Ecology

Cardoso, Y. P. et al. A continental-wide molecular approach unraveling mtDNA diversity and geographic distribution of the Neotropical genus Hoplias. PLoS ONE 13(8), e0202024. https://doi.org/10.1371/journal.pone.0202024 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bertollo, L. A. C., Born, G. G., Dergam, J. A., Fenocchio, A. S. & Moreira-Filho, O. A biodiversity approach in the Neotropical Erythrinidae fish, Hoplias malabaricus: Karyotypic survey, geographic distribution of karyomorphs and cytotaxonomic considerations. Chrom. Res. 8(7), 603–613 (2000).CAS 
Article 

Google Scholar 
Oyakawa, O. T. Family Erythrinidae (Trahiras). in Check list of the freshwater fishes of South and Central America (Reis, R. E., Kullander, S. O. & Ferraris, C.). Edipucrs 238–240 (Porto Alegre, 2003).Dagosta, F. C. P. & de Pinna, M. C. C. The fishes of the Amazon: distribution and biogeographical patterns, with a comprehensive list of species. Bull. Am. Museum Nat. Hist. 431, 1–163 (2019).
Google Scholar 
Da Rosa, R., Vicari, M. R., Dias, A. L. & Giuliano-Caetano, L. New insights into the biogeographic and Karyotypic Evolution of Hoplias Malabaricus. Zebrafish 11(3), 198–206. https://doi.org/10.1089/zeb.2013.0953 (2014).CAS 
Article 
PubMed 

Google Scholar 
Santos, U. et al. Molecular and karyotypic phylogeography in the neotropical Hoplias malabaricus (Erythrinidae) fish in eastern Brazil. J. Fish Biol. 75(9), 2326–2343. https://doi.org/10.1111/j.1095-8649.2009.02489.x (2009).CAS 
Article 
PubMed 

Google Scholar 
Blanco, D. R., Lui, R. L., Bertollo, L. A. C., Diniz, D. & Filho, O. M. Characterization of invasive fish species in a river transposition region: Evolutionary chromosome studies in the genus Hoplias (Characiformes, Erythrinidae). Rev. Fish Biol. Fish. 20(1), 1–8. https://doi.org/10.1007/s11160-009-9116-3 (2010).Article 

Google Scholar 
Jacobina, U. P. et al. DNA barcode sheds light on systematics and evolution of neotropical freshwater trahiras. Genetica 146, 505. https://doi.org/10.1007/s10709-018-0043-x (2018).CAS 
Article 
PubMed 

Google Scholar 
Marques, D. F., Santos, F. A., da Silva, S. S., Sampaio, I. & Rodrigues, L. R. R. Cytogenetic and DNA barcoding reveals high divergence within the trahira, Hoplias malabaricus (Characiformes: Erythrinidae) from the lower Amazon River. Neotrop. Ichthyol. 11(2), 459–466. https://doi.org/10.1590/S1679-62252013000200015 (2013).Article 

Google Scholar 
Paz, F. P. C., Batista, J. S. & Porto, J. I. R. DNA barcodes of rosy tetras and allied species (Characiformes: Characidae: Hyphessobrycon) from the Brazilian Amazon Basin. PLoS ONE 9(5), e98603. https://doi.org/10.1371/journal.pone.0098603 (2014).ADS 
CAS 
Article 

Google Scholar 
Guimarães, K. L. A., de Sousa, M. P. A., Ribeiro, F. R. V., Porto, J. I. R. & Rodrigues, L. R. R. DNA barcoding of fish fauna from low order streams of Tapajós River basin. PLoS ONE 13(12), e0209430. https://doi.org/10.1371/journal.pone.0209430 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Machado, V. N. et al. One thousand DNA barcodes of piranhas and pacus reveal geographic structure and unrecognized diversity in the Amazon. Sci. Rep. 8, 8387. https://doi.org/10.1038/s41598-018-26550-x (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Hebert, P. D. N., Cywinska, A., Ball, S. L. & Dewaard, J. R. Biological identifications through DNA barcodes. Philos. Trans. R. Soc. B 270(1512), 313–321. https://doi.org/10.1098/rspb.2002.2218 (2003).CAS 
Article 

Google Scholar 
Pugedo, M. L., de Andrade Neto, F. R., Pessali, T. C., Birindelli, J. L. O. & Carvalho, D. C. Integrative taxonomy supports new candidate fish species in a poorly studied neotropical region: the Jequitinhonha River Basin. Genetica 144(3), 1–9. https://doi.org/10.1007/s10709-016-9903-4 (2016).Article 

Google Scholar 
Rosso, J. J. et al. Integrative taxonomy reveals a new species of the Hoplias malabaricus species complex (Teleostei: Erythrinidae). Ichthyol. Explor. Freshw. 1, 1–18. https://doi.org/10.23788/IEF-1076 (2018).Article 

Google Scholar 
Azpelicueta, M. M., Benítez, M., Aichino, D. & Mendez, C. M. D. A new species of the genus Hoplias (Characiformes, Erythrinidae), a tararira from the lower Paraná River, in Missiones, Argentina. Acta Zool. Lilloana 59(1–2), 71–82 (2015).
Google Scholar 
Rosso, J. J. et al. A new species of the Hoplias malabaricus species complex (Characiformes: Erythrinidae) from the La Plata River basin. Cybium 40(3), 199–208 (2016).
Google Scholar 
Cardoso, Y. P. & Montoya-Burgos, J. I. Unexpected diversity in the catfish Pseudancistrus brevispinis reveals dispersal routes in a Neotropical center of endemism: The Guyanas Region. Mol. Ecol. 18(5), 947–964. https://doi.org/10.1111/j.1365-294X.2008.04068.x (2009).CAS 
Article 
PubMed 

Google Scholar 
Hoorn, C., Wesselingh, F. P., Hovikoski, J. & Guerrero, J. The development of the Amazonian mega-wetland (Miocene; Brazil, Colombia, Peru, Bolivia). Amazon. Landsc. Species Evol. https://doi.org/10.1002/9781444306408.ch8 (2010).Article 

Google Scholar 
Albert, J. S. & Reis, R. E. Introduction to neotropical freshwaters. In Historical Biogeography of Neotropical Freshwater Fishes (eds Albert, J. S. & Reis, R. E.) 3–19 (University of California Press, 2011).
Google Scholar 
Leys, M., Keller, I., Räsänen, K., Gattolliat, J.-L. & Robinson, C. T. Distribution and population genetic variation of cryptic species of the Alpine mayfly Baetis alpinus (Ephemeroptera: Baetidae) in the Central Alps. BMC Evol. Biol. https://doi.org/10.1186/s12862-016-0643-y (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Aljanabi, S. M. & Martinez, I. Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques. Nucleic Acids Res. 25(22), 4692–4693 (1997).CAS 
Article 

Google Scholar 
Vitorino, C. A., Oliveira, R. C. C., Margarido, V. P. & Venere, P. C. Genetic diversity of Arapaima gigas (Schinz, 1822) (Osteoglossiformes: Arapaimidae) in the Araguaia-Tocantins basin estimated by ISSR marker. Neotrop. Ichthyol. 13, 557–568. https://doi.org/10.1590/1982-0224-20150037 (2015).Article 

Google Scholar 
Ward, R. D., Zemlak, T. S., Innes, B. H., Last, P. R. & Hebert, P. D. N. DNA barcoding Australia’s fish species. Philos. Trans. R. Soc. B 359, 1847–1857. https://doi.org/10.1098/srtb.2005.1716 (2005).Article 

Google Scholar 
Dunn, I. S. & Blattner, F. R. Sharons 36 to 40: Multienzyme, high capacity, recombination deficient replacement vectors with polylinkers and polystuffers. Nucleic Acids Res. 15, 2677–2698 (1987).CAS 
Article 

Google Scholar 
Thompson, J. D., Higgins, D. G. & Gibson, T. J. CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22(22), 4673–4680 (1994).CAS 
Article 

Google Scholar 
Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552. https://doi.org/10.1093/oxfordjournals.molbev.a026334 (2000).CAS 
Article 

Google Scholar 
Ratnasingham, S. & Hebert, P. D. N. DNA-Based registry for all animal species: The Barcode Index Number (BIN) system. PLoS ONE 8(7), e66213. https://doi.org/10.1371/journal.pone.0066213 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Pons, J. et al. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Syst. Biol. 55(4), 595–609. https://doi.org/10.1080/10635150600852011 (2006).Article 
PubMed 

Google Scholar 
Fujisawa, T. & Barraclough, T. G. Delimiting species using single-locus data and the generalized mixed yule coalescent approach: A revised method and evaluation on simulated data sets. Syst. Biol. 62(5), 707–724. https://doi.org/10.1093/sysbio/syt033 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Puillandre, N., Lambert, A., Brouillet, S. & Achaz, G. ABGD, automatic barcode gap discovery for primary species delimitation. Mol. Ecol. 21(8), 1864–1877. https://doi.org/10.1111/j.1365-294X.2011.05239.x (2012).CAS 
Article 
PubMed 

Google Scholar 
Drummond, A. & Rambaut, A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7, 214. https://doi.org/10.1186/1471-2148-7-214 (2007).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Posada, D. jModelTest: Phylogenetic model averaging. Mol. Biol. Evol. 25, 1253–1256. https://doi.org/10.1093/molbev/msn083 (2008).CAS 
Article 
PubMed 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ (2017).Ezard, T., Fujisawa, T. & Barraclough, T. splits: Species Limits by Threshold Statistics. R package version 1.0–19/r52. https://R-Forge.R-project.org/projects/splits/ (2017).Paradis, E. & Schliep, K. ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2018).Article 

Google Scholar 
Bermingham, E., McCafferty, S. S. & Martin, A. P. Fish biogeography and molecular clocks: Perspectives from the Panamanian Isthmus. In Molecular Systematics of Fishes (eds Kocher, T. D. & Stepien, C. A.) 113–128 (Academic Press, 1997).Chapter 

Google Scholar 
Thomaz, A. T., Malabarba, L. R., Bonatto, S. L. & Knowles, L. L. Testing the effect of palaeodrainages versus habitat stability on genetic divergence in riverine systems: Study of a Neotropical fish of the Brazilian coastal Atlantic Forest. J. Biogeogr. 42, 2389–2401. https://doi.org/10.1111/jbi.12597 (2015).Article 

Google Scholar 
Kimura, M. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111–120 (1980).ADS 
CAS 
Article 

Google Scholar 
Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549. https://doi.org/10.1093/molbev/msy096 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Guillot, G., Renaud, S., Ledevin, R., Michaux, J. & Claude, J. A unifying model for the analysis of phenotypic, genetic and geograhic data. Syst. Biol. 61(6), 897–911. https://doi.org/10.1093/sysbio/sys038 (2012).Article 
PubMed 

Google Scholar 
Excoffier, L., Laval, G. & Schneider, S. Arlequin: A Software for Population Data Analysis. Version 3.1. http://cmpg.unibe.ch/software/arlequin3 (2007).Wright, S. Evolution and the genetics of populations: Variability within and among natural populations. Univ. Chicago 4, 580 (1978).
Google Scholar 
Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large datasets. Mol. Biol. Evol. 34, 3299–3302. https://doi.org/10.1093/molbev/msx248 (2017).CAS 
Article 
PubMed 

