Watling, J. I. et al. Support for the habitat amount hypothesis from a global synthesis of species density studies. Ecol. Lett. 23, 674–681 (2020).
Google Scholar
Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).
Google Scholar
Hanski, I. Metapopulation dynamics. Nature 396, 41–49 (1998).
Google Scholar
Ćosović, M., Bugalho, M. N., Thom, D. & Borges, J. G. Stand structural characteristics are the most practical biodiversity indicators for forest management planning in Europe. Forests 11, 343 (2020).
Google Scholar
Bouvet, A. et al. Effects of forest structure, management and landscape on bird and bat communities. Environ. Conserv. 43, 148–160 (2016).
Google Scholar
Froidevaux, J. S., Zellweger, F., Bollmann, K., Jones, G. & Obrist, M. K. From field surveys to LiDAR: shining a light on how bats respond to forest structure. Remote Sens. Environ. 175, 242–250 (2016).
Google Scholar
Fuentes-Montemayor, E. et al. Species mobility and landscape context determine the importance of local and landscape-level attributes. Ecol. Appl. 27, 1541–1554 (2017).
Google Scholar
Jung, K., Kaiser, S., Böhm, S., Nieschulze, J. & Kalko, E. K. Moving in three dimensions: effects of structural complexity on occurrence and activity of insectivorous bats in managed forest stands. J. Appl. Ecol. 49, 523–531 (2012).
Google Scholar
Langridge, J., Pisanu, B., Laguet, S., Archaux, F. & Tillon, L. The role of complex vegetation structures in determining hawking bat activity in temperate forests. For. Ecol. Manag. 448, 559–571 (2019).
Google Scholar
Müller, J. et al. From ground to above canopy—Bat activity in mature forests is driven by vegetation density and height. For. Ecol. Manag. 306, 179–184 (2013).
Google Scholar
Renner, S. C. et al. Divergent response to forest structure of two mobile vertebrate groups. For. Ecol. Manag. 415, 129–138 (2018).
Google Scholar
Fuentes-Montemayor, E., Goulson, D., Cavin, L., Wallace, J. M. & Park, K. J. Fragmented woodlands in agricultural landscapes: the influence of woodland character and landscape context on bats and their insect prey. Agr. Ecosyst. Environ. 172, 6–15 (2013).
Google Scholar
Rachwald, A., Boratyński, J. S., Krawczyk, J., Szurlej, M. & Nowakowski, W. K. Natural and anthropogenic factors influencing the bat community in commercial tree stands in a temperate lowland forest of natural origin (Białowieża Forest). For. Ecol. Manag. 479, 118544 (2021).
Google Scholar
Alder, D., Poore, A., Norrey, J., Newson, S. & Marsden, S. Irregular silviculture positively influences multiple bat species in a lowland temperate broadleaf woodland. For. Ecol. Manag. 118786, 1613 (2020).
Carr, A., Zeale, M. R., Weatherall, A., Froidevaux, J. S. & Jones, G. Ground-based and LiDAR-derived measurements reveal scale-dependent selection of roost characteristics by the rare tree-dwelling bat Barbastella barbastellus. For. Ecol. Manag. 417, 237–246 (2018).
Google Scholar
Kortmann, M. et al. Beauty and the beast: how a bat utilizes forests shaped by outbreaks of an insect pest. Anim. Conserv. 21, 21–30 (2018).
Google Scholar
Ruczyński, I., Nicholls, B., MacLeod, C. & Racey, P. Selection of roosting habitats by Nyctalus noctula and Nyctalus leisleri in Białowieża Forest—adaptive response to forest management?. For. Ecol. Manag. 259, 1633–1641 (2010).
Google Scholar
Ober, H. K. & Hayes, J. P. Influence of forest riparian vegetation on abundance and biomass of nocturnal flying insects. For. Ecol. Manag. 256, 1124–1132 (2008).
Google Scholar
Russo, D. et al. Identifying key research objectives to make European forests greener for bats. Front. Ecol. Evol. 4, 87 (2016).
Google Scholar
Kaňuch, P. et al. Relating bat species presence to habitat features in natural forests of Slovakia (Central Europe). Mamm. Biol. 73, 147–155 (2008).
