1.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).PubMed
Article
PubMed Central
Google Scholar
2.Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).ADS
CAS
PubMed
PubMed Central
Article
Google Scholar
3.Hanski, I. Metapopulation dynamics. Nature 396, 41–49 (1998).ADS
CAS
Article
Google Scholar
4.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).Article
Google Scholar
5.Bouvet, A. et al. Effects of forest structure, management and landscape on bird and bat communities. Environ. Conserv. 43, 148–160 (2016).Article
Google Scholar
6.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).ADS
Article
Google Scholar
7.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).PubMed
Article
PubMed Central
Google Scholar
8.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).Article
Google Scholar
9.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).Article
Google Scholar
10.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).Article
Google Scholar
11.Renner, S. C. et al. Divergent response to forest structure of two mobile vertebrate groups. For. Ecol. Manag. 415, 129–138 (2018).Article
Google Scholar
12.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).Article
Google Scholar
13.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).Article
Google Scholar
14.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).
Google Scholar
15.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).Article
Google Scholar
16.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).Article
Google Scholar
17.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).Article
Google Scholar
18.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).Article
Google Scholar
19.Russo, D. et al. Identifying key research objectives to make European forests greener for bats. Front. Ecol. Evol. 4, 87 (2016).Article
Google Scholar
20.Kaňuch, P. et al. Relating bat species presence to habitat features in natural forests of Slovakia (Central Europe). Mamm. Biol. 73, 147–155 (2008).Article
Google Scholar
21.Kirkpatrick, L. et al. Bat use of commercial coniferous plantations at multiple spatial scales: management and conservation implications. Biol. Cons. 206, 1–10 (2017).Article
Google Scholar
22.Vasko, V. et al. Within-season changes in habitat use of forest-dwelling boreal bats. Ecol. Evol. 10, 4164–4174 (2020).PubMed
PubMed Central
Article
Google Scholar
23.Węgiel, A. et al. The foraging activity of bats in managed pine forests of different ages. Eur. J. Forest Res. 138, 383–396 (2019).Article
Google Scholar
24.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).Article
Google Scholar
25.Apoznański, G. et al. Use of coniferous plantations by bats in western Poland during summer. Balt. For. 26, 232 (2020).Article
Google Scholar
26.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).Article
Google Scholar
27.Charbonnier, Y. et al. Deciduous trees increase bat diversity at stand and landscape scales in mosaic pine plantations. Landscape Ecol. 31, 291–300 (2016).Article
Google Scholar
28.Arroyo‐Rodríguez, V. et al. Designing optimal human‐modified landscapes for forest biodiversity conservation. Ecol. Lett. In Press. (2020).29.Dunning, J. B., Danielson, B. J. & Pulliam, H. R. Ecological processes that affect populations in complex landscapes. Oikos 15, 169–175 (1992).Article
Google Scholar
30.Hatfield, J. H. et al. Mediation of area and edge effects in forest fragments by adjacent land use. Conserv. Biol. 34, 395–404 (2020).PubMed
Article
PubMed Central
Google Scholar
31.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).PubMed
Article
PubMed Central
Google Scholar
32.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).Article
Google Scholar
33.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).Article
Google Scholar
34.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).ADS
PubMed
Article
Google Scholar
35.Dietz, C., Nill, D. & von Helversen, O. Bats of Britain, Europe and Northwest Africa. (A & C Black, 2009).36.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).37.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).Article
Google Scholar
38.Müller, J. et al. Aggregative response in bats: prey abundance versus habitat. Oecologia 169, 673–684 (2012).ADS
PubMed
Article
PubMed Central
Google Scholar
39.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).CAS
PubMed
PubMed Central
Article
Google Scholar
40.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).Article
Google Scholar
41.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).Article
Google Scholar
42.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).Article
Google Scholar
43.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).ADS
Article
Google Scholar
44.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).45.Tews, J. et al. Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures. J. Biogeogr. 31, 79–92 (2004).Article
Google Scholar
46.Summerville, K. S. & Crist, T. O. Contrasting effects of habitat quantity and quality on moth communities in fragmented landscapes. Ecography 27, 3–12 (2004).Article
Google Scholar
47.Vinet, O., Sane, F. & Chaigne, A. Radiopistage de la barbastelle (Barbastella barbastellus) en forêt domaniale de l’Aigoual. (Nimes, France, 2013).
