Philippa Kaur

Ward, M. et al. Impact of 2019–2020 mega-fires on Australian fauna habitat. Nat. Ecol. Evol. 4(10), 1321–1326. https://doi.org/10.1038/s41559-020-1251-1 (2020).Article 

Google Scholar 
Legge, S. et al. Estimates of the impacts of the 2019–20 fires on populations of native animal species, Brisbane (2021).Yibo, H. et al. Genomic evidence for two phylogenetic species and long-term population bottlenecks in red pandas. Sci. Adv. 6(9), eaax5751. https://doi.org/10.1126/sciadv.aax5751 (2022).Article 

Google Scholar 
Grossen, C., Guillaume, F., Keller, L. F. & Croll, D. Purging of highly deleterious mutations through severe bottlenecks in Alpine ibex. Nat. Commun. 11(1), 1001. https://doi.org/10.1038/s41467-020-14803-1 (2020).Article 
ADS 

Google Scholar 
van Aalst, M. K. The impacts of climate change on the risk of natural disasters. Disasters 30(1), 5–18. https://doi.org/10.1111/j.1467-9523.2006.00303.x (2006).Article 

Google Scholar 
Banholzer, S., Kossin, J. & Donner, S. The impact of climate change on natural disasters. In Reducing Disaster: Early Warning Systems For Climate Change (eds Singh, A. & Zommers, Z.) 21–49 (Springer Netherlands, 2014). https://doi.org/10.1007/978-94-017-8598-3_2.Chapter 

Google Scholar 
Frankham, R., Ballou, J. D. & Briscoe, D. A. Introduction to Conservation Genetics 2nd edn. (Cambridge University Press, 2010).Book 

Google Scholar 
Bouzat, J. L. Conservation genetics of population bottlenecks: The role of chance, selection, and history. Conserv. Genet. 11(2), 463–478. https://doi.org/10.1007/s10592-010-0049-0 (2010).Article 

Google Scholar 
Leigh, D. M., Hendry, A. P., Vázquez-Domínguez, E. & Friesen, V. L. Estimated six per cent loss of genetic variation in wild populations since the industrial revolution. Evol. Appl. 12(8), 1505–1512. https://doi.org/10.1111/eva.12810 (2019).Article 

Google Scholar 
Willi, Y., Van Buskirk, J. & Hoffmann, A. A. Limits to the adaptive potential of small populations. Annu. Rev. Ecol. Evol. Syst. 37(1), 433–458 (2006).Article 

Google Scholar 
Tanaka, M. M., Wahl, L. M. & Wahl, L. M. Surviving environmental change: When increasing population size can increase extinction risk. Proc. R. Soc. B 289, 20220439. https://doi.org/10.1098/rspb.2022.0439 (2022).Article 

Google Scholar 
Gomulkiewicz, R. & Holt, R. D. When does evolution by natural selection prevent extinction?. Evolution 49(1), 201–207. https://doi.org/10.1111/j.1558-5646.1995.tb05971.x (1995).Article 

Google Scholar 
Bell, G. Evolutionary rescue. Annu. Rev. Ecol. Evol. Syst. 48(1), 605–627. https://doi.org/10.1146/annurev-ecolsys-110316-023011 (2017).Article 

Google Scholar 
Wood, J. L. A., Yates, M. C. & Fraser, D. J. Are heritability and selection related to population size in nature? Meta-analysis and conservation implications. Evol. Appl. 9(5), 640–657. https://doi.org/10.1111/eva.12375 (2016).Article 

Google Scholar 
Sgrò, C. M., Lowe, A. J. & Hoffmann, A. A. Building evolutionary resilience for conserving biodiversity under climate change. Evol. Appl. 4(2), 326–337 (2011).Article 

Google Scholar 
Hohenlohe, P. A., Funk, W. C. & Rajora, O. P. Population genomics for wildlife conservation and management. Mol. Ecol. 30(1), 62–82. https://doi.org/10.1111/mec.15720 (2021).Article 

Google Scholar 
Walters, A. D. & Schwartz, M. K. Population genomics for the management of wild vertebrate populations. In Population Genomics: Wildlife 419–436 (Springer, 2020).Chapter 

Google Scholar 
Willi, Y. et al. Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species. Proc. Natl. Acad. Sci. USA 119(1), 1–10. https://doi.org/10.1073/pnas.2105076119 (2022).Article 

Google Scholar 
Moore, J. F. et al. The potential and practice of arboreal camera trapping. Methods Ecol. Evol. https://doi.org/10.1111/2041-210X.13666 (2021).Article 

Google Scholar 
Frankham, R. Challenges and opportunities of genetic approaches to biological conservation. Biol. Conserv. 143(9), 1919–1927. https://doi.org/10.1016/j.biocon.2010.05.011 (2010).Article 

Google Scholar 
Allendorf, F. W., Luikart, G. H. & Aitken, S. N. Conservation and the Genetics of Populations 2nd edn. (Wiley, 2012).
Google Scholar 
Franklin, I. Evolutionary change in small populations. In Conservation Biology—An Evolutionary-Ecological Perspective 135–149 (Sinauer Associates, 1980).
Google Scholar 
Soulé, M. E. Thresholds for survival: maintaining fitness and evolutionary potential. In Conservation Biology: An Evolutionary-Ecological Perspective 151–169 (Sinauer, 1980).
Google Scholar 
Hoban, S. et al. Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biol. Conserv. https://doi.org/10.1016/J.BIOCON.2020.108654 (2020).Article 

Google Scholar 
McGregor, D. C. et al. Genetic evidence supports three previously described species of greater glider, Petauroides volans, P. minor, and P. armillatus. Sci. Rep. 10(1), 1–11. https://doi.org/10.1038/s41598-020-76364-z (2020).Article 

Google Scholar 
Hogg, C. J. et al. Threatened species initiative: Empowering conservation action using genomic resources. Proc. Natl. Acad. Sci. USA 119(4), e2115643118. https://doi.org/10.1073/pnas.2115643118 (2022).Article 

Google Scholar 
Pierson, J. C. et al. Genetic factors in threatened species recovery plans on three continents. Front. Ecol. Environ. 14(8), 433–440. https://doi.org/10.1002/fee.1323 (2016).Article 

Google Scholar 
Harris, J. M. & Maloney, K. S. S. Petauroides volans (Diprotodontia: Pseudocheiridae). Mamm. Species 42(866), 207–219. https://doi.org/10.1644/866.1 (2010).Article 

Google Scholar 
Kavanagh, R. P. & Lambert, M. J. Food selection by the greater glider, Petauroides volans: Is foliar nitrogen a determinant of habitat quality?. Austral. Wildl. Res. 17(3), 285–299 (1990).Article 

Google Scholar 
Youngentob, K. N. et al. Foliage chemistry influences tree choice and landscape use of a gliding marsupial folivore. J. Chem. Ecol. 37(1), 71–84. https://doi.org/10.1007/s10886-010-9889-9 (2011).Article 

Google Scholar 
Jensen, L. M., Wallis, I. R. & Foley, W. J. The relative concentrations of nutrients and toxins dictate feeding by a vertebrate browser, the greater glider Petauroides volans. PLoS ONE 10(5), 1–12. https://doi.org/10.1371/journal.pone.0121584 (2015).Article 

Google Scholar 
Kehl, J. & Borsboom, A. Home range, den tree use and activity patterns in the greater glider, Petauroides volans. Possums Gliders 229–236 (1984).Goldingay, R. L. Characteristics of tree hollows used by Australian arboreal and scansorial mammals. Aust. J. Zool. 59(5), 277–294 (2012).Article 

Google Scholar 
Eyre, T. J. Regional habitat selection of large gliding possums at forest stand and landscape scales in southern Queensland, Australia: I. Greater glider (Petauroides volans). For. Ecol. Manag 235(1–3), 270–282. https://doi.org/10.1016/j.foreco.2006.08.338 (2006).Article 

Google Scholar 
Kavanagh, R. P. & Bamkin, K. L. Distribution of nocturnal forest birds and mammals in relation to the logging mosaic in south-eastern New South Wales, Australia. Biol. Conserv. 71(1), 41–53. https://doi.org/10.1016/0006-3207(94)00019-M (1995).Article 

Google Scholar 
Lindenmayer, D. B. et al. Fire severity and landscape context effects on arboreal marsupials. Biol. Conserv. 167, 137–148 (2013).Article 

Google Scholar 
May-Stubbles, J. C., Gracanin, A. & Mikac, K. M. Increasing fire severity negatively affects greater glider density. Wildl. Res. https://doi.org/10.1071/wr21091 (2022).Article 

Google Scholar 
Smith, P. & Smith, J. Decline of the greater glider (Petauroides volans) in the lower Blue Mountains, New South Wales. Aust. J. Zool. 66(2), 103–114. https://doi.org/10.1071/ZO18021 (2019).Article 

Google Scholar 
Kearney, M. R., Wintle, B. A. & Porter, W. P. Correlative and mechanistic models of species distribution provide congruent forecasts under climate change. Conserv. Lett. 3(3), 203–213. https://doi.org/10.1111/j.1755-263X.2010.00097.x (2010).Article 

Google Scholar 
Wagner, B. et al. Climate change drives habitat contraction of a nocturnal arboreal marsupial at its physiological limits. Ecosphere 11(10), e03262 (2020).Article 

Google Scholar 
McLean, C. M., Kavanagh, R. P., Penman, T. & Bradstock, R. The threatened status of the hollow dependent arboreal marsupial, the greater glider (Petauroides volans), can be explained by impacts from wildfire and selective logging. For. Ecol. Manag. 415, 19–25 (2018).Article 

Google Scholar 
Lindenmayer, D. B. et al. Conservation conundrums and the challenges of managing unexplained declines of multiple species. Biol. Conserv. 221, 279–292. https://doi.org/10.1016/j.biocon.2018.03.007 (2018).Article 

Google Scholar 
Lindenmayer, D. B. B. et al. How to make a common species rare: a case against conservation complacency. Biol. Conserv. 144(5), 1663–1672. https://doi.org/10.1016/j.biocon.2011.02.022 (2011).Article 

Google Scholar 
IUCN. The IUCN Red List of Threatened Species (2022) https://www.iucnredlist.org (Accessed 17 Nov 2022).Rübsamen, K., Hume, I. D., Foley, W. J. & Rübsamen, U. Implications of the large surface area to body mass ratio on the heat balance of the greater glider (Petauroides volans: Marsupialia). J. Comp. Physiol. B. 154(1), 105–111. https://doi.org/10.1007/BF00683223 (1984).Article 

Google Scholar 
Wintle, B. A., Legge, S. & Woinarski, J. C. Z. After the megafires: What next for Australian wildlife?. Trends Ecol. Evol. 35(9), 753–757. https://doi.org/10.1016/j.tree.2020.06.009 (2020).Article 

Google Scholar 
Legge, S. et al. Estimates of the impacts of the 2019–2020 fires on populations of native animal species, Brisbane (2021).Hoffmann, A. A. & Sgró, C. M. Climate change and evolutionary adaptation. Nature 470(7335), 479–485. https://doi.org/10.1038/nature09670 (2011).Article 
ADS 

Google Scholar 
Hoffmann, A. A., Sgrò, C. M. & Kristensen, T. N. Revisiting adaptive potential, population size, and conservation. Trends Ecol. Evol. 32(7), 506–517. https://doi.org/10.1016/j.tree.2017.03.012 (2017).Article 

Google Scholar 
Rossetto, M. et al. A conservation genomics workflow to guide practical management actions. Glob. Ecol. Conserv. 26, e01492. https://doi.org/10.1016/j.gecco.2021.e01492 (2021).Article 

Google Scholar 
Mcmahon, B. J., Teeling, E. C. & Höglund, J. How and why should we implement genomics into conservation?. Evol. Appl. 7(9), 999–1007. https://doi.org/10.1111/eva.12193 (2014).Article 

Google Scholar 
Hoffmann, A. et al. A framework for incorporating evolutionary genomics into biodiversity conservation and management. Clim. Change Responses https://doi.org/10.1186/s40665-014-0009-x (2015).Article 