Google Scholar
Kirkpatrick, L. et al. Bat use of commercial coniferous plantations at multiple spatial scales: management and conservation implications. Biol. Cons. 206, 1–10 (2017).
Google Scholar
Vasko, V. et al. Within-season changes in habitat use of forest-dwelling boreal bats. Ecol. Evol. 10, 4164–4174 (2020).
Google Scholar
Węgiel, A. et al. The foraging activity of bats in managed pine forests of different ages. Eur. J. Forest Res. 138, 383–396 (2019).
Google Scholar
Bender, M. J., Castleberry, S. B., Miller, D. A. & Wigley, T. B. Site occupancy of foraging bats on landscapes of managed pine forest. For. Ecol. Manag. 336, 1–10 (2015).
Google Scholar
Apoznański, G. et al. Use of coniferous plantations by bats in western Poland during summer. Balt. For. 26, 232 (2020).
Google Scholar
Buchholz, S., Kelm, V. & Ghanem, S. J. Mono-specific forest plantations are valuable bat habitats: implications for wind energy development. Eur. J. Wildl. Res. 67, 1–12 (2021).
Google Scholar
Charbonnier, Y. et al. Deciduous trees increase bat diversity at stand and landscape scales in mosaic pine plantations. Landscape Ecol. 31, 291–300 (2016).
Google Scholar
Arroyo‐Rodríguez, V. et al. Designing optimal human‐modified landscapes for forest biodiversity conservation. Ecol. Lett. In Press. (2020).
Dunning, J. B., Danielson, B. J. & Pulliam, H. R. Ecological processes that affect populations in complex landscapes. Oikos 15, 169–175 (1992).
Google Scholar
Hatfield, J. H. et al. Mediation of area and edge effects in forest fragments by adjacent land use. Conserv. Biol. 34, 395–404 (2020).
Google Scholar
Barbaro, L. et al. Biotic predictors complement models of bat and bird responses to climate and tree diversity in European forests. Proc. R. Soc. B 286, 20182193 (2019).
Google Scholar
Ethier, K. & Fahrig, L. Positive effects of forest fragmentation, independent of forest amount, on bat abundance in eastern Ontario, Canada. Landsc. Ecol. 26, 865–876 (2011).
Google Scholar
Rodríguez-San Pedro, A. & Simonetti, J. A. The relative influence of forest loss and fragmentation on insectivorous bats: does the type of matrix matter?. Landsc. Ecol. 30, 1561–1572 (2015).
Google Scholar
Charbonnier, Y. M. et al. Bat and bird diversity along independent gradients of latitude and tree composition in European forests. Oecologia 182, 529–537 (2016).
Google Scholar
Dietz, C., Nill, D. & von Helversen, O. Bats of Britain, Europe and Northwest Africa. (A & C Black, 2009).
Law, B., Park, K. J. & Lacki, M. J. in Bats in the Anthropocene: conservation of bats in a changing world (eds Christian C Voigt & T Kingston) 105–150 (Springer, 2016).
Carr, A., Weatherall, A. & Jones, G. The effects of thinning management on bats and their insect prey in temperate broadleaved woodland. For. Ecol. Manag. 457, 117682 (2020).
Google Scholar
Müller, J. et al. Aggregative response in bats: prey abundance versus habitat. Oecologia 169, 673–684 (2012).
Google Scholar
Ware, R. L., Garrod, B., Macdonald, H. & Allaby, R. G. Guano morphology has the potential to inform conservation strategies in British bats. PLoS ONE 15, e0230865 (2020).
Google Scholar
Kirkpatrick, L., Bailey, S. & Park, K. J. Negative impacts of felling in exotic spruce plantations on moth diversity mitigated by remnants of deciduous tree cover. For. Ecol. Manag. 404, 306–315 (2017).
Google Scholar
Fuentes-Montemayor, E., Goulson, D., Cavin, L., Wallace, J. M. & Park, K. J. Factors influencing moth assemblages in woodland fragments on farmland: implications for woodland management and creation schemes. Biol. Cons. 153, 265–275 (2012).
Google Scholar
Rainho, A., Augusto, A. M. & Palmeirim, J. M. Influence of vegetation clutter on the capacity of ground foraging bats to capture prey. J. Appl. Ecol. 47, 850–858 (2010).
