Epigean and hypogean drivers of Neotropical subterranean communities

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<p>Journal of Biogeography. 2020;00:1–14. wileyonlinelibrary.com/journal/jbi  |  1© 2020 John Wiley & Sons Ltd</p><p>Received: 11 September 2019  |  Revised: 29 September 2020  |  Accepted: 29 October 2020</p><p>DOI: 10.1111/jbi.14031</p><p>R E S E A R C H P A P E R</p><p>Epigean and hypogean drivers of Neotropical subterranean</p><p>communities</p><p>Lucas Mendes Rabelo1,2  | Marconi Souza-Silva1,2,3  | Rodrigo Lopes Ferreira1,2</p><p>Handiling Editor: Jani Heino</p><p>1Programa de Pós-graduação em Ecologia</p><p>Aplicada - Universidade Federal de Lavras,</p><p>Lavras, Brazil</p><p>2Centro de Estudos em Biologia</p><p>Subterrânea, Setor de biodiversidade</p><p>Subterrânea, Departamento de Ecologia e</p><p>Conservação, Instituto de Ciências Naturais,</p><p>Universidade Federal de Lavras, Lavras,</p><p>Minas Gerais, Brazil</p><p>3Programa de Pós-graduação em Ecologia,</p><p>Universidade Federal de São João Del Rey,</p><p>São João del Rey, Minas Gerais, Brazil</p><p>Correspondence</p><p>Lucas Mendes Rabelo, Programa de</p><p>Pós-graduação em Ecologia Aplicada -</p><p>Universidade Federal de Lavras, Lavras,</p><p>Minas Gerais, Brazil.</p><p>Email: lucasmrabelo@gmail.com</p><p>Funding information</p><p>Fundação de Amparo à Pesquisa do Estado</p><p>de Minas Gerais, Grant/Award Number:</p><p>APQ 01281-13; Conselho Nacional de</p><p>Desenvolvimento Científico e Tecnológico,</p><p>Grant/Award Number: 308334/2018-3</p><p>Abstract</p><p>Aim: In addition to cave size and other subterranean habitat characteristics, cave</p><p>entrances are important structurers of neotropical cave communities. However, little</p><p>is known about the epigean ecosystems factors that might dictate the influence of</p><p>entrances and the relationship among surface and cave communities, as entrance re-</p><p>gions are ecotonal zones between the epigean and hypogean ecosystems. We aimed</p><p>to assess the influence of epigean and hypogean factors as potential drivers of inver-</p><p>tebrate species richness in Neotropical caves as well as the influence of the regional</p><p>pool of invertebrate diversity on cave invertebrate diversity.</p><p>Location: Limestone caves in south-eastern Brazil.</p><p>Taxon: Invertebrates</p><p>Methods: Data were collected in 48 caves within the Cerrado biome (Brazilian</p><p>Savanna). The fauna sampling was performed by a direct intuitive search (DIS).</p><p>Landscape characteristics and climatic parameters were accessed using geographic</p><p>information systems. The characterization of the caves occurred during each sam-</p><p>pling event. Regional diversity was based on the Taxonomic Catalog of Brazilian</p><p>Fauna. To clarify the factors that significantly influence invertebrate species richness</p><p>of the caves, we used generalized linear models (GLM). The relationship between</p><p>regional diversity and cave diversity was evaluated based on linear models (LM).</p><p>Results: Overall, 1,173 species were found, of which 72 were obligate subterranean</p><p>dwellers. The cave total species richness was influenced by hypogean factors and</p><p>epigean factors. The species richness of obligate cave dwellers was significantly ex-</p><p>plained only by cave size. The regional pool of invertebrate species influenced the</p><p>levels of biodiversity in the studied caves. The taxa with troglobitic species tended to</p><p>be more diverse in caves than expected.</p><p>Main conclusions: In addition to the influences of intrinsic cave variables, we high-</p><p>light the importance of epigean factors on subterranean diversity in the Neotropics.</p><p>The study shows the significant influence of the regional species pool on cave faunal</p><p>composition. These findings reinforce the importance of considering the surrounding</p><p>areas in actions regarding cave biodiversity conservation.</p><p>K E Y W O R D S</p><p>cave, diversity, ecology, invertebrates, karst, speleobiology</p><p>www.wileyonlinelibrary.com/journal/jbi</p><p>mailto:</p><p>https://orcid.org/0000-0001-6276-8590</p><p>https://orcid.org/0000-0002-3184-5319</p><p>https://orcid.org/0000-0003-3288-4405</p><p>mailto:lucasmrabelo@gmail.com</p><p>http://crossmark.crossref.org/dialog/?doi=10.1111%2Fjbi.14031&domain=pdf&date_stamp=2020-12-14</p><p>2  |     MENDES RABELO Et AL.</p><p>1  | INTRODUC TION</p><p>Scientific consensus suggests that caves are excellent ‘natural labo-</p><p>ratories’ due to their environmental stability and simplicity of animal</p><p>communities, especially when compared with adjacent epigean hab-</p><p>itats (Poulson & White, 1969). Several authors have demonstrated</p><p>that many intrinsic features of hypogean systems act as filters in</p><p>selecting epigean species, determining both colonization and estab-</p><p>lishment in subterranean habitats. The permanent absence of light</p><p>precludes photoautotrophic organisms, as well as lowering habitat</p><p>heterogeneity and availability of food resources (Prous et al., 2015;</p><p>Sket, 1999). The particular characteristics of cave habitats favour</p><p>specialized species, known as troglobionts, which are endemic</p><p>to subterranean habitats and usually present reduced eye struc-</p><p>tures, depigmentation and overdevelopment of alternative sensory</p><p>structures (Christiansen, 1962; Sket, 2008). Therefore, caves have</p><p>frequently been used as model systems in studies on evolution</p><p>and ecology (Jaffé et al., 2018; Juan et al., 2010; Mammola, 2018;</p><p>Moldovan et al., 2018).</p><p>In recent years, our understanding of subterranean environments</p><p>has increased considerably (Mammola, Cardoso, Culver, et al., 2019;</p><p>Wynne et al., 2019). As a result, some previously proposed pat-</p><p>terns, such as lowered troglobitic richness in Neotropical regions</p><p>(Deharveng & Bedos, 2012), have been rejected as more data have</p><p>emerged (Ferreira et al., 2018). Ecological studies on cave commu-</p><p>nities both in temperate and tropical regions have also shown that</p><p>extrinsic and intrinsic caves variables are key drivers of hypogean</p><p>biodiversity (Mammola, Cardoso, Angyal, et al., 2019; Souza-Silva</p><p>et al., 2020; Zagmajster et al., 2018). As an example, the positive</p><p>relationship between cave size and richness is recurrent and docu-</p><p>mented in different regions of the world (Jaffé et al., 2018; Mammola,</p><p>Cardoso, Angyal, et al., 2019; Souza-Silva et al., 2020; Zagmajster</p><p>et al., 2018). However, several important factors for structuring cave</p><p>fauna in temperate regions, such as climatic features, ecoregions and</p><p>primary productivity, and the influence of epigean ecosystems over</p><p>subterranean communities, have not yet been tested in Neotropical</p><p>regions (Bregović & Zagmajster, 2016; Christman et al., 2016; Culver</p><p>et al., 2006; Mammola, Piano, Malard, Vernon, et al., 2019; Niemiller</p><p>& Zigler, 2013). Similarly, some patterns observed for Neotropical</p><p>regions have not been documented for temperate areas, such as the</p><p>influence of streams and entrance features over the diversity of the</p><p>terrestrial cave fauna (Prous et al., 2015; Simões et al., 2015; Souza-</p><p>Silva et al., 2020a, 2020b). This is possibly due to the fact that most</p><p>studies of cave fauna in temperate regions are focused on troglobitic</p><p>species (Moldovan et al., 2018). Therefore, it is necessary to eluci-</p><p>date the factors that influence basic ecological parameters in order</p><p>to allow for a better use of caves as ecological models and promote</p><p>greater study robustness (Chesson, 2000; Gaston, 2000).</p><p>Although it is known that Neotropical cave entrances are import-</p><p>ant in determining species richness (Prous et al., 2015; Souza-Silva</p><p>et al., 2020a), little is known about the epigean factors that indirectly</p><p>contribute to this influence. When considering the close association</p><p>between the cave trophic resources and the epigean availability of</p><p>these resources (Schneider et al., 2011; Souza-Silva et al., 2012),</p><p>external primary productivity must also be relevant to Neotropical</p><p>caves, as it is for temperate regions (Culver et al., 2006; Eme</p><p>et al., 2015; Schneider et al., 2011), as entrances directly contribute</p><p>to the energy input in cave ecosystems. Moreover, as the species</p><p>pool supported by environments with greater energy availability</p><p>tends to be larger, energy-rich epigean ecosystems may harbour</p><p>a greater richness of potential cave colonizers (Evans et al., 2005;</p><p>Gaston, 2000; Szinwelski et al., 2015). As caves are colonized by</p><p>surface species capable of overcoming cave environmental</p><p>of the United</p><p>States of America, 110(23), 9391–9396. https://doi.org/10.1073/</p><p>pnas.13016 57110</p><p>Wickham, H. (2009). ggplot2: Elegant graphics for data analysis. Springer-</p><p>verlag, http://ggplo t2.org</p><p>Wynne, J., Howarth, F., Sommer, S., & Dickson, B. (2019). Fifty</p><p>years of cave arthropod sampling: Techniques and best prac-</p><p>tices. International Journal of Speleology, 48(1), 33–48. https://doi.</p><p>org/10.5038/1827-806x.48.1.2231</p><p>Zagmajster, M., Malard, F., Eme, D., & Culver, D. C. (2018). Subterranean</p><p>biodiversity patterns from global to regional scales. In O. T.</p><p>Moldovan, Ľ. Kováč, & S. Halse (Eds.), Cave ecology (1st ed., Vol.</p><p>235, pp. 195–227). Springer International Publishing. https://doi.</p><p>org/10.1007/978-3-319-98852 -8</p><p>Zuur, A. F., Ieno, E. N., & Elphick, C. S. (2010). A protocol for data exploration</p><p>to avoid common statistical problems. Methods in Ecology and Evolution,</p><p>1(1), 3–14. https://doi.org/10.1111/j.2041-210x.2009.00001.x</p><p>Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A., & Smith, G. M. (2009).</p><p>Mixed effects models and extensions in ecology with R (1–579). Springer.</p><p>https://doi.org/10.1007/978-0-387-87458 -6</p><p>AUTHOR BIOG R APHIE S</p><p>Lucas Mendes Rabelo is a biologist, doctor in applied ecology</p><p>by the University of Lavras and researcher linked to the Center</p><p>of Studies in Subterranean Biology. He has been a cave biologist</p><p>since 2011.</p><p>Marconi Souza-Silva has been a cave biologist since 1997. He</p><p>undergraduate in biology in 2000, did his master in 2003 and</p><p>his doctorate in 2008, both in ecology. He got a position as a</p><p>permanent biology professor at the Federal University of Lavras</p><p>(UFLA), Minas Gerais, Brazil in 2013. Nowadays he researches</p><p>with cave ecology and conservation and also works as a student</p><p>advisor and part-time professor in Post graduate Courses of</p><p>Ecology (UFLA).