Google Scholar 
Lindenmayer, D. B. et al. Integrating demographic and genetic studies of the greater glider Petauroides volans in fragmented forests: predicting movement patterns and rates for future testing. Pac. Conserv. Biol. 5(1), 2–8 (1999).Article 

Google Scholar 
Taylor, A. C., Kraaijeveld, K. & Lindenmayer, D. B. Microsatellites for the greater glider, Petauroides volans. Mol. Ecol. Notes 2(1), 57–59. https://doi.org/10.1046/j.1471-8286.2002.00148.x (2002).Article 

Google Scholar 
Taylor, A. C., Tyndale-Biscoe, H. & Lindenmayer, D. B. Unexpected persistence on habitat islands: Genetic signatures reveal dispersal of a eucalypt-dependent marsupial through a hostile pine matrix. Mol. Ecol. 16(13), 2655–2666. https://doi.org/10.1111/j.1365-294X.2007.03331.x (2007).Article 

Google Scholar 
NSW Scientific Committee. Greater glider population in the Mount Gibraltar Reserve area” endangered population listing. Final Determination to list an endangered ecological community under the Threatened Species Conservation Act 1995 (2015).NSW Scientific Committee. Greater glider, Petauroides volans, in the Eurobodalla local government area endangered population listing. Final Determination to list an endangered ecological community under the Threatened Species Conservation Act 1995. (2007).NSW Scientific Committee. Greater Glider population at Seven Mile Beach National Park Endangered population listing. Final Determination to list an endangered ecological community under the Threatened Species Conservation Act 1995 (2016).Woinarski, J. C. Z., Burbidge, A. A. & Harrison, P. L. The Action Plan for Australian Mammals 2012 (CSIRO Publishing, 2014).Book 

Google Scholar 
W. and the E. Department of Agriculture. Conservation advice for Petauroides volans (Greater Glider (southern)), Canberra (2021).Gracanin, A., Pearce, A., Hofman, M., Knipler, M. & Mikac, K. Greater glider (Petauroides volans) live capture methods. Austral. Mammal. 44(2), 280–286 (2021).Article 

Google Scholar 
Comport, S. S., Ward, S. J. & Foley, W. J. Home ranges, time budgets and food-tree use in a high-density tropical population of greater gliders, Petauroides volans minor (Pseudocheiridae: Marsupialia). Wildl. Res. 23(4), 401–419. https://doi.org/10.1071/WR9960401 (1996).Article 

Google Scholar 
Henry, S. R. Social organisation of the greater glider (Petauroides volans) in Victoria. In Possums and Gliders (eds Smith, A. P. & Hume, I. D.) 221–228 (1984).Kilian, A. et al. Diversity arrays technology: A generic genome profiling technology on open platforms. Methods Mol. Biol. 888, 67–89. https://doi.org/10.1007/978-1-61779-870-2_5 (2012).Article 

Google Scholar 
Gruber, B., Unmack, P. J., Berry, O. F. & Georges, A. dartr: An r package to facilitate analysis of SNP data generated from reduced representation genome sequencing. Mol. Ecol. Resour. 18(3), 691–699. https://doi.org/10.1111/1755-0998.12745 (2018).Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
Google Scholar 
Privé, F., Luu, K., Vilhjálmsson, B. J. & Blum, M. G. B. Performing highly efficient genome scans for local adaptation with R package pcadapt version 4. Mol. Biol. Evol. 37(7), 2153–2154. https://doi.org/10.1093/molbev/msaa053 (2020).Article 

Google Scholar 
Luu, K., Bazin, E. & Blum, M. G. B. pcadapt: An R package to perform genome scans for selection based on principal component analysis. Mol. Ecol. Resour. 17(1), 67–77. https://doi.org/10.1111/1755-0998.12592 (2017).Article 

Google Scholar 
Dabney, A., Storey, J. D. & Warnes, G. R. qvalue: Q-value estimation for false discovery rate control. R package version, vol. 1, no. 0 (2010).Oksanen, J. et al. Package “vegan”. Community ecology package, version, vol. 2, no. 9, 1–295 (2013).Pratt, E. A. L. et al. Seascape genomics of coastal bottlenose dolphins along strong gradients of temperature and salinity. Mol. Ecol. 31(8), 2223–2241 (2022).Article 

Google Scholar 
Forester, B. R., Lasky, J. R., Wagner, H. H. & Urban, D. L. Comparing methods for detecting multilocus adaptation with multivariate genotype–environment associations. Mol. Ecol. 27(9), 2215–2233 (2018).Article 

Google Scholar 
Zimmerman, S. J. et al. Environmental gradients of selection for an alpine-obligate bird, the white-tailed ptarmigan (Lagopus leucura). Heredity 126(1), 117–131 (2021).Article 

Google Scholar 
Lott, M. J. et al. Future‐proofing the koala: Synergising genomic and environmental data for effective species management. Mol. Ecol. (2022).Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37(12), 4302–4315 (2017).Article 

Google Scholar 
Goudet, J. HIERFSTAT, a package for R to compute and test hierarchical F-statistics. Mol. Ecol. Notes 5(1), 184–186. https://doi.org/10.1111/J.1471-8286.2004.00828.X (2005).Article 

Google Scholar 
Nei, M. Molecular Evolutionary Genetics (Columbia University Press, 1987).Book 

Google Scholar 
Meirmans, P. G. & Hedrick, P. W. Assessing population structure: FST and related measures. Mol. Ecol. Resour. 11(1), 5–18. https://doi.org/10.1111/J.1755-0998.2010.02927.X (2011).Article 

Google Scholar 
Frankham, R., Ballou, J. D. & Briscoe, D. A. Introduction to Conservation Genetics (Cambridge University Press, 2002). https://doi.org/10.1016/j.foreco.2003.12.001.Book 

Google Scholar 
Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38(6), 1358. https://doi.org/10.2307/2408641 (1984).Article 

Google Scholar 
Pembleton, L. W., Cogan, N. O. I. & Forster, J. W. StAMPP: An R package for calculation of genetic differentiation and structure of mixed-ploidy level populations. Mol. Ecol. Resour. 13(5), 946–952. https://doi.org/10.1111/1755-0998.12129 (2013).Article 

Google Scholar 
Bonferroni, S. Teoria statistica delle classi e calcolo delle probabilita. cir.nii.ac.jp, vol. 8, 3–62 (1936).Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155(2), 945–959 (2000).Article 

Google Scholar 
Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11(1), 1–15. https://doi.org/10.1186/1471-2156-11-94/FIGURES/9 (2010).Article 

Google Scholar 
Janes, J. K. et al. The K = 2 conundrum. Mol. Ecol. 26(14), 3594–3602. https://doi.org/10.1111/MEC.14187 (2017).Article 

Google Scholar 
Miller, J. M., Cullingham, C. I. & Peery, R. M. The influence of a priori grouping on inference of genetic clusters: Simulation study and literature review of the DAPC method. Heredity 125, 269–280. https://doi.org/10.1038/s41437-020-0348-2 (2020).Article 

Google Scholar 
Cullingham, C. I. et al. Confidently identifying the correct K value using the ΔK method: When does K = 2?. Mol. Ecol. 29(5), 862–869. https://doi.org/10.1111/mec.15374 (2020).Article 

Google Scholar 
Pritchard, J., Wen, X. & Falush, D. Documentation for STRUCTURE software: version 2.3|Request PDF (2003).Earl, D. A. & VonHoldt, B. M. STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4(2), 359–361. https://doi.org/10.1007/s12686-011-9548-7 (2012).Article 

Google Scholar 
Stankiewicz, K. H., Vasquez Kuntz, K. L. & Baums, I. B. The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical data sets. Mol. Ecol. Resour. 22(3), 1135–1148. https://doi.org/10.1111/1755-0998.13522 (2022).Article 

Google Scholar 
Jombart, T. Adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24(11), 1403–1405. https://doi.org/10.1093/bioinformatics/btn129 (2008).Article 

Google Scholar 
Harmon, L. J. & Braude, S. Conservation of small populations: effective population sizes, inbreeding, and the 50/500 rule. In An Introduction to Methods and Models in Ecology, Evolution, and Conservation Biology 125–138 (Princeton University Press, 2010).Chapter 

Google Scholar 
Do, C. et al. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data. Mol. Ecol. Resour. 14(1), 209–214. https://doi.org/10.1111/1755-0998.12157 (2014).Article 

Google Scholar 
Waples, R. S. & Do, C. LDNE: A program for estimating effective population size from data on linkage disequilibrium. Mol. Ecol. Resour. 8(4), 753–756. https://doi.org/10.1111/J.1755-0998.2007.02061.X (2008).Article 

Google Scholar 
Potvin, D. A. et al. Genetic erosion and escalating extinction risk in frogs with increasing wildfire frequency. J. Appl. Ecol. 54(3), 945–954. https://doi.org/10.1111/1365-2664.12809 (2017).Article 

Google Scholar 
Catullo, R. A. et al. Benchmarking taxonomic and genetic diversity after the fact: Lessons learned from the catastrophic 2019–2020 Australian bushfires. Front. Ecol. Evol. 9, 292. https://doi.org/10.3389/FEVO.2021.645820/BIBTEX (2021).Article 
ADS 

Google Scholar 
DPIE. Fire Extent and Severity Mapping (FESM) 2019/20 (2021) https://datasets.seed.nsw.gov.au/dataset/fire-extent-and-severity-mapping-fesm-2019-20 (Accessed 23 June 2021).Banks, S. C. et al. Fire severity and landscape context effects on arboreal marsupials. Biol. Conserv. 167, 137–148. https://doi.org/10.1016/j.biocon.2013.07.028 (2013).Article 

Google Scholar 
Andrew, D., Koffel, D., Harvey, G., Griffiths, K. & Fleming, M. Rediscovery of the greater glider Petauroides volans (Marsupialia: Petauroidea) in the Royal National Park, NSW. Austral. Zool. 37(1), 23–28. https://doi.org/10.7882/AZ.2013.008 (2014).Article 

Google Scholar 
Lindenmayer, D. et al. What 15 years of monitoring is telling us about mammals in Booderee National Park (2018).Chafer, C. J. et al. The post-fire measurement of fire severity and intensity in the Christmas 2001 Sydney wildfires. Int. J. Wildland Fire 13(2), 227–240. https://doi.org/10.1071/WF03041 (2004).Article 

Google Scholar 
Vinson, S. G., Johnson, A. P. & Mikac, K. M. Current estimates and vegetation preferences of an endangered population of the vulnerable greater glider at Seven Mile Beach National Park. Austral. Ecol. 46(2), 303–314. https://doi.org/10.1111/aec.12979 (2020).Article 

Google Scholar 
Kavanagh, R. & Wheeler, R. Home-range of the greater glider Petauroides volans in tall montane forest of southeastern New South Wales, and changes following logging. In The Biology of Possums and Gliders (eds Goldingay, R. & Jackson, S.) 413–425 (Surrey Beatty & Sons, 2004).
Google Scholar 
Fleay, D. Gliders of the Gum Trees: The Most Beautiful and Enchanting Australian Marsupials (1947).Wright, S. Isolation by distance under diverse systems of mating. Genetics 31, 39–59 (1946).Article 

Google Scholar 
McGowan, B. & Wright, C. Braidwood’s enduring Chinese heritage. Historic Environ. 23(3), 34–39 (2011).
Google Scholar 
Pérez, I. et al. What is wrong with current translocations? A review and a decision-making proposal. Front. Ecol. Environ. 10(9), 494–501 (2012).Article 

Google Scholar 
Mace, G. M. et al. Quantification of extinction risk: IUCN’s system for classifying threatened species. Conserv. Biol. 22(6), 1424–1442. https://doi.org/10.1111/j.1523-1739.2008.01044.x (2008).Article 

