Using spatial network structure in landscape management and planning: A case study with pond turtles

Pereira, Miguel; Segurado, Pedro; Neves, Nuno

doi:10.1016/j.landurbplan.2010.11.009

Cited by 83 publications

(61 citation statements)

References 38 publications

(52 reference statements)

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“…that affect the species' movement in an optimal way to realistically estimate the cost of movement through any location in the landscape. Resistance values have usually been determined by assigning resistance scored on an arbitrary scale (Beier et al 2008, Pereira et al 2011) on the basis of expert opinion itself or in combination with literature review (Larkin et al 2004, Kautz et al 2006. However, such approaches have frequently been shown to perform poorly (Beier et al 2008, Shirk et al 2010.…”

Section: Introductionmentioning

confidence: 99%

Estimating effective landscape distances and movement corridors: comparison of habitat and genetic data

et al. 2015

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Abstract. Resistance models provide a key foundation for landscape connectivity analyses and are widely used to delineate wildlife corridors. Currently, there is no general consensus regarding the most effective empirical methods to parameterize resistance models, but habitat data (species' presence data and related habitat suitability models) and genetic data are the most widely used and advocated approaches. However, the practical consequences of applying one or the other approach have not been well studied. To address this knowledge gap, we performed a comparative study on the implications of using habitat suitability versus genetic data for determining effective landscape distances (a proxy inversely related to isolation among patches) based on least-cost and circuit-theoretic approaches, and for identifying potential movement corridors. For our comparison, we used data for the Cantabrian brown bear in Spain, an endangered population for which connectivity has been identified as a major conservation concern. Our results show that for brown bears, habitat models tend to overestimate resistance to movement through non-optimal areas, whereas genetic data yield higher estimates of effective distances within habitat areas. Therefore, our results suggest that (1) dispersal might be generally less constrained by landscape conditions than habitat utilization in home ranges, and that (2) dispersing animals might be more flexible in their movement behavior than residents are in their habitat resource utilization behavior, with records for residents dominating species occurrence data and subsequent habitat models. The assessed approaches provided dissimilar connectivity models with notable differences in patterns of predicted corridors across the study area, mainly due to differences in predicted connections between subpopulations. Our results highlight that the functional differences in habitat vs. genetic data, as well as the assumptions and potential limitations of different analytical approaches that use these data, need to be considered more carefully in connectivity modeling and subsequent corridor delineation.

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Section: Introductionmentioning

confidence: 99%

Estimating effective landscape distances and movement corridors: comparison of habitat and genetic data

et al. 2015

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“…The resistance surface is a raster map (mosaic with a value, a larger value corresponds to higher resistance) indicating the level of disturbance or degree of difficulty that target species are expected to encounter when moving between patches, which significantly affects the outputs of ecological network research26. Therefore, many studies construct resistance surfaces based on various methods, such as biological behavior resistance estimates, expert scoring, entropy weighing, and landscape development intensity indexing10272829. However, most studies have constructed landscape resistance surfaces based on expertise and overall ratings for certain land-use types, leading to the resulting landscape resistance surfaces being heavily dependent on grading factors526.…”

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confidence: 99%

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

Gao

Liu

et al. 2017

Sci Rep

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Fragmentation and reduced continuity of habitat patches threaten the environment and biodiversity. Recently, ecological networks are increasingly attracting the attention of researchers as they provide fundamental frameworks for environmental protection. This study suggests a set of procedures to construct an ecological network. First, we proposed a method to construct a landscape resistance surface based on the assessment of habitat quality. Second, to analyze the effect of the resistance surface on corridor simulations, we used three methods to construct resistance surfaces: (1) the method proposed in this paper, (2) the entropy coefficient method, and (3) the expert scoring method. Then, we integrated habitat patches and resistance surfaces to identify potential corridors using graph theory. These procedures were tested in Changzhou, China. Comparing the outputs of using different resistance surfaces demonstrated that: (1) different landscape resistance surfaces contribute to how corridors are identified, but only slightly affect the assessment of the importance of habitat patches and potential corridors; (2) the resistance surface, which is constructed based on habitat quality, is more applicable to corridor simulations; and (3) the assessment of the importance of habitat patches is fundamental for ecological network optimization in the conservation of critical habitat patches and corridors.

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“…The number of components. Components are sub-graphs that are connected within but disconnected among sub-graphs [30]. This measure is a helpful tool to reveal the intermediate scales of network organization [12].…”

Section: Measures Of Divergencementioning

confidence: 99%

A Spatial-Territorial Reorganization Model of Rural Settlements Based on Graph Theory and Genetic Optimization

et al. 2017

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Rural China has experienced rapid urbanization and industrialization, accompanied with rural-urban migration since 1978. This tremendous transition has caused a series of negative consequences, necessitating a spatial-territorial reorganization of rural settlements. Previous studies on the restructuring of rural settlements are insufficient for inter-settlement connection consideration and practical and dynamic decision-making techniques. To overcome these concerns, a dynamic spatial-territorial reorganization model (SRM) of rural settlement is proposed herein based on graph theory and genetic algorithm (GA). The model involves two parts. In Part 1, consolidated settlements are identified according to the socio-economic network performance under four types of attack. In Part 2, GA model is repeatedly executed to scientifically resettle consolidated settlements into nearby townships or central settlements with objectives of suitability, compactness, and local connectivity under the control of the constraints. This paper presents an application of SRM to Chengui Town, Hubei Province. Empirical results suggest that: (1) removing settlements in order of node degree is the least efficient way to destroy the entire functional system; and (2) the proposed model can yield satisfactory solutions in terms of spatial reorganization of settlements. The SRM may also serve as a valuable reference for planners in devising plans and making decisions.

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Using spatial network structure in landscape management and planning: A case study with pond turtles

Cited by 83 publications

References 38 publications

Estimating effective landscape distances and movement corridors: comparison of habitat and genetic data

Estimating effective landscape distances and movement corridors: comparison of habitat and genetic data

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

A Spatial-Territorial Reorganization Model of Rural Settlements Based on Graph Theory and Genetic Optimization

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