</p><p>Rodrigo Lopes Ferreira is the coordinator of the Center of Studies</p><p>on Subterranean Biology (CEBS/UFLA) and Professor of Zoology</p><p>and Subterranean Biology at the Federal University of Lavras,</p><p>Brazil. His group has active production on ecology of subterranean</p><p>ecosystems and taxonomy of cave invertebrates, especially from</p><p>the Neotropics. He has considerable experience in subterranean</p><p>fauna, having executed many works in several regions of Brazil</p><p>and abroad, where he has visited caves in over 25 countries. His</p><p>main specialty is the ecology and conservation of subterranean</p><p>fauna, actively acting in Brazilian policies for cave protection.</p><p>Author contributions: All authors contributed actively in all</p><p>stages of the work.</p><p>SUPPORTING INFORMATION</p><p>Additional supporting information may be found online in the</p><p>Supporting Information section.</p><p>How to cite this article: Mendes Rabelo L, Souza-Silva M,</p><p>Lopes Ferreira R. Epigean and hypogean drivers of</p><p>Neotropical subterranean communities. J Biogeogr.</p><p>2020;00:1–14. https://doi.org/10.1111/jbi.14031</p><p>https://doi.org/10.3897/subtbiol.16.8609</p><p>https://doi.org/10.3897/subtbiol.16.8609</p><p>https://doi.org/10.1636/Ha09-112.1</p><p>https://doi.org/10.1071/is17049</p><p>http://apps.isiknowledge.com/full_record.do?product=UA&search_mode=CitingArticles&qid=2&SID=W1mnsgAXyaggjbcuZuF&page=1&doc=29</p><p>http://apps.isiknowledge.com/full_record.do?product=UA&search_mode=CitingArticles&qid=2&SID=W1mnsgAXyaggjbcuZuF&page=1&doc=29</p><p>http://apps.isiknowledge.com/full_record.do?product=UA&search_mode=CitingArticles&qid=2&SID=W1mnsgAXyaggjbcuZuF&page=1&doc=29</p><p>https://doi.org/10.1016/j.actao.2020.103645</p><p>https://doi.org/10.1016/j.actao.2020.103645</p><p>https://doi.org/10.3897/subtbiol.33.46444</p><p>https://doi.org/10.3897/subtbiol.33.46444</p><p>https://doi.org/10.1371/journal.pone.0139669</p><p>https://doi.org/10.1371/journal.pone.0139669</p><p>https://doi.org/10.6084/m9.figshare.7707605.v3</p><p>https://doi.org/10.1093/jmammal/gyz206</p><p>https://cran.r-project.org/package=washeR</p><p>https://doi.org/10.1073/pnas.1301657110</p><p>https://doi.org/10.1073/pnas.1301657110</p><p>http://ggplot2.org</p><p>https://doi.org/10.5038/1827-806x.48.1.2231</p><p>https://doi.org/10.5038/1827-806x.48.1.2231</p><p>https://doi.org/10.1007/978-3-319-98852-8</p><p>https://doi.org/10.1007/978-3-319-98852-8</p><p>https://doi.org/10.1111/j.2041-210x.2009.00001.x</p><p>https://doi.org/10.1007/978-0-387-87458-6</p><p>https://doi.org/10.1111/jbi.14031</p><p>filters</p><p>(Rivera et al., 2002; Wessel et al., 2013), richer epigean areas may</p><p>therefore present richer caves, in both temperate and Neotropical</p><p>areas. Hence, the limits proposed for ecoregions, which were pri-</p><p>marily based on epigean attributes (such as richness and composi-</p><p>tion of distinct communities), can also be significant for Neotropical</p><p>cave communities, as already shown in temperate regions (Christman</p><p>et al., 2005; Moldovan et al., 2018; Niemiller & Zigler, 2013).</p><p>Considering the high species richness associated with</p><p>Neotropical caves, it is expected that the influence of these factors</p><p>directly linked to epigean ecosystems will also exist in these com-</p><p>munities. Thus, this study aimed to investigate how epigean and hy-</p><p>pogean environmental factors influence cave species richness and</p><p>how the regional species pool influences subterranean biodiversity</p><p>in Neotropical regions. We tested the following hypotheses, that: (a)</p><p>Biodiversity of the Neotropical caves is influenced not only by hypo-</p><p>gean features but also by landscape and climate features; (b) There is</p><p>a direct relationship between the number of species available in the</p><p>regional pool and the number of species found in the sampled caves,</p><p>showing proportionalities in the colonization processes and (c) Taxa</p><p>with troglobitic species present a higher number of species in caves</p><p>than expected compared with all taxa, demonstrating greater affin-</p><p>ity to subterranean ecosystems.</p><p>2  | MATERIAL S AND METHODS</p><p>2.1 | Study area</p><p>Field data were obtained across 48 carbonate caves located in the</p><p>state of Minas Gerais, South-eastern Brazil, between 2014 and</p><p>2015. Sampling was performed once in each cave, always during the</p><p>rainy season from November to March. The caves are distributed</p><p>along an area of 50,575 km2 limited by the latitudes −14.935°(S)/</p><p>−18.824°(S) and longitudes −44.814°(W)/ −43.845°(W) (WGS84).</p><p>This region belongs to the São Francisco river watershed and is lo-</p><p>cated in the South-eastern branch of the largest karstic region of</p><p>South America, the Bambuí limestone group (Auler, 2004, 2019)</p><p>(Figure 1, Appendix S1).</p><p>All the caves are within the Cerrado biome, with 12 of them</p><p>occurring in the ecoregion Atlantic Dry Forests and 36 in the</p><p>Cerrado Woodlands and Savannas (Borsato et al., 2015; Olson</p><p>et al., 2001) (Appendix S1). The caves were located in five phy-</p><p>tophysiognomies: Montane Seasonal Deciduous Forest (20 caves),</p><p>|  3MENDES RABELO Et AL.</p><p>Cerrado strictusensu (12 caves), Field (8 caves), Cerrado field (5</p><p>caves) and Montane Seasonal Semideciduous Forest (3 caves)</p><p>(Carvalho et al., 2006).</p><p>The elevation (measured at each cave's main entrance) ranged</p><p>from 508 to 829 m above sea level. According to the Köppen clas-</p><p>sification (Köppen, 1936), among the 48 caves, 34 are in a region of</p><p>climate type As (tropical with rainy winter), 12 in Aw (well-defined</p><p>seasons with a dry period from July to September) and 2 in type Cwa</p><p>(rainy season from October to March and pluviosity in other months</p><p>of about 42 mm3) (Alvares et al., 2013).</p><p>2.2 | Environmental predictors</p><p>The hypogean features were assessed directly from the cave habi-</p><p>tats. The characteristics measured directly were as follows: number</p><p>of entrances (Ent.), sum of the largest dimensions of entrances (S.</p><p>Ent.), sampled linear development (S.L.D) and presence of streams</p><p>(Streams). The cave entrance size (S. Ent.) was calculated by</p><p>measuring across at the widest point for each opening to the cave.</p><p>Only one measure of each entrance was used, considering the two</p><p>most distant points horizontally or vertically. In the case of caves</p><p>with multiple entrances, the final value was obtained by summing</p><p>the sizes of each entrance, resulting in the metric “cave entrance</p><p>size.” The measurements were obtained in the field with the aid of a</p><p>laser measuring tape. The sampled linear development of each cave</p><p>(cave size) was obtained by summing the linear length of all sampled</p><p>conduits using cave ground plans (maps) or during field samplings</p><p>with the aid of measuring tape. The presence of lotic water bod-</p><p>ies inside the caves was verified during sampling events and were</p><p>considered ‘streams’ independently of their dimensions. The annual</p><p>surface temperature average was used as a proxy for the cave tem-</p><p>perature (Badino, 2010; Mammola & Leroy, 2018) (Appendix S1 and</p><p>S2).</p><p>The epigean landscape and climate features selected were as</p><p>follows: elevation, ecoregion, minimum temperature of the coldest</p><p>month (BIO6; Min T.C.M.), maximum temperature of the warmest</p><p>month (BIO5; Max T.W.M.), precipitation of the driest month (BIO14;</p><p>F I G U R E 1   Study area. (a) location of the sampled caves in the Bambuí karstic region, Brazil, South America; (b) The São Francisco river</p><p>watershed; C: area of the Cerrado biome</p><p>(a) (b)</p><p>(c)</p><p>4  |     MENDES RABELO Et AL.</p><p>Prec D.M.), precipitation of the wettest month (BIO13; Prec W.M.)</p><p>and mean annual evapotranspiration (Mean A.ET.) (Appendix S2).</p><p>Cave entrance elevation was captured using Google Earth Pro®</p><p>(Google LLC, 2019). The ecoregions were accessed by overlap-</p><p>ping the geographic coordinates of the cave main entrances to the</p><p>shapefile containing the limits proposed by Olson et al. (2001) for</p><p>the world ecoregions. The climatic variables were obtained from</p><p>WorldClim Version 2 (Fick & Hijmans, 2017). The mean annual</p><p>evapotranspiration datasets were obtained from the Global High-</p><p>Resolution Soil-Water Balance dataset (Trabucco & Zomer, 2019).</p><p>Temperature and precipitation extremes (defined as months which</p><p>historically presented the maximum and minimum values) were se-</p><p>lected in order to generate variables that act directly on species dis-</p><p>tributions (Cox et al., 2016).</p><p>2.3 | Sampling and identification of cave fauna</p><p>Invertebrates were collected along all accessible extensions of the</p><p>cave, except in streams and adjacent aquatic environments such as</p><p>marginal ponds. Aquatic habitats disconnected from streams, like</p><p>travertine pools, were inventoried. Sampling was conducted by di-</p><p>rect intuitive searches (DIS) using tweezers, brushes, suckers and</p><p>hand nets for catches (Wynne et al., 2019). A standard effort av-</p><p>eraging 1 min per square meter of floor was applied, as the floor</p><p>microhabitats require more effort than the walls and the ceiling is</p><p>generally inaccessible. The sampling team was always composed of</p><p>four biologists with at least 2 years of experience in sampling subter-</p><p>ranean fauna. Collected individuals were preserved in plastic pots</p><p>containing 70% alcohol and taken to the laboratory where they were</p><p>identified.</p><p>All collected individuals were sorted and identified to the</p><p>lowest accessible taxonomic level. After separating all individu-</p><p>als into morphotypes, some taxa (Acari, Amblypygi, Amphipoda,</p><p>Araneae, Collembola, Diplopoda, Hemiptera, Opiliones, Orthoptera,</p><p>Psocoptera, Isopoda, Isoptera, Ephemeroptera, Turbellaria,</p><p>Hymenoptera and Palpigradi) were sent to experts for specific</p><p>identifications.</p><p>The determination of troglomorphic species was made based</p><p>on criteria in the literature specific to each taxonomic group</p><p>and expert assessment (Baptista & Giupponi, 2003; Brescovit</p><p>et al., 2012; Iniesta & Ferreira, 2015; Pinto-da-Rocha, 1996;</p><p>Prevorcnik et al., 2012; Ratton et al., 2012; Souza & Ferreira, 2010).</p><p>Examples of some troglomorphisms commonly observed in spe-</p><p>cies of distinct taxonomic groups are the reduction or absence of</p><p>eyes, elongation of locomotor and sensory appendages, reduction</p><p>or loss of pigmentation, increasing of body size and the number of</p><p>trichobothria (Barr, 1968; Christiansen, 1962; Novak et al., 2012;</p><p>Trajano & Bichuette, 2010). However, some specific troglomor-</p><p>phisms such as elongation of flagellomeres and increased number</p><p>of blades in lateral organs are observed in the order Palpigradi</p><p>(Souza & Ferreira, 2018). All species presenting troglomorphisms</p><p>were considered troglobionts, that is, living strictly in subterra-</p><p>nean habitats (Sket, 2008).