48.Obrist, M. K. et al. Response of bat species to sylvo-pastoral abandonment. For. Ecol. Manag. 261, 789–798 (2011).Article
Google Scholar
49.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).ADS
Article
Google Scholar
50.Swift, S. & Racey, P. Gleaning as a foraging strategy in Natterer’s bat Myotis nattereri. Behav. Ecol. Sociobiol. 52, 408–416 (2002).Article
Google Scholar
51.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).Article
Google Scholar
52.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).Article
Google Scholar
53.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).Article
Google Scholar
54.Plank, M., Fiedler, K. & Reiter, G. Use of forest strata by bats in temperate forests. J. Zool. 286, 154–162 (2012).Article
Google Scholar
55.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).
Google Scholar
56.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).Article
Google Scholar
57.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).Article
Google Scholar
58.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).
Google Scholar
59.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).PubMed
Article
PubMed Central
Google Scholar
60.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).Article
Google Scholar
61.Wolters, V., Bengtsson, J. & Zaitsev, A. S. Relationship among the species richness of different taxa. Ecology 87, 1886–1895 (2006).PubMed
Article
PubMed Central
Google Scholar
62.Larrieu, L. et al. Cost-efficiency of cross-taxon surrogates in temperate forests. Ecol. Ind. 87, 56–65 (2018).Article
Google Scholar
63.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).Article
Google Scholar
64.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).Article
Google Scholar
65.Bitterlich, W. The relascope idea. Relative measurements in forestry. Farnham Royal: Commonwealth Agricultural Bureaux, Slough. (1984).
66.Bachelot, B. Sky: canopy openness analyzer package. R package version 1.0. https://cran.r-project.org/web/packages/Sky/index.html. (2016).67.R Development Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. (2019).68.Blondel, J. & Cuvillier, R. Une méthode simple et rapide pour décrire les habitats d’oiseaux: le stratiscope. Oikos 29, 326–331 (1977).Article
Google Scholar
69.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).Article
Google Scholar
70.Froidevaux, J. S., Zellweger, F., Bollmann, K. & Obrist, M. K. Optimizing passive acoustic sampling of bats in forests. Ecol. Evol. 4, 4690–4700 (2014).PubMed
PubMed Central
Article
Google Scholar
71.Bas, Y., Bas, D. & Julien, J.-F. Tadarida: a toolbox for animal detection on acoustic recordings. J. Open Res. Softw. 5, 6 (2017).Article
Google Scholar
72.Barré, K. et al. Accounting for automated identification errors in acoustic surveys. Methods Ecol. Evol. 10, 1171–1188 (2019).Article
Google Scholar
73.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).Article
Google Scholar
74.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).Article
Google Scholar
75.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).
Google Scholar
76.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).Article
Google Scholar
77.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).Article
Google Scholar
78.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).Article
Google Scholar
79.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).Article
Google Scholar
80.Burnham, K. P. & Anderson, D. R. A practical information-theoretic approach. Model Sel. Multimodel Inference 2, 15 (2002).MATH
Google Scholar
81.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).Article
Google Scholar
82.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).83.Mazerolle, M. J. AICcmodavg. R package version 2.3-1. https://cran.r-project.org/web/packages/AICcmodavg/index.html. (2020).84.Grueber, C., Nakagawa, S., Laws, R. & Jamieson, I. Multimodel inference in ecology and evolution: challenges and solutions. J. Evol. Biol. 24, 699–711 (2011).CAS
PubMed
Article
PubMed Central
Google Scholar
85.Nakagawa, S. & Cuthill, I. C. Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol. Rev. 82, 591–605 (2007).PubMed
Article
PubMed Central
Google Scholar
86.Arnold, T. W. Uninformative parameters and model selection using Akaike’s Information Criterion. J. Wildl. Manag. 74, 1175–1178 (2010).Article
Google Scholar
87.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). More