Disentangling the relative effect of light pollution, impervious surfaces and intensive agriculture on bat activity with a national-scale monitoring program

Azam, Clémentine; Viol, Isabelle Le; Julien, Jean‐François; Bas, Yves; Kerbiriou, Christian

doi:10.1007/s10980-016-0417-3

Cited by 85 publications

(86 citation statements)

References 73 publications

(84 reference statements)

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“…We used an acoustic dataset collected previously to study the effect of wind turbines on bat activity (Barré et al., ) because it was based on a random sampling design with high variability and no confounding effects in terms of environmental variables (Figure S1). The following environmental variables are known as good predictors of bat activity: type of site that is, hedgerow versus open area habitat located at an average of 86 m ( SD : 70 m) away from any hedgerow (Lacoeuilhe, Machon, Julien, & Kerbiriou, ; Verboom & Huitema, ), the distance in meters to a forest ( M = 700, SD = 506; Boughey, Lake, Haysom, & Dolman, ; Frey‐Ehrenbold, Bontadina, Arlettaz, & Obrist, ), the distance to an urban area ( M = 335, SD = 170; Azam, Le Viol, Julien, Bas, & Kerbiriou, ), the distance to a wetland ( M = 579, SD = 363; Sirami, Jacobs, & Cumming, ; Santos, Rodrigues, Jones, & Rebelo, ) and the total length of hedgerows in meters within a 1,000 m radius ( M = 3,439, SD = 1,622; Verboom & Huitema, ; Lacoeuilhe et al., ). The latter four variables presented important environmental variability, and a similar gradient between sites located close to hedgerows and those in open areas (Figure S1).…”

Section: Methodsmentioning

confidence: 99%

Accounting for automated identification errors in acoustic surveys

et al. 2019

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Assessing the state and trend of biodiversity in the face of anthropogenic threats requires large‐scale and long‐time monitoring, for which new recording methods offer interesting possibilities. Reduced costs and a huge increase in storage capacity of acoustic recorders have resulted in an exponential use of passive acoustic monitoring (PAM) on a wide range of animal groups in recent years. PAM has led to a rapid growth in the quantity of acoustic data, making manual identification increasingly time‐consuming. Therefore, software detecting sound events, extracting numerous features and automatically identifying species have been developed. However, automated identification generates identification errors, which could influence analyses which look at the ecological response of species. Taking the case of bats for which PAM constitutes an efficient tool, we propose a cautious method to account for errors in acoustic identifications of any taxa without excessive manual checking of recordings. We propose to check a representative sample of the outputs of a software commonly used in acoustic surveys (Tadarida), to model the identification success probability of 10 species and two species groups as a function of the confidence score provided for each automated identification. Using this relationship, we then investigated the effect of setting different false positive tolerances (FPTs), from a 50% to 10% false positive rate, above which data are discarded, by repeating a large‐scale analysis of bat response to environmental variables and checking for consistency in the results. Considering estimates, standard errors and significance of species response to environmental variables, the main changes occurred between the naive (i.e. raw data) and robust analyses (i.e. using FPTs). Responses were highly stable between FPTs. We conclude it was essential to, at least, remove data above 50% FPT to minimize false positives. We recommend systematically checking the consistency of responses for at least two contrasting FPTs (e.g. 50% and 10%), in order to ensure robustness, and only going on to conclusive interpretation when these are consistent. This study provides a huge saving of time for manual checking, which will facilitate the improvement in large‐scale monitoring, and ultimately our understanding of ecological responses.

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Section: Methodsmentioning

confidence: 99%

Accounting for automated identification errors in acoustic surveys

et al. 2019

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“…In the study area, population density is 52.6 inhabitants per km 2 , mainly located in small villages or isolated farms where artificial lighting at night is scarce or absent. The effect of artificial lighting on connectivity (Azam, Le Viol, Julien, Bas, & Kerbiriou, ; Hale et al., ) was thus not taken into account in this study.…”

Section: Methodsmentioning

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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“…Interestingly, the size of colonies was better predicted by the amount of artificial light at night (ALAN) than the proportion of urban area. This finding may arise from the fact that ALAN within landscapes is not systematically restricted to urban areas and may affect the adjacent habitats, thus reducing the foraging areas available for bats (Threlfall et al 2013;Azam et al 2016). Furthermore, ALAN-which could also be related to road densitymay act as a barrier to movement by altering gap crossing behaviour (Hale et al 2015).…”

Section: Landscape Characteristics Affect Colony Size At Different Spmentioning

confidence: 99%

Factors driving population recovery of the greater horseshoe bat (Rhinolophus ferrumequinum) in the UK: implications for conservation

et al. 2017

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Although populations of many bat species appear to be recovering in some European countries, the extrinsic and intrinsic factors driving these increases have not yet been assessed. Disentangling the benefits of conservation management from other factors such as climate change is a crucial step for improving evidence-based conservation strategies. We used the greater horseshoe bat (Rhinolophus ferrumequinum) as a case study for understanding the recovery of bat populations, as its north-western populations have increased substantially over the past two decades following severe population declines. Using summer roost count data from the UK National Bat Monitoring Programme spanning an 18 year period from 1997 to 2014, we investigated the effects of (i) landscape characteristics associated with the implementation of the agri-environment schemes on colony trends and size, and (ii) meteorological variables on annual colony growth rate. We also assessed the relationship between colony size and colony growth to investigate intrinsic factors such as an Allee effect. Our results indicated that colony size was positively related to a range of landscape features (e.g. amount of broadleaf woodland and grassland, and density of linear features) surrounding the roost, while the amount of artificial light at night had a significant negative effect. Spring temperatures and precipitation (the latter with a lag of one year) were associated with annual colony growth. We also identified a negative density-dependence effect within colonies. Though the conservation of essential landscape elements may have contributed to population increases in the long-term, we conclude that recent population recovery has also been driven by climate Communicated by Dirk Sven Schmeller.Electronic supplementary material The online version of this article (doi:10.1007/s10531-017-1320-1) contains supplementary material, which is available to authorized users. change. Finally we recommend that the conservation of photophobic bat species such as R. ferrumequinum should focus on both the improvement of foraging/commuting habitats and the creation of dark areas.

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Disentangling the relative effect of light pollution, impervious surfaces and intensive agriculture on bat activity with a national-scale monitoring program

Cited by 85 publications

References 73 publications

Accounting for automated identification errors in acoustic surveys

Accounting for automated identification errors in acoustic surveys

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

Factors driving population recovery of the greater horseshoe bat (Rhinolophus ferrumequinum) in the UK: implications for conservation

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