Google Scholar 
Bandelt, H. J., Forster, P. & Röhl, A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16(1), 37–48 (1999).CAS 
Article 

Google Scholar 
Leigh, J. W. & Bryant, D. POPART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116. https://doi.org/10.1111/2041-210X.12410 (2015).Article 

Google Scholar 
Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595 (1989).CAS 
Article 

Google Scholar 
Fu, Y. X. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147, 915–925 (1997).CAS 
Article 

Google Scholar 
Austin, M. P. Continuum concept, ordination methods, and niche theory. Annu. Rev. Ecol. Syst. 16(1), 39–61. https://doi.org/10.1146/annurev.es.16.110185.000351 (1985).MathSciNet 
Article 

Google Scholar 
Graham, A., Atkinson, P. & Danson, F. Spatial analysis for epidemiology. Acta Trop. 91(3), 219–225. https://doi.org/10.1016/j.actatropica.2004.05.001 (2004).CAS 
Article 
PubMed 

Google Scholar 
Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190(3–4), 231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026 (2006).Article 

Google Scholar 
Guimarães, K. L. A., Rosso, J. J., Souza, M. F. B., de Astarloa, J. M. D. & Rodrigues, L. R. R. Integrative taxonomy reveals disjunct distribution and first record of Hoplias misionera (Characiformes: Erythrinidae) in the Amazon River basin: Morphological, DNA barcoding and cytogenetic considerations. Neotrop. Ichthyol. 19(2), e200110. https://doi.org/10.1590/1982-0224-2020-0110 (2021).Article 

Google Scholar 
Queiroz, L. J. et al. Evolutionary units delimitation and continental multilocus phylogeny of the hyperdiverse catfish genus Hypostomus. Mol. Phylogenet. Evol. 145, 106711. https://doi.org/10.1016/j.ympev.2019.106711 (2020).Article 

Google Scholar 
Phillips, J. D., Gillis, D. J. & Hanner, R. H. Incomplete estimates of genetic diversity within species: Implications for DNA barcoding. Ecol. Evol. https://doi.org/10.1002/ece3.4757 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Blaxter, M. L. The promise of a DNA taxonomy. Philos. Trans. R. Soc. B. 359(1444), 669–679. https://doi.org/10.1098/rstb.2003.1447 (2004).CAS 
Article 

Google Scholar 
Nwani, C. D. et al. DNA barcoding discriminates freshwater fishes from southeastern Nigeria and provides river system-level phylogeographic resolution within some species. Mitochondrial DNA 22(1), 43–51. https://doi.org/10.3109/19401736.2010.536537 (2011).CAS 
Article 
PubMed 

Google Scholar 
Aguirre, W. E., Shervette, V. R., Navarrete, R., Calle, P. & Agorastos, S. Morphological and genetic divergence of Hoplias microlepis (Characiformes: Erythrinidae) in rivers and artificial impoundments of Western Ecuador. Copeia 2013(2), 312–323. https://doi.org/10.1643/ci-12-083 (2013).Article 

Google Scholar 
Pires, W. M. M., Barros, M. C. & Fraga, E. C. DNA Barcoding unveils cryptic lineages of Hoplias malabaricus from Northeastern Brazil. Braz. J. Biol. 81(4), 917–927. https://doi.org/10.1590/1519-6984.231598 (2020).Article 

Google Scholar 
Souza, F. H. S. et al. interspecific genetic differences and historical demography in South American Arowanas (Osteoglossiformes, Osteoglossidae, Osteoglossum). Genes 10(9), 693. https://doi.org/10.3390/genes10090693 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
Torati, L. S. et al. Genetic diversity and structure in Arapaima gigas populations from Amazon and Araguaia-Tocantins river basins. BMC Genet. https://doi.org/10.1186/s12863-018-0711-y (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Lovejoy, N. R. & Araujo, M. L. G. Molecular systematics, biogeography and population structure of Neotropical freshwater needlefishes of the genus Potamorrhaphis. Mol. Ecol. 9(3), 259–268. https://doi.org/10.1046/j.1365-294x.2000.00845.x (2000).CAS 
Article 
PubMed 

Google Scholar 
Mabesoone, J. M. Sedimentary Basins of Northeast Brazil (Federal University of Pernambuco, 1994).
Google Scholar 
Haffer, J. & Prance, G. T. Impulsos climáticos da evolução na Amazônia durante o Cenozóico: Sobre a teoria dos Refúgios da diferenciação biótica. Estudos Avançados USP 46, 175–208. https://doi.org/10.1590/S0103-40142002000300014 (2002).Article 

Google Scholar 
Riker, S. R. L., Lima, F. J. C., Motta, M. B. Evidências de glaciação Pleistocênica na Amazônia Brasileira. Anais do 14° Simpósio de Geologia da Amazônia, Sociedade Brasileira de Geologia 15–18 (2015).Albert, J. S., Val, P. & Hoorn, C. The changing course of the Amazon River in the Neogene: Center stage for Neotropical diversification. Neotrop. Ichthyol. 16(3), e180033. https://doi.org/10.1590/1982-0224-20180033 (2018).Article 

Google Scholar 
Lundberg, J. G. et al. The stage for Neotropical fish diversification: a history of tropical South American rivers. (eds. Malabarba, L. R., Reis, R. E., Vari, R. P., Lucena, Z. M., Lucena, C. A. S. Phylogeny and classification of Neotropical fishes). Edipucrs 13–48 (1998).Hubert, N. & Renno, J. F. Historical biogeography of South American freshwater fishes. J. Biogeogr. 33(8), 1414–1436. https://doi.org/10.1111/j.1365-2699.2006.01518.x (2006).Article 

Google Scholar 
Farias, I. P. & Hrbek, T. Patterns of diversification in the discus fishes (Symphysodon spp. Cichlidae) of the Amazon basin. Mol. Phylogenet. Evol. 49, 32–43. https://doi.org/10.1016/j.ympev.2008.05.033 (2008).CAS 
Article 
PubMed 

Google Scholar 
Tagliacollo, V. A., Bernt, M. J., Craig, J. M., Oliveira, C. & Albert, J. S. Model-based total evidence phylogeny of Neotropical electric knifefishes (Teleostei, Gymnoti-formes). Mol. Phylogenet. Evol. 95, 20–33. https://doi.org/10.1016/j.ympev.2015.11.007 (2015).Article 
PubMed 

Google Scholar 
Hutchinson, G. E. Concluding remarks. Cold Spring Harbor Symposium. Quant. Biol. 22, 415–427 (1957).Article 

Google Scholar 
Wiens, J. J. & Graham, C. H. Niche conservatism: Inte-grating evolution, ecology, and conservation biology. Annu. Rev. Ecol. Evol. Syst. 36, 519–539 (2005).Article 

Google Scholar 
McNyset, K. M. Ecological niche conservatism in North American freshwater fishes. Biol. J. Lin. Soc. 96, 282–295 (2009).Article 

Google Scholar 
Silva, W. C., Marceniuk, A. P., Sales, J. B. L. & Araripe, J. Early pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species. Neotrop. Ichthyol. https://doi.org/10.1590/1982-0224-20150184 (2016).Article 

Google Scholar 
Lemopoulos, A. & Covain, R. Biogeography of the freshwater fishes of the Guianas using a partitioned parsimony analysis of endemicity with reappraisal of ecoregional boundaries. Cladistics 35(2019), 106–124. https://doi.org/10.1111/cla.12341 (2018).Article 
PubMed 

Google Scholar 
Hoorn, C. Marine incursions and the influence of Andean tectonics on the Miocene depositional history of northwestern Amazonia: Results of a palynostratigraphic study. Palaeogeogr. Palaeoclimatol. Palaeoecol. 105, 267–309. https://doi.org/10.1016/0031-0182(93)90087-Y (1993).Article 

Google Scholar 
Hoorn, C., Guerreiro, J. & Sarmiento, G. Andean tectonics as a cause for changing drainage patterns in Miocene Northern South America. Geology 23(3), 237–240. https://doi.org/10.1130/0091-7613(1995)023%3c0237:ATAACF%3e2.3.CO;2 (1995).ADS 
Article 

Google Scholar 
Ribeiro, A. C. Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: An example of faunal evolution associated with a divergent continental margin. Neotrop. Ichthyol. 4(2), 225–246. https://doi.org/10.1590/S1679-62252006000200009 (2006).Article 

Google Scholar 
Lovejoy, N. R., Albert, J. S. & Crampton, W. G. R. Miocene marine incursions and marine/freshwater transitions: Evidence from Neotropical fishes. J. S. Am. Earth Sci. 21(1–2), 5–13. https://doi.org/10.1016/j.jsames.2005.07.009 (2006).Article 

Google Scholar  More

Steffen, W. et al. Planetary boundaries: guiding human development on a changing planet. Science 347, 1259855 (2015).PubMed 
PubMed Central 

Google Scholar 
Kanter, D. R. et al. Nitrogen pollution policy beyond the farm. Nat. Food 1, 27–32 (2020).
Google Scholar 
Tian, H. Q. et al. A comprehensive quantification of global nitrous oxide sources and sinks. Nature 586, 248–256 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Thompson, R. L. et al. Acceleration of global N2O emissions seen from two decades of atmospheric inversion. Nat. Clim. Change 9, 993–998 (2019).CAS 

Google Scholar 
Isobe, K., Allison, S. D., Khalili, B., Martiny, A. C. & Martiny, J. B. H. Phylogenetic conservation of bacterial responses to soil nitrogen addition across continents. Nat. Commun. 10, 2499 (2019).PubMed 
PubMed Central 

Google Scholar 
Dai, Z. M. et al. Long-term nitrogen fertilization decreases bacterial diversity and favors the growth of Actinobacteria and Proteobacteria in agro-ecosystems across the globe. Glob. Change Biol. 24, 3452–3461 (2018).
Google Scholar 
Wallenstein, M., Myrold, D., Firestone, M. & Voytek, M. Environmental controls on denitrifying communities and denitrification rates: insights from molecular methods. Ecol. Appl 16, 2143–2152 (2006).PubMed 
PubMed Central 

Google Scholar 
Scheer, C., Fuchs, K., Pelster, D. E. & Butterbach-Bahl, K. Estimating global terrestrial denitrification from measured N2O:(N2O + N2) product ratios. Curr. Opin. Enviro 47, 72–80 (2020).
Google Scholar 
Inatomi, M., Hajima, T. & Ito, A. Fraction of nitrous oxide production in nitrification and its effect on total soil emission: a meta-analysis and global-scale sensitivity analysis using a process-based model. PLoS One 14, e0219159 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Liang, D. & Robertson, G. P. Nitrification is a minor source of nitrous oxide (N2O) in an agricultural landscape and declines with increasing management intensity. Glob. Change Biol. 27, 5599–5613 (2021).
Google Scholar 
Zumft, W. G. Cell biology and molecular basis of denitrification. Microbiol Mol. Biol. R. 61, 533–616 (1997).CAS 

Google Scholar 
Graf, D. R. H., Jones, C. M. & Hallin, S. Intergenomic comparisons highlight modularity of the denitrification pathway and underpin the importance of community structure for N2O emissions. PLoS One 9, e114118 (2014).PubMed 
PubMed Central 

