Does matrix resistance influence Red squirrel (Sciurus vulgaris L. 1758) distribution in an urban landscape?

Verbeylen, Goedele; Bruyn, Luc De; Adriaensen, Frank; Matthysen, Erik

doi:10.1023/b:land.0000014492.50765.05

Cited by 177 publications

(151 citation statements)

References 41 publications

Supporting

Mentioning

148

Contrasting

Order By: Relevance

“…We took into account the different impacts on species movement caused by different land-use types. The value of the coefficient is based on existing empirical data [52][53][54][55]. Typically, if a landscape such as grass or woodland is easily passed through, the resistance coefficient is 1.…”

Section: The Ecological Network Patterns Of the Green Landscapementioning

confidence: 99%

Ecological Security Pattern Analysis Based on InVEST and Least-Cost Path Model: A Case Study of Dongguan Water Village

Lin

Mao

et al. 2016

Sustainability

View full text Add to dashboard Cite

Abstract:The famous "world's factory" city, Dongguan, like many other places in China, is a typical beneficiary of China's Reform and Opening-up Policy. However, rapid urban sprawl and economic growth are at the expense of the destruction of the local environment. Therefore, it is of great importance to establish an ecological security network for sustainable development. InVEST models, effective tools to measure sensitivity and intensity of external threats to quantify habitat value, are used to calculate habitat quality of water and land. By combining structural connectivity and the Least-Cost Path model (LCP model), in which corridors are determined based on the minimum accumulative cost path between each critical point, ecological security patterns were calculated. According to the results, the northwest region of Dongguan, having a large quantity of farmlands and water and therefore many corridors and critical patches, is the most essential area in the overall security of ecological environments, which should be protected first. If developed, it should be dominated by eco-tourism and eco-agriculture. We hope that research on the ecological network, which includes critical patches and corridors formed by greenland and rivers, will lead toward better-informed proposals for local urban planning and regional sustainable development.

show abstract

Section: The Ecological Network Patterns Of the Green Landscapementioning

confidence: 99%

Ecological Security Pattern Analysis Based on InVEST and Least-Cost Path Model: A Case Study of Dongguan Water Village

Lin

Mao

et al. 2016

Sustainability

View full text Add to dashboard Cite

show abstract

“…1), which has been shown to increase the explanatory power of effective distance studies (Verbeylen et al 2003). Patch i was a 30 m x 30 m cell around the sampling point.…”

Section: Movement Through the Landscapementioning

confidence: 99%

“…When calculating the effective distance between habitat patches, different land cover types are assigned different costs and the simplest or least-cost path is calculated through them. Effective distance measures have been used to investigate the movement of ground beetles (Jopp & Reuter 2005), butterflies (Sutcliffe et al 2003), amphibians (Ray et al 2002;Stevens et al 2006), squirrels (Verbeylen et al 2003), and grizzly bears (Singleton et al 2004) and have generally met with good success. We determined the connectivity of appropriately scaled landscapes for four species of longhorned beetle that occur in Indiana, U.S.A., in terms of both Euclidean and effective distances.…”

Section: Introductionmentioning

confidence: 99%

Do flying beetles respond to human-dominated landscapes as complex mosaics or binary patterns

Foley

Holland

2010

View full text Add to dashboard Cite

Understanding and measuring functional connectivity for animals with habitats that have been fragmented by human activity requires that the biology and movement of the species be considered. We used least cost paths in GIS to test hypotheses regarding how different species of longhorned beetles likely connect habitats with dispersal. We predicted that there would be differences in the functional connectivity of landscapes depending on species larval niche breadth, adult feeding habits, and the potential for use of non-forest habitats. For the species with very specialized larvae, we developed a classification tree to determine areas likely to contain the appropriate species of host tree. Connectivity calculated using least cost paths did not out-perform Euclidean distances for three generalist beetles. This was also the case for the specialist beetle species when all forest was considered habitat. However, when we delineated habitat based on areas likely to support the host tree the functional connectivity incorporating least cost paths was a much better predictor than that using Euclidean distances. Generalists may respond to fragmented habitat in a binary habitat-matrix way while more specialized species may respond to a mosaic. These trends are obscured if habitat is defined by human perceptions rather than species biology.

show abstract

“…The least-cost path avoids landscape regions that are more resistant to movement and prefers paths through permeable features. LCD can be approximated by the path that minimizes the sum of the 'costs' of every raster cell traversed along the path [20,21]. Costs are defined by the geographical information embedded in the landscape and the behavioral and ecological characteristics of the species being evaluated [22].…”

Section: Introductionmentioning

confidence: 99%

Landscape features influence gene flow as measured by cost-distance and genetic analyses: a case study for giant pandas in the Daxiangling and Xiaoxiangling Mountains

et al. 2010

View full text Add to dashboard Cite

BackgroundGene flow maintains genetic diversity within a species and is influenced by individual behavior and the geographical features of the species' habitat. Here, we have characterized the geographical distribution of genetic patterns in giant pandas (Ailuropoda melanoleuca) living in four isolated patches of the Xiaoxiangling and Daxiangling Mountains. Three geographic distance definitions were used with the "isolation by distance theory": Euclidean distance (EUD), least-cost path distance (LCD) defined by food resources, and LCD defined by habitat suitability.ResultsA total of 136 genotypes were obtained from 192 fecal samples and one blood sample, corresponding to 53 unique genotypes. Geographical maps plotted at high resolution using smaller neighborhood radius definitions produced large cost distances, because smaller radii include a finer level of detail in considering each pixel. Mantel tests showed that most correlation indices, particularly bamboo resources defined for different sizes of raster cell, were slightly larger than the correlations calculated for the Euclidean distance, with the exception of Patch C. We found that natural barriers might have decreased gene flow between the Xiaoxiangling and Daxiangling regions.ConclusionsLandscape features were found to partially influence gene flow in the giant panda population. This result is closely linked to the biological character and behavior of giant pandas because, as bamboo feeders, individuals spend most of their lives eating bamboo or moving within the bamboo forest. Landscape-based genetic analysis suggests that gene flow will be enhanced if the connectivity between currently fragmented bamboo forests is increased.

show abstract

Does matrix resistance influence Red squirrel (Sciurus vulgaris L. 1758) distribution in an urban landscape?

Cited by 177 publications

References 41 publications

Ecological Security Pattern Analysis Based on InVEST and Least-Cost Path Model: A Case Study of Dongguan Water Village

Ecological Security Pattern Analysis Based on InVEST and Least-Cost Path Model: A Case Study of Dongguan Water Village

Do flying beetles respond to human-dominated landscapes as complex mosaics or binary patterns

Landscape features influence gene flow as measured by cost-distance and genetic analyses: a case study for giant pandas in the Daxiangling and Xiaoxiangling Mountains

Contact Info

Product

Resources

About