Google Scholar 
Franklin, I. ‘Evolutionary change in small populations. In Conservation Biology—An Evolutionary-Ecological Perspective 135–149 (Sinauer Associates, 1980).
Google Scholar 
Frankham, R., Bradshaw, C. J. A. & Brook, B. W. Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biol. Conserv. 170, 56–63. https://doi.org/10.1016/J.BIOCON.2013.12.036 (2014).Article 

Google Scholar 
Seaborn, T. et al. Integrating genomics in population models to forecast translocation success. Restor. Ecol. 29(4), e13395. https://doi.org/10.1111/rec.13395 (2021).Article 

Google Scholar 
Christie, M. R. & Knowles, L. L. Habitat corridors facilitate genetic resilience irrespective of species dispersal abilities or population sizes. Evol. Appl. 8(5), 454–463 (2015).Article 

Google Scholar 
Office of Environment and Heritage. Woody extent and foliage projective cover (2016) http://data.auscover.org.au/xwiki/bin/view/Product+pages/nsw+5m+woody+extent+and+fpc (Accessed 29 Oct 2020).Ashman, K. R., Watchorn, D. J., Lindenmayer, D. B. & Taylor, M. F. J. Is Australia’s environmental legislation protecting threatened species? A case study of the national listing of the greater glider. Pac. Conserv. Biol. 1980, 277–289. https://doi.org/10.1071/PC20077 (2021).Article 

Google Scholar 
ESRI. ArcGIS 10.7.1. (Environmental Systems Research Institute, 2011). More

Griggs, D. et al. Sustainable development goals for people and planet. Nature 495, 305–307 (2013).Article 
CAS 

Google Scholar 
Charlop-Powers, Z. et al. Urban park soil microbiomes are a rich reservoir of natural product biosynthetic diversity. Proc. Natl Acad. Sci. USA 113, 14811 (2016).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. Global homogenization of the structure and function in the soil microbiome of urban greenspaces. Sci. Adv. 7, eabg5809 (2021).Article 
CAS 

Google Scholar 
Martínez, J. L. Antibiotics and antibiotic resistance genes in natural environments. Science 321, 365–367 (2008).Article 

Google Scholar 
Forsberg, K. J. et al. The shared antibiotic resistome of soil bacteria and human pathogens. Science 337, 1107–1111 (2012).Article 
CAS 

Google Scholar 
Byrnes, J. E. K. et al. Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions. Methods Ecol. Evolution 5, 111–124 (2014).Article 

Google Scholar 
Gamfeldt, L. & Roger, F. Revisiting the biodiversity–ecosystem multifunctionality relationship. Nat. Ecol. Evolution 1, 0168 (2017).Article 

Google Scholar 
Lefcheck, J. S. et al. Biodiversity enhances ecosystem multifunctionality across trophic levels and habitats. Nat. Commun. 6, 6936 (2015).Article 
CAS 

Google Scholar 
Zavaleta, E. S. et al. Sustaining multiple ecosystem functions in grassland communities requires higher biodiversity. Proc. Natl Acad. Sci. USA 107, 1443 (2010).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat. Commun. 7, 10541 (2016).Article 
CAS 

Google Scholar 
Wagg, C. et al. Soil biodiversity and soil community composition determine ecosystem multifunctionality. Proc. Natl Acad. Sci. USA 111, 5266 (2014).Article 
CAS 

Google Scholar 
van der Heijden, M. G. A. et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72 (1998).Article 

Google Scholar 
Delgado-Baquerizo, M. et al. Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nat. Ecol. Evol. 4, 210–220 (2020).Article 

Google Scholar 
Ramirez, K. S. et al. Biogeographic patterns in below-ground diversity in New York City’s Central Park are similar to those observed globally. Proc. R. Soc. B 281, 20141988 (2014).Article 

Google Scholar 
Schittko, C. et al. Biodiversity maintains soil multifunctionality and soil organic carbon in novel urban ecosystems. J. Ecol. https://doi.org/10.1111/1365-2745.13852 (2022).Maestre, F. T. et al. Plant species richness and ecosystem multifunctionality in global drylands. Science 335, 214–218 (2012).Article 
CAS 

Google Scholar 
Jing, X. et al. The links between ecosystem multifunctionality and above-and belowground biodiversity are mediated by climate. Nat. Commun. 6, 1–8 (2015).Article 

Google Scholar 
Kadowaki, K. et al. Mycorrhizal fungi mediate the direction and strength of plant–soil feedbacks differently between arbuscular mycorrhizal and ectomycorrhizal communities. Commun. Biol. 1, 196 (2018).Article 

Google Scholar 
Soliveres, S. et al. Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality. Nature 536, 456–459 (2016).Article 
CAS 

Google Scholar 
Berman, J. J. in Taxonomic Guide to Infectious Diseases (ed. Berman, J. J.) 37–47 (Academic Press, 2012).Berman, J. J. in Taxonomic Guide to Infectious Diseases (ed. Berman, J. J.) 25–31 (Academic Press, 2012).Busse, H.-J. in Methods in Microbiology (eds Rainey, F. & Oren. A.) Vol. 38, 239–259 (Academic Press, 2011).van den Hoogen, J. et al. Soil nematode abundance and functional group composition at a global scale. Nature 572, 194–198 (2019).Article 

Google Scholar 
van Bergeijk, D. A. et al. Ecology and genomics of Actinobacteria: new concepts for natural product discovery. Nat. Rev. Microbiol. 18, 546–558 (2020).Article 

Google Scholar 
Orellana, L. H. et al. Verrucomicrobiota are specialist consumers of sulfated methyl pentoses during diatom blooms. ISME J. 16, 630–641 (2022).Article 
CAS 

Google Scholar 
Fincker, M. et al. Metabolic strategies of marine subseafloor Chloroflexi inferred from genome reconstructions. Environ. Microbiol. 22, 3188–3204 (2020).Article 
CAS 

Google Scholar 
Stralis-Pavese, N. et al. Analysis of methanotroph community composition using a pmoA-based microbial diagnostic microarray. Nat. Protoc. 6, 609–624 (2011).Article 
CAS 

Google Scholar 
Berube, P. M. et al. Physiology and evolution of nitrate acquisition in Prochlorococcus. ISME J. 9, 1195–1207 (2015).Article 
CAS 

Google Scholar 
Liang, J.-L. et al. Novel phosphate-solubilizing bacteria enhance soil phosphorus cycling following ecological restoration of land degraded by mining. ISME J. 14, 1600–1613 (2020).Article 
CAS 

Google Scholar 
Hättenschwiler, S. & Gasser, P. Soil animals alter plant litter diversity effects on decomposition. Proc. Natl Acad. Sci. USA 102, 1519 (2005).Article 

Google Scholar 
Erktan, A. et al. The physical structure of soil: determinant and consequence of trophic interactions. Soil Biol. Biochem. 148, 107876 (2020).Article 
CAS 

Google Scholar 
Grime, J. P. Benefits of plant diversity to ecosystems: immediate, filter and founder effects. J. Ecol. 86, 902–910 (1998).Article 

Google Scholar 
Barberán, A. et al. Why are some microbes more ubiquitous than others? Predicting the habitat breadth of soil bacteria. Ecol. Lett. 17, 794–802 (2014).Article 

Google Scholar 
Chen, Q. L. et al. Rare microbial taxa as the major drivers of ecosystem multifunctionality in long-term fertilized soils. Soil Biol. Biochem. 141, 107686 (2020).Article 
CAS 

Google Scholar 
Zhang, Z. et al. Rare species-driven diversity-ecosystem multifunctionality relationships are promoted by stochastic community assembly. mBio. mBio. 13, e00449–22 (2022).Article 

Google Scholar 
Domínguez-García, V. et al. Unveiling dimensions of stability in complex ecological networks. Proc. Natl Acad. Sci. USA 116, 25714 (2019).Article 

Google Scholar 
Zhang, L. et al. Signal beyond nutrient, fructose, exuded by an arbuscular mycorrhizal fungus triggers phytate mineralization by a phosphate solubilizing bacterium. ISME J. 12, 2339–2351 (2018).Article 
CAS 

Google Scholar 
Couturier, M. et al. Lytic xylan oxidases from wood-decay fungi unlock biomass degradation. Nat. Chem. Biol. 14, 306–310 (2018).Article 
CAS 

Google Scholar 
Steinberg, G. et al. A lipophilic cation protects crops against fungal pathogens by multiple modes of action. Nat. Commun. 11, 1608 (2020).Article 
CAS 

Google Scholar 
Johnston, A. S. A. & Sibly, R. M. The influence of soil communities on the temperature sensitivity of soil respiration. Nat. Ecol. Evol. 2, 1597–1602 (2018).Article 

Google Scholar 
Watson, C. J. et al. Ecological and economic benefits of low-intensity urban lawn management. J. Appl. Ecol. 57, 436–446 (2020).Article 

Google Scholar 
Williams, N. S. G. et al. A conceptual framework for predicting the effects of urban environments on floras. J. Ecol. 97, 4–9 (2009).Article 

Google Scholar 
Trabucco, A. & Zomer, R. Global Aridity Index and Potential Evapotranspiration (ET0) Climate Database v2 (figshare, 2019); https://doi.org/10.6084/m9.figshare.7504448.v3Kettler, T. A. et al. Simplifed method for soil particle-size determination to accompany soil-quality analyses. Soil Sci. Soc. Am. J. 65, 849–852 (2001).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. Changes in belowground biodiversity during ecosystem development. Proc. Natl Acad. Sci. USA 116, 6891 (2019).Article 
CAS 

Google Scholar 
Ramirez, K. S. et al. Biogeographic patterns in below-ground diversity in New York City’s Central Park are similar to those observed globally. Proc. Biol. Sci. 281, 22 (2014).
Google Scholar 
Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).Article 
CAS 

Google Scholar 
Tedersoo, L. et al. Regional-scale in-depth analysis of soil fungal diversity reveals strong pH and plant species effects in Northern Europe. Front. Microbiol. 11, 1953 (2020).Article 

Google Scholar 
Bastida, F. et al. Microbiological degradation index of soils in a semiarid climate. Soil Biol. Biochem. 38, 3463–3473 (2006).Article 
CAS 

Google Scholar 
Lugato, E. et al. Different climate sensitivity of particulate and mineral-associated soil organic matter. Nat. Geosci. 14, 295–300 (2021).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. The influence of soil age on ecosystem structure and function across biomes. Nat. Commun. 11, 4721 (2020).Article 
CAS 

Google Scholar 
Frostegård, Å. et al. Use and misuse of PLFA measurements in soils. Soil Biol. Biochem. 43, 1621–1625 (2011).Article 

Google Scholar 
Olsson, P. A. et al. The use of phospholipid and neutral lipid fatty acids to estimate biomass of arbuscular mycorrhizal fungi in soil. Mycol. Res. 99, 623–629 (1995).Article 
CAS 

Google Scholar 
Campbell, C. D. et al. A rapid microtiter plate method to measure carbon dioxide evolved from carbon substrate amendments so as to determine the physiological profiles of soil microbial communities by using whole soil. Appl. Environ. Microbiol. 69, 3593–3599 (2003).Article 
CAS 

Google Scholar 
Bell, C. W. et al. High-throughput fluorometric measurement of potential soil extracellular enzyme activities. J. Vis. Exp. 15, e50961 (2013).
Google Scholar 
Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).Article 

Google Scholar 
Fierer, N. et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc. Natl Acad. Sci. USA 109, 21390–21395 (2012).Article 
CAS 

Google Scholar 
Fierer, N. et al. Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States. Science 342, 621–624 (2013).Article 
CAS 

Google Scholar 
Buchfink, B., Reuter, K. & Drost, H. G. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat. Methods 18, 366–368 (2021).Article 
CAS 

Google Scholar 
Manning, P. et al. Redefining ecosystem multifunctionality. Nat. Ecol. Evolution 2, 427–436 (2018).Article 

Google Scholar 
Legendre, P. & Legendre, L. Interpretation of Ecological Structures Numerical Ecology 3rd English edn (Elsevier Science BV, 2012).Grace, J. B. Structural Equation Modeling and Natural Systems (Cambridge University Press, 2006).Subramanian, S. et al. Persistent gut microbiota immaturity in malnourished Bangladeshi children. Nature 510, 417 (2014).Article 
CAS 