Google Scholar 
Lycus, P. et al. Phenotypic and genotypic richness of denitrifiers revealed by a novel isolation strategy. ISME J. 11, 2219–2232 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Roco, C. A., Bergaust, L. L., Bakken, L. R., Yavitt, J. B. & Shapleigh, J. P. Modularity of nitrogen-oxide reducing soil bacteria: linking phenotype to genotype. Environ. Microbiol 19, 2507–2519 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Hallin, S., Philippot, L., Loffler, F. E., Sanford, R. A. & Jones, C. M. Genomics and ecology of novel N2O-reducing microorganisms. Trends Microbiol 26, 43–55 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Philippot, L., Andert, J., Jones, C. M., Bru, D. & Hallin, S. Importance of denitrifiers lacking the genes encoding the nitrous oxide reductase for N2O emissions from soil. Glob. Change Biol. 17, 1497–1504 (2011).
Google Scholar 
Domeignoz-Horta, L. A. et al. Non-denitrifying nitrous oxide-reducing bacteria—an effective N2O sink in soil. Soil Biol. Biochem 103, 376–379 (2016).CAS 

Google Scholar 
Ramirez, K. S., Craine, J. M. & Fierer, N. Consistent effects of nitrogen amendments on soil microbial communities and processes across biomes. Glob. Change Biol. 18, 1918–1927 (2012).
Google Scholar 
Leff, J. W. et al. Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe. Proc. Natl. Acad. Sci. USA 112, 10967–10972 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Shi, S. et al. The interconnected rhizosphere: high network complexity dominates rhizosphere assemblages. Ecol. Lett. 19, 926–936 (2016).PubMed 
PubMed Central 

Google Scholar 
Huang, R. L. et al. Plant-microbe networks in soil are weakened by century-long use of inorganic fertilizers. Micro. Biotechnol. 12, 1464–1475 (2019).CAS 

Google Scholar 
Tylianakis, J. M. & Morris, R. J. Ecological networks across environmental gradients. Annu. Rev. Ecol. Evol. S 48, 25–48 (2017).
Google Scholar 
Geisseler, D. & Scow, K. M. Long-term effects of mineral fertilizers on soil microorganisms—a review. Soil Biol. Biochem 75, 54–63 (2014).CAS 

Google Scholar 
Simek, M. & Cooper, J. The influence of soil pH on denitrification: progress towards the understanding of this interaction over the last 50 years. Eur. J. Soil Sci. 53, 345–354 (2002).CAS 

Google Scholar 
Klemedtsson, L., von Arnold, K., Weslien, P. & Gundersen, P. Soil CN ratio as a scalar parameter to predict nitrous oxide emissions. Glob. Change Biol. 11, 1142–1147 (2005).
Google Scholar 
Parn, J. et al. Nitrogen-rich organic soils under warm well-drained conditions are global nitrous oxide emission hotspots. Nat. Commun. 9, 1135 (2018).PubMed 
PubMed Central 

Google Scholar 
Maeda, K. et al. Relative contribution of nirK-and nirS-bacterial denitrifiers as well as fungal denitrifiers to nitrous oxide production from dairy manure compost. Environ. Sci. Technol. 51, 14083–14091 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Coyotzi, S. et al. Agricultural soil denitrifiers possess extensive nitrite reductase gene diversity. Environ. Microbiol 19, 1189–1208 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Nadeau, S. A. et al. Metagenomic analysis reveals distinct patterns of denitrification gene abundance across soil moisture, nitrate gradients. Environ. Microbiol 21, 1255–1266 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Enwall, K., Throbäck, I. N., Stenberg, M., Söderström, M. & Hallin, S. Soil resources influence spatial patterns of denitrifying communities at scales compatible with land management. Appl Environ. Microbiol 76, 2243–2250 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Jones, C. M. & Hallin, S. Ecological and evolutionary factors underlying global and local assembly of denitrifier communities. ISME J. 4, 633–641 (2010).PubMed 

Google Scholar 
Silverman, J. D., Washburne, A. D., Mukherjee, S. & David, L. A. A phylogenetic transform enhances analysis of compositional microbiota data. eLife 6, 5721 (2017).
Google Scholar 
Magurran, A. E. & Henderson, P. A. Explaining the excess of rare species in natural species abundance distributions. Nature 422, 714–716 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Dai, Z. et al. Long-term nitrogen fertilization decreases bacterial diversity and favors the growth of Actinobacteria and Proteobacteriain agro-ecosystems across the globe. Glob. Change Biol. 24, 3452–3461 (2018).
Google Scholar 
Fierer, N. et al. Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients. ISME J. 6, 1007–1017 (2011).PubMed 
PubMed Central 

Google Scholar 
Naether, A. et al. Environmental factors affect acidobacterial communities below the subgroup level in grassland and forest soils. Appl Environ. Microbiol. 78, 7398–7406 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Navarrete, A. A. et al. Differential response of Acidobacteria subgroups to forest-to-pasture conversion and their biogeographic patterns in the Western Brazilian Amazon. Front. Microbiol. 6, 1443 (2015).PubMed 
PubMed Central 

Google Scholar 
Jones, C. M., Stres, B., Rosenquist, M. & Hallin, S. Phylogenetic analysis of nitrite, nitric oxide, and nitrous oxide respiratory enzymes reveal a complex evolutionary history for denitrification. Mol. Biol. Evol. 25, 1955–1966 (2008).CAS 
PubMed 

Google Scholar 
Kuypers, M. M. M., Marchant, H. K. & Kartal, B. The microbial nitrogen-cycling network. Nat. Rev. Microbiol 16, 263–274 (2018).CAS 
PubMed 

Google Scholar 
Zhou, J., Deng, Y., Luo, F., He, Z. & Yang, Y. Phylogenetic molecular ecological network of soil microbial communities in response to elevated CO2. MBio 2, e00122-00111–e00122-00111 (2011).
Google Scholar 
Huang, R. et al. Plant–microbe networks in soil are weakened by century‐long use of inorganic fertilizers. Micro. Biotechnol. 12, 1464–1475 (2019).CAS 

Google Scholar 
Bar-Massada, A. Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities. Proc. Royal Soc. B 282, 20150927 (2015).
Google Scholar 
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M. & Hwang, D. U. Complex networks: structure and dynamics. Phys. Rep. 424, 175–308 (2006).
Google Scholar 
Yuan, M. M. et al. Climate warming enhances microbial network complexity and stability. Nat. Clim. Change 11, 343–U100 (2021).
Google Scholar 
Freilich, S. et al. The large-scale organization of the bacterial network of ecological co-occurrence interactions. Nucleic Acids Res. 38, 3857–3868 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Samad, M. D. S. et al. Phylogenetic and functional potential links pH and N2O emissions in pasture soils. Sci. Rep. 6, 35990 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wang, Y. et al. Soil pH as the chief modifier for regional nitrous oxide emissions: new evidence and implications for global estimates and mitigation. Glob. Change Biol. 24, E617–E626 (2018).
Google Scholar 
Jones, C. M. et al. Recently identified microbial guild mediates soil N2O sink capacity. Nat. Clim. Change 4, 801–805 (2014).CAS 

Google Scholar 
Dorsch, P., Braker, G. & Bakken, L. R. Community-specific pH response of denitrification: experiments with cells extracted from organic soils. FEMS Microbiol Ecol. 79, 530–541 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Linton, N. F., Machado, P. V. F., Deen, B., Wagner-Riddle, C. & Dunfield, K. E. Long-term diverse rotation alters nitrogen cycling bacterial groups and nitrous oxide emissions after nitrogen fertilization. Soil Biol. Biochem 149, 107917 (2020).CAS 

Google Scholar 
Xu, X. Y. et al. nosZ clade II rather than clade I determine in situ N2O emissions with different fertilizer types under simulated climate change and its legacy. Soil Biol. Biochem 150, 107974 (2020).CAS 

Google Scholar 
Philippot, L. et al. Loss in microbial diversity affects nitrogen cycling in soil. ISME J. 7, 1609–1619 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Delgado-Baquerizo, M., Grinyer, J., Reich, P. B. & Singh, B. K. Relative importance of soil properties and microbial community for soil functionality: insights from a microbial swap experiment. Funct. Ecol. 30, 1862–1873 (2016).
Google Scholar 
Kottek, M., Grieser, J., Beck, C., Rudolf, B. & Rubel, F. World map of the Köppen–Geiger climate classification updated. Meteorol. Z. 15, 259–263 (2006).
Google Scholar 
Lu, C. Q. & Tian, H. Q. Global nitrogen and phosphorus fertilizer use for agriculture production in the past half century: shifted hot spots and nutrient imbalance. Earth Syst. Sci. Data 9, 181–192 (2017).
Google Scholar 
Van Meter, K. J., Basu, N. B., Veenstra, J. J. & Burras, C. L. The nitrogen legacy: emerging evidence of nitrogen accumulation in anthropogenic landscapes. Environ. Res. Lett. 11, 035014–035013 (2016).
Google Scholar 
Takahashi, S., Tomita, J., Nishioka, K., Hisada, T. & Nishijima, M. Development of a prokaryotic universal primer for simultaneous analysis of bacteria and archaea using next-generation sequencing. PLoS One 9, e105592 (2014).PubMed 
PubMed Central 

Google Scholar 
Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: a fast and accurate illumina paired-end reAd mergeR. Bioinformatics 30, 614–620 (2014).CAS 
PubMed 

Google Scholar 
Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4, e2584 (2016).PubMed 
PubMed Central 

Google Scholar 
Pruesse, E., Peplies, J. & Glöckner, F. O. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 28, 1823–1829 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ludwig, W. et al. ARB: a software environment for sequence data. Nucleic Acids Res. 32, 1363–1371 (2004).CAS 
PubMed 
PubMed Central 

Google Scholar 
Oksanen J. vegan: Community Ecology Package version 1.8–5 (Semantic Scholar, 2007).McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8, e61217 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Palarea-Albaladejo, J. & Martin-Fernandez, J. A. zCompositions—R package for multivariate imputation of left-censored data under a compositional approach. Chemom. Intell. Lab 143, 85–96 (2015).CAS 

Google Scholar 
Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).
Google Scholar 
Csardi, G. & Nepusz, T. The igraph software package for complex network research. Int. J. Complex Syst. 1695, 1–9 (2006).
Google Scholar 
Menzel, U. RMThreshold: Signal-Noise Separation in Random Matrices by Using Eigenvalue. R Package Version 1.1 edn. https://rdrr.io/cran/RMThreshold/man/RMThreshold-package.html (2016).Gu, Z. G., Gu, L., Eils, R., Schlesner, M. & Brors, B. circlize implements and enhances circular visualization in R. Bioinformatics 30, 2811–2812 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Goenawan, I. H., Bryan, K. & Lynn, D. J. DyNet: visualization and analysis of dynamic molecular interaction networks. Bioinformatics 32, 2713–2715 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Jones, C. M. & Hallin, S. Geospatial variation in co-occurrence networks of nitrifying microbial guilds. Mol. Ecol. 28, 293–306 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Newman, M. E. J. & Girvan, M. Finding and evaluating community structure in networks. Phys. Rev. E 69, 268–215 (2004).
Google Scholar 
Deng, Y. et al. Molecular ecological network analyses. BMC Bioinform. 13, 113 (2012).
Google Scholar 
Elith, J., Leathwick, J. R. & Hastie, T. A working guide to boosted regression trees. J. Anim. Ecol. 77, 802–813 (2008).CAS 
PubMed 
PubMed Central 