</p><p>2.4 |</p><p>Collection of literature data on the regional</p><p>pool of invertebrate species</p><p>The regional pool of epigean invertebrate species (Regional pool)</p><p>was defined as all-known species recorded based on bibliographic</p><p>survey in the available database with the best overlap with occur-</p><p>rence area of the studied caves. The bibliographic survey focused</p><p>on the taxonomic groups found during the caves sampling events.</p><p>The most updated available database that best overlapped with</p><p>the sampled region was the Taxonomic Catalog of Brazilian Fauna</p><p>(Brasil, 2019). Data were accessed on May 9th, 2019 (Appendix S3).</p><p>2.5 | Statistical analyses</p><p>Firstly, before building the models, we applied a data explora-</p><p>tion protocol to meet the premises of the analysis methods used</p><p>(Zuur et al., 2010). Outliers were evaluated using nonparametric</p><p>methods (Venturini, 2018). The independence between the ob-</p><p>servations used as a response variable was assessed (Bjornstad</p><p>& Cai, n.d.). The colinearity between the independent variables</p><p>was tested using Spearman's correlation matrix (Peterson &</p><p>Carl, 2014). Redundant variables were considered as those whose</p><p>correlation values greater than or equal to 60% (Booth et al., 1994;</p><p>Zuur et al., 2009). The elimination of collinear variables was per-</p><p>formed using the variance inflation factors (VIFs). The variables</p><p>that presented high VIF values were eliminated one by one until all</p><p>had VIF less than 3 (Zuur et al., 2010).</p><p>We used generalized linear models (GLMs) to evaluate how</p><p>epigean and hypogean environmental factors influence the bio-</p><p>diversity of subterranean communities in Neotropical caves. Total</p><p>species richness and troglobitic species richness, accessed by sam-</p><p>pling events, were used as dependent variables. To assess the most</p><p>appropriate family for the distribution of the models, we used dis-</p><p>persion parameters. The best set of models was selected based on</p><p>corrected Akaike information criteria (AICc) and included the models</p><p>presenting ΔAICc ≤ 2, from which the average coefficients for each</p><p>variable were extracted (Burnham et al., 2011). Among the variables</p><p>incorporated by the set of the best models, those presenting an av-</p><p>erage coefficient different from the average intercept were consid-</p><p>ered significant (Burnham et al., 2011; Zuur et al., 2009). Residual</p><p>diagnostic plots were used to examine the assumption of the regres-</p><p>sion models (Hartig, 2019). To compare regression coefficients, all</p><p>variables were standardized using Z scores that generated the same</p><p>set of models with better performance than non-standard variables.</p><p>The Relative Variable Importance (RVI) of those that were included</p><p>in the set of best models (ΔAICc ≤ 2) was calculated according to</p><p>the sum of Akaike weights of all models in which each variable</p><p>|  5MENDES RABELO Et AL.</p><p>appeared (Barton, 2016; Burnham & Anderson, 2002; Johnson &</p><p>Omland, 2004).</p><p>Linear models were used to assess whether the Regional pool</p><p>influenced Subterranean biodiversity. For this, the species found</p><p>during cave sampling events were grouped into taxonomic groups</p><p>(Taxa). The number of sampled cave species obtained for each of</p><p>these Taxa, henceforth termed “Subterranean biodiversity,” was</p><p>used as a dependent variable. The known number of species that</p><p>composed the “Regional pool” of each of these Taxa (based on the</p><p>Taxonomic Catalog of Brazilian Fauna) was used as an independent</p><p>variable. To test the normality of the data, we used Shapiro-Wilk tests</p><p>(Shapiro & Wilk, 1965). In order to normalize the data and reduce</p><p>the data range, considering the great natural variation in the number</p><p>of known species in each arthropod Order, both the Subterranean</p><p>biodiversity and the Regional pool were log-transformed. From the</p><p>results of this regression model, residuals of data dispersion in rela-</p><p>tion to the predicted model were extracted (data variation not ex-</p><p>plained by the model), from now on called “Residuals”. To evaluate</p><p>whether Taxa with the occurrence of troglobitic species tend to have</p><p>a greater number of species colonizing caves than expected by the</p><p>regression model, we performed more linear models using troglo-</p><p>bitic species richness of each taxa as a dependent variable and the</p><p>Residuals as an independent variable. To visualize which taxa with</p><p>occurrence of troglobitic species presented positive or negative</p><p>Residual values, a bar plot was used. All analyses were done in the</p><p>software R (R Core Team, 2019). Graphs were made with the pack-</p><p>age “ggplot2”(Wickham, 2009).</p><p>3  | RESULTS</p><p>A total of 1,173 invertebrate species were obtained across the 48</p><p>caves sampled. These species were distributed across 49 orders and</p><p>263 families. The richest cave was Lapa Sem Fim with 151 species,</p><p>7 of them troglobionts. Conversely, Madeira cave had the lowest</p><p>richness with 12 species and none of them troglobiont. The av-</p><p>erage species richness obtained for all the caves was 60.64 spp./</p><p>cave (SD = 28.92). Caves with highest richness of troglobitic species</p><p>were as follows: Lapa d’Água cave (municipality of Montes Claros)</p><p>and Nestor cave (municipality of Itacarambi), each with 10 species.</p><p>However, 22.9% of caves did not have any troglobitic species. The</p><p>average richness of obligate cave species (troglobionts) was 2.83</p><p>spp./cave (SD = 2.65) (Appendix S2). The highest number of en-</p><p>trances was 8 (Lapa da Lagoinha cave and Joaquim Rodrigues cave),</p><p>while the largest sum of entrance extensions was 36 m (São José I</p><p>cave). The sampled linear development ranged from 20 m (Zezinho</p><p>de Dionila cave) to 2,200 m (Lapa Sem Fim cave). Adding the sam-</p><p>pled linear development in all caves, a total of 21.72 km of sampled</p><p>conducts was obtained (Appendix S1 and S2).</p><p>No outliers were detected among the used variables. Several of</p><p>the explanatory variables were highly correlated with each other.</p><p>Considering the criterion adopted for the sequence of elimination of</p><p>the variables (VIF), the elimination sequence was as follows: BIO6, TA</p><p>B</p><p>LE</p><p>1</p><p>M</p><p>od</p><p>el</p><p>s</p><p>el</p><p>ec</p><p>tio</p><p>n</p><p>ta</p><p>bl</p><p>e</p><p>fo</p><p>r G</p><p>LM</p><p>a</p><p>na</p><p>ly</p><p>si</p><p>s</p><p>co</p><p>ns</p><p>id</p><p>er</p><p>in</p><p>g</p><p>th</p><p>e</p><p>to</p><p>ta</p><p>l s</p><p>pe</p><p>ci</p><p>es</p><p>ri</p><p>ch</p><p>ne</p><p>ss</p><p>In</p><p>t.</p><p>El</p><p>ev</p><p>.</p><p>S.</p><p>L.</p><p>D</p><p>.</p><p>Ec</p><p>or</p><p>eg</p><p>io</p><p>n</p><p>En</p><p>t.</p><p>S.</p><p>E</p><p>nt</p><p>.</p><p>BI</p><p>O</p><p>13</p><p>St</p><p>re</p><p>am</p><p>s</p><p>R2</p><p>df</p><p>lo</p><p>gL</p><p>ik</p><p>A</p><p>IC</p><p>c</p><p>D</p><p>el</p><p>ta</p><p>W</p><p>ei</p><p>gh</p><p>t</p><p>4.</p><p>05</p><p>5</p><p>0.</p><p>17</p><p>35</p><p>0.</p><p>17</p><p>34</p><p>0.</p><p>11</p><p>56</p><p>0</p><p>0.</p><p>13</p><p>04</p><p>0.</p><p>43</p><p>22</p><p>00</p><p>6</p><p>−2</p><p>12</p><p>.4</p><p>20</p><p>43</p><p>8.</p><p>9</p><p>0.</p><p>00</p><p>0.</p><p>13</p><p>6</p><p>4.</p><p>05</p><p>2</p><p>−0</p><p>.0</p><p>92</p><p>51</p><p>0.</p><p>18</p><p>98</p><p>0.</p><p>20</p><p>47</p><p>0.</p><p>11</p><p>10</p><p>0</p><p>0.</p><p>14</p><p>24</p><p>0.</p><p>46</p><p>05</p><p>00</p><p>7</p><p>−2</p><p>11</p><p>.1</p><p>96</p><p>43</p><p>9.</p><p>2</p><p>0.</p><p>30</p><p>0.</p><p>11</p><p>7</p><p>4.</p><p>06</p><p>0</p><p>0.</p><p>17</p><p>51</p><p>0.</p><p>20</p><p>03</p><p>0.</p><p>12</p><p>78</p><p>0.</p><p>38</p><p>68</p><p>00</p><p>5</p><p>−2</p><p>14</p><p>.2</p><p>67</p><p>44</p><p>0.</p><p>0</p><p>1.</p><p>07</p><p>0.</p><p>08</p><p>0</p><p>4.</p><p>05</p><p>7</p><p>−0</p><p>.0</p><p>97</p><p>64</p><p>0.</p><p>19</p><p>23</p><p>0.</p><p>23</p><p>34</p><p>0.</p><p>14</p><p>15</p><p>0.</p><p>41</p><p>86</p><p>00</p><p>6</p><p>−2</p><p>12</p><p>.9</p><p>88</p><p>44</p><p>0.</p><p>0</p><p>1.</p><p>14</p><p>0.</p><p>07</p><p>7</p><p>4.</p><p>05</p><p>3</p><p>0.</p><p>16</p><p>67</p><p>0.</p><p>14</p><p>54</p><p>0.</p><p>11</p><p>70</p><p>0</p><p>0.</p><p>06</p><p>38</p><p>9</p><p>0.</p><p>13</p><p>95</p><p>0.</p><p>44</p><p>67</p><p>00</p><p>7</p><p>−2</p><p>11</p><p>.8</p><p>02</p><p>44</p><p>0.</p><p>4</p><p>1.</p><p>51</p><p>0.</p><p>06</p><p>4</p><p>A</p><p>bb</p><p>re</p><p>vi</p><p>at</p><p>io</p><p>ns</p><p>: B</p><p>IO</p><p>13</p><p>, p</p><p>re</p><p>ci</p><p>pi</p><p>ta</p><p>tio</p><p>n</p><p>of</p><p>w</p><p>et</p><p>te</p><p>st</p><p>m</p><p>on</p><p>th</p><p>; E</p><p>le</p><p>v.</p><p>, e</p><p>le</p><p>va</p><p>tio</p><p>n;</p><p>In</p><p>t,</p><p>In</p><p>te</p><p>rc</p><p>ep</p><p>t;</p><p>S.</p><p>L.</p><p>D</p><p>.,</p><p>sa</p><p>m</p><p>pl</p><p>ed</p><p>li</p><p>ne</p><p>ar</p><p>d</p><p>ev</p><p>el</p><p>op</p><p>m</p><p>en</p><p>t.</p><p>6  |     MENDES RABELO Et AL.</p><p>BIO1, BIO14, Mean A.ET. and BIO5. Among the variables that were</p><p>kept, ecoregion presented redundancy in relation to: Mean A.ET.</p><p>(rs = 0.75), BIO1 (rs = −0.73), BIO6 (rs = −0.75) and BIO14 (rs = 0.75).</p><p>The precipitation of wettest month (BIO13) presented redun-</p><p>dancy in relation to: Mean A.ET. (rs = 0.62), BIO1 (rs = −0.65), BIO6</p><p>(rs = −0.73) and BIO14 (rs = 0.71). The elevation presented redun-</p><p>dancy in relation to: BIO5 (rs = −0.67). Thus, for the GLM analyses,</p><p>7 of the 12 variables initially selected were used (Ent., S. Ent., S.L.D.,</p><p>Streams, Elevation, Ecoregion and BIO13).</p><p>A negative binomial distribution was the most appropriate disper-</p><p>sion parameter according to the residual diagnostics for hierarchical</p><p>regression models. Five representative models were run to explain</p><p>the observed variation for the total species richness. Together, they</p><p>contained six of the seven available variables (Table 1). Among the</p><p>independent</p><p>variables, only S. Ent. has not been incorporated into</p><p>at least one of the models. However, although all others were in at</p><p>least one of the models, elevation and precipitation of the wettest</p><p>month (BIO13) did not significantly explain the total species richness</p><p>(Figure 2, Table 2). Sampled linear development, presence of streams</p><p>and ecoregion were covariates with the greatest RVI in all the best</p><p>set models. The number of entrances was included into three of the</p><p>five models. Considering the independent variables eliminated in the</p><p>pre-treatment of the analyses due to the detection of redundancy,</p><p>the mean annual evapotranspiration, annual mean temperature</p><p>(BIO1), minimum temperature of the coldest month (BIO6) and pre-</p><p>cipitation of the driest month (BIO14) are also relevant to the total</p><p>species richness.