Google Scholar 
Fan, K. et al. Soil biodiversity supports the delivery of multiple ecosystem functions in urban greenspaces. figshare https://doi.org/10.6084/m9.figshare.21175492.v3 (2022). More

Samples collection and preparationFreshwater and sediment samples were collected from 5 irrigation drains (EL-Shikah, EL- Tramsa, EL-Mahrosa, EL-Aslia, and EL-Rawy) located in the geographical area of Qena city, the capital of Qena Governorate, 600 km south of Cairo, (Figs. 1 and 2). 3 sites inside each drain were randomly selected as sampling site; one of these sites represents the outlet of the drain into the Nile River. In addition, one site facing each drain in the main stream of the Nile River was selected to collect freshwater only, thus the total number of samples are 20 freshwater and 15 sediment samples.Figure 1Location map of the area under study (ArcGIS software 10.8.1; ArcGIS Online).Full size imageFigure 2Irrigation drain under study.Full size imagePolyethylene Marinelli beakers with a capacity of 1.4 L are used as collection and measuring containers. The beakers were washed with dilute hydrochloric acid and distilled water before use, filled to brim, and then pressed the tight lid to eliminate the internal air. Drops of HNO3 were added to the samples to prevent the adhesive of radionuclides with bottle walls8.Sediment samples were collected by Ekman grab sediment sampler. The collected samples were dried using electrical oven at a temperature of 105℃ for 24 h, then sieved through 200 mesh size. The dried samples were filled in hermetical sealed 500 ml polyethylene beakers. The prepared water and sediment samples were stored for 4 weeks to reach a secular equilibrium of radium and thorium with their progenies9.Measuring systemsGamma-ray spectrometer consisting of ″3 × 3″ NaI (Tl) detector enclosed in 5 cm thick cylindrical lead shield to reduce the background radiation and connected with 1024 multichannel analyzer was used. The spectrometer was calibrated for energy using 60Co and 137Cs standard point sources, and calibrated for efficiency using a multi-nuclides standard solution which covers a wide range of energy10. The spectrum was accumulated from each sample over 24 h and analyzed by Maestro software. The background was measured under the same condition of sample measurement.226Ra was determined using 214Bi and 214Pb gamma-lines at 609 keV and 352 keV, respectively, while 232Th from gamma-lines of 228Ac (911 keV) and 212Pb (238 keV). 40K was determined from its single gamma-line at 1460 keV. The activity concentration was calculated using the following formula (Eq. 1)11.$$A = frac{{C_{n} }}{{T times varepsilon { } times {text{P}} times {text{V }}left( {{text{or}}} right){text{M}}}}$$
(1)

where A is the activity concentration (Bq kg−1) or (Bq l−1), Cn is the net counts under a given peak area, T the sample counting time, (varepsilon) is the detection efficiency at measured energy, P is the emission probability and V is the sample volume in liter, M is the sample mass in kilogram. Minimum detectable activity (MDA) was estimated according to Currie definition using Eq. 212 and the MDA values were 0.031, 0.035 and 1.94 Bq L−1 for 226Ra, 232Th, and 40K, respectively.$${text{MDA}} = frac{2.71 + 465sqrt B }{{T times varepsilon times P times V}}$$
(2)

where B is the background counts under a given peak area,T,ɛ, P, and V are defined above.Doses for aquatic organismsThe external and internal absorbed dose rate for aquatic organisms (Phytoplankton, Mollusca, and Crustacean) in the studied irrigation drains was calculated based on the measured activity concentrations of 226Ra, 232Th, and 40K in environmental media (water and sediment) and using dose conversion coefficients of a given radionuclide for the reference organisms according to the method outlined by Brown et al. described below13,14.$$begin{aligned}& left( {Sediment,, conc. ,,wet} right)_{radionuclide} = (Sediment ,,conc. ,,dry)_{radionuclide} times left( {solids ,,fraction} right) \& qquad qquad + (water ,,conc.)_{radionuclide} times (1 – left( {solids ,,fraction} right). \ end{aligned}$$
(3)
$$begin{aligned}& left( {user2{External ,,dose ,,rate}} right)_{radionuclide,, organism} = DPUC_{radionuclide, ,organism}^{external} times left[ {Sediment ,conc. ,wet_{radionuclide} times left( {fsed_{organism} + fsedsur_{organism} /2} right)} right. \& quad quad left. { + left( {fwater_{organism} + fsedsur_{organism} /2} right) times water ,conc._{radionuclide } /1000} right] \ end{aligned}$$
(4)
$$left( {user2{Internal,dose,rate}} right)_{{radionuclide,,organism}} = ~left( {water,conc.} right)_{{radionuclide}} times CF_{{radionuclide}}^{{organism}} times DPUC_{{radionuclide,,organism}}^{{internal}}$$
(5)

where sediment conc. is the sediment activity concentration of a given radionuclide in Bq kg−1,water conc. is the water activity concentration of a given radionuclide in Bq m−3, CF is distribution coefficient factors for given radionuclide in freshwater sediment in m3 kg−1, DPUC is the dose rate per unit concentration coefficients (fresh weight) in μGy h−1 per Bq kg−1 weighted for radiation type (alpha = 10, low energy beta = 3, and high energy beta and gamma = 1), solids fraction of wet sediment (0.4), fsed organism is the time fraction spends by organism in sediment, fsedsur organism is the time fraction spends by organism at the sediment/water interface, fwater organism is the time fraction spends by organism in the water column. All parameters used in calculation are taken from Pröhl (2003)15 and Vives i Battle et al. (2004)16. The total dose is then calculated by summating the external and internal doses. More

Jones, E. L. Agriculture and economic growth in England, 1660–1750: Agricultural change. J. Econ. Hist. 25, 1–18 (1965).Article 

Google Scholar 
Chambers, J. D. & Mingay, G. E. The Agricultural Revolution: 1750–1880 (Batsford, 1966).
Google Scholar 
Kerridge, E. The Agricultural Revolution (Allen & Unwin, Paris, 1967).
Google Scholar 
Thompson, F. M. L. The second agricultural revolution, 1815–1880. Econ. Hist. Rev. 21, 62–77 (1968).
Google Scholar 
Overton, M. Agricultural Revolution in England: The Transformation of the Agrarian Economy 1500–1850 (Cambridge University Press, 1996).Book 

Google Scholar 
Turner, M. E., Beckett, J. V. & Afton, B. Farm Production in England 1700–1914 (Oxford University Press, 2001).Book 

Google Scholar 
Williamson, T. The Transformation of Rural England: Farming and the Landscape, 1700–1870 (University of Exeter Press, 2002).
Google Scholar 
Davis, J. M. & Beckett, J. V. Animal husbandry and agricultural improvement: The archaeological evidence from animal bones and teeth. Rural Hist. 10, 1–17 (1999).Article 
CAS 

Google Scholar 
Thomas, R. Zooarchaeology, improvement and the British agricultural revolution. Int. J. Hist. Archaeol. 9, 71–88 (2005).Article 

Google Scholar 
Sologestoa, I. G. & Albarella, U. (eds) The Rural World in the Sixteenth Century: Exploring the Archaeology of Innovation in Europe (Brepols, 2002).
Google Scholar 
Doherty, S. P. & Henderson, S. Production of parchment legal deeds in England, 1690–1830. Hist. Res. 95, 575–585 (2022).Article 

Google Scholar 
DeNiro, M. J. & Epstein, S. Influence of diet on the distribution of carbon isotopes in animals. Geochim. Cosmochim. Acta 42, 495–506 (1978).Article 
ADS 
CAS 

Google Scholar 
Bateman, A. S. & Kelly, S. D. Fertilizer nitrogen isotope signatures. Isotopes Environ. Health Stud. 43, 237–247 (2007).Article 
CAS 

Google Scholar 
Szpak, P. Complexities of nitrogen isotope biogeochemistry in plant–soil systems: Implications for the study of ancient agricultural and animal management practices. Front. Plant Sci. 5, 288 (2014).Article 
ADS 

Google Scholar 
Trentacoste, A. et al. Heading for the hills? A multi-isotope study of sheep management in first-millennium BC Italy. J. Archaeol. Sci. Rep. 29, 102036 (2020).
Google Scholar 
Doherty, S., Alexander, M. M., Vnouček, J., Newton, J. & Collins, M. J. Measuring the impact of parchment production on skin collagen stable isotope (δ13C and δ15N) values. STAR Sci. Technol. Archaeol. Res. 7, 1–12 (2021).
Google Scholar 
Doherty, S. P. et al. A modern baseline for the paired isotopic analysis of skin and bone in terrestrial mammals. R. Soc. Open Sci. 9, 211587 (2022).Article 
ADS 
CAS 

Google Scholar 
Camin, F. et al. Multi-element (H, C, N, S) stable isotope characteristics of lamb meat from different European regions. Anal. Bioanal. Chem. 389, 309–320 (2007).Article 
CAS 

Google Scholar 
Kohn, M. J. Carbon isotope compositions of terrestrial C3 plants as indicators of (paleo)ecology and (paleo)climate. Proc. Natl. Acad. Sci. U.S.A. 107, 19691–19695 (2010).Article 
ADS 
CAS 

Google Scholar 
Clarkson, L. A. The manufacture of leather. In The Agrarian History of England and Wales, Vol VI, 1750–1820 (ed. Mingay, G. E.) 466–485 (Cambridge University Press, 1989).
Google Scholar 
Millard, A. R., Dodd, L. & Nowell, G. Palace Green Library excavations 2013 (PGL13): Isotopic Studies Project Report (2015).Bleasdale, M. et al. Multidisciplinary investigations of the diets of two post-medieval populations from London using stable isotopes and microdebris analysis. Archaeol. Anthropol. Sci. 11, 6161–6181 (2019).Article 

Google Scholar 
Thirsk, J. The English Rural Landscape (Oxford University Press, 2000).
Google Scholar 
Home, T. H. The Complete Grazier 5th edn. (Baldwin & Cradock, 1830).
Google Scholar 
Ellman, J. On folding sheep. The Farmers Magazine 110 (1831).Bogaard, A., Heaton, T. H. E., Poulton, P. & Merbach, I. The impact of manuring on nitrogen isotope ratios in cereals: Archaeological implications for reconstruction of diet and crop management practices. J. Archaeol. Sci. 34, 335–343 (2007).Article 

Google Scholar 
Schwertl, M., Auerswald, K., Schäufele, R. & Schnyder, H. Carbon and nitrogen stable isotope composition of cattle hair: Ecological fingerprints of production systems?. Agric. Ecosyst. Environ. 109, 153–165 (2005).Article 
CAS 

Google Scholar 
Trow-Smith, R. A History of British Livestock Husbandry, 1700–1900 (Keegan & Paul, 1959).
Google Scholar 
Babraj, J. A. et al. Collagen synthesis in human musculoskeletal tissues and skin. Am. J. Physiol. Endocrinol. Metab. 289, E864–E869 (2005).Article 
CAS 

Google Scholar 
El-Harake, W. A. et al. Measurement of dermal collagen synthesis rate in vivo in humans. Am. J. Physiol. 274, E586–E591 (1998).CAS 

Google Scholar 
Fuller, B. T., Fuller, J. L., Harris, D. A. & Hedges, R. E. M. Detection of breastfeeding and weaning in modern human infants with carbon and nitrogen stable isotope ratios. Am. J. Phys. Anthropol. 129, 279–293 (2006).Article 
CAS 

Google Scholar 
Houghton, J. Friday 7th 1694. In Husbandry and Trade Improv’d (ed. Bradley, R.) 323–330 (Woodman and Lyon, 1728).
Google Scholar 
de La Lande, J. & McCauley, G. The art of making parchment. Art Transl. 13, 326–386 (2021).Article 