Google Scholar 
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2012).
Google Scholar 
Kuhn, M. Building predictive models in R using the caret package. J. Stat. Softw. 28, 1–26 (2008).
Google Scholar 
Greenwell, B. M. & Boehmke, B. C. Variable importance plots-an introduction to the vip package. R. J. 12, 343–366 (2020).
Google Scholar 
Molnar, C. iml: An R package for Interpretable. Mach. Learn. J. Open Source Softw. 3, 786 (2018).
Google Scholar  More

Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History (LUOMUS), University of Helsinki, Helsinki, FinlandStefano Mammola, Jagoba Malumbres-Olarte, Pedro Cardoso, Caroline S. Fukushima, Tuuli Korhonen, Marija Miličić & Joni A. SaarinenMolecular Ecology Group (MEG), Water Research Institute, National Research Council of Italy (CNR-IRSA), Largo Tonolli 50, 28922, Verbania Pallanza, ItalyStefano Mammola & Alejandro MartínezCE3C – Centre for Ecology, Evolution and Environmental Changes / Azorean Biodiversity Group and Universidade dos Açores, Angra do Heroísmo, Azores, PortugalJagoba Malumbres-OlarteAlbert Katz International School for Desert Studies, Ben-Gurion University of the Negev, Sede Boqer Campus, Beersheba, IsraelValeria ArabeskyBlaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Beersheba, IsraelValeria Arabesky & Yael LubinColección Nacional de Arácnidos, Instituto de Biología, Universidad Nacional Autónoma de México (UNAM), Mexico City, MexicoDiego Alejandro Barrales-AlcaláEnvironmental Biology Division, Institute of Biological Sciences, College of Arts and Sciences and Museum of Natural History, University of the Philippines Los Banos, 4031, Los Baños, PhilippinesAimee Lynn Barrion-DupoCentro Universitario de Rivera, Universidad de la República, Montevideo, UruguayMarco Antonio BenamúLab. Ecotoxicología de Artrópodos Terrestres, Centro Univeritario de Rivera, Universidad de la República, Montevideo, UruguayMarco Antonio BenamúLaboratorio Ecología del Comportamiento, Instituto de Investigaciones Biológicas clemente Estable (IIBCE), Montevideo, UruguayMarco Antonio BenamúDitsong National Museum of Natural History, PO Box 4197, Pretoria, 0001, South AfricaTharina L. BirdDepartment of Zoology and Entomology, University of Pretoria, Private Bag X20, Hatfield, 0028, South AfricaTharina L. BirdFreelance translator, Verbania Pallanza, ItalyMaria BogomolovaDepartment of Molecular Biology and Genetics, Democritus University of Thrace, Komotini, GreeceMaria ChatzakiDepartment of Life sciences, National Chung Hsing University, No.145 Xingda Rd., South Dist., Taichung City, 402204, TaiwanRen-Chung Cheng & Tien-Ai ChuDepartment of Biology, Macelwane Hall, 3507 Laclede Avenue, Saint Louis University, St. Louis, MO, 63103, USALeticia M. Classen-RodríguezCroatian Biospeleological Society, Rooseveltov trg 6, Zagreb, CroatiaIva Čupić & Martina PavlekProgram Sarjana, Fakultas Biologi, Universitas Gadjah Mada, Yogyakarta, IndonesiaNaufal Urfi Dhiya’ulhaqInsectarium de Montréal, Espace pour la vie, 4101, rue Sherbrooke Est, Montréal, Québec, H1X 2B2, CanadaAndré-Philippe Drapeau PicardSerket, Arachnid Collection of Egypt (ACE), Cairo, EgyptHisham K. El-HennawyErzincan Binali Yıldırım University, Faculty of Science and Arts, Biology Department, 24002, Erzincan, TurkeyMert ElvericiThe National Natural History Collections, The Hebrew University of Jerusalem, Edmond J. Safra Campus, Givat Ram, Jerusalem, 9190401, IsraelZeana Ganem & Efrat Gavish-RegevThe Department of Ecology, Evolution and Behavior, The Hebrew University of Jerusalem, Edmond J. Safra Campus, Givat Ram, Jerusalem, 9190401, IsraelZeana GanemBotswana International University of Science and Technology, Palapye, BotswanaNaledi T. 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BOX 40658- 00100, Nairobi, KenyaGrace Mwende KiokoSchool for Advanced Studies IUSS, Science, Technology and Society Department, 25100, Pavia, ItalyVeronica NanniInstitute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, MalaysiaYusoff Norma-RashidDepartment of Animal and Environmental Biology, Federal University, Oye-Ekiti, Ekiti State, NigeriaDaniel NwankwoTe Aka Mātuatua School of Science, University of Waikato, Private Bag 3105, Hamilton, 3240, New ZealandChristina J. PaintingIndependent researcher, Toronto, CanadaAleck PangMuseo Civico di Scienze Naturali “E. Caffi”, Piazza Cittadella, 10, I-24129, Bergamo, ItalyPaolo PantiniRuđer Bošković Institute, Bijenička cesta 54, 10000, Zagreb, CroatiaMartina PavlekBiodiversity Research Laboratory, Moreton Morrell, Warwickshire College University Centre, Warwickshire, United KingdomRichard PearceInstitute for Coastal and Marine Research, Nelson Mandela University, Port Elizabeth, South AfricaJulien PétillonDepartment of Entomology, University of Antananrivo, Antananarivo, MadagascarOnjaherizo Christian RaberahonaSchool of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, United StatesLaura Segura-HernándezDepartment of Biological Sciences, University of Toronto Scarborough, 1265 Military Trail, Scarborough, Ontario, M1C 1A4, CanadaLenka SentenskáNatural Sciences, Auckland War Memorial Museum, Parnell, Auckland, 1010, New ZealandLeilani WalkerTe Pūnaha Matatini, University of Auckland, Auckland, New ZealandLeilani WalkerMurang’a University of Technology, Department of Physical & Biological Sciences, P.O.Box 75-10200, Murang’a, KenyaCharles M. WaruiInstitute of Biology and Earth Sciences, Pomeranian University in Słupsk, Arciszewskiego 22a, 76-200, Słupsk, PolandKonrad WiśniewskiZoological Museum, Biodiversity Unit, FI-20014, University of Turku, Turku, FinlandAlireza ZamaniDepartment of Psychology, University of Tennessee, Knoxville, Tennessee, USAAngela ChuangDepartment of Entomology and Nematology, Citrus Research and Education Center, University of Florida, Lake Alfred, Florida, USAAngela ChuangConceptualization: SM, JM-O, CS, AC; Data collection & validation: all authors; Data management: SM, VN, AC; Data analysis & visualization (Figs. 2–5): SM; Summary illustration (Fig. 1): JM-O; Writing (first draft): SM; Writing, contributions: JM-O, CS, AC; All authors read the text, provided comments, suggestions, and corrections, and approved the final version. More

Schemske, D. W. in Foundations of Tropical Forest Biology (eds Chazdon, R. L. & Whitmore, T. C.) 163–173 (Univ. Chicago Press, 2002).Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).
Google Scholar 
Schemske, D. W., Mittelbach, G. G., Cornell, H. V., Sobel, J. M. & Roy, K. Is there a latitudinal gradient in the importance of biotic interactions? Annu. Rev. Ecol. Evol. Syst. 40, 245–269 (2009).
Google Scholar 
Schweiger, O., Settele, J., Kudrna, O., Klotz, S. & Kühn, I. Climate change can cause spatial mismatch of trophically interacting species. Ecology 89, 3472–3479 (2008).PubMed 

Google Scholar 
Hegland, S. J., Nielsen, A., Lázaro, A., Bjerknes, A.-L. & Totland, Ø. How does climate warming affect plant–pollinator interactions? Ecol. Lett. 12, 184–195 (2009).PubMed 

Google Scholar 
Walther, G.-R. Community and ecosystem responses to recent climate change. Philos. Trans. R. Soc. B 365, 2019–2024 (2010).
Google Scholar 
Blois, J. L., Zarnetske, P. L., Fitzpatrick, M. C. & Finnegan, S. Climate change and the past, present and future of biotic interactions. Science 341, 499–504 (2013).CAS 
PubMed 

Google Scholar 
Schleuning, M. et al. Ecological networks are more sensitive to plant than to animal extinction under climate change. Nat. Commun. 7, 13965 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Bascompte, J., García, M. B., Ortega, R., Rezende, E. L. & Pironon, S. Mutualistic interactions reshuffle the effects of climate change on plants across the tree of life. Sci. Adv. 5, eaav2539 (2019).PubMed 
PubMed Central 

Google Scholar 
Memmott, J., Craze, P. G., Waser, N. M. & Price, M. V. Global warming and the disruption of plant–pollinator interactions. Ecol. Lett. 10, 710–717 (2007).PubMed 

Google Scholar 
Tylianakis, J. M., Didham, R. K., Bascompte, J. & Wardle, D. A. Global change and species interactions in terrestrial ecosystems. Ecol. Lett. 11, 1351–1363 (2008).PubMed 

Google Scholar 
Dalsgaard, B. et al. Specialization in plant–hummingbird networks is associated with species richness, contemporary precipitation and Quaternary climate-change velocity. PLoS ONE 6, e25891 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Dalsgaard, B. et al. Historical climate-change influences modularity and nestedness of pollination networks. Ecography 36, 1331–1340 (2013).
Google Scholar 
Memmott, J., Waser, N. M. & Price, M. V. Tolerance of pollination networks to species extinctions. Proc. R. Soc. Lond. B 271, 2605–2611 (2004).
Google Scholar 
Kaiser-Bunbury, C. N., Muff, S., Memmott, J., Müller, C. B. & Caflisch, A. The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour. Ecol. Lett. 13, 442–452 (2010).PubMed 

Google Scholar 
Dáttilo, W. et al. Unravelling Darwin’s entangled bank: architecture and robustness of mutualistic networks with multiple interaction types. Proc. R. Soc. B 283, 20161564 (2016).PubMed 
PubMed Central 

Google Scholar 
Dalsgaard, B. et al. Trait evolution, resource specialization and vulnerability to plant extinctions among Antillean hummingbirds. Proc. R. Soc. B 285, 20172754 (2018).PubMed 
PubMed Central 

Google Scholar 
Gilman, S. E., Urban, M. C., Tewksbury, J., Gilchrist, G. W. & Holt, R. D. A framework for community interactions under climate change. Trends Ecol. Evol. 25, 325–331 (2010).PubMed 

Google Scholar 
Rahbek, C. & Graves, G. R. Multiscale assessment of patterns of avian species richness. Proc. Natl Acad. Sci. USA 98, 4534–4539 (2001).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rahbek, C. & Graves, G. R. Detection of macro-ecological patterns in South American hummingbirds is affected by spatial scale. Proc. R. Soc. Lond. B 267, 2259–2265 (2000).CAS 