</p><p>To explain the values obtained for the troglobitic species rich-</p><p>ness, 11 models were obtained as the best set. Together the best</p><p>set incorporated 6 of the 7 available variables (Table 3). However,</p><p>only hypogean factors were significant to explain troglobitic species</p><p>richness. ‘Number of entrances’ was not included in any of the mod-</p><p>els. The only variable that significantly explained troglobitic species</p><p>richness was sampled linear development (Figure 3, Table 4).</p><p>Of the 49 invertebrate orders found in the sampled caves, 3</p><p>were not present in the Taxonomic Catalog of Brazilian Fauna re-</p><p>cords. Thus, these taxa (Pauropoda, Astigmata and Siphonophorida)</p><p>were excluded from the Subterranean biodiversity data. Coleoptera</p><p>had the greatest richness both in Subterranean biodiversity,</p><p>with 221 species, and in the Regional pool of 33,145 known spe-</p><p>cies. Endeostigmata, Protura, Scorpiones, Scutigeromorpha,</p><p>Thysanoptera and Nematomorpha presented the lowest richness</p><p>F I G U R E 2   Generalized Linear Models results: Independent variables selected by the set of best models for explaining the total cave</p><p>species richness in Brazil</p><p>Estimate Std. Error</p><p>Adjusted</p><p>SE Z value Pr(>|z|) RVI</p><p>Intercept 405.514 0.05288 0.05441 74.523 <2e−16 —</p><p>S.L.D. 0.17993 0.05507 0.05663 3.178 0.00148 1</p><p>Ecoregion 0.19167 0.06416 0.06571 2.917 0.00353 1</p><p>Streams 0.13595 0.05494 0.05651 2.406 0.01615 1</p><p>Entrances 0.11418 0.05429 0.05588 2.044 0.04100 0.67</p><p>Elevation −0.09455 0.05870 0.06042 1.565 0.11764 0.41</p><p>BIO13 0.06389 0.05953 0.06130 1.042 0.29724 0.13</p><p>Abbreviations: BIO13, precipitation of wettest month; RVI, relative variable importance; S.L.D.,</p><p>sampled linear development.</p><p>TA B L E 2   Conditional averages of the</p><p>model-averaged coefficients for GLM</p><p>analysis considering the total species</p><p>richness</p><p>|  7MENDES RABELO Et AL.</p><p>in Subterranean biodiversity, with only one species each against</p><p>the known 4 (Endeostigmata), 27 (Protura), 158 (Scorpiones), 3</p><p>(Scutigeromorpha), 607 (Thysanoptera) and 16 (Nematomorpha)</p><p>species in the Regional pool. Regarding troglobionts, 72 species</p><p>across 12 orders and 30 families were recorded in the Subterranean</p><p>biodiversity, with Isopoda and Araneae standing out with 14 and 13</p><p>species respectively (Appendix S3).</p><p>The linear model relating Subterranean biodiversity to the</p><p>Regional pool shows a positive and significant relationship (Table 5,</p><p>LM 1; Figure 4 A). However, this relationship was not observed for</p><p>the troglobitic species richness in each taxa (Table 5, LM 2; Figure 4</p><p>B). Nevertheless, a significant positive relationship exists between</p><p>the residuals of the LM 1 and the troglobitic species richness of each</p><p>taxa (Table 5, LM 3; Figure 4 C). It shows that taxa with troglobitic</p><p>species tend to have greater representativeness in Subterranean</p><p>biodiversity than the other taxa that compose the Regional Pool.</p><p>Considering only taxa with occurrence of troglobitic species, it</p><p>is possible to observe the relationship more clearly (Table 5, LM</p><p>4; Figure 4d). Among the 12 orders with occurrence of troglobitic</p><p>species, only Orthoptera presented negative residuals (−0.19616)</p><p>(Figure 5).</p><p>4  | DISCUSSION</p><p>Although cave habitats present distinct environmental conditions in</p><p>comparison to the epigean habitats (Sánchez-Fernández et al., 2018),</p><p>we have demonstrated that Neotropical cave invertebrate commu-</p><p>nities are influenced by several attributes common to epigean eco-</p><p>systems. In addition to showing the influence of climatic factors,</p><p>primary productivity and ecoregions in cave species richness, we</p><p>also highlighted the connection of surface regional species pools and</p><p>the subterranean biodiversity. Besides that, we reinforce the influ-</p><p>ence of cave size, number of entrances and presence of streams on</p><p>cave species richness. Furthermore, we showed that in addition to</p><p>the length of the cave favouring the occurrence of troglobitic spe-</p><p>cies, cave habitats might favour the occurrence of some taxa rather</p><p>than others, as taxa with troglobitic species presented more cave</p><p>colonizing species than expected.</p><p>The influence of epigean ecosystems is remarkable in the</p><p>Neotropical cave fauna. As in temperate regions, climatic fea-</p><p>tures, primary productivity and ecoregions proved to be deter-</p><p>minant in structuring Neotropical cave communities (Bregović</p><p>& Zagmajster, 2016; Christman et al., 2016; Culver et al., 2006;</p><p>Mammola, Cardoso, Angyal, et al., 2019; Niemiller & Zigler, 2013).</p><p>Climate is an important factor for most of the Earth's ecosys-</p><p>tems (Cox et al., 2016), including caves (Culver et al., 2006; Elith</p><p>& Leathwick, 2009; Mammola, Cardoso, Angyal, et al., 2019;</p><p>Mammola, Piano, Malard, et al., 2019). As an example, precipitation</p><p>positively influences cave species richness in regions with a higher</p><p>incidence of rain during the dry periods. As water is one of the main</p><p>speleogenetic agents, caves are frequently associated with locally</p><p>active hydrological systems (Milanovic, 2005). Furthermore, water is TA</p><p>B</p><p>LE</p><p>3</p><p>M</p><p>od</p><p>el</p><p>s</p><p>el</p><p>ec</p><p>tio</p><p>n</p><p>ta</p><p>bl</p><p>e</p><p>fo</p><p>r G</p><p>LM</p><p>a</p><p>na</p><p>ly</p><p>si</p><p>s</p><p>co</p><p>ns</p><p>id</p><p>er</p><p>in</p><p>g</p><p>th</p><p>e</p><p>tr</p><p>og</p><p>lo</p><p>bi</p><p>tic</p><p>s</p><p>pe</p><p>ci</p><p>es</p><p>ri</p><p>ch</p><p>ne</p><p>ss</p><p>In</p><p>t.</p><p>El</p><p>ev</p><p>.</p><p>S.</p><p>L.</p><p>D</p><p>.</p><p>Ec</p><p>or</p><p>eg</p><p>io</p><p>n</p><p>En</p><p>t.</p><p>S.</p><p>E</p><p>nt</p><p>.</p><p>BI</p><p>O</p><p>13</p><p>St</p><p>re</p><p>am</p><p>s</p><p>R2</p><p>df</p><p>lo</p><p>gL</p><p>ik</p><p>A</p><p>IC</p><p>c</p><p>D</p><p>el</p><p>ta</p><p>W</p><p>ei</p><p>gh</p><p>t</p><p>0.</p><p>91</p><p>72</p><p>−0</p><p>.2</p><p>54</p><p>00</p><p>0.</p><p>41</p><p>81</p><p>0.</p><p>22</p><p>33</p><p>0.</p><p>27</p><p>47</p><p>5</p><p>−9</p><p>7.</p><p>03</p><p>9</p><p>20</p><p>5.</p><p>5</p><p>0.</p><p>00</p><p>0.</p><p>06</p><p>7</p><p>0.</p><p>94</p><p>05</p><p>−0</p><p>.2</p><p>06</p><p>70</p><p>0.</p><p>42</p><p>94</p><p>0.</p><p>22</p><p>93</p><p>4</p><p>−9</p><p>8.</p><p>49</p><p>6</p><p>20</p><p>5.</p><p>9</p><p>0.</p><p>42</p><p>0.</p><p>05</p><p>4</p><p>0.</p><p>90</p><p>24</p><p>−0</p><p>.2</p><p>65</p><p>30</p><p>0.</p><p>37</p><p>52</p><p>0.</p><p>23</p><p>76</p><p>0.</p><p>17</p><p>38</p><p>0.</p><p>30</p><p>57</p><p>6</p><p>−9</p><p>5.</p><p>99</p><p>3</p><p>20</p><p>6.</p><p>0</p><p>0.</p><p>53</p><p>0.</p><p>05</p><p>1</p><p>0.</p><p>91</p><p>74</p><p>0.</p><p>37</p><p>06</p><p>−0</p><p>.2</p><p>90</p><p>60</p><p>0.</p><p>31</p><p>83</p><p>0.</p><p>26</p><p>54</p><p>5</p><p>−9</p><p>7.</p><p>34</p><p>4</p><p>20</p><p>6.</p><p>1</p><p>0.</p><p>61</p><p>0.</p><p>04</p><p>9</p><p>0.</p><p>90</p><p>14</p><p>−0</p><p>.1</p><p>93</p><p>40</p><p>0.</p><p>40</p><p>90</p><p>−0</p><p>.2</p><p>02</p><p>90</p><p>0.</p><p>32</p><p>01</p><p>0.</p><p>30</p><p>29</p><p>6</p><p>−9</p><p>6.</p><p>08</p><p>9</p><p>20</p><p>6.</p><p>2</p><p>0.</p><p>72</p><p>0.</p><p>04</p><p>7</p><p>0.</p><p>96</p><p>40</p><p>0.</p><p>37</p><p>96</p><p>0.</p><p>17</p><p>62</p><p>3</p><p>−1</p><p>00</p><p>.0</p><p>96</p><p>20</p><p>6.</p><p>7</p><p>1.</p><p>23</p><p>0.</p><p>03</p><p>6</p><p>0.</p><p>88</p><p>71</p><p>−0</p><p>.2</p><p>03</p><p>60</p><p>0.</p><p>36</p><p>63</p><p>−0</p><p>.2</p><p>02</p><p>40</p><p>0.</p><p>33</p><p>43</p><p>0.</p><p>17</p><p>51</p><p>0.</p><p>33</p><p>39</p><p>7</p><p>−9</p><p>4.</p><p>99</p><p>7</p><p>20</p><p>6.</p><p>8</p><p>1.</p><p>29</p><p>0.</p><p>03</p><p>5</p><p>0.</p><p>92</p><p>91</p><p>−0</p><p>.2</p><p>14</p><p>20</p><p>0.</p><p>39</p><p>17</p><p>0.</p><p>15</p><p>32</p><p>0.</p><p>25</p><p>37</p><p>5</p><p>−9</p><p>7.</p><p>72</p><p>6</p><p>20</p><p>6.</p><p>9</p><p>1.</p><p>37</p><p>0.</p><p>03</p><p>4</p><p>0.</p><p>90</p><p>51</p><p>0.</p><p>33</p><p>05</p><p>−0</p><p>.2</p><p>96</p><p>10</p><p>0.</p><p>33</p><p>36</p><p>0.</p><p>16</p><p>40</p><p>0.</p><p>29</p><p>24</p><p>6</p><p>−9</p><p>6.</p><p>44</p><p>7</p><p>20</p><p>6.</p><p>9</p><p>1.</p><p>44</p><p>0.</p><p>03</p><p>3</p><p>0.</p><p>91</p><p>12</p><p>−0</p><p>.2</p><p>41</p><p>30</p><p>0.</p><p>38</p><p>14</p><p>0.</p><p>12</p><p>44</p><p>0.</p><p>22</p><p>31</p><p>0.</p><p>28</p><p>86</p><p>6</p><p>−9</p><p>6.</p><p>57</p><p>6</p><p>20</p><p>7.</p><p>2</p><p>1.</p><p>70</p><p>0.</p><p>02</p><p>9</p><p>0.</p><p>90</p><p>87</p><p>0.</p><p>33</p><p>31</p><p>−0</p><p>.2</p><p>83</p><p>50</p><p>0.</p><p>14</p><p>58</p><p>0.</p><p>31</p><p>89</p><p>0.</p><p>28</p><p>42</p><p>6</p><p>−9</p><p>6.</p><p>72</p><p>2</p><p>20</p><p>7.</p><p>5</p><p>1.</p><p>99</p><p>0.</p><p>02</p><p>5</p><p>A</p><p>bb</p><p>re</p><p>vi</p><p>at</p><p>io</p><p>ns</p><p>: B</p><p>IO</p><p>13</p><p>, p</p><p>re</p><p>ci</p><p>pi</p><p>ta</p><p>tio</p><p>n</p><p>of</p><p>w</p><p>et</p><p>te</p><p>st</p><p>m</p><p>on</p><p>th</p><p>; E</p><p>le</p><p>v.</p><p>, e</p><p>le</p><p>va</p><p>tio</p><p>n;</p><p>In</p><p>t,</p><p>In</p><p>te</p><p>rc</p><p>ep</p><p>t;</p><p>S.</p><p>L.</p><p>D</p><p>.,</p><p>sa</p><p>m</p><p>pl</p><p>ed</p><p>li</p><p>ne</p><p>ar</p><p>d</p><p>ev</p><p>el</p><p>op</p><p>m</p><p>en</p><p>t.</p><p>8  |     MENDES RABELO Et AL.</p><p>one of the most important agents transporting organic matter into</p><p>the caves (Culver & Pipan, 2019). Hence, large amounts of rainwater</p><p>run into subterranean systems in karstic regions, thus contributing</p><p>both to the maintenance of moisture and to the transport of organic</p><p>matter (Souza-Silva et al., 2012).