Evaluating the effect of habitat connectivity on the distribution of lesser horseshoe bat maternity roosts using landscape graphs

Tournant, Pierline; Afonso, Eve; Roué, Sébastien; Giraudoux, Patrick; Foltête, Jean-Christophe

doi:10.1016/j.biocon.2013.04.013

Cited by 50 publications

(34 citation statements)

References 40 publications

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“…Colony size was positively influenced by broadleaved woodland proportion at both spatial scales. This validates and refines previous studies, in which woodland areas was one of the best landscape predictors of maternity roost presence (Bontadina et al, 2002;Reiter, 2004;Schofield, 1996;Tournant et al, 2013). Indeed, broadleaf woodlands, often offering a higher richness and abundance of insects than coniferous plantations (Benton et al, 2002;Goiti et al, 2004), are more intensively used as foraging areas by R. hipposideros than any other habitat (Bontadina et al, 2002;Schofield, 1996).…”

Section: Identification Of Key Habitats For R Hipposideros Populatiosupporting

confidence: 88%

“…Inf. B) according to previous knowledge gathered at the individual level on lesser horseshoe bat's ecology (Bontadina et al, 2002;Tournant et al, 2013), namely: broadleaved woodland, coniferous woodland, artificial area, water bodies, cropland, and open land (other than crops and artificial). For each buffer we calculated six FRAGSTATS metrics (McGarigal and Marks, 1995) describing the composition and the configuration of the landscape pattern: the proportion of the landscape occupied by each class (%LAND), the mean SHAPE index (MSI) of each class, the Simpson's diversity index (SIDI), the Shannon's diversity index (SHDI), the Shannon's evenness index (SHEI) and the mean patch size (MPS).…”

Section: Assessment Of the Effect Of Landscape Variables On Bat Populmentioning

confidence: 99%

“…The lesser horseshoe bat, Rhinolophus hipposideros, has undergone a massive decline in the northern part of its distribution range during the last century for reasons that are still not fully understood, although pesticides use, decline in insect prey, and habitat destruction were suspected causes (Bontadina et al, 2000). This stressed the need for a better understanding of its habitat requirement, leading to numerous telemetry studies (e.g Bontadina et al, 2002;Downs et al, 2016;Reiter et al, 2013;Schofield, 1996) and, more recently, to larger scale presence/absence studies (Le Roux et al, 2017;Tournant et al, 2013). These studies mainly focused on habitat selection by females during the crucial period of parturition, during which they gather in maternity colonies.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Population-level sensitivity to landscape variables reflects individual-based habitat selection in a woodland bat species

Jan

Zarzoso-Lacoste

Fourcy

et al. 2019

Preprint

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Understanding the relationship between habitat quality and population dynamics is fundamental for long-term management and range predictions in ecology. However, habitat suitability is generally only investigated at the individual scale, as it is the case for the lesser horseshoe bat (Rhinolophus hipposideros), a species of conservation concern. Using a statistical modelling approach and census data of 94 lesser horseshoe bat colonies located in Brittany (France), we analysed the effect of landscape composition and configuration on the demography of surveyed maternity colonies (i.e. colony size, fecundity and growth rate), and compared our result to those provided by individual-based studies. Our results validated that the landscape in a 500meter buffer around colonies (core foraging area) is crucial for population size and dynamics, and confirmed the positive influence of broadleaved woodland proportion on bat colony size. We revealed a positive effect of lakeshores and riverbanks on colony size and growth rate, underlying the importance of these habitats for the long-term conservation of this non-migratory forest species. Importantly, our results refine previous knowledge concerning the threat posed by the intensification of human activities (e.g. urbanization, agriculture, habitat fragmentation), and highlight the negative effect of large and regular patches of artificial and crop lands and of open land patches shape complexity on all demographic variables investigated. Finally, by confirming and specifying the conclusions of previous individual level studies about lesser horseshoe bats' habitat selection and quality requirements, our results support the dependence of population dynamics and associated conservation management to individual behaviour and sensitivity.

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Section: Identification Of Key Habitats For R Hipposideros Populatiosupporting

confidence: 88%

Section: Assessment Of the Effect Of Landscape Variables On Bat Populmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Population-level sensitivity to landscape variables reflects individual-based habitat selection in a woodland bat species

Jan

Zarzoso-Lacoste

Fourcy

et al. 2019

Preprint

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“…Despite a growing and valuable interest for connectivity in bat conservation, to our knowledge all but one (Hale et al, 2015) of the studies focusing on connectivity modelling (for bat species) estimated a landscape resistance based on expert insight or from Species Distribution Modelling outputs (Henry, Pons, & Cosson, 2007;Le Roux et al, 2017;Razgour, 2015;Roscioni et al, 2014;Tournant, Afonso, Roué, Giraudoux, & Foltête, 2013). The "gapcrossing" framework adopted in our study could be largely used for other species or sites to obtain an empirical measure of parameters affecting movement resistance.…”

