Scale dependence in habitat selection: the case of the endangered brown bear (<i>Ursus arctos</i>) in the Cantabrian Range (NW Spain)

Sánchez, María Cruz Mateo; Cushman, Samuel A.; Saura, Santiago

doi:10.1080/13658816.2013.776684

Cited by 146 publications

(127 citation statements)

References 45 publications

(55 reference statements)

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“…This suggests that anthropogenic pressures affect habitat selection at a home‐range level, whilst environmental variables influence site‐level habitat selection (Boyce, 2018; DeCesare et al., 2012). A similar result was found for brown bears ( Ursus arctos ) in the Cantabrian Range, northwest Spain (Sánchez, Cushman, & Saura, 2014). Brown bears within this region perceived anthropogenic disturbances, such as building density, agriculture, and transportation infrastructure, at broad scales, while environmental variables, such as edge effects amongst cover types and canopy closure, were selected at finer scales (Sánchez et al., 2014).…”

Section: Discussionsupporting

confidence: 79%

“…A similar result was found for brown bears ( Ursus arctos ) in the Cantabrian Range, northwest Spain (Sánchez, Cushman, & Saura, 2014). Brown bears within this region perceived anthropogenic disturbances, such as building density, agriculture, and transportation infrastructure, at broad scales, while environmental variables, such as edge effects amongst cover types and canopy closure, were selected at finer scales (Sánchez et al., 2014). Here, we show the importance of taking scale into account when conducting habitat selection studies, which is supported by other studies on, for example, Mexican spotted owl (Timm et al., 2016), mountain bongo antelope ( Tragelaphus euryceros isaaci ; Estes, Okin, Mwangi, & Shugart, 2008) and brown bears (Sánchez et al., 2014).…”

Section: Discussionsupporting

confidence: 79%

“…Brown bears within this region perceived anthropogenic disturbances, such as building density, agriculture, and transportation infrastructure, at broad scales, while environmental variables, such as edge effects amongst cover types and canopy closure, were selected at finer scales (Sánchez et al., 2014). Here, we show the importance of taking scale into account when conducting habitat selection studies, which is supported by other studies on, for example, Mexican spotted owl (Timm et al., 2016), mountain bongo antelope ( Tragelaphus euryceros isaaci ; Estes, Okin, Mwangi, & Shugart, 2008) and brown bears (Sánchez et al., 2014). However, the multiscale approach within habitat selection studies is still uncommon (McGarigal et al., 2016) and to our knowledge this is the first multiscale habitat selection study for cheetahs.…”

Section: Discussionmentioning

confidence: 99%

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Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Klaassen

Broekhuis

2018

Ecology and Evolution

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Animals select habitats that will ultimately optimize their fitness through access to favorable resources, such as food, mates, and breeding sites. However, access to these resources may be limited by bottom‐up effects, such as availability, and top‐down effects, such as risk avoidance and competition, including that with humans. Competition between wildlife and people over resources, specifically over space, has played a significant role in the worldwide decrease in large carnivores. The goal of this study was to determine the habitat selection of cheetahs (Acinonyx jubatus) in a human‐wildlife landscape at multiple spatial scales. Cheetahs are a wide‐ranging, large carnivore, whose significant decline is largely attributed to habitat loss and fragmentation. It is believed that 77% of the global cheetah population ranges outside protected areas, yet little is known about cheetahs’ resource use in areas where they co‐occur with people. The selection, or avoidance, of three anthropogenic variables (human footprint density, distance to main roads and wildlife areas) and five environmental variables (open habitat, semiclosed habitat, edge density, patch density and slope), at multiple spatial scales, was determined by analyzing collar data from six cheetahs. Cheetahs selected variables at different scales; anthropogenic variables were selected at broader scales (720–1440 m) than environmental variables (90–180 m), suggesting that anthropogenic pressures affect habitat selection at a home‐range level, whilst environmental variables influence site‐level habitat selection. Cheetah presence was best explained by human presence, wildlife areas, semiclosed habitat, edge density and slope. Cheetahs showed avoidance for humans and steep slopes and selected for wildlife areas and areas with high proportions of semiclosed habitat and edge density. Understanding a species’ resource requirements, and how these might be affected by humans, is crucial for conservation. Using a multiscale approach, we provide new insights into the habitat selection of a large carnivore living in a human‐wildlife landscape.

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Section: Discussionsupporting

confidence: 79%

Section: Discussionsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

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Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Klaassen

Broekhuis

2018

Ecology and Evolution

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“…However, like for data quality, the lack of translation between theory and practice is problematic; while there are methods to properly account for scale in ecological mapping and modeling (e.g., Detto and Muller-Landau, 2013;Matteo Sánchez et al, 2014), practical solutions are often not implemented in user-friendly, easily accessible software (Hamil et al, 2016). Until such tools become available, scale information should always be explicitly stated in the metadata and conservation and management plans to effectively support decision-makers (Wolff et al, 2016).…”

Section: Scalementioning

confidence: 99%

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

Lecours

2017

Front. Mar. Sci.

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Conservation planning and management typically require accurate and spatially explicit data at scales that are relevant for conservation objectives. In marine conservation, these data are often combined with spatial analytical techniques to produce marine habitat maps. While marine habitat mapping is increasingly used to inform conservation efforts, this field is still relatively young and its methods are rapidly evolving. Because conservation efforts do not always specify standards or guidelines for the production of habitat maps, results can vary dramatically. As representations of real environmental characteristics, habitat maps are highly sensitive to how they are produced. In this review paper, I present four concepts that are known to cause variation in spatial representation and prediction of habitats: the methodology used, the quality and scale of the data, and the choice of variables in regards to fitness for use. I then discuss the potential antinomy associated with the use of habitat maps in conservation: while habitat maps have become an invaluable tool to inform and assist decision-making, maps of the same area built using different methods and data may provide dissimilar representations, thus providing different information and possibly leading to different decisions. Exploring the theories and methods that have proved effective in terrestrial conservation and the spatial sciences, and how they can be integrated in marine habitat mapping practices, could help improve maps used to support marine conservation efforts and result in more reliable products to inform conservation decisions. Having a strong, consistent, transparent, repeatable, and science-based protocol for data collection and mapping is essential for effectively supporting decision-makers in developing conservation and management plans. The development of user-friendly tools to assist in the application of such protocol is crucial to a widespread improvement in practices. I discuss the potential to use interactive and collaborative Geographic Information Systems (GIS) to encourage the conservation and management community, from data collectors and mapmakers to decision-makers, to move toward a digital resilience and to develop such science-based protocol. Until standards and protocols are developed, habitat maps should always be interpreted with care, and the methods and metadata associated with their production should always be explicitly stated.

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“…Males and females have intra and inter-sexually overlapping home ranges (Dahle and Swenson 2003) and dispersal primarily occurs by males, while females typically are philopatric (Swenson et al 1998). Brown bear is highly dependent on large landscapes with low human-footprint and large extents of forest cover (Clevenger et al 1997, Apps et al 2004, Mateo-Sánchez et al 2014a. The brown bear population in the Cantabrian Range suffered a dramatic decline in the last several centuries as a result of human persecution and progressive loss and fragmentation of its habitat (Naves et al 2003).…”

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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Scale dependence in habitat selection: the case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain)

Cited by 146 publications

References 45 publications

Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

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

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