</p><p>Temperature also showed to be an important climatic factor for</p><p>cave communities, as regions with the highest minimum tempera-</p><p>ture presented the higher species richness. This reinforces known</p><p>global biodiversity standards</p><p>that, even considering different taxo-</p><p>nomic groups, demonstrate that warmer regions tend to have greater</p><p>species richness (Gaston, 2000). The average annual external tem-</p><p>perature, considered to be important for subterranean ecosystems</p><p>due to the similarity with cave temperatures (Badino, 2010), was</p><p>also important to explain the total species richness in Neotropical</p><p>caves. However, the pattern observed was different from that ob-</p><p>served for temperate regions, where the average annual external</p><p>F I G U R E 3   Generalized Linear Models results: Independent variables selected by the set of best models for explaining the presence of</p><p>Troglobitic species in Brazilian cave systems</p><p>Estimate Std. Error Adjusted SE Z value Pr(>|z|) RVI</p><p>Intercept 0.9173 0.1254 0.1289 7.116 < 2e−16 —</p><p>S.L.D. 0.3866 0.1108 0.1138 3.398 0.000679 1</p><p>BIO13 0.2823 0.1425 0.1462 1.931 0.053455 0.73</p><p>Elevation −0.2278 0.1265 0.1299 1.753 0.079520 0.69</p><p>Ecoregion −0.2525 0.1495 0.1534 1.645 0.099869 0.41</p><p>Streams 0.1675 0.1203 0.1238 1.353 0.176190 0.33</p><p>S. Ent. 0.1343 0.1272 0.1309 1.026 0.304757 0.12</p><p>Abbreviations: BIO13, precipitation of wettest month; RVI, relative variable importance; S. Ent,</p><p>sum of the largest dimensions of entrances; S.L.D., sampled linear development.</p><p>TA B L E 4   Conditional averages of the</p><p>model-averaged coefficients for GLM</p><p>analysis considering the troglobitic species</p><p>richness</p><p>TA B L E 5   Linear models results</p><p>Linear Model</p><p>Dependent</p><p>variable</p><p>Independent</p><p>variable Int. β F p R2</p><p>Representative</p><p>figure</p><p>LM 1 Subterranean</p><p>biodiversity</p><p>Regional pool −0.451 0.488 65.6 <.001 0.6 Figure 4a</p><p>LM 2 Troglobitic s. r. of</p><p>each taxa</p><p>Regional pool 0.034 0.078 7.341 .153 0.051 Figure 4b</p><p>LM 3 Troglobitic s. r. of</p><p>each taxa</p><p>LM 1 residuals 0.452 0.345 7.341 .01 0.14 Figure 4c</p><p>LM 4 Troglobitic s. r. no</p><p>zero</p><p>LM 1 residuals 1.175 1.017 5.375 .04 0.35 Figure 4d</p><p>Abbreviations: Troglobitic s. r. no zero, troglobitic species richness considering only taxa with at least one registered troglobiont during the sample</p><p>events; Troglobitic s. r. of each taxa, troglobitic species richness of each taxa.</p><p>|  9MENDES RABELO Et AL.</p><p>temperature is an important predictor for troglobitic species biodi-</p><p>versity (Mammola, Cardoso, Angyal, et al., 2019). In Neotropics, the</p><p>average annual temperature is important for cave biodiversity as a</p><p>whole and not specifically for troglobitic species.</p><p>Another variable related to the climate, which also showed rel-</p><p>evance to cave species richness, was the average annual evapo-</p><p>transpiration, a frequently used proxy of primary productivity</p><p>(Maurer, 2009; Pereira & Papadakis, 2014). Subterranean commu-</p><p>nities are strongly dependent on allochthonous resources due to</p><p>the absence of photoautotrophic organisms (Schneider et al., 2011;</p><p>Souza-Silva et al., 2012). In general, higher availability of resources</p><p>in a given system increases its capability to support more species,</p><p>both in epigean and hypogean environments, although there are</p><p>some exceptions (Gaston, 2000). As shown for temperate regions,</p><p>cave species are significantly influenced by the primary produc-</p><p>tivity of adjacent surface ecosystems, as the amount of available</p><p>resources in the epigean environment potentially affects the avail-</p><p>ability of resources in subterranean systems (Culver et al., 2006;</p><p>Culver & Pipan, 2019; Souza-Silva et al., 2012). Differently from the</p><p>temperate regions, however, no significant influence of primary pro-</p><p>ductivity was found over the troglobitic species richness. This could</p><p>be due to methodological issues, as different methods were used</p><p>F I G U R E 4   Linear models depicting: (a) Subterranean biodiversity and Regional pool; (b) Troglobitic species richness of each taxa (number</p><p>of troglobitic species found in sampled caves; log + 1 transformed) and Regional pool; (c) All taxa with their respective troglobitic richness</p><p>and residuals (residual values for the linear model relating Subterranean biodiversity and Regional pool); Troglobitic species richness of each</p><p>taxa and residuals disregarding taxa with no one record of troglobitic species. Data from Brazilian cave systems</p><p>0</p><p>2</p><p>4</p><p>2.5 5.0 7.5 10.0</p><p>Regional pool (log)</p><p>Su</p><p>bt</p><p>er</p><p>ra</p><p>ne</p><p>an</p><p>b</p><p>io</p><p>di</p><p>ve</p><p>rs</p><p>ity</p><p>(l</p><p>og</p><p>)</p><p>(a)</p><p>0</p><p>1</p><p>2</p><p>2.5 5.0 7.5 10.0</p><p>Regional pool(log)Tr</p><p>og</p><p>lo</p><p>bi</p><p>tic</p><p>sp</p><p>ec</p><p>ie</p><p>s r</p><p>ic</p><p>hn</p><p>es</p><p>s o</p><p>f e</p><p>ac</p><p>h</p><p>ta</p><p>xa</p><p>(l</p><p>og</p><p>+1</p><p>) (b)</p><p>−1</p><p>0</p><p>1</p><p>2</p><p>−2 −1 0 1</p><p>Residuals (S. biodiversity (log) vs. R. pool (log))Tr</p><p>og</p><p>lo</p><p>bi</p><p>tic</p><p>sp</p><p>ec</p><p>ie</p><p>s r</p><p>ic</p><p>hn</p><p>es</p><p>s o</p><p>f e</p><p>ac</p><p>h</p><p>ta</p><p>xa</p><p>(l</p><p>og</p><p>+1</p><p>) (c)</p><p>1</p><p>2</p><p>3</p><p>0.0 0.4 0.8 1.2</p><p>Residuals (S. biodiversity (log) vs. R. pool (log))Tr</p><p>og</p><p>lo</p><p>bi</p><p>tic</p><p>sp</p><p>ec</p><p>ie</p><p>s r</p><p>ic</p><p>hn</p><p>es</p><p>s o</p><p>f e</p><p>ac</p><p>h</p><p>ta</p><p>xa</p><p>(l</p><p>og</p><p>+1</p><p>) (d)</p><p>10  |     MENDES RABELO Et AL.</p><p>to analyse the data (Culver et al., 2006), but could also be related</p><p>to the high productivity observed in tropical regions, so that even</p><p>areas with relatively low productivity are capable of providing suf-</p><p>ficient resources for cave-restricted species, which usually present</p><p>low metabolic rates and, thus, demand less organic resources than</p><p>non-troglobitic species (Howarth & Moldovan, 2018). However, the</p><p>epigean primary productivity was relevant for the whole cave biodi-</p><p>versity, presenting a positive influence on the total species richness.</p><p>Another relevant landscape factor for the cave species richness</p><p>were the ecoregions. Despite being designed based on epigean com-</p><p>munities (Olson et al., 2001), they have already shown to be signif-</p><p>icant for the richness of obligate cave species in temperate regions</p><p>(Niemiller & Zigler, 2013). In Neotropical regions, the influence was</p><p>not significant for troglobitic species when independently evaluated.</p><p>However, it was important for understanding the cave total species</p><p>richness.</p><p>On the other hand, different from that observed in temperate</p><p>regions, none of the variables referring to epigean ecosystems were</p><p>relevant for the troglobitic species richness (Culver et al., 2003;</p><p>Niemiller & Zigler, 2013). However, as already noted in other stud-</p><p>ies, the cave size, which favours the occurrence of more isolated</p><p>subterranean habitats, was a relevant factor for troglobitic species</p><p>richness (Jaffé et al., 2018; Simões et al., 2015). Organic resources</p><p>tend to become scarce as we move away from the entrance regions</p><p>(Sket, 1999). Hence, larger caves tend to present stronger selective</p><p>pressures related to food scarcity, especially in areas far from en-</p><p>trances, thus, favouring the occurrence of specialized fauna which</p><p>present sensory, morphological and behavioural adaptations that en-</p><p>able their permanence in oligotrophic environments (Mitchell, 1969;</p><p>Romero, 2009a).</p><p>In addition to contributing to troglobitic species richness, cave</p><p>size also favours non-troglobitic species richness. Larger caves are</p><p>more attractive for bat colonies (Brunet & Medellín, 2001), which</p><p>promote greater microhabitat heterogeneity by importing or-</p><p>ganic resources such as food waste, guano and carcasses (Ferreira</p><p>et al., 2000; de Guimarães, 2014). Furthermore, regardless of the</p><p>presence of bats, larger caves are usually more complex regard-</p><p>ing their morphology, thus, presenting a higher variety of physical</p><p>microhabitats when compared with smaller caves (Vargas-Mena</p><p>et al., 2020). The heterogeneity of microhabitats and other re-</p><p>sources are important drivers of diversity and tend to be higher as</p><p>the habitat area increases (Gleason, 1922; Pacheco et al., 2020).</p><p>The greater the variety of resources, the greater the diversity</p><p>of associated colonizers (Smrž et al., 2015). In this sense, other</p><p>hypogean features, such as streams, also contribute to heteroge-</p><p>neity and consequently favour species richness, reinforcing that</p><p>observed by Simões et al. (2015) and Souza-Silva et al. (2020).</p><p>Additionally, cave entrances play a key role in structuring sub-</p><p>terranean communities as they represent the interface between</p><p>epigean and hypogean ecosystems. This allows us to understand</p><p>the positive relationship</p><p>between the number of entrances and</p><p>the cave's species richness (Prous et al., 2004, 2015; Souza-Silva</p><p>et al., 2020a).</p><p>In addition to all aforementioned factors from the epigean eco-</p><p>systems which influence the subterranean fauna, the cave species</p><p>composition also indicates a strong relationship with external fauna.</p><p>The relationship between taxa species richness of Subterranean bio-</p><p>diversity and Regional pools demonstrates that there is a propor-</p><p>tional association between the fauna of epigean and subterranean</p><p>ecosystems. Most of the cave invertebrate community can be pre-</p><p>dicted by the epigean community, but significant differences are ob-</p><p>served in the representativeness of groups in the cave environment.</p><p>Such differences may be attributed to the environmental filters in-</p><p>trinsic to the subterranean habitats, like the absence of light, oligot-</p><p>rophy and biological filters (Prous et al., 2015). As demonstrated by</p><p>the residual values of this regression model (LM 1), there is a signifi-</p><p>cant influence of such filters so that some taxa, such as Diptera and</p><p>Araneae, occur at higher proportions than expected while others,</p><p>like Thysanoptera, are much less frequently observed than expected.</p><p>The absence of a significant relationship between taxa troglobitic</p><p>species richness and their respective Regional pool species richness</p><p>indicates the role of environmental filters as diversity drivers. The</p><p>opposite was observed for the overall community, which mostly rep-</p><p>resented a proportional sample of the Regional pool, potentially as a</p><p>function of stochastic colonization events and the occurrence of oc-</p><p>casional species. However, as we observed, taxa containing troglo-</p><p>bitic species were favoured by these filters and presented a positive</p><p>relationship with LM 1 residuals, with significant explanatory power</p><p>F I G U R E 5   Residual values for the</p><p>taxa with recorded troglobitic species</p><p>extracted from the linear model relating</p><p>to the Subterranean biodiversity and the</p><p>Regional pool in Brazil (LM 1)</p><p>Orthoptera</p><p>Opiliones</p><p>Hemiptera</p><p>Amblypygi</p><p>Collembola</p><p>Spirostreptida</p><p>Isopoda</p><p>Palpigradi</p><p>Coleoptera</p><p>Polydesmida</p><p>Pseudoscorpiones</p><p>Araneae</p><p>0.0 0.4 0.8 1.2</p><p>Residual values</p><p>Ta</p><p>xa Richness</p><p>Below expected</p><p>Above expected</p><p>|  11MENDES RABELO Et AL.