Google Scholar 
Reed, R. Ancient Skins, Parchments and Leather (Seminar Press, 1973).
Google Scholar 
Mekota, A.-M., Grupe, G., Ufer, S. & Cuntz, U. Serial analysis of stable nitrogen and carbon isotopes in hair: Monitoring starvation and recovery phases of patients suffering from anorexia nervosa. Rapid Commun. Mass Spectrom. 20, 1604–1610 (2006).Article 
ADS 
CAS 

Google Scholar 
Neuberger, F. M., Jopp, E., Graw, M., Püschel, K. & Grupe, G. Signs of malnutrition and starvation–reconstruction of nutritional life histories by serial isotopic analyses of hair. Forensic Sci. Int. 226, 22–32 (2013).Article 
CAS 

Google Scholar 
Hargis, A. M. & Myers, S. The intergument. In Pathological Basis of Veterinary Disease 6th edn (ed. Zachary, J. F.) 1009–1146 (Elsevier, 2017).Chapter 

Google Scholar 
Hansard’s Parliamentary Debates, Volume 28, Third Series, comprising the period from 22nd May to 26th June 1835. (T.C. Hansard, 1835).US Department of Agriculture. Foot Rot of Sheep, FB2206 (USDA, 1972).
Google Scholar 
The House of Commons. Reports from Committees, Volume 8, Part 1 79–288 (Select Committee on Agricultural Distress, 1836).
Google Scholar 
Pálsson, H. & Vergés, J. B. Effects of the plane of nutrition on growth and the development of carcass quality in lambs Part I. The effects of High and Low planes of nutrition at different ages. J. Agric. Sci. 42, 1–92 (1952).Article 

Google Scholar 
Grau-Sologestoa, I. & Albarella, U. The ‘long’ sixteenth century: A key period of animal husbandry change in England. Archaeol. Anthropol. Sci. 11, 2781–2803 (2019).Article 

Google Scholar 
Fisher, A. & Thomas, R. Isotopic and zooarchaeological investigation of later medieval and post-medieval cattle husbandry at Dudley Castle, West Midlands. Environ. Archaeol. 17, 151–167 (2012).Article 

Google Scholar 
Jones, E. L. The Development of English Agriculture, 1815–1873 (Palgrave, 1968).Book 

Google Scholar 
Perren, R. Agriculture in Depression 1870–1940 (Cambridge University Press, 1995).
Google Scholar 
Osorio, M. T., Moloney, A. P., Schmidt, O. & Monahan, F. J. Beef authentication and retrospective dietary verification using stable isotope ratio analysis of bovine muscle and tail hair. J. Agric. Food Chem. 59, 3295–3305 (2011).Article 
CAS 

Google Scholar 
Zazzo, A. et al. Isotopic composition of sheep wool records seasonality of climate and diet. Rapid Commun. Mass Spectrom. 29, 1357–1369 (2015).Article 
ADS 
CAS 

Google Scholar 
Anonymous. Supplementary Chapter to ‘An Essay on Calcareous Manures’. in The Farmer’s Register. Vol. I. 76–79 (Printed for Edmund Ruffin, 1834).Szpak, P., Longstaffe, F. J., Millaire, J.-F. & White, C. D. Stable isotope biogeochemistry of seabird guano fertilization: Results from growth chamber studies with maize (Zea mays). PLoS One 7, e33741 (2012).Article 
ADS 
CAS 

Google Scholar 
Caird, S. J. English Agriculture in 1850–51 (Longman, Brown, Green, and Longmans, 1852).Book 

Google Scholar 
Prothero, R. E. English Farming, Past and Present (Longmans, Green, 1912).
Google Scholar 
Doherty, S. P., Henderson, S., Fiddyment, S., Finch, J. & Collins, M. J. Scratching the surface: The use of sheepskin parchment to deter textual erasure in early modern legal deeds. Herit. Sci. 9, 29 (2021).Article 
CAS 

Google Scholar 
Fiddyment, S. et al. Animal origin of 13th-century uterine vellum revealed using noninvasive peptide fingerprinting. Proc. Natl. Acad. Sci. U.S.A. 112, 15066–15071 (2015).Article 
ADS 
CAS 

Google Scholar 
Campana, M. G. et al. A flock of sheep, goats and cattle: Ancient DNA analysis reveals complexities of historical parchment manufacture. J. Archaeol. Sci. 37, 1317–1325 (2010).Article 

Google Scholar 
Szpak, P., Metcalfe, J. Z. & Macdonald, R. A. Best practices for calibrating and reporting stable isotope measurements in archaeology. J. Archaeol. Sci. Rep. 13, 609–616 (2017).
Google Scholar 
Dombrosky, J. A. ~1000-year 13C Suess correction model for the study of past ecosystems. Holocene 30, 474–478 (2020).Article 
ADS 

Google Scholar  More

Wingard, G. L., Bernhardt, C. E. & Wachnicka, A. H. The role of paleoecology in restoration and resource management—the past as a guide to future decision-making: review and example from the Greater Everglades ecosystem, U.S.A. Front. Ecol. Evol 5, 11 (2017).Article 

Google Scholar 
Gillson, L., Dirk, C. & Gell, P. Using long-term data to inform a decision pathway for restoration of ecosystem resilience. Anthropocene 36, 100315 (2021).Article 

Google Scholar 
Nieto-Lugilde, D. et al. Time to better integrate paleoecological research infrastructures with neoecology to improve understanding of biodiversity long-term dynamics and to inform future conservation. Environ. Res. Lett. 16, 095005 (2021).Article 

Google Scholar 
Leo, G. A. D. & Levin, S. A. The multifaceted aspects of ecosystem integrity. Conserv. Ecol. 1, 3 (1997).
Google Scholar 
Mason, N. & Mouillot, D. in Encyclopedia of Biodiversity (ed. Levin, S. A.) 597–608 (Elsevier, 2013).Carvalho, F. et al. A method for reconstructing temporal changes in vegetation functional trait composition using Holocene pollen assemblages. PLoS ONE 14, e0216698 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Brussel, T. & Brewer, S. C. Functional paleoecology and the pollen-plant functional trait linkage. Front. Ecol. Evol 8, 564609 (2021).Article 

Google Scholar 
Brussel, T., Minckley, T. A., Brewer, S. C. & Long, C. J. Community-level functional interactions with fire track long-term structural development and fire adaptation. J. Veg. Sci. 29, 450–458 (2018).Article 

Google Scholar 
Barboni, D. et al. Relationships between plant traits and climate in the Mediterranean region: a pollen data analysis. J. Veg. Sci. 15, 635–646 (2004).Article 

Google Scholar 
Reitalu, T. et al. Novel insights into post-glacial vegetation change: functional and phylogenetic diversity in pollen records. J. Veg. Sci. 26, 911–922 (2015).Article 

Google Scholar 
Blaus, A. et al. Modern pollen-plant diversity relationships inform palaeoecological reconstructions of functional and phylogenetic diversity in calcareous fens. Front. Ecol. Evol 8, 207 (2020).Article 

Google Scholar 
Morris, J. L. et al. Stable or seral? Fire-driven alternative states in aspen forests of western North America. Biol. Lett. 15, 20190011 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Ordonez, A. & Svenning, J.-C. Greater tree species richness in eastern North America compared to Europe is coupled to denser, more clustered functional trait space filling, not to trait space expansion. Glob. Ecol. Biogeogr. 27, 1288–1299 (2018).Article 

Google Scholar 
van der Sande, M. T. et al. A 7000-year history of changing plant trait composition in an Amazonian landscape; the role of humans and climate. Ecol. Lett. 22, 925–935 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Lacourse, T. & Adeleye, M. A. Climate and species traits drive changes in Holocene forest composition along an elevation gradient in Pacific Canada. Front. Ecol. Evol 10, 838545 (2022).Article 

Google Scholar 
Lacourse, T. Environmental change controls postglacial forest dynamics through interspecific differences in life-history traits. Ecology 90, 2149–2160 (2009).Article 
PubMed 

Google Scholar 
Veeken, A., Santos, M. J., McGowan, S., Davies, A. L. & Schrodt, F. Pollen-based reconstruction reveals the impact of the onset of agriculture on plant functional trait composition. Ecol. Lett. 25, 1937–1951 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Ellis, E. C., Antill, E. C. & Kreft, H. All is not loss: plant biodiversity in the anthropocene. PLoS ONE 7, e30535 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
GILL, A. M. Fire and the Australian flora: a review. Aust. For. 38, 4–25 (1975).Article 

Google Scholar 
Crisp, M. D., Burrows, G. E., Cook, L. G., Thornhill, A. H. & Bowman, D. M. J. S. Flammable biomes dominated by eucalypts originated at the Cretaceous–Palaeogene boundary. Nat. Commun. 2, 193 (2011).Article 
PubMed 

Google Scholar 
Keith, D. A. Australian Vegetation (Cambridge Univ. Press, 2017).Woinarski, J. C. Z., Burbidge, A. A. & Harrison, P. L. Ongoing unraveling of a continental fauna: decline and extinction of Australian mammals since European settlement. Proc. Natl Acad. Sci. USA 112, 4531–4540 (2015).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Broadhurst, L. & Coates, D. Plant conservation in Australia: current directions and future challenges. Plant Divers. 39, 348–356 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Adeleye, M. A., Connor, S. E., Haberle, S. G., Herbert, A. & Brown, J. European colonization and the emergence of novel fire regimes in southeast Australia. Anthr. Rev. https://doi.org/10.1177/205301962110446 (2021).Gallagher, R. V. et al. High fire frequency and the impact of the 2019–2020 megafires on Australian plant diversity. Divers. Distrib. 27, 1166–1179 (2021).Article 

Google Scholar 
Gallagher, R. V. et al. An integrated approach to assessing abiotic and biotic threats to post-fire plant species recovery: lessons from the 2019–2020 Australian fire season. Glob. Ecol. Biogeogr. 31, 2056–2069.Mariani, M. et al. Disruption of cultural burning promotes shrub encroachment and unprecedented wildfires. Front. Ecol. Environ. 20, 292–300 (2022).Article 

Google Scholar 
Williams, A. N., Mooney, S. D., Sisson, S. A. & Marlon, J. Exploring the relationship between Aboriginal population indices and fire in Australia over the last 20,000 years. Palaeogeogr. Palaeoclimatol. Palaeoecol. 432, 49–57 (2015).Article 

Google Scholar 
Bird, M. I., O’Grady, D. & Ulm, S. Humans, water, and the colonization of Australia. Proc. Natl Acad. Sci. USA 113, 11477–11482 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Adeleye, M. A., Haberle, S. G., Connor, S. E., Stevenson, J. & Bowman, D. M. J. S. Indigenous fire-managed landscapes in Southeast Australia during the Holocene—new insights from the Furneaux Group Islands, Bass Strait. Fire 4, 17 (2021).Article 

Google Scholar 
Fletcher, M.-S., Romano, A., Connor, S., Mariani, M. & Maezumi, S. Y. Catastrophic bushfires, Indigenous fire knowledge and reframing science in Southeast Australia. Fire 4, 61 (2021).Article 

Google Scholar 
Fletcher, M.-S., Hall, T. & Alexandra, A. N. The loss of an indigenous constructed landscape following British invasion of Australia: an insight into the deep human imprint on the Australian landscape. Ambio 50, 138–149 (2021).Article 
CAS 
PubMed 

Google Scholar 
Adeleye, M. A. et al. Long-term drivers of vegetation turnover in Southern Hemisphere temperate ecosystems. Glob. Ecol. Biogeogr. 30, 557–571 (2021).Article 

Google Scholar 
Kershaw, A. P., D’Costa, D. M., McEwen Mason, J. R. C. & Wagstaff, B. E. Palynological evidence for Quaternary vegetation and environments of mainland southeastern Australia. Quat. Sci. Rev. 10, 391–404 (1991).Article 

Google Scholar 
Colhoun, E. A. & Shimeld, P. W. in Peopled Landscapes: Archaeological and Biogeographic Approaches to Landscapes (eds. Haberle, S. G. & David, B.) 297–328 (ANU Press, 2012).Madani, N. et al. Future global productivity will be affected by plant trait response to climate. Sci. Rep. 8, 2870 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Squire, D. T. et al. Likelihood of unprecedented drought and fire weather during Australia’s 2019 megafires. npj Clim. Atmos. Sci. 4, 64 (2021).Article 

