Optimizing the Geometry of Wildlife Corridors in Conservation Reserve Design

John, Rachel St.; Tóth, Sándor; Zabinsky, Zelda B.

doi:10.1287/opre.2018.1758

Cited by 21 publications

(21 citation statements)

References 41 publications

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“…Commonly, harvest scheduling is performed at finer spatial scales, but for the sake of practicality, it may be necessary, as in our case, to coarsen the resolution of harvest planning while maintaining the minimum width of the established corridors. Potentially, an approach similar to that presented in St. John et al (2018) could ensure the minimum width of habitat corridors, but is likely to increase the size of the optimization problem substantially.…”

Section: Potential Model Extensionsmentioning

confidence: 99%

Section: Recommendations For Resource Managersmentioning

confidence: 99%

“…An alternative approach combines harvest planning and habitat connectivity models in a single optimization problem (St. John, Tóth, & Zabinsky, 2018; St. John et al, 2016; Yemshanov et al, 2020). St. John et al (2016) proposed a multitemporal MIP model for forest harvesting and protection of reindeer habitat and migration corridors.…”

Section: Introductionmentioning

confidence: 99%

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Protecting wildlife habitat in managed forest landscapes—How can network connectivity models help?

Yemshanov

Haight

Rempel

et al. 2020

Natural Resource Modeling

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Industrial forestry in boreal regions increases fragmentation and may decrease the viability of some wildlife populations, particularly the woodland caribou, Rangifer tarandus caribou. Caribou protection often calls for changes in forestry practices, which may increase the cost and reduce the available timber supply. We present a linear programming model that assesses the trade-off between habitat protection and harvesting objectives by combining harvest scheduling and optimal habitat connectivity problems. We formulate the habitat connectivity model as a network flow problem that maximizes the amount of habitat connected over a desired time span in a forested landscape, while the forestry objective maximizes net undiscounted revenues from timber harvest subject to even harvest flow and environmental sustainability constraints. We applied the approach to explore the trade-off between caribou habitat protection and harvesting goals in the Armstrong-Whitesand Forest, Ontario, Canada, a boreal forest area with prime caribou habitat. Our model also incorporates Dynamic Caribou Harvesting Scheduling

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Section: Potential Model Extensionsmentioning

confidence: 99%

Section: Recommendations For Resource Managersmentioning

confidence: 99%

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Protecting wildlife habitat in managed forest landscapes—How can network connectivity models help?

Yemshanov

Haight

Rempel

et al. 2020

Natural Resource Modeling

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“…Ecologists and computer scientists have also teamed up to use artificial intelligence to optimize wildlife corridors in computer‐modeled landscapes (St. John et al. ). Finally, ecologists and computer scientists are using new machine learning methods (sensu Peters et al.…”

Section: Increasing Collaboration Between Computer Scientists and Ecomentioning

confidence: 99%

Enhancing collaboration between ecologists and computer scientists: lessons learned and recommendations forward

et al. 2019

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In the era of big data, ecologists are increasingly relying on computational approaches and tools to answer existing questions and pose new research questions. These include both software applications (e.g., simulation models, databases and machine learning algorithms) and hardware systems (e.g., wireless sensor networks, supercomputing, drones and satellites), motivating the need for greater collaboration between computer scientists and ecologists. Here, we outline some synergistic opportunities for scientists in both disciplines that can be gained by building collaborations between the computer science and ecology research communities, with a focus on the benefits to ecology specifically. We also identify past contributions of computer science to ecology, including high‐frequency environmental sensor technology, advanced supercomputing capacity for ecological modeling, databases for long‐term and high‐frequency datasets, and software programs for ecological analyses, to anticipate future potential contributions. These examples highlight the power and potential for further integration of computer science technology and ideas into the ecological research community. Finally, we translate our own experiences working together as a team of computer scientists and ecologists over the past decade into a conceptual framework with recommendations for supporting productive collaborations at the interface of the two disciplines. We specifically focus on how to apply best practices of team science for bridging computer science and ecology, which we advocate will substantially benefit ecology long‐term.

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“…Following those earlier studies, some integer programming formulations have successfully incorporated spatial attributes in reserve site selection (see [6,14,15] for reviews). Several recent papers used networks and graph theoretic concepts to model reserve contiguity [16][17][18][19][20][21][22], contiguity and compactness [23][24][25], and connecting corridors [26][27][28]. Most of these studies considered only one spatial attribute, or, when multiple attributes were involved, the analysis was restricted to only one species.…”

Section: Introductionmentioning

confidence: 99%

Optimizing conservation planning for multiple cohabiting species

et al. 2020

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Conservation planning often involves multiple species occupying large areas including habitat sites with varying characteristics. For a given amount of financial resources, designing a spatially coherent nature reserve system that provides the best possible protection to targeted species is an important ecological and economic problem. In this paper, we address this problem using optimization methods. Incorporating spatial criteria in an optimization framework considering spatial habitat needs of multiple species poses serious challenges because of modeling and computational complexities. We present a novel linear integer programming model to address this issue considering spatial contiguity and compactness of the reserved area. The model uses the concept of path in graph theory to ensure contiguity and minimizes the sum of distances between selected sites and a central site in individual reserves to promote compactness. We test the computational efficiency of the model using randomly generated data sets. The results show that the model can be solved quite efficiently in most cases. We also present an empirical application of the model to simultaneous protection of two cohabiting species, Gopher Tortoise and Gopher Frogs, in a military installation in Georgia, USA.

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Optimizing the Geometry of Wildlife Corridors in Conservation Reserve Design

Cited by 21 publications

References 41 publications

Protecting wildlife habitat in managed forest landscapes—How can network connectivity models help?

Protecting wildlife habitat in managed forest landscapes—How can network connectivity models help?

Enhancing collaboration between ecologists and computer scientists: lessons learned and recommendations forward

Optimizing conservation planning for multiple cohabiting species

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