</p><p>regarding the initial model. This probably is related to the pre-ad-</p><p>aptations which allowed even the typically epigean taxa to colonize</p><p>deep zones of the subterranean habitats, thus, overcoming environ-</p><p>mental filter barriers (Chapman, 1982; Romero, 2009b). This rein-</p><p>forces the idea that diversity of troglophilic species can influence</p><p>the future diversity of troglobitic species (Howarth, 1980; Pipan &</p><p>Culver, 2012).</p><p>The present study demonstrates that cave biodiversity in</p><p>Neotropical regions, mainly troglobitic species, can respond in dif-</p><p>ferent ways compared with some patterns observed in temperate</p><p>regions. The biodiversity of Neotropical caves is highly influenced</p><p>by epigean and cave habitat features. Subterranean biodiversity is</p><p>influenced by the Regional pool, by the ecoregion it is in and the</p><p>number of cave entrances. This shows that a great part of the spe-</p><p>cies richness of subterranean habitats seems to be determined by</p><p>the species richness of the surrounding epigean ecosystems and can</p><p>be occasional. Moreover, most epigean taxa are partially composed</p><p>of a group of species able to occur in subterranean habitats, which</p><p>in general is a proportional sample of the Regional pool. This high-</p><p>lights the importance of caves for strategies in conserving inverte-</p><p>brate biodiversity as the Brazilian laws that guide the conservation</p><p>of caves consider not only the cave but also its surrounding area</p><p>of influence. This area is defined based on the long-term mainte-</p><p>nance of all physical and biotic attributes associated with the cave</p><p>(Resolução CONAMA No 347 & September10, 2004). Therefore,</p><p>such protection must include not only the area required to maintain</p><p>the energetic input but also the area to maintain the local pool of</p><p>epigean species, therefore guaranteeing the fauna flow. Also, caves</p><p>may represent strategic habitats for species conservation in the</p><p>face of climate change, as already shown in cases of relict species</p><p>(Mammola,Piano, Cardoso, et al., 2019; Pérez-González et al., 2017).</p><p>It is also important to highlight the high biotechnological potential</p><p>that they have (Mazina et al., 2019; Paula et al., 2019). However,</p><p>caves are still severely threatened and lack efficient conservation</p><p>strategies (Rabelo et al., 2018).</p><p>ACKNOWLEDG MENTS</p><p>We thank Professor Paulo dos Santos Pompeu, Anaíle Mendes</p><p>Rabelo and Marcela Pyles for suggestions and statistical support;</p><p>Stefano Mammola, Jon Sadler and anonymous reviewers for their</p><p>contributions; Jessica Schulte for contributions and English review;</p><p>taxonomists that helped on taxa identifications (L. Bernardi, A. C.</p><p>Vasconcelos, R. Bastos-Pereira, A. Brescovit, D. Zeppelini, R. Brito,</p><p>E. Araujo, L. F. Iniesta, L. Ázara, M. Villela, A. Neri, A. Silva-Neto, A.</p><p>Riverón, A. Asenjo, R. Souza, J. Vaz, L. Guimarães, P. Grossi, F. Vaz-</p><p>de-Melo, L. Hellman and S. Amaral); to the team from the Center of</p><p>Studies on Subterranean Biology who assisted with field work, to</p><p>the people who helped guide and accompany us while finding the</p><p>cave sites (Santinho, Bira, E. Gomes, E. Veloso, R. Sarmento, Lorão,</p><p>Aldelice and Nilsinho); to the managers and staff of Parque Estadual</p><p>da Lapa Grande for the welcome; to the staff of Parque Nacional</p><p>Cavernas do Peruaçu; to the people who helped in locating caves</p><p>and sending maps (F. Gonçalves, L. Zogbi, A. Auler and E. Rubioli);</p><p>to the groups of speleology who provided topographic maps (EPL,</p><p>GBPE and SEE), especially the espeleogrupo Peter Lund which also</p><p>accompanied in several field trips and the institutions that funded</p><p>the present project, scholarships and infrastructure (FAPEMIG, pro-</p><p>cess nº APQ 01281-13, CAPES, UFLA and VALE). RLF is also grateful</p><p>to the CNPq (grant n° 308334/2018-3). The samples were collected</p><p>according to the authorization for activities with scientific purpose</p><p>SISBIO Nº47829, Nº 54444 and IEF Nº 114/2014</p><p>DATA AVAIL ABILIT Y S TATEMENT</p><p>The data supporting the findings of this study are available within</p><p>the article and its appendices.</p><p>ORCID</p><p>Lucas Mendes Rabelo https://orcid.org/0000-0001-6276-8590</p><p>Marconi Souza-Silva https://orcid.org/0000-0002-3184-5319</p><p>Rodrigo Lopes Ferreira https://orcid.org/0000-0003-3288-4405</p><p>R E FE R E N C E S</p><p>Alvares, C. A., Stape, J. L., Sentelhas, P. C., De Moraes Gonçalves,</p><p>J. L., & Sparovek, G. (2013). Köppen’s climate classification map</p><p>for Brazil. Meteorologische Zeitschrift, 22(6), 711–728. https://doi.</p><p>org/10.1127/0941-2948/2013/0507</p><p>Auler, A. (2004). America, South. In J. Gunn (Eds.), Encyclopedia of Caves</p><p>and Karst Science (pp. 110–118). Taylor & Francis e-Library.</p><p>Auler, A. S. (2019). As Regiões Espeleológicas do Brasil. In E. Rubbioli,</p><p>A. S. Auler, D. Menin, & R. Brandi (Eds.), Cavernas - Atlas do Brasil</p><p>Subterrâneo (pp. 13–52). ICMBio - Instituto Chico Mendes de</p><p>Conservação da Biodiversidade.</p><p>Badino, G. (2010). Underground meteorology - “ What ’ S the weather</p><p>underground?” Podzemna Meteorologija : “ Kaksno Je Vreme</p><p>V Podzemlju ?”. Acta Carsologica, 39(3), 427–448. https://doi.</p><p>org/10.3986/ac.v39i3.74</p><p>Baptista, R. L. C., & Giupponi, A. D. L. P. (2003). A new troglomorphic</p><p>Charinus from Minas Gerais state, Brazil (Arachnida: Charinidae).</p><p>Revista Ibérica De Aracnología, 7(1981), 79–84.</p><p>Barr, T. C. (1968). Cave ecology and the evolution of troglobites. In T.</p><p>Dobzhansky, M. K. Hecht, & W. C. Steere (Eds.), Evolutionary biology,</p><p>(Vol. 2; pp. 35–102). Plenun press.</p><p>Barton, K. (2016). MuMIn: Multi-Model Inference. R package version 1. R</p><p>package version 1.15.6. https://cran.r-proje ct.org/packa ge=MuMIn</p><p>Bjornstad, O. N., & Cai, J. (n.d.). ncf: Spatial covariance functions. In R</p><p>Package (1.2-8; p. 45). https://cran.r-proje ct.org/packa ge=ncf</p><p>Booth, G. D., Niccolucci,</p><p>M. J., & Schuster, E. G. (1994). Identifying proxy</p><p>sets in multiple linear regression: An aid to better coefficient inter-</p><p>pretation. United States Department of Agriculture, Forest Service.</p><p>Intermountain Research Station, INT-470, 368.</p><p>Borsato, R., Loyola, R., Lemes, P., Silva, A., Cioato, M., & Garcia, M. (Eds.)</p><p>(2015). Ecorregiões do Brasil: Prioridades Terrestres e Marinhas: Vol III.</p><p>Instituto LIFE.</p><p>Brasil. (2019). Catálogo Taxonômico da Fauna do Brasil. http://</p><p>fauna.jbrj.gov.br/fauna/ lista Brasi l/Princ ipalU C/Princ ipalUC.do?-</p><p>lingu a=pt</p><p>Bregović, P., & Zagmajster, M. (2016). Understanding hotspots within a</p><p>global hotspot – identifying the drivers of regional species richness</p><p>patterns in terrestrial subterranean habitats. Insect Conservation</p><p>and Diversity, 9(4), 268–281. https://doi.org/10.1111/icad.12164</p><p>Brescovit, A. D., Ferreira, R. L., Silva, M. S., & Rheims, C. A. (2012).</p><p>Brasilomma gen. nov., a new prodidomid genus from Brazil (Araneae,</p><p>Prodidomidae). Zootaxa, 32(3572), 23–32.</p><p>https://orcid.org/0000-0001-6276-8590</p><p>https://orcid.org/0000-0001-6276-8590</p><p>https://orcid.org/0000-0002-3184-5319</p><p>https://orcid.org/0000-0002-3184-5319</p><p>https://orcid.org/0000-0003-3288-4405</p><p>https://orcid.org/0000-0003-3288-4405</p><p>https://doi.org/10.1127/0941-2948/2013/0507</p><p>https://doi.org/10.1127/0941-2948/2013/0507</p><p>https://doi.org/10.3986/ac.v39i3.74</p><p>https://doi.org/10.3986/ac.v39i3.74</p><p>https://cran.r-project.org/package=MuMIn</p><p>https://cran.r-project.org/package=ncf</p><p>http://fauna.jbrj.gov.br/fauna/listaBrasil/PrincipalUC/PrincipalUC.do?lingua=pt</p><p>http://fauna.jbrj.gov.br/fauna/listaBrasil/PrincipalUC/PrincipalUC.do?lingua=pt</p><p>http://fauna.jbrj.gov.br/fauna/listaBrasil/PrincipalUC/PrincipalUC.do?lingua=pt</p><p>https://doi.org/10.1111/icad.12164</p><p>12  |     MENDES RABELO Et AL.</p><p>Brunet, A. K., & Medellín, R. A. (2001). The species-area relationship in</p><p>bat assemblages of tropical caves. Journal of Mammalogy, 82(4), 1114–</p><p>1122. https://doi.org/10.1644/1545-1542(2001)082<1114:TSARI</p><p>B>2.0.CO;2</p><p>Burnham, K. P. & Anderson, D. R. (Eds.) (2002). Information and</p><p>Likelihood Theory: A Basis for Model Selection and Inference. In</p><p>Model selection and multimodel inference: A practical information-theo-</p><p>retic approach (Vol. 172, 2nd ed., pp. 49–97). Springer-verlag. https://</p><p>doi.org/10.1016/j.ecolm odel.2003.11.004</p><p>Burnham, K. P., Anderson, D. R., & Huyvaert, K. P. (2011). AIC model selec-</p><p>tion and multimodel inference in behavioral ecology: Some background,</p><p>observations, and comparisons. Behavioral Ecology and Sociobiology,</p><p>65(1), 23–35. https://doi.org/10.1007/s0026 5-010-1029-6</p><p>Carvalho, L. M. T., Oliveira, A. D., Mello, J. M., Acerbi Junior, F. W.,</p><p>Cavalcanti, H. C., & Vargas Filho, R. (2006). Projeto monitoramento</p><p>2005. In J. R. S. Scolforo & L. M. T. d. Carvalho (Eds.), Mapeamento</p><p>e inventario da flora nativa e reflorestamentos de Minas Gerais (1st ed.,</p><p>pp. 58–63). Editora UFLA.</p><p>Chapman, P. (1982). The origin of troglobites. Proceedings of the University</p><p>of Bristol Spelaeological Society, 16(2), 133–141.</p><p>Chesson, P. (2000). Mechanisms of maintenance of species diversity.</p><p>Annual Review of Ecology and Systematics, 31(1), 343–366. https://doi.</p><p>org/10.1146/annur ev.ecols ys.31.1.343</p><p>Christiansen, K. (1962). Proposition pour la classification des animaux</p><p>cavernicoles. Spelunca, 2, 75–78. https://doi.org/10.1017/CBO97</p><p>81107 415324.004</p><p>Christman, M. C., Culver, D. C., Madden, M. K., & White, D. (2005).</p><p>Patterns of endemism of the eastern North American cave</p><p>fauna. Journal of Biogeography, 32(8), 1441–1452. https://doi.</p><p>org/10.1111/j.1365-2699.2005.01263.x</p><p>Christman, M. C., Doctor, D. H., Niemiller, M. L., Weary, D. J., Young,</p><p>A., Zigler, K. S., & Culver, D. C. (2016). Predicting the occurrence of</p><p>cave-inhabiting fauna based on features of the earth surface envi-</p><p>ronment. PLoS One, 11(8), e0160408. https://doi.org/10.1371/journ</p><p>al.pone.0160408</p><p>Cox, C. B., Moore, P. D., & Ladle, R. J. (2016). Biogeography an ecological</p><p>and evolutionary approach, 9th ed. John Wiley & Sons.