Google Scholar 
Ukkola, A. M., De Kauwe, M. G., Roderick, M. L., Abramowitz, G. & Pitman, A. J. Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation. Geophys. Res. Lett. 47, e2020GL087820 (2020).Article 

Google Scholar 
Mori, A. S., Furukawa, T. & Sasaki, T. Response diversity determines the resilience of ecosystems to environmental change. Biol. Rev. 88, 349–364 (2013).Article 
PubMed 

Google Scholar 
Arias, P. A. et al. In Climate Change 2021: The Physical Science Basis (eds. Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Laliberté, E., Legendre, P. & Shipley, B. FD: measuring (FD) from multiple traits, and other tools for functional ecology. R package version 1.0-12 (2014).Laliberté, E. & Legendre, P. A distance-based framework for measuring from multiple traits. Ecology 91, 299–305 (2010).Article 
PubMed 

Google Scholar 
Tilman, D. in Encyclopedia of Biodiversity (ed. Levin, S. A.) 109–120 (Elsevier, 2001).Fletcher, M.-S. & Moreno, P. I. Have the Southern Westerlies changed in a zonally symmetric manner over the last 14,000 years? A hemisphere-wide take on a controversial problem. Quat. Int. 253, 32–46 (2012).Article 

Google Scholar 
Markgraf, V., Bradbury, J. P. & Busby, J. R. Paleoclimates in Southwestern Tasmania during the last 13,000 years. PALAIOS 1, 368 (1986).Article 

Google Scholar 
Moros, M. et al. Hydrographic shifts south of Australia over the last deglaciation and possible interhemispheric linkages. Quat. Res. 102, 130–141 (2021).Article 

Google Scholar 
Perner, K. et al. Heat export from the tropics drives mid to late Holocene palaeoceanographic changes offshore southern Australia. Quat. Sci. Rev. 180, 96–110 (2018).Article 

Google Scholar 
Mariani, M. & Fletcher, M.-S. Long-term climate dynamics in the extra-tropics of the South Pacific revealed from sedimentary charcoal analysis. Quat. Sci. Rev. 173, 181–192 (2017).Article 

Google Scholar 
McWethy, D. B. et al. A conceptual framework for predicting temperate ecosystem sensitivity to human impacts on fire regimes. Glob. Ecol. Biogeogr. 22, 900–912 (2013).Article 

Google Scholar 
Baker, A. G., Catterall, C. & Benkendorff, K. Invading rain forest pioneers initiate positive fire suppression feedbacks that reinforce shifts from open to closed forest in eastern Australia. J. Veg. Sci. 32, e13102 (2021).Article 

Google Scholar 
Lambeck, K. & Chappell, J. Sea level change through the last glacial cycle. Science 292, 679–686 (2001).Article 
CAS 
PubMed 

Google Scholar 
Sloss, C. R., Murray-Wallace, C. V. & Jones, B. G. Holocene sea-level change on the southeast coast of Australia: a review. Holocene 17, 999–1014 (2007).Article 

Google Scholar 
Adeleye, M. A. et al. Holocene heathland development in temperate oceanic Southern Hemisphere: key drivers in a global context. J. Biogeogr. 48, 1048–1062 (2021).Article 

Google Scholar 
McWethy, D. B., Haberle, S. G., Hopf, F. & Bowman, D. M. J. S. Aboriginal impacts on fire and vegetation on a Tasmanian island. J. Biogeogr. 44, 1319–1330 (2017).Article 

Google Scholar 
Hope, G. Vegetation and fire response to late Holocene human occupation in island and mainland north west Tasmania. Quat. Int. 59, 47–60 (1999).Article 

Google Scholar 
Sim, R. The Archaeology of Isolation? Prehistoric Occupation in the Furneaux Group of Islands, Bass Strait, Tasmania. PhD thesis, Australian National Univ. (1998).Lourandos, H. Intensification: a late Pleistocene-Holocene archaeological sequence from Southwestern Victoria. Archaeol. Ocean. 18, 81–94 (1983).Article 

Google Scholar 
Bowman, D. M. J. S. The impact of Aboriginal landscape burning on the Australian biota. New Phytol. 140, 385–410 (1998).Article 
CAS 
PubMed 

Google Scholar 
Iversen, J. in Systematics of Today (ed. Hedberg, O.) 210–215 (Acta Universitatis Upsaliensis/Uppsala Universitets Årsskrift, 1958).Colhoun, E. A. Application of Iversen’s glacial–interglacial cycle to interpretation of the late last glacial and Holocene vegetation history of western Tasmania. Quat. Sci. Rev. 15, 557–580 (1996).Article 

Google Scholar 
Adeleye, M. A., Haberle, S. G., Ondei, S. & Bowman, D. M. J. S. Ecosystem transformation following the mid-nineteenth century cessation of Aboriginal fire management in Cape Pillar, Tasmania. Reg. Environ. Change 22, 99 (2022).Article 

Google Scholar 
Mccann, K. The diversity–stability debate. Nature 405, 228–233 (2000).Article 
CAS 
PubMed 

Google Scholar 
Hallett, L. M., Stein, C. & Suding, K. N. Functional diversity increases ecological stability in a grazed grassland. Oecologia 183, 831–840 (2017).Article 
PubMed 

Google Scholar 
Bello, Fde et al. Functional trait effects on ecosystem stability: assembling the jigsaw puzzle. Trends Ecol. Evol. 36, 822–836 (2021).Article 
PubMed 

Google Scholar 
Lucini, F. A., Morone, F., Tomassone, M. S. & Makse, H. A. Diversity increases the stability of ecosystems. PLoS ONE 15, e0228692 (2020).Article 

Google Scholar 
Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).Article 
CAS 
PubMed 

Google Scholar 
Gallagher, R. V., Hughes, L. & Leishman, M. R. Species loss and gain in communities under future climate change: consequences for functional diversity. Ecography 36, 531–540 (2013).Article 

Google Scholar 
Song, Y., Wang, P., Li, G. & Zhou, D. Relationships between and ecosystem functioning: a review. Acta Ecol. Sin. 34, 85–91 (2014).Article 
CAS 

Google Scholar 
Li, W. et al. Plant can be independent of species diversity: observations based on the impact of 4-yrs of nitrogen and phosphorus additions in an alpine meadow. PLoS ONE 10, e0136040 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Lewis, C. J., Huang, Y., Siems, S. T. & Manton, M. J. Wintertime orographic precipitation over western Tasmania. J. South. Hemisphere Earth Syst. Sci. 68, 22–40 (2018).Article 

Google Scholar 
Andrew, S. C. et al. Functional diversity of the Australian flora: strong links to species richness and climate. J. Veg. Sci. 32, e13018 (2021).Article 

Google Scholar 
Biswas, S. R. & Mallik, A. U. Species diversity and relationship varies with disturbance intensity. Ecosphere 2, art52 (2011).Article 

Google Scholar 
Gallagher, R. V. et al. A guide to using species trait data in conservation. One Earth 4, 927–936 (2021).Article 

Google Scholar 
Siefert, A. et al. A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. Ecol. Lett. 18, 1406–1419 (2015).Article 
PubMed 

Google Scholar 
Harris, S. & Kitchener, A. From Forest to Fjaeldmark. Descriptions of Tasmania’s Vegetation (Department of Primary Industries, Water and Environment, Tasmania, 2005).Adeleye, M. A., Haberle, S. G., McWethy, D., Connor, S. E. & Stevenson, J. Environmental change during the last glacial on an ancient land bridge of southeast Australia. J. Biogeogr. 48, 2946–2960 (2021).Article 

Google Scholar 
Hopf, F. V. L., Colhoun, E. A. & Barton, C. E. Late-glacial and Holocene record of vegetation and climate from Cynthia Bay, Lake St Clair, Tasmania. J. Quat. Sci. 15, 725–732 (2000).Article 

Google Scholar 
Stahle, L. N., Whitlock, C. & Haberle, S. G. A 17,000-year-long record of vegetation and fire from Cradle Mountain National Park, Tasmania. Front. Ecol. Evol 4, 82 (2016).Article 

Google Scholar 
Michael-Shawn, F. et al. The influence of climatic change, fire and species invasion on a Tasmanian temperate rainforest system over the past 18,000 years. Quat. Sci. Rev. 260, 106824 (2021).Article 

Google Scholar 
Climate and Water Availability in South-Eastern Australia: A Synthesis of Findings From Phase 2 of the South-Eastern Australian Climate initiative (SEACI) (CSIRO, 2012); https://doi.org/10.4225/08/584af3986fe96Australian Climate Influences (Commonwealth of Australia, Bureau of Meteorology, 2010); http://www.bom.gov.au/watl/about-weather-and-climate/australian-climate-influences.shtmlRisbey, J. S., Pook, M. J., McIntosh, P. C., Wheeler, M. C. & Hendon, H. H. On the remote drivers of rainfall variability in Australia. Mon. Weather Rev. 137, 3233–3253 (2009).Article 

Google Scholar 
Mariani, M., Fletcher, M.-S., Holz, A. & Nyman, P. ENSO controls interannual fire activity in southeast Australia. Geophys. Res. Lett. 43, 10891–10900 (2016).Article 

Google Scholar 
Mariani, M. & Fletcher, M.-S. The Southern Annular Mode determines interannual and centennial-scale fire activity in temperate southwest Tasmania, Australia. Geophys. Res. Lett. 43, 1702–1709 (2016).Article 

Google Scholar 
Herbert, A. V. & Harrison, S. P. Evaluation of a modern-analogue methodology for reconstructing Australian palaeoclimate from pollen. Rev. Palaeobot. Palynol. 226, 65–77 (2016).Article 

Google Scholar 
Blaauw, M. et al. rbacon: Age-depth modelling using Bayesian statistics. R package version 4.2.0 (2022).Hogg, A. G. et al. SHCal20 Southern Hemisphere calibration, 0–55,000 years cal BP. Radiocarbon 62, 759–778 (2020).Article 
CAS 

Google Scholar 
Falster, D. et al. AusTraits, a curated plant trait database for the Australian flora. Sci. Data 8, 254 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Pérez-Harguindeguy, N. et al. Corrigendum to: New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 64, 715–716 (2016).Article 

Google Scholar 
Wright, I. J. et al. Global climatic drivers of leaf size. Science 357, 917–921 (2017).Article 
CAS 
PubMed 

Google Scholar 
Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).Article 
CAS 
PubMed 

Google Scholar 
Westoby, M., Falster, D. S., Moles, A. T., Vesk, P. A. & Wright, I. J. Plant ecological strategies: some leading dimensions of variation between species. Annu. Rev. Ecol. Syst. 33, 125–159 (2002).Article 

Google Scholar 
Moles, A. T. & Westoby, M. Seed size and plant strategy across the whole life cycle. Oikos 113, 91–105 (2006).Article 

Google Scholar 
Leishman, M. R. & Westoby, M. The role of seed size in seedling establishment in dry soil conditions—experimental evidence from semi-arid species. J. Ecol. 82, 249–258 (1994).Article 

Google Scholar 
Falster, D. S. & Westoby, M. Plant height and evolutionary games. Trends Ecol. Evol. 18, 337–343 (2003).Article 

Google Scholar 
Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).Article 
PubMed 

Google Scholar 
Mason, N. W. H., Mouillot, D., Lee, W. G. & Wilson, J. B. Functional richness, functional evenness and functional divergence: the primary components of functional diversity. Oikos 111, 112–118 (2005).Article 

Google Scholar 
Pakeman, R. J. Functional trait metrics are sensitive to the completeness of the species’ trait data? Methods Ecol. Evol. 5, 9–15 (2014).Article 

Google Scholar 
Scheiner, S. M., Kosman, E., Presley, S. J. & Willig, M. R. Decomposing. Methods Ecol. Evol. 8, 809–820 (2017).Article 