Google Scholar 
Dalsgaard, B. et al. The influence of biogeographical and evolutionary histories on morphological trait-matching and resource specialization in mutualistic hummingbird–plant networks. Funct. Ecol. 35, 1120–1133 (2021).
Google Scholar 
Sandel, B. et al. The influence of Late Quaternary climate-change velocity on species endemism. Science 334, 660–664 (2011).CAS 
PubMed 

Google Scholar 
Scherrer, D. & Körner, C. Topographically controlled thermal-habitat differentiation buffers alpine plant diversity against climate warming. J. Biogeogr. 38, 406–416 (2011).
Google Scholar 
Graves, G. R. & Rahbek, C. Source pool geometry and the assembly of continental avifaunas. Proc. Natl Acad. Sci. USA 102, 7871–7876 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects (eds Barros, V. R. et al.) (Cambridge Univ. Press, 2014).Hoegh-Guldberg, O. et al. in Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) 175–311 (IPCC, WMO, 2018).Watson, J. E. M., Iwamura, T. & Butt, N. Mapping vulnerability and conservation adaptation strategies under climate change. Nat. Clim. Change 3, 989–994 (2013).
Google Scholar 
Martín González, A. M., Dalsgaard, B. & Olesen, J. M. Centrality measures and the importance of generalist species in pollination networks. Ecol. Complex. 7, 36–43 (2010).
Google Scholar 
Burgos, E. et al. Why nestedness in mutualistic networks? J. Theor. Biol. 249, 307–313 (2007).PubMed 

Google Scholar 
Bersier, L.-F., Banašek-Richter, C. & Cattin, M.-F. Quantitative descriptors of food-web matrices. Ecology 83, 2394–2407 (2002).
Google Scholar 
Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856 (2010).PubMed 

Google Scholar 
Tylianakis, J. M., Laliberté, E., Nielsen, A. & Bascompte, J. Conservation of species interaction networks. Biol. Conserv. 143, 2270–2279 (2010).
Google Scholar 
Grass, I., Jauker, B., Steffan-Dewenter, I., Tscharntke, T. & Jauker, F. Past and potential future effects of habitat fragmentation on structure and stability of plant–pollinator and host–parasitoid networks. Nat. Ecol. Evol. 2, 1408–1417 (2018).PubMed 

Google Scholar 
Stouffer, D. B. & Bascompte, J. Compartmentalization increases food-web persistence. Proc. Natl Acad. Sci. USA 108, 3648–3652 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Blüthgen, N., Menzel, F. & Blüthgen, N. Measuring specialization in species interaction networks. BMC Ecol. 6, 9 (2006).PubMed 
PubMed Central 

Google Scholar 
Dormann, C. F. & Strauss, R. A method for detecting modules in quantitative bipartite networks. Methods Ecol. Evol. 5, 90–98 (2014).
Google Scholar 
Bascompte, J., Jordano, P., Melián, C. J. & Olesen, J. M. The nested assembly of plant–animal mutualistic networks. Proc. Natl Acad. Sci. USA 100, 9383–9387 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rahbek, C. et al. Humboldt’s enigma: what causes global patterns of mountain biodiversity? Science 365, 1108–1113 (2019).CAS 

Google Scholar 
Cracraft, J. Historical biogeography and patterns of differentiation within the South American avifauna: areas of endemism. Ornithol. Monogr. 36, 49–84 (1985).
Google Scholar 
Hazzi, N. A., Moreno, J. S., Ortiz-Movliav, C. & Palacio, R. D. Biogeographic regions and events of isolation and diversification of the endemic biota of the tropical Andes. Proc. Natl Acad. Sci. USA 115, 7985–7990 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Jønsson, K. A. et al. Tracking animal dispersal: from individual movement to community assembly and global range dynamics. Trends Ecol. Evol. 31, 204–214 (2016).PubMed 

Google Scholar 
McGuire, J. A. et al. Molecular phylogenetics and the diversification of hummingbirds. Curr. Biol. 24, 910–916 (2014).CAS 
PubMed 

Google Scholar 
Proctor, M., Yeo, P. & Lack, A. The Natural History of Pollination (HarperCollins, 1996).Simberloff, D. S. & Wilson, E. O. Experimental zoogeography of islands: the colonization of empty islands. Ecology 50, 278–296 (1969).
Google Scholar 
Connor, E. F. & Simberloff, D. Species number and compositional similarity of the Galapagos flora and avifauna. Ecol. Monogr. 48, 219–248 (1978).
Google Scholar 
Grant, P. R. & Abbott, I. Interspecific competition, island biogeography and null hypotheses. Evolution 34, 332–341 (1980).CAS 
PubMed 

Google Scholar 
Thomas, C. D. Climate, climate change and range boundaries. Divers. Distrib. 16, 488–495 (2010).
Google Scholar 
Almeida-Neto, M., Guimarães, P., Guimarães, P. R. Jr, Loyola, R. D. & Ulrich, W. A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement. Oikos 117, 1227–1239 (2008).
Google Scholar 
Simmons, B. I. et al. Moving from frugivory to seed dispersal: incorporating the functional outcomes of interactions in plant–frugivore networks. J. Anim. Ecol. 87, 995–1007 (2018).PubMed 
PubMed Central 

Google Scholar 
Benadi, G., Blüthgen, N., Hovestadt, T. & Poethke, H.-J. Contrasting specialization–stability relationships in plant–animal mutualistic systems. Ecol. Model. 258, 65–73 (2013).
Google Scholar 
Beckett, S. J. Improved community detection in weighted bipartite networks. R. Soc. Open Sci. 3, 140536 (2016).PubMed 
PubMed Central 

Google Scholar 
Sonne, J. et al. Ecological mechanisms explaining interactions within plant–hummingbird networks: morphological matching increases towards lower latitudes. Proc. R. Soc. B 287, 20192873 (2020).PubMed 
PubMed Central 

Google Scholar 
Patefield, W. Algorithm AS 159: an efficient method of generating random R × C tables with given row and column totals. J. R. Stat. Soc. C 30, 91–97 (1981).
Google Scholar 
Dalsgaard, B. et al. Opposed latitudinal patterns of network‐derived and dietary specialization in avian plant–frugivore interaction systems. Ecography 40, 1395–1401 (2017).
Google Scholar 
Dormann, C. F., Gruber, B. & Fründ, J. Introducing the bipartite package: analysing ecological networks. R News 8, 8–11 (2008).Holt, B. G. et al. An update of Wallace’s zoogeographic regions of the world. Science 339, 74–78 (2013).CAS 
PubMed 

Google Scholar 
Two-Minute Gridded Global Relief Data (ETOPO2) v. 2 (NOAA National Geophysical Data Center, 2006); https://doi.org/10.7289/V5J1012QJetz, W. & Rahbek, C. Geographic range size and determinants of avian species richness. Science 297, 1548–1551 (2002).CAS 
PubMed 

Google Scholar 
Dobzhansky, T. Evolution in the tropics. Am. Sci. 38, 209–221 (1950).
Google Scholar 
Currie, D. J., Francis, A. P. & Kerr, J. T. Some general propositions about the study of spatial patterns of species richness. Écoscience 6, 392–399 (1999).
Google Scholar 
Hurlbert et al. The effect of energy and seasonality on avian species richness and community composition. Am. Nat. 161, 83–97 (2003).PubMed 

Google Scholar 
Karger, D. N. et al. Climatologies at high resolution for the Earth’s land surface areas. Sci. Data 4, 170122 (2017).PubMed 
PubMed Central 

Google Scholar 
Mateo, R. G., Felicísimo, Á. M. & Muñoz, J. Effects of the number of presences on reliability and stability of MARS species distribution models: the importance of regional niche variation and ecological heterogeneity. J. Veg. Sci. 21, 908–922 (2010).
Google Scholar 
Blonder, B. et al. Linking environmental filtering and disequilibrium to biogeography with a community climate framework. Ecology 96, 972–985 (2015).PubMed 

Google Scholar 
Vizentin-Bugoni, J., Debastiani, V. J., Bastazini, V. A. G., Maruyama, P. K. & Sperry, J. H. Including rewiring in the estimation of the robustness of mutualistic networks. Methods Ecol. Evol. 11, 106–116 (2020).
Google Scholar 
Rahbek, C., Borregaard, M. K., Hermansen, B., Nogues-Bravo, D. & Fjeldså, J. Definition and Description of the Montane Regions of the World (Center for Macroecology, Evolution and Climate, 2019); https://macroecology.ku.dk/resources/mountain_regions/definition-and-description-of-the-montane-regions-of-the-world_kopi/Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biom. J. 50, 346–363 (2008).PubMed 

Google Scholar  More

Pereira, H. M. et al. Scenarios for global biodiversity in the 21st century. Science 330, 1496–1501 (2010).CAS 
PubMed 

Google Scholar 
Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377 (2012).PubMed 
PubMed Central 

Google Scholar 
Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).CAS 
PubMed 

Google Scholar 
Steinbauer, M. J. et al. Accelerated increase in plant species richness on mountain summits is linked to warming. Nature 556, 231–234 (2018).CAS 
PubMed 

Google Scholar 
Feeley, K. J., Bravo-Avila, C., Fadrique, B., Perez, T. M. & Zuleta, D. Climate-driven changes in the composition of New World plant communities. Nat. Clim. Change 10, 965–970 (2020).CAS 

Google Scholar 
Radeloff, V. C. et al. The rise of novelty in ecosystems. Ecol. Appl. 25, 2051–2068 (2015).PubMed 

Google Scholar 
Davis, A. J., Jenkinson, L. S., Lawton, J. H., Shorrocks, B. & Wood, S. Making mistakes when predicting shifts in species range in response to global warming. Nature 391, 783–786 (1998).CAS 
PubMed 

Google Scholar 
Suttle, K. B., Thomsen, M. A. & Power, M. E. Species interactions reverse grassland responses to changing climate. Science 315, 640–642 (2007).CAS 
PubMed 

Google Scholar 
van der Putten, W. H., Macel, M. & Visser, M. E. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels. Proc. R. Soc. B 365, 2025–2034 (2010).
Google Scholar 
Gaüzère, P., Iversen, L. L., Barnagaud, J.-Y., Svenning, J.-C. & Blonder, B. Empirical predictability of community responses to climate change. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00186 (2018).Mangan, S. A. et al. Negative plant–soil feedback predicts tree-species relative abundance in a tropical forest. Nature 466, 752–755 (2010).CAS 
PubMed 

Google Scholar 
Bennett, J. A. et al. Plant–soil feedbacks and mycorrhizal type influence temperate forest population dynamics. Science 355, 181–184 (2017).CAS 
PubMed 

Google Scholar 
Teste, F. P. et al. Plant–soil feedback and the maintenance of diversity in Mediterranean-climate shrublands. Science 355, 173–176 (2017).CAS 
PubMed 

Google Scholar 
Kardol, P., Bezemer, T. M. & van der Putten, W. H. Temporal variation in plant–soil feedback controls succession. Ecol. Lett. 9, 1080–1088 (2006).PubMed 