</p><p>Culver, D. C., Christman, M. C., Elliott, W. R., Iii, H. H. H., & Reddell, J.</p><p>R. (2003). The North American obligate cave fauna: Regional pat-</p><p>terns. Biodiversity and Conservation, 12, 441–468. https://doi.</p><p>org/10.1023/A:10224 25908017</p><p>Culver, D. C., Deharveng, L., Bedos, A., Lewis, J. J., Madden, M., Reddell,</p><p>J. R., Sket, B., Trontelj, P., & White, D. (2006). The mid-latitude bio-</p><p>diversity ridge in terrestrial cave fauna. Ecography, 29(1), 120–128.</p><p>https://doi.org/10.1111/j.2005.0906-7590.04435.x</p><p>Culver, D. C., & Pipan, T. (2019). The biology of caves and other subter-</p><p>ranean habitats (Second edi). Oxford University Press, https://doi.</p><p>org/10.1093/oso/97801 98820 765.001.0001</p><p>de Guimarães, M. (2014). Morcegos Cavernícolas Do Brasil: Composição,</p><p>Distribuição E Serviços Ambientais. Universidade Federal de Lavras.</p><p>de Paula, C. C. P., Montoya, Q. V., Meirelles, L. A., Farinas, C. S., Rodrigues,</p><p>A., & Seleghim, M. H. R. (2019). High cellulolytic activities in filamen-</p><p>tous fungi isolated from an extreme oligotrophic subterranean envi-</p><p>ronment (Catão cave) in Brazil. Anais Da Academia Brasileira De Ciências,</p><p>91(3), 1–11. https://doi.org/10.1590/0001-37652 01920 180583</p><p>Deharveng, L. & Bedos, A. (2012). Diversity patterns in the tropics. In</p><p>W. B. White & D. C. Culver (Eds.), Encyclopedia of caves (2nd ed., pp.</p><p>238–250). Elsevier Academic Press. https://doi.org/10.1029/2003G</p><p>L0173 52.Wang.</p><p>Elith, J., & Leathwick, J. R. (2009). Species distribution models: Ecological</p><p>s. Annual Review of Ecology, Evolution, and Systematics, 40, 677–697.</p><p>https://doi.org/10.1146/annur ev.ecols ys.110308.120159</p><p>Eme, D., Zagmajster, M., Fišer, C., Galassi, D., Marmonier, P., Stoch,</p><p>F., Cornu, J. F., Oberdorff, T., & Malard, F. (2015). Multi-causality</p><p>and spatial non-stationarity in the determinants of groundwater</p><p>crustacean diversity in Europe. Ecography, 38(5), 531–540. https://</p><p>doi.org/10.1111/ecog.01092</p><p>Evans, K. L., Warren, P. H., & Gaston, K. J. (2005). Species- en-</p><p>ergy relationships at the macroecological scale: A review of the</p><p>mechanisms. March, 1–25. https://doi.org/10.1017/S1464 79310</p><p>4006517</p><p>Ferreira, R. L., de Oliveira, M. P. A., & Souza-Silva, M. (2018). Subterranean</p><p>biodiversity in Ferruginous Landscapes. In O. T. Moldovan, Ľ. Kováč,</p><p>& S. Halse (Eds.), Cave ecology (1st ed., Vol. 235, pp. 435–447).</p><p>Springer International Publishing. https://doi.org/10.1007/978-3-</p><p>319-98852 -8</p><p>Ferreira, R. L., Martins, R. P., & Yanega, D. (2000). Ecology of bat guano</p><p>arthropod communities in a Brazilian dry cave. Ecotropica, 6(2),</p><p>105–116.</p><p>Fick, S. E., & Hijmans R. J. (2017). WorldClim 2: New 1-km spatial reso-</p><p>lution climate surfaces for global land areas. International Journal of</p><p>Climatology, 37(12), 4302–4315. https://doi.org/10.1002/joc.5086</p><p>Gaston, K. J. (2000). Global patterns in biodiversity. Nature, 405(6783),</p><p>220–227. https://doi.org/10.1038/35012228</p><p>Gleason, H. A. (1922). On the relation between species and area. Ecology,</p><p>3(2), 158–162. https://doi.org/10.2307/1929150</p><p>Google LLC. (2019). Google Earth Pro (7.3.2.5776 (32-bit)). Google LLC.</p><p>Hartig, F. (2019). DHARMa: Residual Diagnostics for Hierarchical (Multi-</p><p>Level /Mixed) Regression Models (R package version 0.2.6). https://</p><p>cran.r-proje ct.org/packa ge=DHARMa</p><p>Howarth, F. G. (1980). The zoogeography of specialized cave ani-</p><p>mals: A bioclimatic model. Evolution, 34(2), 394–406. https://doi.</p><p>org/10.2307/2407402</p><p>Howarth, F. G. & Moldovan, O. T. (2018). The ecological classification</p><p>of cave animals and their adaptations. In O. T. Moldovan, Ľ. Kováč,</p><p>& S. Halse (Eds.), Cave ecology (pp. 41–67). Springer. https://doi.</p><p>org/10.1007/978-3-319-98852 -8_4</p><p>Iniesta, L. F. M., & Ferreira, R. L. (2015). Pseudonannolene lundi n.</p><p>sp., a new troglobitic millipede from a Brazilian limestone cave</p><p>(Spirostreptida: Pseudonannolenidae). Zootaxa, 3949(1), 123–128.</p><p>https://doi.org/10.11646/ zoota xa.3949.1.6.</p><p>Jaffé, R., Prous, X., Calux, A., Gastauer, M., Nicacio, G., Zampaulo,</p><p>R., Souza-Filho, P. W. M., Oliveira, G., Brandi, I. V., & Siqueira, J.</p><p>O. (2018). Conserving relics from ancient underground worlds:</p><p>Assessing the influence of cave and landscape features on obligate</p><p>iron cave dwellers from the Eastern Amazon. PeerJ, 6, e4531. https://</p><p>doi.org/10.7717/peerj.4531</p><p>Johnson, J. B., & Omland, K. S. (2004). Model selection in ecology and</p><p>evolution. Trends in Ecology and Evolution, 19(2), 101–108. https://doi.</p><p>org/10.1016/j.tree.2003.10.013</p><p>Juan, C., Guzik, M. T., Jaume, D., & Cooper, S. J. B. (2010). Evolution</p><p>in caves: Darwin’s “wrecks of ancient life” in the molecu-</p><p>lar era. Molecular Ecology, 19(18), 3865–3880. https://doi.</p><p>org/10.1111/j.1365-294X.2010.04759.x</p><p>Köppen, W. (1936). Das geographische System der Klimate. Handbuch</p><p>Der Klimatologie, c, 7–30, https://doi.org/10.3354/cr01204</p><p>Mammola, S. (2019). Finding answers in the dark: Caves as models in</p><p>ecology fifty years after Poulson and White. Ecography, 42(7),</p><p>1331–1351.</p><p>Mammola, S., Cardoso, P., Angyal, D., Balázs, G., Blick, T., Brustel, H.,</p><p>Carter, J., Ćurčić, S., Danflous, S., Dányi, L., Déjean, S., Deltshev, C.,</p><p>Elverici, M., Fernández, J., Gasparo, F., Komnenov, M., Komposch,</p><p>C., Kováč, L., Kunt, K. B., … Isaia, M. (2019). Local-versus broad-</p><p>scale environmental drivers of continental β-diversity patterns in</p><p>subterranean spider communities across Europe. Proceedings of</p><p>the Royal Society B: Biological Sciences, 286(1914), 1–9. https://doi.</p><p>org/10.1098/rspb.2019.1579</p><p>Mammola, S., Cardoso, P., Culver, D. C., Deharveng, L., Ferreira, R. L.,</p><p>Fišer, C., Galassi, D. M. P., Griebler, C., Halse, S., Humphreys, W. F.,</p><p>Isaia, M., Malard, F., Martinez, A., Moldovan, O. T., Niemiller, M. L.,</p><p>https://doi.org/10.1644/1545-1542(2001)082%3C1114:TSARIB%3E2.0.CO;2</p><p>https://doi.org/10.1644/1545-1542(2001)082%3C1114:TSARIB%3E2.0.CO;2</p><p>https://doi.org/10.1016/j.ecolmodel.2003.11.004</p><p>https://doi.org/10.1016/j.ecolmodel.2003.11.004</p><p>https://doi.org/10.1007/s00265-010-1029-6</p><p>https://doi.org/10.1146/annurev.ecolsys.31.1.343</p><p>https://doi.org/10.1146/annurev.ecolsys.31.1.343</p><p>https://doi.org/10.1017/CBO9781107415324.004</p><p>https://doi.org/10.1017/CBO9781107415324.004</p><p>https://doi.org/10.1111/j.1365-2699.2005.01263.x</p><p>https://doi.org/10.1111/j.1365-2699.2005.01263.x</p><p>https://doi.org/10.1371/journal.pone.0160408</p><p>https://doi.org/10.1371/journal.pone.0160408</p><p>https://doi.org/10.1023/A:1022425908017</p><p>https://doi.org/10.1023/A:1022425908017</p><p>https://doi.org/10.1111/j.2005.0906-7590.04435.x</p><p>https://doi.org/10.1093/oso/9780198820765.001.0001</p><p>https://doi.org/10.1093/oso/9780198820765.001.0001</p><p>https://doi.org/10.1590/0001-3765201920180583</p><p>https://doi.org/10.1029/2003GL017352.Wang</p><p>https://doi.org/10.1029/2003GL017352.Wang</p><p>https://doi.org/10.1146/annurev.ecolsys.110308.120159</p><p>https://doi.org/10.1111/ecog.01092</p><p>https://doi.org/10.1111/ecog.01092</p><p>https://doi.org/10.1017/S1464793104006517</p><p>https://doi.org/10.1017/S1464793104006517</p><p>https://doi.org/10.1007/978-3-319-98852-8</p><p>https://doi.org/10.1007/978-3-319-98852-8</p><p>https://doi.org/10.1002/joc.5086</p><p>https://doi.org/10.1038/35012228</p><p>https://doi.org/10.2307/1929150</p><p>https://cran.r-project.org/package=DHARMa</p><p>https://cran.r-project.org/package=DHARMa</p><p>https://doi.org/10.2307/2407402</p><p>https://doi.org/10.2307/2407402</p><p>https://doi.org/10.1007/978-3-319-98852-8_4</p><p>https://doi.org/10.1007/978-3-319-98852-8_4</p><p>https://doi.org/10.11646/zootaxa.3949.1.6.</p><p>https://doi.org/10.7717/peerj.4531</p><p>https://doi.org/10.7717/peerj.4531</p><p>https://doi.org/10.1016/j.tree.2003.10.013</p><p>https://doi.org/10.1016/j.tree.2003.10.013</p><p>https://doi.org/10.1111/j.1365-294X.2010.04759.x</p><p>https://doi.org/10.1111/j.1365-294X.2010.04759.x</p><p>https://doi.org/10.3354/cr01204</p><p>https://doi.org/10.1098/rspb.2019.1579</p><p>https://doi.org/10.1098/rspb.2019.1579</p><p>|  13MENDES RABELO Et AL.</p><p>Pavlek, M., Reboleira, A. S. P. S., Souza-Silva, M., Teeling, E. C., …</p><p>Zagmajster, M. (2019). Scientists’ warning on the conservation of</p><p>subterranean ecosystems. BioScience, 69(8), 641–650. https://doi.</p><p>org/10.1093/biosc i/biz064</p><p>Mammola, S., & Leroy, B. (2018). Applying species distribution models to</p><p>caves and other subterranean habitats. Ecography, 41(7), 1194–1208.</p><p>https://doi.org/10.1111/ecog.03464</p><p>Mammola, S., Piano, E., Cardoso, P., Vernon, P., Domínguez-Villar, D.,</p><p>Culver, D. C., Pipan, T., & Isaia, M. (2019). Climate change going</p><p>deep: The effects of global climatic alterations on cave ecosystems.</p><p>Anthropocene Review, 6(1–2), 98–116. https://doi.org/10.1177/20530</p><p>19619 851594</p><p>Mammola, S., Piano, E., Malard, F., Vernon, P., & Isaia, M. (2019).</p><p>Extending Janzen’s hypothesis to temperate regions: A test using</p><p>subterranean ecosystems. Functional Ecology, 33(9), 1638–1650.</p><p>https://doi.org/10.1111/1365-2435.13382</p><p>Maurer, B. A. (2009). Spatial patterns of species diversity in terrestrial</p><p>environments. In S. A. Levin (Ed.), The princeton guide to Ecology (1st</p><p>ed., pp. 464–473). Princeton University Press.</p><p>Mazina, S. E., Egorov, M. I., & Harlamova, M. D. (2019). Plastics biode-</p><p>struction under the impact of caves micromycetes. IOP Conference</p><p>Series: Earth and Environmental Science, 272(3), 032068. https://doi.</p><p>org/10.1088/1755-1315/272/3/032068</p><p>Milanovic, P. T. (2005). Water resources engineering in karst. Vol.1. CRC</p><p>Press Taylor & Francis Group.</p><p>Mitchell, R. W. (1969). A comparison of temperate and tropical cave</p><p>communities. The Southwestern Naturalist, 14(1), 73–88. https://doi.</p><p>org/10.2307/3669249</p><p>Moldovan, O. T., Kováč, Ľ., & Halse, S. (Eds.) (2018). Cave ecology. Vol.</p><p>235. Springer International Publishing. https://doi.org/10.1007/978-</p><p>3-319-98852 -8</p><p>Niemiller, M. L., & Zigler, K. S. (2013). Patterns of cave biodiversity and</p><p>endemism in the appalachians and interior plateau of Tennessee,</p><p>USA. PLoS One, 8(5), e64177. https://doi.org/10.1371/journ</p><p>al.pone.0064177</p><p>Novak, T., Perc, M., Lipovšek, S., & Janžekovič, F. (2012). Duality of ter-</p><p>restrial subterranean fauna. International Journal of Speleology Official</p><p>Journal of Union Internationale De Spéléologie, 41(2), 181–188. https://</p><p>doi.org/10.5038/1827-806X.41.2.5</p><p>Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D.,</p><p>Powell, G. V. N., Underwood, E. C., D'amico, J. A., Itoua, I., Strand, H.