Google Scholar 
Ripley, B. et al. MASS: Support functions and datasets for venables and Ripley’s MASS. R package version ??? (2022).Moy, C. M., Seltzer, G. O., Rodbell, D. T. & Anderson, D. M. Variability of El Niño/Southern Oscillation activity at millennial timescales during the Holocene epoch. Nature 420, 162–165 (2002).Article 
CAS 
PubMed 

Google Scholar  More

Zupan Hajna, N. Dinaric karst: Geography and geology in Encyclopedia of Caves (eds. White, W. B. & Culver, D. C.) 195–203 (Academic Press, 2012).Jug-Dujaković, M., Ninčević, T., Liber, Z., Grdiša, M. & Šatović, Z. Salvia officinalis survived in situ Pleistocene glaciation in ‘refugia within refugia’ as inferred from AFLP markers. Plant Syst. Evol. 306, 1–12 (2020).Article 

Google Scholar 
Bănărescu, P. M. Distribution pattern of the aquatic fauna of the Balkan Peninsula in Balkan Biodiversity. Pattern and Process in the European Hotspot (eds. Griffiths, H. I., Kryštufek, B. & Reed J. M.) 203–217 (Kluwer Academic Publishers, 2004).Sket, B. Diversity patterns in the Dinaric Karst in Encyclopedia of Caves (eds. White, W. B. & Culver, D. C.) 228–238 (Academic Press, 2012).Griffiths, H. I., Kryštufek, B., & Reed, J. M. Balkan biodiversity. Pattern and Process in the European Hotspot (eds. Griffiths, H. I., Kryštufek, B., & Reed, J. M.) 1–332 (Kluwer Academic Publishers, 2004).Culver, D. C., Pipan, T. & Schneider, K. Vicariance, dispersal and scale in the aquatic subterranean fauna of karst regions. Freshw. Biol. 54, 918–929 (2009).Article 

Google Scholar 
Gottstein Matočec, S. et al. An overview of the cave and interstitial biota of Croatia. Nat. Croat. 11, 1–112 (2002).
Google Scholar 
Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).Article 
ADS 

Google Scholar 
Bilandžija, H., Morton, B., Podnar, M. & Ćetković, H. Evolutionary history of relict Congeria (Bivalvia: Dreissenidae): Unearthing the subterranean biodiversity of the Dinaric Karst. Front. Zool. 10, 1–18 (2013).Article 

Google Scholar 
Bedek, J., Taiti, S., Bilandžija, H., Ristori, E. & Baratti, M. Molecular and taxonomic analyses in troglobiotic Alpioniscus (Illyrionethes) species from the Dinaric Karst (Isopoda: Trichoniscidae). Zool. J. Linn. Soc. 187, 539–584 (2019).Article 

Google Scholar 
Vörös, J., Márton, O., Schmidt, B. R., Gál, J. T. & Jelić, D. Surveying Europe’s only cave-dwelling chordate species (Proteus anguinus) using environmental DNA. PLoS ONE 12, e0170945. https://doi.org/10.1371/journal.pone.0170945 (2017).Article 

Google Scholar 
Delić, T., Švara, V., Coleman, C. O., Trontelj, P. & Fišer, C. The giant cryptic amphipod species of the subterranean genus Niphargus (Crustacea, Amphipoda). Zool. Scr. 46, 740–752 (2017).Article 

Google Scholar 
Delić, T., Trontelj, P., Rendoš, M. & Fišer, C. The importance of naming cryptic species and the conservation of endemic subterranean amphipods. Sci. Rep. 7, 1–12 (2017).Article 

Google Scholar 
Delić, T., Stoch, F., Borko, Š., Flot, J. F. & Fišer, C. How did subterranean amphipods cross the Adriatic Sea? Phylogenetic evidence for dispersal–vicariance interplay mediated by marine regression–transgression cycles. J. Biogeogr. 47, 1875–1887 (2020).Article 

Google Scholar 
Podnar, M., Grbac, I., Tvrtković, N., Hörweg, C. & Haring, E. Hidden diversity, ancient divergences, and tentative Pleistocene microrefugia of European scorpions (Euscorpiidae: Euscorpiinae) in the eastern Adriatic region. J. Zool. Syst. Evol. Res. 59, 1824–1849 (2021).Article 

Google Scholar 
Beron, P. Zoogeography of Arachnida (ed. Beron, P.) Meth. Ecol. Evol. 1–987 (Springer Cham, 2018).Ćurčić, B. P. M. Cave-dwelling pseudoscorpions of the Dinaric karst (ed. Ćurčić, B. P. M.) 1–192 (Slovenska Akademija Znanosti in Umetnosti, 1988).Harms, D., Roberts, J. D. & Harvey, M. S. Climate variability impacts on diversification processes in a biodiversity hotspot: A phylogeography of ancient pseudoscorpions in south-western Australia. Zool. J. Linn. Soc. 186, 934–949 (2019).Article 

Google Scholar 
Muster, C., Schmarda, T. & Blick, T. Vicariance in a cryptic species pair of European pseudoscorpions (Arachnida, Pseudoscorpiones, Chthoniidae). Zool. Anz. 242, 299–311 (2004).Article 

Google Scholar 
Ozimec, R. List of Croatian pseudoscorpion fauna (Arachnida, Pseudoscorpiones). Nat. Croat. 13, 381–394 (2004).
Google Scholar 
World Pseudoscorpiones Catalog. Natural History Museum Bern. https://wac.nmbe.ch (2022).Ćurčić, B. P. M., Dimitrijević, R. N., Rađa, T., Makarov, S. E. & Ilić, B. S. Archaeoroncus, a new genus of pseudoscorpions from Croatia (Pseudoscorpiones, Neobisiidae), with descriptions of two new species. Acta Zool. Bulg. 64, 333–340 (2012).
Google Scholar 
Ćurčić, B. P. M. et al. On two new cave species of pseudoscorpions (Neobisiidae, Pseudoscorpiones) from Herzegovina and Dalmatia. Arch. Biol. Sci. 66, 377–384 (2014).Article 

Google Scholar 
Ćurčić, B. P. M. et al. Roncus sutikvae sp. n. (Pseudoscorpiones: Neobisiidae), a new epigean pseudoscorpion from central Dalmatia (Croatia). Arthropoda Sel. 30, 205–215 (2021).Article 

Google Scholar 
Ćurčić, B. P. M., Rađa, T., Dimitrijević, R., Ćurčić, N. B. & Ćurčić, S. Roncus ladestani sp. n. and Roncus pecmliniensis sp. n., two new Pseudoscorpions (Pseudoscorpiones, Neobisiidae) from Croatia and Bosnia and Herzegovina, respectively. Zool. Zhurnal. 100, 159–169 (2021).
Google Scholar 
Hebert, P. D. N., Cywinska, A., Ball, S. L. & DeWaard, J. R. Biological identifications through DNA barcodes. Proc. Royal Soc. B. 270, 313–321 (2003).Article 

Google Scholar 
Page, R. D. DNA barcoding and taxonomy: Dark taxa and dark texts. Philos. Trans. R. Soc. Lond., B. Biol. Sci. 371, 20150334. https://doi.org/10.1098/rstb.2015.0334 (2016).Article 

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

Google Scholar 
Kekkonen, M. & Hebert, P. D. DNA barcode-based delineation of putative species: Efficient start for taxonomic workflows. Mol. Ecol. Res. 14, 706–715 (2014).Article 

Google Scholar 
Christophoryová, J., Šťáhlavský, F. & Fedor, P. An updated identification key to the pseudoscorpions (Arachnida: Pseudoscorpiones) of the Czech Republic and Slovakia. Zootaxa 2876, 35–48 (2011).Article 

Google Scholar 
Gardini, G. A revision of the species of the pseudoscorpion subgenus Chthonius (Ephippiochthonius) (Arachnida, Pseudoscorpiones, Chthoniidae) from Italy and neighbouring areas. Zootaxa 3655, 1–151 (2013).Article 

Google Scholar 
Gardini, G. The species of the Chthonius heterodactylus group (Arachnida, Pseudoscorpiones, Chthoniidae) from the eastern Alps and the Carpathians. Zootaxa 3887, 101–137 (2014).Article 

Google Scholar 
Gardini, G. The Italian species of the Chthonius ischnocheles group (Arachnida, Pseudoscorpiones, Chthoniidae), with reference to neighbouring countries. Zootaxa 4987, 1–131 (2021).Article 

Google Scholar 
Zaragoza, J. A. Revision of the Ephippiochthonius complex in the Iberian Peninsula, Balearic Islands and Macaronesia, with proposed changes to the status of the Chthonius subgenera (Pseudoscorpiones, Chthoniidae). Zootaxa 4246, 1–221 (2017).Article 

Google Scholar 
Gams, I. Kras v Sloveniji v prostoru in času. (ed. Gams, I.) 1–516 (Postojna: Inštitut za raziskovanje Krasa, 2004).European Union, Copernicus Land Monitoring Service. https://land.copernicus.eu (2016).Maddison, W. P., & Maddison, D. R. Mesquite: a modular system for evolutionary analysis. http://mesquiteproject.org (2019).Katoh, K., Rozewicki, J. & Yamada, K. D. MAFFT online service: Multiple sequence alignment, interactive sequence choice and visualization. Brief. Bioinform. 20, 1160–1166 (2019).Article 

Google Scholar 
Villesen, P. FaBox: An online toolbox for fasta sequences. Mol. Ecol. Notes. 7, 965–968 (2007).Article 

Google Scholar 
Felsenstein, J. Maximum likelihood and minimum-steps methods for estimating evolutionary trees from data on discrete characters. Syst. Biol. 22, 240–249 (1973).Article 

Google Scholar 
Minh, B. Q. et al. IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534 (2020).Article 

Google Scholar 
Hoang, D. T., Chernomor, O., Von Haeseler, A., Minh, B. Q. & Vinh, L. S. UFBoot2: Improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518–522 (2018).Article 

Google Scholar 
Muster, C. et al. The dark side of pseudoscorpion diversity: The German Barcode of Life campaign reveals high levels of undocumented diversity in European false scorpions. Ecol. Evol. 11, 13815–13829 (2021).Article 

Google Scholar 
Ontano, A. Z. et al. Taxonomic sampling and rare genomic changes overcome long-branch attraction in the phylogenetic placement of pseudoscorpions. Mol. Biol. Evol. 38, 2446–2467 (2021).Article 

Google Scholar 
Rambaut A. FigTree v1.4.3 http://tree.bio.ed.ac.uk/software/figtree/ (2016).Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v5: An online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–W296 (2021).Article 

Google Scholar 
Talavera, G. & Castresana, J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst. Biol. 56, 564–577 (2007).Article 

Google Scholar 
Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: Assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).Article 

Google Scholar 
Ronquist, F. et al. MrBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542 (2012).Article 

Google Scholar 
Lanfear, R., Frandsen, P. B., Wright, A. M., Senfeld, T. & Calcott, B. PartitionFinder 2: New methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. Evol. 34, 772–773 (2017).
Google Scholar 
Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Syst. Biol. 67, 901–904 (2018).Article 

Google Scholar 
Miller, M. A., Pfeiffer, W., & Schwartz, T. Creating the CIPRES Science Gateway for inference of large phylogenetic trees in Proceedings of the Gateway Computing Environments Workshop (GCE). https://doi.org/10.1109/GCE.2010.5676129 (2010).Kimura, M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111–120 (1980).Article 
ADS 

Google Scholar 
Paradis, E. & Schliep, K. ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/ (2020).Brown, S. D. et al. Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding. Mol. Ecol. Resour. 12, 562–565 (2012).Article 

Google Scholar 
Meier, R., Shiyang, K., Vaidya, G. & Ng, P. K. L. DNA barcoding and taxonomy in Diptera: A tale of high intraspecific variability and low identification success. Syst. Biol. 55, 715–728 (2006).Article 

Google Scholar 
Puillandre, N., Lambert, A., Brouillet, S. & Achaz, G. J. M. E. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol. Ecol. 21, 1864–1877 (2012).Article 

