Combining a dispersal model with network theory to assess habitat connectivity

Lookingbill, Todd R.; Gardner, Robert H.; Ferrari, Joseph R.; Keller, Cherry

doi:10.1890/09-0073.1

Cited by 107 publications

(78 citation statements)

References 67 publications

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“…However, it remains a challenge to identify the mechanisms by which stable home ranges can emerge from unbounded movement paths, with a number of alternative modelling approaches in use [207]. In many of the existing IBMs of movement processes across complex landscapes the key questions being addressed have related to connectivity [208][209][210], emergent dispersal mortality [211,212], and home range formation [206,213,214], but in many cases these individual-based movement models have not been linked to models of population dynamics. When such links are made, it is possible to gain important new insights into the dynamics of species living on complex landscapes and into potential consequences of alternative management interventions [215].…”

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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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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“…In ecology and conservation, network analysis is increasingly being used to assess population connectivity across landscapes (9)(10)(11)(12)(13). Because of the importance of connectivity in conservation and its relevance to population and community ecology (14)(15)(16), network analysis and the accompanying use of graph theory are often emphasized as powerful approaches that have modest data requirements for assessing connectivity (10,11,13).…”

mentioning

confidence: 99%

Social network models predict movement and connectivity in ecological landscapes

Fletcher¹,

Acevedo²,

Reichert³

et al. 2011

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

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Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.dispersal | graph theory | habitat fragmentation | latent space models | landscape ecology N etwork analysis has recently exploded across scientific disciplines, including the social sciences, physics, cellular biology, and ecology (1-4). Topics as divergent as the stability of the Internet and the structure of metabolic reactions can be depicted through network analysis (1, 3). Such analysis is beneficial because it can facilitate the identification of complex, and often emergent, patterns, and can provide hypotheses for relationships between structure and function in many systems (2, 3). Nonetheless, a growing, widespread concern in the topic of network analysis is the reliability of data used in constructing networks (4-8).In ecology and conservation, network analysis is increasingly being used to assess population connectivity across landscapes (9-13). Because of the importance of connectivity in conservation and its relevance to population and community ecology (14-16), network analysis and the accompanying use of graph theory are often emphasized as powerful approaches that have modest data requirements for assessing connectivity (10,11,13). In this spatial context, resource patches are considered nodes (or vertices) and movements and/or flows between pat...

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“…The implication of landscape connectivity for wildlife viability and persistence is well studied with clear evidence that increased connectivity can increase population abundance and prevent extinction (Dobson et al, 1999;Fahrig and Merriam, 1985;Henein and Merriam, 1990;Lookingbill et al, 2010;Schumaker, 1996;van Andel and Aronson, 2012). However, it has been argued that increased connectivity may also promote the spread of infectious disease (Bienen, 2002;Hess, 1994;Real and Biek, 2007).…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore poor connectivity may lead to a higher probability of local extinction (Fahrig and Merriam, 1985;Henein and Merriam, 1990;Schumaker, 1996) and reduced likelihood of natural re-establishment via dispersal (Fahrig and Merriam, 1985;van Andel and Aronson, 2012). Evidence therefore supports the maintenance of dispersal corridors to promote growth and local population persistence and diversity (Beier and Noss, 1998;Dobson et al, 1999;Lookingbill et al, 2010;van Andel and Aronson, 2012). However, enhanced connectivity between subpopulations can increase the spread of infectious disease leading to detrimental impacts on native populations (Hess, 1994;Real and Biek, 2007).…”

Section: Introductionmentioning

confidence: 88%

Incorporating habitat distribution in wildlife disease models: conservation implications for the threat of squirrelpox on the Isle of Arran

Macpherson

Davidson

Duncan

et al. 2015

Animal Conservation

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Emerging infectious diseases are a substantial threat to native populations. The spread of disease through naive native populations will depend on both demographic and disease parameters, as well as on habitat suitability and connectivity. Using the potential spread of squirrelpox virus (SQPV) on the Isle of Arran as a case study, we develop mathematical models to examine the impact of an emerging disease on a population in a complex landscape of dierent habitat types. Furthermore, by considering a range of disease parameters, we infer more generally how complex landscapes interact with disease characteristics to determine the spread and persistence of disease. Specic ndings indicate that a SQPV outbreak on Arran is likely to be short lived and localised to the point of introduction allowing recovery of red squirrels to pre-infection densities; this has important consequences for the conservation of red squirrels. More generally, we nd the extent of disease spread is dependent on the rare passage of infection through poor quality corridors connecting good quality habitats. Acute, highly transmissible infectious diseases are predicted to spread rapidly causing high mortality. Nonetheless the disease typically fades out following local epidemics and is not supported in the long-term. A chronic infectious disease is predicted to spread more slowly but can remain endemic in the population. This allows the disease to spread more extensively in the long-term as it increases the chance of spread between poorly connected populations. Our results highlight how a detailed understanding of landscape connectivity is crucial when considering conservation strategies to protect native species from disease threats.

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Combining a dispersal model with network theory to assess habitat connectivity

Cited by 107 publications

References 67 publications

Emerging Opportunities for Landscape Ecological Modelling

Emerging Opportunities for Landscape Ecological Modelling

Social network models predict movement and connectivity in ecological landscapes

Incorporating habitat distribution in wildlife disease models: conservation implications for the threat of squirrelpox on the Isle of Arran

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