</p><p>E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y.,</p><p>Lamoreux, J. F., Wettengel, W. W., Hedao, P., & Kassem, K. R. (2001).</p><p>Terrestrial ecoregions of the World: A new map of life on earth.</p><p>BioScience, 51(11), 933–938.</p><p>Pacheco, G. S. M., Silva, M. S., Cano, E., & Ferreira, R. L. (2020). The role</p><p>of microhabitats in structuring cave invertebrate communities in</p><p>Guatemala. International Journal of Speleolog, 49(2), 161–169. https://</p><p>doi.org/10.5038/1827-806X.49.2.2333</p><p>Pereira, H. C. & Papadakis, J. (2014). Potential Evapotranspiration. In M.</p><p>B. Kirkham (Ed.), Principles of soil and plant water relations (2nd edn)</p><p>(Second, Vol. 2, Issue 2, pp. 455–468). Academic Press. https://doi.</p><p>org/10.2307/2401496</p><p>Pérez-González, A., Ceccarelli, F. S., Monte, B. G. O., Proud, D. N.,</p><p>DaSilva, M. B., & Bichuette, M. E. (2017). Light from dark: A relict-</p><p>ual troglobite reveals a broader ancestral distribution for kimulid</p><p>harvestmen (Opiliones: Laniatores: Kimulidae) in South America.</p><p>PLoS One, 12(11), e0187919, https://doi.org/10.1371/journ</p><p>al.pone.0187919</p><p>Peterson, B. G., & Carl, P. (2014). PerformanceAnalytics: Econometric</p><p>tools for performance and risk analysis. R package version</p><p>1.4.3541.ht tps://cran.r–project .org/package=Performance</p><p>Analytics</p><p>Pinto-da-Rocha, R. (1996). Iandumoema uai, a new genus and spe-</p><p>cies of troglobitic harvestman from Brazil (Arachnida, Opiliones,</p><p>Gonyleptidae). Revista Brasileira De Zoologia, 13(4), 843–848. https://</p><p>doi.org/10.1590/S0101 -81751 99600 0400005</p><p>Pipan, T., & Culver, D. C. (2012). Convergence and divergence in the subter-</p><p>ranean realm: A reassessment. Biological Journal of the Linnean Society,</p><p>107(1), 1–14. https://doi.org/10.1111/j.1095-8312.2012.01964.x</p><p>Poulson, L. T., & White, B. W. (1969). The cave environment. Science,</p><p>165(3897), 971–981.</p><p>Prevorcnik, S., Ferreira, R. L., & Sket, B. (2012). Brasileirinidae, a new iso-</p><p>pod family (Crustaceae: Isopoda) from the cave in Bahia (Brazil) with</p><p>a discussion on its taxonomic position. Zootaxa, 65(3452), 47–65.</p><p>Prous, X., Ferreira, R. L., & Jacobi, C. M. (2015). The entrance as a com-</p><p>plex ecotone in a Neotropical cave. International Journal of Speleology,</p><p>44(2), 177–189. https://doi.org/10.5038/1827-806X.40.1.2</p><p>Prous, X., Ferreira, R. L., & Martins, R. P. (2004). Ecotone delimitation:</p><p>Epigean – hypogean transition in cave ecosystems. Austral Ecology,</p><p>29, 374–382.</p><p>R Core Team (2019). R: A Language and Environment for Statistical</p><p>Computing (3.3.2). R Foundation for Statistical Computing. https://</p><p>www.r-proje ct.org/</p><p>Rabelo, L. M., Souza-Silva, M., & Ferreira, R. L. (2018). Priority caves for</p><p>biodiversity conservation in a key karst area of Brazil: Comparing</p><p>the applicability of cave conservation indices. Biodiversity and</p><p>Conservation, 27(9), 2097–2129. https://doi.org/10.1007/s1053</p><p>1-018-1554-6</p><p>Ratton, P., Mahnert, V., & Ferreira, R. L. (2012). A new cave-dwelling</p><p>species of Spelaeobochica (Pseudoscorpiones: Bochicidae) from</p><p>Brazil. Journal of Arachnology, 40, 274–280. https://doi.org/10.1636/</p><p>Ha12-39.1</p><p>Resolução CONAMA No 347, de 10 de setembro de 2004, Diário oficial</p><p>da união (2004). https://doi.org/10.1017/CBO97 81107 415324.004</p><p>Rivera, M. A. J., Howarth, F. G., Taiti, S., & Roderick, G. K. (2002). Evolution</p><p>in Hawaiian cave-adapted isopods (Oniscidea: Philosciidae): Vicariant</p><p>speciation or adaptive shifts? Molecular Phylogenetics and Evolution,</p><p>25(1), 1–9. https://doi.org/10.1016/S1055 -7903(02)00353 -6</p><p>Romero, A. (Ed.) (2009a). The ecology of cave organisms. A. Romero,</p><p>In Cave biology life in darkness (1st ed., pp. 159–181). Cambridge</p><p>University Press.</p><p>Romero, A. (Ed.) (2009b). The evolutionary biology of cave organisms.</p><p>In Cave biology life in darkness (1st ed., pp. 130–158). Cambridge</p><p>University Press.</p><p>Sánchez-Fernández, D., Rizzo, V., Bourdeau, C., Cieslak, A., Comas, J.,</p><p>Faille, A., Fresneda, J., Lleopart, E., Millán, A., Montes, A., Pallarés, S.,</p><p>& Ribera, I. (2018). The deep subterranean environment as a poten-</p><p>tial model system in ecological, biogeographical and evolutionary re-</p><p>search. Subterranean Biology, 25, 1–7. https://doi.org/10.3897/subtb</p><p>iol.25.23530</p><p>Schneider, K., Christman, M. C., & Fagan, W. F. (2011). The influence of</p><p>resource subsidies on cave invertebrates: Results from an ecosys-</p><p>tem-level manipulation experiment. Ecology, 92(3), 765–776. https://</p><p>doi.org/10.1890/10-0157.1</p><p>Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for nor-</p><p>mality (Complete Samples). Biometrika, 52(3/4), 591–611. https://doi.</p><p>org/10.1093/biome t/52.3-4.591</p><p>Simões, M. H., Souza-silva, M., & Ferreira, R. L. (2015). Cave physical</p><p>attributes influencing the structure of terrestrial invertebrate com-</p><p>munities in Neotropics. Subterranean Biology, 16, 103–121. https://</p><p>doi.org/10.3897/subtb iol.16.5470</p><p>Sket, B. (1999). The nature of biodiversity in hypogean waters and how</p><p>it is endangered. Biodiversity and Conservation, 8(10), 1319–1338.</p><p>https://doi.org/10.1023/A:10089 16601121</p><p>Sket, B. (2008). Can we agree on an ecological classification of subter-</p><p>ranean animals? Journal of Natural History, 42(21–22), 1549–1563.</p><p>https://doi.org/10.1080/00222 93080 1995762</p><p>Smrž, J., Kováč, Ľ., Mikeš, J., Šustr, V., Lukešová, A., Tajovsky, K.,</p><p>Nováková, A., & Režňáková, P. (2015). Food sources of selected</p><p>https://doi.org/10.1093/biosci/biz064</p><p>https://doi.org/10.1093/biosci/biz064</p><p>https://doi.org/10.1111/ecog.03464</p><p>https://doi.org/10.1177/2053019619851594</p><p>https://doi.org/10.1177/2053019619851594</p><p>https://doi.org/10.1111/1365-2435.13382</p><p>https://doi.org/10.1088/1755-1315/272/3/032068</p><p>https://doi.org/10.1088/1755-1315/272/3/032068</p><p>https://doi.org/10.2307/3669249</p><p>https://doi.org/10.2307/3669249</p><p>https://doi.org/10.1007/978-3-319-98852-8</p><p>https://doi.org/10.1007/978-3-319-98852-8</p><p>https://doi.org/10.1371/journal.pone.0064177</p><p>https://doi.org/10.1371/journal.pone.0064177</p><p>https://doi.org/10.5038/1827-806X.41.2.5</p><p>https://doi.org/10.5038/1827-806X.41.2.5</p><p>https://doi.org/10.5038/1827-806X.49.2.2333</p><p>https://doi.org/10.5038/1827-806X.49.2.2333</p><p>https://doi.org/10.2307/2401496</p><p>https://doi.org/10.2307/2401496</p><p>https://doi.org/10.1371/journal.pone.0187919</p><p>https://doi.org/10.1371/journal.pone.0187919</p><p>https://doi.org/10.1590/S0101-81751996000400005</p><p>https://doi.org/10.1590/S0101-81751996000400005</p><p>https://doi.org/10.1111/j.1095-8312.2012.01964.x</p><p>https://doi.org/10.5038/1827-806X.40.1.2</p><p>https://www.r-project.org/</p><p>https://www.r-project.org/</p><p>https://doi.org/10.1007/s10531-018-1554-6</p><p>https://doi.org/10.1007/s10531-018-1554-6</p><p>https://doi.org/10.1636/Ha12-39.1</p><p>https://doi.org/10.1636/Ha12-39.1</p><p>https://doi.org/10.1017/CBO9781107415324.004</p><p>https://doi.org/10.1016/S1055-7903(02)00353-6</p><p>https://doi.org/10.3897/subtbiol.25.23530</p><p>https://doi.org/10.3897/subtbiol.25.23530</p><p>https://doi.org/10.1890/10-0157.1</p><p>https://doi.org/10.1890/10-0157.1</p><p>https://doi.org/10.1093/biomet/52.3-4.591</p><p>https://doi.org/10.1093/biomet/52.3-4.591</p><p>https://doi.org/10.3897/subtbiol.16.5470</p><p>https://doi.org/10.3897/subtbiol.16.5470</p><p>https://doi.org/10.1023/A:1008916601121</p><p>https://doi.org/10.1080/00222930801995762</p><p>14  |     MENDES RABELO Et AL.</p><p>terrestrial cave arthropods. Subterranean Biology, 16, 37–46. https://</p><p>doi.org/10.3897/subtb iol.16.8609</p><p>Souza, M. F., & Ferreira, R. L. (2010). Eukoenenia (Palpigradi:</p><p>Eukoeneniidae) in Brazilian caves with the first troglobiotic palpi-</p><p>grade from South America. The Journal of Arachnology, 38(3), 415–</p><p>424. https://doi.org/10.1636/Ha09-112.1</p><p>Souza, M. F. V. R., & Ferreira, R. L. (2018). Pandora is on Earth: New</p><p>species of Eukoenenia (Palpigradi) emerging at risk of extinction.</p><p>Invertebrate Systematics, 32(3), 581. https://doi.org/10.1071/is17049</p><p>Souza-Silva, M., Bernardi, L. F. O., Martins, R. P., & Ferreira, R. L. (2012).</p><p>Transport and consumption of organic detritus in a neotropical lime-</p><p>stone cave. Acta Carstologica, 41(1), 139–150. http://apps.isikn owled</p><p>ge.com/full_record.do?produ ct=UA&search_mode=Citin gArti</p><p>cles&qid=2&SID=W1mns gAXya ggjbc uZuF&page=1&doc=29</p><p>Souza-Silva, M., Iniesta, L. F. M., & Ferreira, R. L. (2020a). Cave lithology</p><p>effect on subterranean biodiversity: A case study in quartzite and</p><p>granitoid caves. Acta Oecologica, 108(August), 103645. https://doi.</p><p>org/10.1016/j.actao.2020.103645</p><p>Souza-Silva, M., Iniesta, L. F. M., & Ferreira, R. L. (2020b). Invertebrates</p><p>diversity in mountain Neotropical quartzite caves : Which factors</p><p>can influence the composition, richness, and distribution of the</p><p>cave communities ? Subterranean Biology, 33, 23–43. https://doi.</p><p>org/10.3897/subtb iol.33.46444</p><p>Szinwelski, N., Rosa, C. S., De Castro Solar, R. R., & Sperber, C. F.</p><p>(2015). Aggregation of cricket activity in response to resource ad-</p><p>dition increases local diversity. PLoS One, 10(10), 1–11. https://doi.</p><p>org/10.1371/journ al.pone.0139669</p><p>Trabucco, A., & Zomer, R. J. (2019). Global high-resolution soil-water bal-</p><p>ance. Figshare. https://doi.org/10.6084/m9.figsh are.77076 05.v3</p><p>Trajano, E., & Bichuette, M. E. (2010). Diversity of Brazilian subterranean</p><p>invertebrates, with a list of troglomorphic taxa. Subterranean Biology,</p><p>7(August), 1–16.</p><p>Vargas-Mena, J. C., Cordero-Schmidt, E., Rodriguez-Herrera, B., Medellín,</p><p>R. A., de Bento, D. M., & Venticinque, E. M. (2020). Inside or out?</p><p>Cave size and landscape effects on cave-roosting bat assemblages</p><p>in Brazilian Caatinga caves. Journal of Mammalogy, 101(2), 464–475.</p><p>https://doi.org/10.1093/jmamm al/gyz206</p><p>Venturini, A. (2018). washeR: Time Series Outlier Detection (R package</p><p>version 0.1.2; pp. 1–6). https://cran.r-proje ct.org/packa ge=washeR</p><p>Wessel, A., Hoch, H., Asche, M., Von Rintelen, T., Stelbrink, B.,</p><p>Heck, V., Stone, F. D., & Howarth, F. G. (2013). Founder effects</p><p>initiated rapid species radiation in Hawaiian cave planthoppers.</p><p>Proceedings of the National Academy of Sciences</p>