Google Scholar
Blakey, R. V., Law, B. S., Kingsford, R. T. & Stoklosa, J. Terrestrial laser scanning reveals below-canopy bat trait relationships with forest structure. Remote Sens. Environ. 198, 40–51 (2017).
Google Scholar
Laforge, A. et al. Landscape composition and life-history traits influence bat movement and space use: analysis of 30 years of published telemetry data. (Submitted).
Tews, J. et al. Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures. J. Biogeogr. 31, 79–92 (2004).
Google Scholar
Summerville, K. S. & Crist, T. O. Contrasting effects of habitat quantity and quality on moth communities in fragmented landscapes. Ecography 27, 3–12 (2004).
Google Scholar
Vinet, O., Sane, F. & Chaigne, A. Radiopistage de la barbastelle (Barbastella barbastellus) en forêt domaniale de l’Aigoual. (Nimes, France, 2013).
Obrist, M. K. et al. Response of bat species to sylvo-pastoral abandonment. For. Ecol. Manag. 261, 789–798 (2011).
Google Scholar
Norberg, U. M. & Rayner, J. M. Ecological morphology and flight in bats (Mammalia; Chiroptera): wing adaptations, flight performance, foraging strategy and echolocation. Philos. Trans. R. Soc. Lond. B Biol. Sci. 316, 335–427 (1987).
Google Scholar
Swift, S. & Racey, P. Gleaning as a foraging strategy in Natterer’s bat Myotis nattereri. Behav. Ecol. Sociobiol. 52, 408–416 (2002).
Google Scholar
Brigham, R., Grindal, S., Firman, M. & Morissette, J. The influence of structural clutter on activity patterns of insectivorous bats. Can. J. Zool. 75, 131–136 (1997).
Google Scholar
Bender, M. J., Perea, S., Castleberry, S. B., Miller, D. A. & Wigley, T. B. Influence of insect abundance and vegetation structure on site-occupancy of bats in managed pine forests. For. Ecol. Manag. 482, 118839 (2021).
Google Scholar
Ancillotto, L. et al. The importance of non-forest landscapes for the conservation of forest bats: lessons from barbastelles (Barbastella barbastellus). Biodivers. Conserv. 24, 171–185 (2015).
Google Scholar
Plank, M., Fiedler, K. & Reiter, G. Use of forest strata by bats in temperate forests. J. Zool. 286, 154–162 (2012).
Google Scholar
Kusch, J., Weber, C., Idelberger, S. & Koob, T. Foraging habitat preferences of bats in relation to food supply and spatial vegetation structures in a western European low mountain range forest. Folia Zool. 53, 113–128 (2004).
Siemers, B. M. & Schnitzler, H.-U. Natterer’s bat (Myotis nattereri Kuhl, 1818) hawks for prey close to vegetation using echolocation signals of very broad bandwidth. Behav. Ecol. Sociobiol. 47, 400–412 (2000).
Google Scholar
Arrizabalaga-Escudero, A. et al. Trophic requirements beyond foraging habitats: the importance of prey source habitats in bat conservation. Biol. Conserv. 191, 512–519 (2015).
Google Scholar
Carr, A. et al. Moths consumed by the Barbastelle Barbastella barbastellus require larval host plants that occur within the bat’s foraging habitats. Acta Chiropterologica 22, 257–269 (2021).
van der Plas, F. et al. Continental mapping of forest ecosystem functions reveals a high but unrealised potential for forest multifunctionality. Ecol. Lett. 21, 31–42 (2018).
Google Scholar
Lindenmayer, D., Franklin, J. & Fischer, J. General management principles and a checklist of strategies to guide forest biodiversity conservation. Biol. Conserv. 131, 433–445 (2006).
Google Scholar
Wolters, V., Bengtsson, J. & Zaitsev, A. S. Relationship among the species richness of different taxa. Ecology 87, 1886–1895 (2006).
Google Scholar
Larrieu, L. et al. Cost-efficiency of cross-taxon surrogates in temperate forests. Ecol. Ind. 87, 56–65 (2018).