Google Scholar 
van der Putten, W. H., van Dijk, C. & Peters, B. A. M. Plant-specific soil-borne diseases contribute to succession in foredune vegetation. Nature 362, 53–56 (1993).
Google Scholar 
Bever, J. D. Feedback between plants and their soil communities in an old field community. Ecology 75, 1965–1977 (1994).
Google Scholar 
Bever, J. D., Westover, K. M. & Antonovics, J. Incorporating the soil community into plant population dynamics: the utility of the feedback approach. J. Ecol. 85, 561–573 (1997).
Google Scholar 
Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).
Google Scholar 
Bever, J. D. Soil community feedback and the coexistence of competitors: conceptual frameworks and empirical tests. New Phytol. 157, 465–473 (2003).PubMed 

Google Scholar 
Revilla, T. A., Veen, G. F., Eppinga, M. B. & Weissig, F. J. Plant–soil feedbacks and the coexistence of competing plants. Theor. Ecol. 6, 99–113 (2013).
Google Scholar 
Molofsky, J. & Bever, J. D. A novel theory to explain species diversity in landscapes: positive frequency dependence and habitat suitability. Proc. R. Soc. B 269, 2389–2393 (2002).PubMed 
PubMed Central 

Google Scholar 
Ke, P. J. & Wan, J. Effects of soil microbes on plant competition: a perspective from modern coexistence theory. Ecol. Monogr. 90, e01391 (2020).
Google Scholar 
Mack, K. M. L. & Bever, J. D. Coexistence and relative abundance in plant communities are determined by feedbacks when the scale of feedback and dispersal is local. J. Ecol. 102, 1195–1201 (2014).PubMed 
PubMed Central 

Google Scholar 
Bauer, J. T., Mack, K. M. L. & Bever, J. D. Plant–soil feedbacks as drivers of succession: evidence from remnant and restored tallgrass prairies. Ecosphere 6, art158 (2015).
Google Scholar 
Kulmatiski, A., Beard, K. H., Grenzer, J., Forero, L. & Heavilin, J. Using plant–soil feedbacks to predict plant biomass in diverse communities. Ecology 97, 2064–2073 (2016).PubMed 

Google Scholar 
Reinhart, K. O. et al. Globally, plant–soil feedbacks are weak predictors of plant abundance. Ecol. Evol. 11, 1756–1768 (2021).PubMed 
PubMed Central 

Google Scholar 
Casper, B. B. & Castelli, J. P. Evaluating plant–soil feedback together with competition in a serpentine grassland. Ecol. Lett. 10, 394–400 (2007).PubMed 

Google Scholar 
Shannon, S., Flory, S. L. & Reynolds, H. Competitive context alters plant–soil feedback in an experimental woodland community. Oecologia 169, 235–243 (2012).PubMed 

Google Scholar 
Lekberg, Y. et al. Relative importance of competition and plant–soil feedback, their synergy, context dependency and implications for coexistence. Ecol. Lett. 21, 1268–1281 (2018).PubMed 

Google Scholar 
Kostenko, O., van de Voorde, T. F. J., Mulder, P. P. J., van der Putten, W. H. & Bezemer, M. T. Legacy effects of aboveground–belowground interactions. Ecol. Lett. 15, 813–821 (2012).PubMed 

Google Scholar 
Bezemer, M. T. et al. Above- and below-ground herbivory effects on below-ground plant–fungus interactions and plant–soil feedback responses. J. Ecol. 101, 325–333 (2013).
Google Scholar 
Classen, A. T. et al. Direct and indirect effects of climate change on soil microbial and soil microbial–plant interactions: what lies ahead? Ecosphere 6, art130 (2015).
Google Scholar 
McCarthy-Neumann, S. & Kobe, R. K. Site soil-fertility and light availability influence plant–soil feedback. Front. Ecol. Evol. 7, 383 (2019).
Google Scholar 
Smith-Ramesh, L. M. & Reynolds, H. L. The next frontier of plant–soil feedback research: unraveling context dependence across biotic and abiotic gradients. J. Veg. Sci. 28, 484–494 (2017).
Google Scholar 
Crawford, K. M. et al. When and where plant–soil feedback may promote plant coexistence: a meta-analysis. Ecol. Lett. 22, 1274–1284 (2019).PubMed 

Google Scholar 
de Long, J. R., Fry, E. L., Veen, G. F. & Kardol, P. Why are plant–soil feedbacks so unpredictable, and what to do about it? Funct. Ecol. 33, 118–128 (2019).
Google Scholar 
Beals, K. K. et al. Predicting plant–soil feedback in the field: meta-analysis reveals that competition and environmental stress differentially influence PSF. Front. Ecol. Evol. 8, 191 (2020).
Google Scholar 
van der Putten, W. H., Bradford, M. A., Brinkman, P. E., van de Voorde, T. F. J. & Veen, G. F. Where, when and how plant–soil feedback matters in a changing world. Funct. Ecol. 30, 1109–1121 (2016).
Google Scholar 
Pugnaire, F. I. et al. Climate change effects on plant–soil feedbacks and consequences for biodiversity and functioning of terrestrial ecosystems. Sci. Adv. 5, eaaz1834 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Trenberth, K. E. Changes in precipitation with climate change. Clim. Res. 47, 123–138 (2011).
Google Scholar 
Pendergrass, A. G., Knutti, R., Lehner, F., Deser, C. & Sanderson, B. M. Precipitation variability increases in a warmer climate. Sci. Rep. 7, 17966 (2017).PubMed 
PubMed Central 

Google Scholar 
Fierer, N., Schimel, J. P. & Holden, P. A. Influence of drying–rewetting frequency on soil bacterial community structure. Microb. Ecol. 45, 63–71 (2003).CAS 
PubMed 

Google Scholar 
Drenovsky, R. E., Vo, D., Graham, K. J. & Scow, K. M. Soil water content and organic carbon availability are major determinants of soil microbial community composition. Microb. Ecol. 48, 424–430 (2004).CAS 
PubMed 

Google Scholar 
Brockett, B. F., Prescott, C. E. & Grayston, S. J. Soil moisture is the major factor influencing microbial community structure and enzyme activities across seven biogeoclimatic zones in western Canada. Soil Biol. Biochem. 44, 9–20 (2012).CAS 

Google Scholar 
Manzoni, S., Schimel, J. P. & Porporato, A. Responses of soil microbial communities to water stress: results from a meta-analysis. Ecology 93, 930–938 (2012).PubMed 

Google Scholar 
de Vries, F. T. et al. Soil bacterial networks are less stable under drought than fungal networks. Nat. Commun. 9, 3033 (2018).PubMed 
PubMed Central 

Google Scholar 
de Oliveira, T. B. et al. Fungal communities differentially respond to warming and drought in tropical grassland soil. Mol. Ecol. 29, 1550–1559 (2020).PubMed 

Google Scholar 
Eastburn, D. M., McElrone, A. J. & Bilgin, D. D. Influence of atmospheric and climatic change on plant–pathogen interactions. Plant Pathol. 60, 54–69 (2011).
Google Scholar 
Suzuki, N., Rivero, R. M., Shulaev, V., Blumwald, E. & Mittler, R. Abiotic and biotic stress combinations. New Phytol. 203, 32–43 (2014).PubMed 

Google Scholar 
Cavagnaro, T. R. Soil moisture legacy effects: impacts on soil nutrients, plants and mycorrhizal responsiveness. Soil Biol. Biochem. 95, 173–179 (2016).CAS 

Google Scholar 
Crawford, K. M. & Hawkes, C. V. Soil precipitation legacies influence intraspecific plant–soil feedback. Ecology 101, e03142 (2020).PubMed 

Google Scholar 
Fry, E. L. et al. Drought neutralises plant–soil feedback of two mesic grassland forbs. Oecologia 186, 1113–1125 (2018).PubMed 
PubMed Central 

Google Scholar 
Snyder, A. E. & Harmon-Threatt, A. N. Reduced water-availability lowers the strength of negative plant–soil feedbacks of two Asclepias species. Oecologia 190, 425–432 (2019).PubMed 

Google Scholar 
Kulmatiski, A., Beard, K. H., Stevens, J. R. & Cobbold, S. M. Plant–soil feedbacks: a meta-analytical review. Ecol. Lett. 11, 980–992 (2008).PubMed 

Google Scholar 
Brinkman, P. E., van der Putten, W. H., Bakker, E.-J. & Verhoeven, K. J. Plant–soil feedback: experimental approaches, statistical analyses and ecological interpretations. J. Ecol. 98, 1063–1073 (2010).
Google Scholar 
Bever, J. D. Negative feedback within a mutualism: host-specific growth of mycorrhizal fungi reduces plant benefit. Proc. R. Soc. B 269, 2595–2601 (2002).PubMed 
PubMed Central 

Google Scholar 
Castelli, J. P. & Casper, B. B. Intraspecific AM fungal variation contributes to plant–fungal feedback in a serpentine grassland. Ecology 84, 323–336 (2003).
Google Scholar 
Mangan, S. A., Herre, E. A. & Bever, J. D. Specificity between neotropical tree seedlings and their fungal mutualists leads to plant–soil feedback. Ecology 91, 2594–2603 (2010).PubMed 

Google Scholar 
Bever, J. D., Mangan, S. A. & Alexander, H. M. Maintenance of plant species diversity by pathogens. Annu. Rev. Ecol. Evol. Syst. 46, 305–325 (2015).
Google Scholar 
Gilbert, G. S. & Parker, I. M. The evolutionary ecology of plant disease: a phylogenetic perspective. Annu. Rev. Phytopathol. 54, 549–578 (2016).CAS 
PubMed 

Google Scholar 
Milici, V. R., Dalui, D., Mickley, J. G. & Bagchi, R. Responses of plant–pathogen interactions to precipitation: implications for tropical tree richness in a changing world. J. Ecol. 108, 1800–1809 (2020).
Google Scholar 
Kaisermann, A., de Vries, F. T., Griffiths, R. I. & Bardgett, R. D. Legacy effects of drought on plant–soil feedbacks and plant–plant interactions. New Phytol. 215, 1413–1424 (2017).CAS 
PubMed 

Google Scholar 
Revillini, D., Gehring, C. A. & Johnson, N. C. The role of locally adapted mycorrhizas and rhizobacteria in plant–soil feedback systems. Funct. Ecol. 30, 1086–1098 (2016).
Google Scholar 
Ji, B. & Bever, J. D. Plant preferential allocation and fungal reward decline with soil phosphorus: implications for mycorrhizal mutualism. Ecosphere 7, e01256 (2016).
Google Scholar 
Rubin, R. L., van Groenigen, K. J. & Hungate, B. A. Plant growth promoting rhizobacteria are more effective under drought: a meta-analysis. Plant Soil 416, 309–323 (2017).CAS 

Google Scholar 
Brinkman, E. P., Duyts, H., Karssen, G., van der Stoel, C. D. & van der Putten, W. H. Plant-feeding nematodes in coastal sand dunes: occurrence, host specificity and effects on plant growth. Plant Soil 397, 17–30 (2015).CAS 

Google Scholar 
Hoeksema, J. D. et al. A meta-analysis of context-dependency in plant response to inoculation with mycorrhizal fungi. Ecol. Lett. 13, 394–407 (2010).PubMed 

