Least-Cost Modelling and Landscape Ecology: Concepts, Applications, and Opportunities

Etherington, Thomas R.

doi:10.1007/s40823-016-0006-9

Cited by 128 publications

(105 citation statements)

References 93 publications

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“…Using a distance‐based approach to define the links allows this, but, operationally, this definition should be informed by the biology of the species and the structure of the landscape of interest. Directly assessing connectivity from biological information via least‐cost distances (Etherington ) or resistance distances (McRae et al . ) is not easy and so an approach that relies on potential linkages, as ours does, is easier to implement (Zeller, McGarigal & Whiteley ).…”

Section: Discussionmentioning

confidence: 99%

Using network connectivity to prioritise sites for the control of invasive species

Perry

Moloney

Etherington

2016

Journal of Applied Ecology

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Summary Habitat connectivity is a crucial determinant of population dynamics in fragmented landscapes. The corollary of the emphasis on maintaining connectivity to enhance the movement of organisms is that disrupting connectivity should minimise it. Here, we evaluate the efficiency of an invasive species control strategy that targets the most connected habitats in a landscape. A network (spatial graph) provides an intuitive representation of a landscape, and the topology of this network can be used to identify the most connected patches. We implemented a simulation model of the spread of an invasive species on a network and used it to evaluate whether targeting the better‐connected components of the landscape enhances control effectiveness. Control strategies based on network topology consistently outperformed both a null strategy of random habitat selection and one based on separation distance alone. The advantages of the connectivity‐based strategy were strongest in the early phases of the invasion process, when a small number of habitats are occupied at low population density. However, if long‐distance dispersal events were common, the advantages of the connectivity approach weakened. The performance of the connectivity‐based strategy is robust to habitat‐level demographic stochasticity. In fact, connectivity‐based targeting outperforms a strategy focussing on source habitats, with the additional benefit that it requires less information to be implemented. Synthesis and applications. Our simulation model outcomes demonstrate that deliberately targeting the best‐connected components of a landscape is an efficient control strategy for invasive species when long‐distance dispersal is infrequent, and it is likely to be cheaper than other alternatives such as targeting population sources. Network scientists have developed a range of methods designed to identify the minimal set of nodes on a graph that will disrupt the network as a whole; these tools have potential to aid in the design of more effective control strategies.

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Section: Discussionmentioning

confidence: 99%

Using network connectivity to prioritise sites for the control of invasive species

Perry

Moloney

Etherington

2016

Journal of Applied Ecology

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“…the matrix. However, extensions to the classical approach do now account for the matrix, most often by assuming that different matrix environments are more or less readily moved through by a dispersing organisms, and then calculating the least cost paths between patches and using these in place of the Euclidean distances [180][181][182].…”

Section: Process-based Modelsmentioning

confidence: 99%

Emerging Opportunities for Landscape Ecological Modelling

Synes

Brown

Watts

et al. 2016

Curr Landscape Ecol Rep

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Landscape ecological modelling provides a vital means for understanding the interactions between geographical, climatic, and socio-economic drivers of land-use and the dynamics of ecological systems. This growing field is playing an increasing role in informing landscape spatial planning and management. Here, we review the key modelling approaches that are used in landscape modelling and in ecological modelling. We identify an emerging theme of increasingly detailed representation of process in both landscape and ecological modelling, with complementary suites of modelling approaches ranging from correlative, through aggregated process based approaches to models with much greater structural realism that often represent behaviours at the level of agents or individuals. We provide examples of the considerable progress that has been made at the intersection of landscape modelling and ecological modelling, while also highlighting that the majority of this work has to date exploited a relatively small number of the possible combinations of model types from each discipline. We use this review to identify key gaps in existing landscape ecological modelling effort and highlight emerging opportunities, in particular for future work to progress in novel directions by combining classes of landscape models and ecological models that have rarely been used together.

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“…This framework, what we term the 'spatial absorbing Markov chain' (SAMC), differs from other connectivity mapping approaches (Calabrese and Fagan 2004, Rudnick et al 2012, Fletcher et al 2016 in several ways. Unlike individual-based modeling of connectivity (Bocedi et al 2014), the SAMC is an analytical framework like least-cost analysis (Etherington 2016), randomized shortest paths (Saerens et al 2009), and circuit theory (McRae et al 2008). Overall, it is most similar to circuit theory: SAMC and circuit theory are both rooted in Markov chain theory.…”

Section: Introductionmentioning

confidence: 99%

samc: an R package for connectivity modeling with spatial absorbing Markov chains

et al. 2020

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Quantifying landscape connectivity is fundamental to better understand and predict how populations respond to environmental change. Currently, popular methods to quantify landscape connectivity emphasize how landscape features provide resistance to movement. While many tools are available to quantify landscape resistance, these do not discern between two fundamentally different sources of resistance: movement behavior and mortality. To address this issue, we developed the samc R package that quantifies landscape connectivity using absorbing Markov chain theory. Within this mathematical framework, movements are represented as transient states in the Markov chain, while mortality is represented by transitions to absorbing states. Not only does this framework explicitly account for these different issues, it provides a probabilistic approach that can incorporate both short‐term and long‐term dynamics, as well as species distribution and abundance. The package includes functions to quantify life expectancy, long‐term visitation rates, and various spatially and temporally explicit measures of mortality and movement at the local and landscape scales. These functions in samc have been optimized to find computationally practical solutions in landscapes comprised of > 2 × 106 cells. Here, we illustrate the workflow of the samc package with publicly available movement and mortality data on the endangered Florida panther Puma concolor coryi. This analysis showed that movement and mortality are generally correlated except for locations near roads (areas of high mortality risk) that are within the dispersal range of source locations. This pattern would have been undetectable with current methods that quantify movement resistance. Overall, the samc package provides a means for implementing spatial absorbing Markov chains that can distinguish between movement behavior and mortality resulting in more reliable landscape connectivity measures.

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Least-Cost Modelling and Landscape Ecology: Concepts, Applications, and Opportunities

Cited by 128 publications

References 93 publications

Using network connectivity to prioritise sites for the control of invasive species

Using network connectivity to prioritise sites for the control of invasive species

Emerging Opportunities for Landscape Ecological Modelling

samc: an R package for connectivity modeling with spatial absorbing Markov chains

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