Google Scholar
Westgate, M. J., Tulloch, A. I., Barton, P. S., Pierson, J. C. & Lindenmayer, D. B. Optimal taxonomic groups for biodiversity assessment: a meta-analytic approach. Ecography 40, 539–548 (2017).
Google Scholar
Larrieu, L. et al. Assessing the potential of routine stand variables from multi-taxon data as habitat surrogates in European temperate forests. Ecol. Ind. 104, 116–126 (2019).
Google Scholar
Bitterlich, W. The relascope idea. Relative measurements in forestry. Farnham Royal: Commonwealth Agricultural Bureaux, Slough. (1984).
Bachelot, B. Sky: canopy openness analyzer package. R package version 1.0. https://cran.r-project.org/web/packages/Sky/index.html. (2016).
R Development Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. (2019).
Blondel, J. & Cuvillier, R. Une méthode simple et rapide pour décrire les habitats d’oiseaux: le stratiscope. Oikos 29, 326–331 (1977).
Google Scholar
Hesselbarth, M. H., Sciaini, M., With, K. A., Wiegand, K. & Nowosad, J. landscapemetrics: an open-source R tool to calculate landscape metrics. Ecography 42, 1648–1657 (2019).
Google Scholar
Froidevaux, J. S., Zellweger, F., Bollmann, K. & Obrist, M. K. Optimizing passive acoustic sampling of bats in forests. Ecol. Evol. 4, 4690–4700 (2014).
Google Scholar
Bas, Y., Bas, D. & Julien, J.-F. Tadarida: a toolbox for animal detection on acoustic recordings. J. Open Res. Softw. 5, 6 (2017).
Google Scholar
Barré, K. et al. Accounting for automated identification errors in acoustic surveys. Methods Ecol. Evol. 10, 1171–1188 (2019).
Google Scholar
Russo, D., Ancillotto, L. & Jones, G. Bats are still not birds in the digital era: echolocation call variation and why it matters for bat species identification. Can. J. Zool. 96, 63–78 (2018).
Google Scholar
Obrist, M. K., Boesch, R. & Flückiger, P. F. Variability in echolocation call design of 26 Swiss bat species: consequences, limits and options for automated field identification with a synergetic pattern recognition approach. Mammalia 68, 307–322 (2004).
Google Scholar
Barataud, M. Acoustic ecology of european bats: species identification, study of their habitats and foraging behaviour. Paris: Muséum national d’Histoire naturelle & Mèze: Biotope (Inventaires & biodiversité) 352, 115 (2015).
Truxa, C. & Fiedler, K. Attraction to light-from how far do moths (Lepidoptera) return to weak artificial sources of light?. Eur. J. Entomol. 109, 1053 (2012).
Google Scholar
Froidevaux, J. S., Fialas, P. C. & Jones, G. Catching insects while recording bats: impacts of light trapping on acoustic sampling. Remote Sens. Ecol. Conserv. 4, 240–247 (2018).
Google Scholar
Andreas, M., Reiter, A., Cepáková, E. & Uhrin, M. Body size as an important factor determining trophic niche partitioning in three syntopic rhinolophid bat species. Biologia 68, 170–175 (2013).
Google Scholar
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R J. 9, 378–400 (2017).
Google Scholar
Burnham, K. P. & Anderson, D. R. A practical information-theoretic approach. Model Sel. Multimodel Inference 2, 15 (2002).
Google Scholar
Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).
Google Scholar
Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.3.2.0. https://cran.r-project.org/web/packages/DHARMa/index.html. (2017).
Mazerolle, M. J. AICcmodavg. R package version 2.3-1. https://cran.r-project.org/web/packages/AICcmodavg/index.html. (2020).
Grueber, C., Nakagawa, S., Laws, R. & Jamieson, I. Multimodel inference in ecology and evolution: challenges and solutions. J. Evol. Biol. 24, 699–711 (2011).
Google Scholar
Nakagawa, S. & Cuthill, I. C. Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol. Rev. 82, 591–605 (2007).
Google Scholar
Arnold, T. W. Uninformative parameters and model selection using Akaike’s Information Criterion. J. Wildl. Manag. 74, 1175–1178 (2010).
Google Scholar
Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.5.0. https://cran.r-project.org/web/packages/emmeans/index.html. (2020).
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