Google Scholar 
Chase, J. M. Community assembly: when should history matter? Oecologia 136, 489–498 (2003).PubMed 

Google Scholar 
Fukami, T. Historical contingency in community assembly: integrating niches, species pools, and priority effects. Annu. Rev. Ecol. Evol. Syst. 46, 1–23 (2015).
Google Scholar 
Reinhart, K. O. & Rinella, M. J. A common soil handling technique can generate incorrect estimates of soil biota effects on plants. New Phytol. 210, 786–789 (2016).PubMed 

Google Scholar 
Mehlich, A. Mehlich-3 soil test extractant: a modification of Mehlich-2 extractant. Commun. Soil Sci. Plant Anal. 15, 1409–1416 (1984).CAS 

Google Scholar 
Rhoades, J. D. in Methods of Soil Analysis: Part 2 (eds Page, A. L. et al.) Ch. 10 (American Society of Agronomy and Soil Science Society of America, 1982).Schofield, R. K. & Taylor, A. W. The measurement of soil pH. Soil Sci. Soc. Am. Proc. 19, 164–167 (1955).CAS 

Google Scholar 
Keeney, D. R. in Methods of Soil Analysis: Part 2 (eds Page, A. L. et al.) Ch. 35 (American Society of Agronomy and Soil Science Society of America, 1982).Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Pauvert, C. et al. Bioinformatics matters: the accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline. Fungal Ecol. 41, 23–33 (2019).
Google Scholar 
Abarenkov, K. et al UNITE QIIME Release for Fungi. Version 04.02.2020 (UNITE Community, 2020).Francioli, D., van Ruijven, J., Bakker, L. & Mommer, L. Drivers of total and pathogenic soil-borne fungal communities in grassland plant species. Fungal Ecol. 48, 100987 (2020).
Google Scholar 
Nhu, H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).
Google Scholar 
Brooks, M. B. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).
Google Scholar 
Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Google Scholar 
Lou, J. Entropy and diversity. Oikos 113, 363–375 (2006).
Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package. R version 2.5–7 https://CRAN.R-project.org/package=vegan (2020).Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2020).
Google Scholar 
Wilensky, U. NetLogo http://ccl.northwestern.edu/netlogo (1999).Salecker, J., Sciaini, M., Meyer, K. M. & Wiegand, K. The NLRX R package: a next-generation framework for reproducible NetLogo model analyses. Methods Ecol. Evol. 10, 1854–1863 (2019).
Google Scholar 
Wickham et al. Welcome to the tidyverse. J. Open Source Softw. 4, 1686 (2019).
Google Scholar 
R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020). More

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ReferencesLeBrun, E. G., Jones, M., Plowes, R. M. & Gilbert, L. E. Proc. Natl Acad. Sci. USA 119, e2114558119 (2022).PubMed 
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Ceballos, G., García, A. & Ehrlich, P. R. The sixth extinction crisis: Loss of animal populations and species. J. Cosmol. 8, 31 (2010).
Google Scholar 
Johnson, C. N. et al. Biodiversity losses and conservation responses in the Anthropocene. Science 356, 270–275 (2017).CAS 
PubMed 

Google Scholar 
Scott, J. M., Goble, D. D., Haines, A. M., Wiens, J. A. & Neel, M. C. Conservation-reliant species and the future of conservation. Conserv. Lett. 3, 91–97 (2010).
Google Scholar 
Johnson, M. A., Kirby, R., Wang, S. & Losos, J. What drives variation in habitat use by Anolis lizards: Habitat availability or selectivity?. Can. J. Zool. 84, 877–886 (2006).
Google Scholar 
Gaston, K. J., Blackburn, T. M. & Lawton, J. H. Interspecific abundance-range size relationships: an appraisal of mechanisms. J. Anim. Ecol. 66, 579–601 (1997).
Google Scholar 
Devictor, V. et al. Defining and measuring ecological specialization. J. Appl. Ecol. 47, 15–25 (2010).
Google Scholar 
Razgour, O., Hanmer, J. & Jones, G. Using multi-scale modelling to predict habitat suitability for species of conservation concern: The grey long-eared bat as a case study. Biol. Cons. 144, 2922–2930 (2011).
Google Scholar 
Jetz, W., Sekercioglu, C. H. & Watson, J. E. Ecological correlates and conservation implications of overestimating species geographic ranges. Conserv. Biol. 22, 110–119 (2008).PubMed 

Google Scholar 
Seddon, P. J. From reintroduction to assisted colonization: Moving along the conservation translocation spectrum. Restor. Ecol. 18, 796–802 (2010).
Google Scholar 
Tomlinson, S., Lewandrowski, W., Elliott, C. P., Miller, B. P. & Turner, S. R. High-resolution distribution modeling of a threatened short-range endemic plant informed by edaphic factors. Ecol. Evol. 10, 763–773 (2019).PubMed 
PubMed Central 

Google Scholar 
Tomlinson, S., Webber, B. L., Bradshaw, S. D., Dixon, K. W. & Renton, M. Incorporating biophysical ecology into high-resolution restoration targets: insect pollinator habitat suitability models. Restor. Ecol. 26, 338–347 (2018).
Google Scholar 
Glen, A. S., Sutherland, D. R. & Cruz, J. An improved method of microhabitat assessment relevant to predation risk. Ecol. Res. 25, 311–314 (2010).
Google Scholar 
Limberger, D., Trillmich, F., Biebach, H. & Stevenson, R. D. Temperature regulation and microhabitat choice by free-ranging Galapagos fur seal pups (Arctocephalus galapagoensis). Oecologia 69, 53–59 (1986).PubMed 

Google Scholar 
Parmenter, R. R., Parmenter, C. A. & Cheney, C. D. Factors influencing microhabitat partitioning in arid-land darkling beetles (Tenebrionidae): temperature and water conservation. J. Arid Environ. 17, 57–67 (1989).
Google Scholar 
Kleckova, I., Konvicka, M. & Klecka, J. Thermoregulation and microhabitat use in mountain butterflies of the genus Erebia: importance of fine-scale habitat heterogeneity. J. Therm. Biol 41, 50–58 (2014).PubMed 

Google Scholar 
Napierała, A. & Błoszyk, J. Unstable microhabitats (merocenoses) as specific habitats of Uropodina mites (Acari: Mesostigmata). Exp. Appl. Acarol. 60, 163–180 (2013).PubMed 
PubMed Central 

Google Scholar 
Marshall, K. L., Philpot, K. E. & Stevens, M. Microhabitat choice in island lizards enhances camouflage against avian predators. Sci. Rep. 6, 1–10 (2016).
Google Scholar 
Lovell, P. G., Ruxton, G. D., Langridge, K. V. & Spencer, K. A. Egg-laying substrate selection for optimal camouflage by quail. Curr. Biol. 23, 260–264 (2013).CAS 
PubMed 

Google Scholar 
Wrege, P. H., Rowland, E. D., Keen, S. & Shiu, Y. Acoustic monitoring for conservation in tropical forests: Examples from forest elephants. Methods Ecol. Evol. 8, 1292–1301 (2017).
Google Scholar 
Measey, G. J., Stevenson, B. C., Scott, T., Altwegg, R. & Borchers, D. L. Counting chirps: Acoustic monitoring of cryptic frogs. J. Appl. Ecol. 54, 894–902 (2017).
Google Scholar 
Lambert, K. T. & McDonald, P. G. A low-cost, yet simple and highly repeatable system for acoustically surveying cryptic species. Austral Ecol. 39, 779–785 (2014).
Google Scholar 
Picciulin, M., Kéver, L., Parmentier, E. & Bolgan, M. Listening to the unseen: Passive Acoustic Monitoring reveals the presence of a cryptic fish species. Aquat. Conserv. Mar. Freshwat. Ecosyst. 29, 202–210 (2019).
Google Scholar 
Linkie, M. et al. Cryptic mammals caught on camera: assessing the utility of range wide camera trap data for conserving the endangered Asian tapir. Biol. Cons. 162, 107–115 (2013).
Google Scholar 
Balme, G. A., Hunter, L. T. & Slotow, R. Evaluating methods for counting cryptic carnivores. J. Wildl. Manag. 73, 433–441 (2009).
Google Scholar 
Carbone, C. et al. The use of photographic rates to estimate densities of tigers and other cryptic mammals in Animal Conservation forum. 75–79 (2001) (Cambridge University Press).Russell, J. C., Hasler, N., Klette, R. & Rosenhahn, B. Automatic track recognition of footprints for identifying cryptic species. Ecology 90, 2007–2013 (2009).PubMed 

Google Scholar 
Jarvie, S. & Monks, J. Step on it: can footprints from tracking tunnels be used to identify lizard species?. N. Z. J. Zool. 41, 210–217 (2014).
Google Scholar 
Watts, C., Thornburrow, D., Rohan, M. & Stringer, I. Effective monitoring of arboreal giant weta (Deinacrida heteracantha and D. mahoenui; Orthoptera: Anostostomatidae) using footprint tracking tunnels. J. Orthop. Res. 22, 93–100 (2013).
Google Scholar 
Williams, E. M. Developing monitoring methods for cryptic species: a case study of the Australasian bittern, Botaurus poiciloptilus: a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Ecology at Massey University, Manawatū, New Zealand, Massey University (2016).Hacking, J., Abom, R. & Schwarzkopf, L. Why do lizards avoid weeds?. Biol. Invasions 16, 935–947 (2014).
Google Scholar 
Valentine, L. E. Habitat avoidance of an introduced weed by native lizards. Austral. Ecol. 31, 732–735 (2006).
Google Scholar 
Hawkins, J. P., Roberts, C. M. & Clark, V. The threatened status of restricted-range coral reef fish species in Animal Conservation forum. 81–88 (2000) (Cambridge University Press).Mason, L. D., Bateman, P. W. & Wardell-Johnson, G. W. The pitfalls of short-range endemism: High vulnerability to ecological and landscape traps. PeerJ 6, e4715 (2018).PubMed 
PubMed Central 