Section: Discussionmentioning

confidence: 99%

Modelling landscape connectivity for greater horseshoe bat using an empirical quantification of resistance

Pinaud

Claireau

Leuchtmann

et al. 2018

Journal of Applied Ecology

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Habitat fragmentation and isolation as a result of human activities have been recognized as great threats to population viability. Evaluating landscape connectivity in order to identify and protect linkages has therefore become a key challenge in applied ecology and conservation. One useful approach to evaluate connectivity is least‐cost path (LCP) analysis. However, several studies have highlighted importance of parameterization with empirical, biologically relevant proxies of factors affecting movements as well as the need to validate the LCP model with an independent dataset. We used LCP analysis incorporating quantitative, empirical data about behaviour of the greater horseshoe bat Rhinolophus ferrumequinum to build up a model of functional connectivity in relation to landscape connecting features. We then validated the accumulated costs surface from the LCP model with two independent datasets; one at an individual level with radiotracking data and one at a population level with acoustic data. When defining resistance, we found that the probability of bat presence in a hedgerow is higher when the distance between hedgerows is below 38 m, and decrease rapidly when gaps are larger than 50 m. The LCP model was validated by both datasets: the independent acoustic data showed that the probability of bat presence was significantly higher in areas with lower accumulated costs, and the radiotracking data showed that foraging was more likely in areas where accumulated costs were significantly lower. Synthesis and applications. Through our modelling approach, we recommend a maximum of 38 m (and no more than 50 m) between connecting features around colonies of greater horseshoe bats. Our quantitative study highlights the value of this framework for conservation: results are directly applicable in the field and the framework can be applied to other species sensitive to habitat loss, including other bats. Provided that it is parameterized with empirical, biologically relevant data, this modelling approach can be used for restoring and evaluating green networks in agri‐environmental schemes and management plans.

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“…Species locations or favourable habitat patches often represent the nodes of the network and the connections between nodes are determined by underlying resistance surfaces, based on ecological assumptions about the move-ments of the species within the landscape (Tournant et al 2013). Due to limited information regarding factors affecting animal movement and dispersal, SDMs are increasingly and successfully used to develop resistance surfaces (Wang et al 2008, Milanesi et al 2016a and attention recently shifted from ecological corridor identification amongst species locations to independent node-based models (Koen et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Patterns of distribution and landscape connectivity of the stag beetle in a human-dominated landscape

Rocca¹,

Bogliani²,

Milanesi³

2017

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Urbanisation and the spread of agriculture have resulted in high levels of forest loss, habitat fragmentation and degradation in many regions of the world. In Italy, the Po Plain is the most human-dominated landscape of the country and, after decades of exploitation, old-growth forests have been reduced to small and isolated patches, often threatened by invasive tree species such as the black locust (Robinia pseudoacacia). In these habitats, the occurrence of many forest-dependent species is related to the quality and availability of suitable areas, as well as the connectivity between the remaining forested patches.Thus, recently developed species distribution models have been applied, namely the Ensemble of Small Models (ESMs), to identify areas of occurrence for a rare and protected saproxylic beetle species, the stag beetle Lucanus cervus and the inverse of the resulting distribution maps as resistance maps have been used to estimate landscape connectivity for this species.Response curves suggested that the probability of the stag beetle occurrence increased with habitat diversity, grassland coverage and native forests, especially oak and mixed forests. The other forest coverage, such as those with black locust, beech, chestnut and black cherry, showed a unimodal relationship peaking approximately at 70%, 8%, 55% and 13% respectively. The stag beetle occurrence was unimodal related to distance to watercourses and distance to human settlements and negatively related to shrub-lands, croplands, sparse and dense human settlements. Landscape connectivity showed similar patterns, except for oak forest coverage, which showed a negative relationship to landscape connectivity.In conclusion, stag beetles can persist in a human dominated landscape only in the presence of forest patches, including those with black locust trees. It is also inferred that ESMs may be suitable for modelling rare species distributions and estimating landscape connectivity to promote species conservation.

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Evaluating the effect of habitat connectivity on the distribution of lesser horseshoe bat maternity roosts using landscape graphs

Cited by 50 publications

References 40 publications

Population-level sensitivity to landscape variables reflects individual-based habitat selection in a woodland bat species

Population-level sensitivity to landscape variables reflects individual-based habitat selection in a woodland bat species

Modelling landscape connectivity for greater horseshoe bat using an empirical quantification of resistance

Patterns of distribution and landscape connectivity of the stag beetle in a human-dominated landscape

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