitats. By predicting where animal movement and humans collide, we provide a basis to plan for broad-scale conservation and the mutual well-being of wildlife and people in shared landscapes.

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Section: Resultsmentioning

confidence: 99%

th element of F , which describe the total time a disperser spends at location

if starting in location

.…”

Section: Methodsmentioning

confidence: 99%

Mapping the connectivity–conflict interface to inform conservation

Vasudev

Fletcher

Srinivas

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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“…Our findings provide several quantified estimates of important aspects for carnivore conservation translocations that can be compared among potential reintroduction or colonization areas by managers for any species. Previously, Fletcher et al (2022) demonstrated the effectiveness of the SAMC framework to predict population structure better than more traditional methods of connectivity analysis, such as least-cost and circuit theory, because of its ability to consider directional movement resistance. Vasudev et al (2023) were able to test SAMC model predictions using conflict data for Asian elephant (Elephas maximus) in a shared landscape and found that accounting for animal movement improved their predictive ability of conflict hotspots, which could then be integrated into the Importantly, the flexibility of the SAMC framework can be tailored to the specifics of any locale and species and can be designed to test model assumptions and assess a wide variety of possible scenarios.…”

Section: Discussionmentioning

confidence: 99%

“…Regardless of the areas occupied by wolves, the SAMC framework can be updated and expanded (e.g. to include gene flow; Fletcher et al, 2022) to better model wolf recovery as restoration progresses, more empirical data become available, and more specific management goals are developed or policies change (e.g. protection status of wolves federally or in surrounding states).…”

Section: Discussionmentioning

confidence: 99%

Predicting dispersal and conflict risk for wolf recolonization in Colorado

Ditmer,

Wittemyer,

Zeller

et al. 2023

Journal of Applied Ecology

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The colonization of suitable yet unoccupied habitat due to natural dispersal or human introduction can benefit recovery of threatened species. Predicting habitat suitability and conflict potential of colonization areas can facilitate conservation planning. Planning for reintroduction of gray wolves (Canis lupus) to the US state of Colorado is underway. Assessing which occupancy sites minimize the likelihood of human–wolf conflict during dispersal events and seasonal movements is critical to the success of this initiative. We used a spatial absorbing Markov chain (SAMC) framework, which extends random walk theory and probabilistically accounts for both movement behaviour and mortality risk, to compare the viability of potential occupancy sites (public lands >500 km2 to minimally meet wolf pack range area). The SAMC framework produced spatially explicit predictions of wolf dispersal, philopatry and conflict risk ahead of recolonization prior to reintroduction efforts. Our SAMC model included: (1) movement resistance based on terrain, roads and housing density; (2) mortality risk and potential conflict (absorption) based on livestock presence, social tolerance, land ownership and state boundaries; and (3) site fidelity based on habitat quality. Using this model, we compared 21 public land units by deriving predictions of: (A) relative survival time outside each site, (B) intensity of use and retention time within each site and (C) the probability of use on adjacent public lands. We also predicted and mapped potential conflict hotspots associated with each site. Among the units assessed, a complex of USFS Wilderness areas near Aspen, chiefly the Hunter‐Fryingpan and Collegiate Peaks Wilderness areas, had the best overall rankings when comparing predictions of each metric. The area balances high‐quality, well‐connected habitat with relatively low livestock density and high social tolerance. Synthesis and applications. Our findings highlight the utility of the SAMC framework for assessing colonization areas and the capacity to identify locations for effective proactive management, especially of conflict prone species. The flexibility of the SAMC framework enables predicting likely areas of philopatry and human–wildlife conflict using spatially explicit metrics which can improve the success of conservation translocations and management of species with changing geographic extents.

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“…Interactions between organisms and their environment shape fundamental ecological phenomena such as species ranges (Kearney & Porter 2009), population dynamics Kareiva et al 1990), community composition (Menge & Olson 1990), and evolutionary feedbacks . These relationships also provide critical applied insights about, for example, spatiotemporal patterns of biological diversity Woodin et al 2013;Evans et al 2015), population trends Madin et al 2012), or genetic connectivity (Cushman & 3 Lewis 2010;Creel et al 2019;Fletcher Jr et al 2022) -insights necessary to address the twin planetaryscale ecological crises of climate change and biodiversity loss . Therefore, there is significant value in frameworks that can link the relationship between organisms and their environments to their niches (Kearney 2006;Matthiopoulos 2022), and make predictions from such relationships about the distribution of individuals and species geographically Inferring relationships between individuals and their environment has traditionally relied on observations of occurrence patterns over some set of environmental contexts which vary geographically , typically by using environmental dimensions to contrast observations from locations where organisms are putatively absent (Mackey & Lindenmayer 2001;Johnson et al 2006;Moorcroft & Barnett 2008).…”

Section: Introductionmentioning

confidence: 99%

Choices to landscapes: Mechanisms of animal movement scale to landscape patterns

Rogers,

Yanco,

Jetz

2024

Preprint

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Understanding the geographic distributions of animals is central to ecological inquiry and conservation planning. Movement-based habitat selection models, like discrete-time step-selection functions, are useful for identifying key environmental attributes which animals select upon and can nearly perfectly capture preference patterns between environmental conditions. However, predictions based only on selection can often fail to accurately describe true geographic distributions. We show that by integrating local selection patterns, movement models, and explicit landscape constraints within the same framework, we can better predict simulated distributions than occurrence-based frameworks of selection alone. Using three case studies, we show that this framework can better predict distributions of organisms across increasing scales of out-of-sample prediction: within individuals, between individuals, and even between regional contexts. Movement modeling is a powerful tool to describe both the selection paradigm that organisms apply to the environment and the movement patterns that enable them to apply those selection paradigms. By understanding movement and selection at the same time, habitats that species “prefer” may not be ultimately occupied, as many “preferred” patches may be unreachable given movement strategies and landscape context, often leading to smaller geographic distributions than estimated by selection or occurrence alone.

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Extending isolation by resistance to predict genetic connectivity

Cited by 9 publications

References 52 publications

Mapping the connectivity–conflict interface to inform conservation

Mapping the connectivity–conflict interface to inform conservation

Predicting dispersal and conflict risk for wolf recolonization in Colorado

Choices to landscapes: Mechanisms of animal movement scale to landscape patterns

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