Google Scholar 
Dassot, M., Constant, T. & Fournier, M. The use of terrestrial LiDAR technology in forest science: Application fields, benefits and challenges. Ann. For. Sci. 68, 959–974 (2011).
Google Scholar 
Weber, H. LiDAR Sensor Functionality and Variants (2018).Michel, P., Jenkins, J., Mason, N., Dickinson, K. & Jamieson, I. Assessing the ecological application of lasergrammetric techniques to measure fine-scale vegetation structure. Eco. Inform. 3, 309–320 (2008).
Google Scholar 
Lim, K., Treitz, P., Wulder, M., St-Onge, B. & Flood, M. LiDAR remote sensing of forest structure. Prog. Phys. Geogr. 27, 88–106 (2003).
Google Scholar 
Anderson, L. & Burgin, S. Patterns of bird predation on reptiles in small woodland remnant edges in peri-urban north-western Sydney, Australia. Landsc. Ecol. 23, 1039–1047 (2008).
Google Scholar 
Hannam, M. & Moskal, L. M. Terrestrial laser scanning reveals seagrass microhabitat structure on a tideflat. Remote Sensing 7, 3037–3055 (2015).
Google Scholar 
Zavalas, R., Ierodiaconou, D., Ryan, D., Rattray, A. & Monk, J. Habitat classification of temperate marine macroalgal communities using bathymetric LiDAR. Remote Sens. 6, 2154–2175 (2014).
Google Scholar 
Mandlburger, G., Hauer, C., Wieser, M. & Pfeifer, N. Topo-bathymetric LiDAR for monitoring river morphodynamics and instream habitats—A case study at the Pielach River. Remote Sens. 7, 6160–6195 (2015).
Google Scholar 
Laize, C. et al. Use of LIDAR to characterise river morphology (2014).Cooper, C. & Withers, P. Physiological significance of the microclimate in night refuges of the numbat Myrmecobius fasciatus. Austral. Mammal. 27, 169–174 (2005).
Google Scholar 
Orell, P. & Morris, K. Chuditch recovery plan. Western Austral. Wildl. Manag. Program 13, 1 (1994).
Google Scholar 
Pearson, D. Western Spiny-Tailed Skink (Egernia stokesii) Recovery Plan (Department of Environment and Conservation, 2012).
Google Scholar 
McPeek, M. A., Cook, B. & McComb, W. Habitat selection by small mammals. Trans. Kentucky Acad. Sci. 44, 68–73 (1983).
Google Scholar 
Armstrong, K. The distribution and roost habitat of the orange leaf-nosed bat, Rhinonicteris aurantius, in the Pilbara region of Western Australia. Wildl. Res. 28, 95–104 (2001).
Google Scholar 
Mancina, C. et al. Endemics under threat: an assessment of the conservation status of Cuban bats. Hystrix Ital. J. Mammal. 18, 3–15 (2007).
Google Scholar 
Webb, M. H., Holdsworth, M. C. & Webb, J. Nesting requirements of the endangered Swift Parrot (Lathamus discolor). Emu-Austral. Ornithol. 112, 181–188 (2012).
Google Scholar 
Watson, S. J., Watson, D. M., Luck, G. W. & Spooner, P. G. Effects of landscape composition and connectivity on the distribution of an endangered parrot in agricultural landscapes. Landsc. Ecol. 29, 1249–1259 (2014).
Google Scholar 
Duffield, G. & Bull, M. Stable social aggregations in an Australian lizard, Egernia stokesii. Naturwissenschaften 89, 424–427 (2002).CAS 
PubMed 

Google Scholar 
Duffield, G. A. & Bull, M. Characteristics of the litter of the gidgee skink, Egernia stokesii. Wildl. Res. 23, 337–341 (1996).
Google Scholar 
Ecoscape. Blue Hills – Mungada East Terrestrial Fauna Assessment. (Sinosteel Midwest Corporation, 2016).Silver Lake Resources. Department of Water and Environmental Regulation Prescribe Premise Licence Application. (Egan Street Resources Limited, 2021).Maptek. I-Site 8800 Scanning System Solutions for Mining (2010).SoilWater Group. 3D LiDAR Scanning (2018).United States Department of Transportation. Ground-Based LiDAR Rock Slope Mapping and Assessment (2008).R Core Team. R: a language and environment for statistical computing, https://www.R-project.org/ (2017).Bartoń, K. Package ‘MuMIn’, https://cran.r-project.org/web/packages/MuMIn/MuMIn.pdf (2020).Converse, S. J., White, G. C. & Block, W. M. Small mammal responses to thinning and wildfire in ponderosa pine-dominated forests of the southwestern United States. J. Wildl. Manag. 70, 1711–1722 (2006).
Google Scholar 
Vieira, I. C. G. et al. Classifying successional forests using Landsat spectral properties and ecological characteristics in eastern Amazonia. Remote Sens. Environ. 87, 470–481 (2003).
Google Scholar 
Whitford, K. & Williams, M. Hollows in jarrah (Eucalyptus marginata) and marri (Corymbia calophylla) trees: II. Selecting trees to retain for hollow dependent fauna. For. Ecol. Manag. 160, 215–232 (2002).
Google Scholar 
Salmona, J., Dixon, K. M. & Banks, S. C. The effects of fire history on hollow-bearing tree abundance in montane and subalpine eucalypt forests in southeastern Australia. For. Ecol. Manag. 428, 93–103 (2018).
Google Scholar 
Lindenmayer, D., Cunningham, R., Donnelly, C., Tanton, M. & Nix, H. The abundance and development of cavities in Eucalyptus trees: a case study in the montane forests of Victoria, southeastern Australia. For. Ecol. Manage. 60, 77–104 (1993).
Google Scholar 
Craig, M. D. et al. How many mature microhabitats does a slow-recolonising reptile require? Implications for restoration of bauxite minesites in south-western Australia. Aust. J. Zool. 59, 9–17 (2011).
Google Scholar 
Schwarzkopf, L., Barnes, M. & Goodman, B. Belly up: Reduced crevice accessibility as a cost of reproduction caused by increased girth in a rock-using lizard. Austral Ecol. 35, 82–86 (2010).
Google Scholar 
Cooper, W. E. Jr. & Whiting, M. J. Islands in a sea of sand: Use of Acacia trees by tree skinks in the Kalahari Desert. J. Arid Environ. 44, 373–381 (2000).
Google Scholar 
Webb, J. K. & Shine, R. Out on a limb: conservation implications of tree-hollow use by a threatened snake species (Hoplocephalus bungaroides: Serpentes, Elapidae). Biol. Cons. 81, 21–33 (1997).
Google Scholar 
Fitzgerald, M., Shine, R. & Lemckert, F. Radiotelemetric study of habitat use by the arboreal snake Hoplocephalus stephensii (Elapidae) in eastern Australia. Copeia 2002, 321–332 (2002).
Google Scholar 
Grimm-Seyfarth, A., Mihoub, J. B. & Henle, K. Too hot to die? The effects of vegetation shading on past, present, and future activity budgets of two diurnal skinks from arid Australia. Ecol. Evol. 7, 6803–6813 (2017).PubMed 
PubMed Central 

Google Scholar 
Attum, O., Eason, P., Cobbs, G. & El Din, S. M. B. Response of a desert lizard community to habitat degradation: Do ideas about habitat specialists/generalists hold?. Biol. Cons. 133, 52–62 (2006).
Google Scholar 
Melville, J. & Schulte Ii, J. A. Correlates of active body temperatures and microhabitat occupation in nine species of central Australian agamid lizards. Austral. Ecol. 26, 660–669. https://doi.org/10.1046/j.1442-9993.2001.01152.x (2001).Article 

Google Scholar 
Munguia-Vega, A., Rodriguez-Estrella, R., Shaw, W. W. & Culver, M. Localized extinction of an arboreal desert lizard caused by habitat fragmentation. Biol. Cons. 157, 11–20 (2013).
Google Scholar 
Pietrek, A., Walker, R. & Novaro, A. Susceptibility of lizards to predation under two levels of vegetative cover. J. Arid Environ. 73, 574–577 (2009).
Google Scholar 
Moreno, S., Delibes, M. & Villafuerte, R. Cover is safe during the day but dangerous at night: The use of vegetation by European wild rabbits. Can. J. Zool. 74, 1656–1660 (1996).
Google Scholar 
Tchabovsky, A. V., Krasnov, B., Khokhlova, I. S. & Shenbrot, G. I. The effect of vegetation cover on vigilance and foraging tactics in the fat sand rat Psammomys obesus. J. Ethol. 19, 105–113 (2001).
Google Scholar 
Pizzuto, T. A., Finlayson, G. R., Crowther, M. S. & Dickman, C. R. Microhabitat use by the brush-tailed bettong (Bettongia penicillata) and burrowing bettong (B. lesueur) in semiarid New South Wales: Implications for reintroduction programs. Wildl. Res. 34, 271–279 (2007).
Google Scholar 
Hawlena, D., Saltz, D., Abramsky, Z. & Bouskila, A. Ecological trap for desert lizards caused by anthropogenic changes in habitat structure that favor predator activity. Conserv. Biol. 24, 803–809 (2010).PubMed 

Google Scholar 
Oversby, W., Ferguson, S., Davis, R. A. & Bateman, P. Bad news for bobtails: Understanding predatory behaviour of a resource-subsidised corvid towards an island endemic reptile. Wildl. Res. 45, 595–601 (2018).
Google Scholar 
Pianka, E. R. Rarity in A ustralian desert lizards. Austral Ecol. 39, 214–224 (2014).
Google Scholar 
Germano, J. M. & Bishop, P. J. Suitability of amphibians and reptiles for translocation. Conserv. Biol. 23, 7–15 (2009).PubMed 

Google Scholar 
Tsiouvaras, C., Havlik, N. & Bartolome, J. Effects of goats on understory vegetation and fire hazard reduction in a coastal forest in California. For. Sci. 35, 1125–1131 (1989).
Google Scholar 
Tasker, E. M. & Bradstock, R. A. Influence of cattle grazing practices on forest understorey structure in north-eastern New South Wales. Austral. Ecol. 31, 490–502 (2006).
Google Scholar 
Payne, A., Van Vreeswyk, A., Leighton, K., Pringle, H. & Hennig, P. An inventory and condition survey of the Sandstone-Yalgoo-Paynes Find area, Western Australia (1998).Shoo, L. P., Freebody, K., Kanowski, J. & Catterall, C. P. Slow recovery of tropical old-field rainforest regrowth and the value and limitations of active restoration. Conserv. Biol. 30, 121–132 (2016).PubMed 

Google Scholar 
Lamb, D. in Regreening the Bare Hills 325–358 (Springer, 2011).Bowler, D. E. & Benton, T. G. Causes and consequences of animal dispersal strategies: Relating individual behaviour to spatial dynamics. Biol. Rev. 80, 205–225 (2005).PubMed 

Google Scholar 
Stow, A. J., Sunnucks, P., Briscoe, D. & Gardner, M. The impact of habitat fragmentation on dispersal of Cunningham’s skink (Egernia cunninghami): Evidence from allelic and genotypic analyses of microsatellites. Mol. Ecol. 10, 867–878 (2001).CAS 
PubMed 

Google Scholar 
Stow, A. & Sunnucks, P. High mate and site fidelity in Cunningham’s skinks (Egernia cunninghami) in natural and fragmented habitat. Mol. Ecol. 13, 419–430 (2004).CAS 
PubMed 

Google Scholar  More

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•    You will stand out much more if you have a niche and unique story. It could be your rare field of science or a special angle that you use to tell the story of your work. Being different is awesome.
•    Set the bar very high. You can find dozens of examples of truly high-quality content on the Internet. And you can almost always find resources that can help you to learn how to create work of the same calibre. With practice, your skills will inevitably rise — but at any given time, it’s important to know the level you should aim for.
•    Find people who are cooler than you. Don’t hesitate to ask them for advice or to shadow them. Have them share their experiences, stand behind them and observe their work if they’ll let you. Few things are more useful than real work experience, both your own and that of others.
•    Take on a project. This could be a an illustrated workbook for colleagues or students, a guide book, a lecture for schoolchildren with compelling visuals, a course for students or a documentary on your topic.
•    If you work in a team, you can raise the bar even higher. Use each other’s strengths, share experiences, make plans, apply for grants and take on challenging science-communication projects together. This multiplies the fun and the results. More