Google Scholar 
Puillandre, N., Brouillet, S. & Achaz, G. ASAP: Assemble species by automatic partitioning. Mol. Ecol. Resour. 21, 609–620 (2020).Article 

Google Scholar 
Zhang, J., Kapli, P., Pavlidis, P. & Stamatakis, A. A general species delimitation method with applications to phylogenetic placements. Bioinformatics 29, 2869–2876 (2013).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 (2018).Article 

Google Scholar 
Karney, C. F. Algorithms for geodesics. J. Geod. 87, 43–55 (2013).Article 
ADS 

Google Scholar 
Leigh, J. W. & Bryant, D. POPART: Full-feature software for haplotype network construction. Meth. Ecol. Evol. 6, 1110–1116 (2015).Article 

Google Scholar 
Bregović, P., Fišer, C. & Zagmajster, M. Contribution of rare and common species to subterranean species richness patterns. Ecol. Evol. 9, 11606–11618 (2019).Article 

Google Scholar 
Hunter, J. D. Matplotlib: A 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).Article 

Google Scholar 
Young, M. R. & Hebert, P. D. Patterns of protein evolution in cytochrome c oxidase 1 (COI) from the class Arachnida. PLoS ONE 10, e0135053. https://doi.org/10.1371/journal.pone.0135053 (2015).Article 

Google Scholar 
Yin, Y. et al. DNA barcoding uncovers cryptic diversity in minute herbivorous mites (Acari, Eriophyoidea). Mol. Ecol. Resour. 22, 1986–1998 (2022).Article 

Google Scholar 
Doña, J. et al. DNA barcoding and minibarcoding as a powerful tool for feather mite studies. Mol. Ecol. Resour. 15, 1216–1225 (2015).Article 

Google Scholar 
Blagoev, G. A. et al. Untangling taxonomy: A DNA barcode reference library for Canadian spiders. Mol. Ecol. Resour. 16, 325–341 (2016).Article 

Google Scholar 
Aliabadian, M., Kaboli, M., Nijman, V. & Vences, M. Molecular identification of birds: Performance of distance-based DNA barcoding in three genes to delimit parapatric species. PLoS ONE 4, e4119. https://doi.org/10.1371/journal.pone.0004119 (2009).Article 
ADS 

Google Scholar 
Moritz, C. & Cicero, C. DNA barcoding: promise and pitfalls. PLoS Biol. 2, e354. https://doi.org/10.1371/journal.pbio.0020354 (2004).Article 

Google Scholar 
Dellicour, S. & Flot, J. F. The hitchhiker’s guide to single-locus species delimitation. Mol. Ecol. Resour. 18, 1234–1246 (2018).Article 

Google Scholar 
Polak, S., Delić, T., Kostanjšek, R. & Trontelj, P. Molecular phylogeny of the cave beetle genus Hadesia (Coleoptera: Leiodidae: Cholevinae: Leptodirini), with a description of a new species from Montenegro. Arthropod Syst. 74, 241–254 (2016).
Google Scholar 
Lukić, M., Delić, T., Pavlek, M., Deharveng, L. & Zagmajster, M. Distribution pattern and radiation of the European subterranean genus Verhoeffiella (Collembola, Entomobryidae). Zool. Scr. 49, 86–100 (2019).Article 

Google Scholar 
Casale, A., Jalžić, B., Lohaj, R. & Mlejnek, R. Two new highly specialised subterranean beetles from the Velebit massif (Croatia): Velebitaphaenops (new genus) giganteus Casale & Jalžić, new species (Coleoptera: Carabidae: Trechini) and Velebitodromus ozrenlukici Lohaj, Mlejnek & Jalžić, new species (Coleoptera: Cholevidae: Leptodirini). Nat. Croat. 21, 129–153 (2012).
Google Scholar 
Andersen, T. et al. Blind flight? A new troglobiotic Orthoclad (Diptera, Chironomidae) from the Lukina Jama-Trojama Cave in Croatia. PLoS ONE 11, e0152884. https://doi.org/10.1371/journal.pone.0152884 (2016).Article 

Google Scholar 
Velić, J. et al. A geological overview of glacial accumulation and erosional occurrences at the Velebit and the Biokovo Mts., Croatia. The Min. Geol. Petrol. Eng. Bull. 32, 77–96 (2017).
Google Scholar 
Bickford, D. et al. Cryptic species as a window on diversity and conservation. Trends Ecol. Evol. 22, 148–155 (2007).Article 

Google Scholar 
Trontelj, P. Adaptation and natural selection in caves in Encyclopedia of Caves (eds. White, W. B., Culver, D. B. & Pipan, T.) 40–46 (Academic Press, 2019).Beier, M. Die Höhlenpseudoscorpione der Balkanhalbinsel. Studien aus dem Gebiete der Allgemeinen Karstforschung, der Wissenschaftlichen Höhlenkunde, der Eiszeitforschung und den Nachbargebieten. 4, 1–83 (1939).
Google Scholar 
Antić, D., Dražina, T., Rađa, T., Tomić, V. T. & Makarov, S. E. Review of the family Anthogonidae (Diplopoda, Chordeumatida), with descriptions of three new species from the Balkan Peninsula. Zootaxa 3948, 151–181 (2015).Article 

Google Scholar 
Pretner, E. Koleopterološka fauna pećina i jama Hrvatske s historijskim pregledom istraživanja. Krš Jugoslavije. 8, 101–239 (1973).
Google Scholar 
Zaragoza, J. A. & Šťáhlavský, F. A new Roncus species (Pseudoscorpiones: Neobisiidae) from Montseny Natural Park (Catalonia, Spain), with remarks on karyology. Zootaxa 1693, 27–40 (2008).Article 

Google Scholar 
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A. & Kent, J. Biodiversity hotspots for conservation priorities. Nature 403, 853–858 (2000).Article 
ADS 

Google Scholar 
Médail, F. & Diadema, K. Glacial refugia influence plant diversity patterns in the Mediterranean Basin. J. Biogeogr. 36, 1333–1345 (2009).Article 

Google Scholar 
Borko, Š., Trontelj, P., Seehausen, O., Moškrič, A. & Fišer, C. A subterranean adaptive radiation of amphipods in Europe. Nat. Commun. 12, 1–12 (2021).Article 

Google Scholar 
Fišer, C. et al. The European green deal misses Europe’s subterranean biodiversity hotspots. Nat. Ecol. Evol. 6, 1403–1404 (2022).Article 

Google Scholar 
Moritz, C. Defining ‘evolutionarily significant units’ for conservation. Trends Ecol. Evol. 9, 373–375 (1994).Article 

Google Scholar  More

Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543, 373–377 (2017).Article 
CAS 

Google Scholar 
Arkema, K. K., Fisher, D. M., Wyatt, K., Wood, S. A. & Payne, H. J. Advancing sustainable development and protected area mManagement with social media-based tourism data. Sustainability 13, 2427 (2021).Article 

Google Scholar 
Tourism in the 2030 Agenda (UNWTO, 2015); https://www.unwto.org/tourism-in-2030-agendaCowburn, B., Moritz, C., Birrell, C., Grimsditch, G. & Abdulla, A. Can luxury and environmental sustainability co-exist? Assessing the environmental impact of resort tourism on coral reefs in the Maldives. Ocean Coast. Manag. 158, 120–127 (2018).Article 

Google Scholar 
Lin, B. Close encounters of the worst kind: reforms needed to curb coral reef damage by recreational divers. Coral Reefs 40, 1429–1435 (2021).Article 

Google Scholar 
Asner, G. P. et al. Large-scale mapping of live corals to guide reef conservation. Proc. Natl Acad. Sci. USA 117, 33711–33718 (2020).Article 
CAS 

Google Scholar 
Wood, S. A., Guerry, A. D., Silver, J. M. & Lacayo, M. Using social media to quantify nature-based tourism and recreation. Sci. Rep. 3, 2976 (2013).Article 

Google Scholar 
Wood, S. A. et al. Next-generation visitation models using social media to estimate recreation on public lands. Sci. Rep. 10, 15419 (2020).Article 
CAS 

Google Scholar 
Hausmann, A. et al. Social media data can be used to understand tourists’ preferences for nature-based experiences in protected areas. Conserv. Lett. 11, e12343 (2018).Article 

Google Scholar 
Tenkanen, H. et al. Instagram, Flickr, or Twitter: assessing the usability of social media data for visitor monitoring in protected areas. Sci. Rep. 7, 17615 (2017).Article 

Google Scholar 
Sessions, C., Wood, S. A., Rabotyagov, S. & Fisher, D. M. Measuring recreational visitation at U.S. National Parks with crowd-sourced photographs. J. Environ. Manag. 183, 703–711 (2016).Article 

Google Scholar 
Mancini, F., Coghill, G. M. & Lusseau, D. Using social media to quantify spatial and temporal dynamics of nature-based recreational activities. PLoS One 13, e0200565 (2018).Article 

Google Scholar 
Spalding, M. et al. Mapping the global value and distribution of coral reef tourism. Mar. Policy 82, 104–113 (2017).Article 

Google Scholar 
van Zanten, B. T. et al. Continental-scale quantification of landscape values using social media data. Proc. Natl Acad. Sci. USA 113, 12974–12979 (2016).Article 

Google Scholar 
Department of Land and Natural Resources. Beach Access (Office of Conservation and Coastal Lands, 2013); https://dlnr.hawaii.gov/occl/beach-access/Mobile LTE Coverage Map (Federal Communications Commission, 2021).Arkema, K. K. et al. Embedding ecosystem services in coastal planning leads to better outcomes for people and nature. Proc. Natl Acad. Sci. USA 112, 7390–7395 (2015).Article 
CAS 

Google Scholar 
Neuvonen, M., Pouta, E., Puustinen, J. & Sievänen, T. Visits to national parks: effects of park characteristics and spatial demand. J. Nat. Conserv. 18, 224–229 (2010).Article 

Google Scholar 
Rodgers, K., Cox, E. & Newtson, C. Effects of mechanical fracturing and experimental trampling on hawaiian corals. Environ. Manag. 31, 0377–0384 (2003).Article 

Google Scholar 
Downs, C. A. et al. Toxicopathological effects of the sunscreen UV filter, oxybenzone (benzophenone-3), on coral planulae and cultured primary cells and its environmental contamination in Hawaii and the U.S. Virgin Islands. Arch. Environ. Contam. Toxicol. 70, 265–288 (2016).Article 
CAS 

Google Scholar 
Côté, I. M., Darling, E. S. & Brown, C. J. Interactions among ecosystem stressors and their importance in conservation. Proc. R. Soc. B. 283, 20152592 (2016).Article 

Google Scholar 
Bruno, J. F. & Valdivia, A. Coral reef degradation is not correlated with local human population density. Sci. Rep. 6, 29778 (2016).Article 
CAS 

Google Scholar 
Johnson, J. V., Dick, J. T. A. & Pincheira-Donoso, D. Local anthropogenic stress does not exacerbate coral bleaching under global climate change. Glob. Ecol. Biogeogr. (2022).Darling, E. S., McClanahan, T. R. & Côté, I. M. Combined effects of two stressors on Kenyan coral reefs are additive or antagonistic, not synergistic. Conserv. Lett. 3, 122–130 (2010).Article 

Google Scholar 
Severino, S. J. L., Rodgers, K. S., Stender, Y. & Stefanak, M. Hanauma Bay Biological Carrying Capacity Survey 2019–20 2nd Annual Report https://www.honolulu.gov/rep/site/dpr/hanaumabay_docs/Hanauma_Bay_Carrying_Capacity_Report_August_2020.pdf (City and County of Honolulu Parks and Recreation Department, 2020).Selenium WebDriver (Software Freedom Conservancy, 2022); https://www.selenium.dev/documentation/en/webdriver/Geospatial Data Portal. Hawaii Statewide GIS Program (Hawaii State Office of Planning, 2017); https://geoportal.hawaii.gov/Wedding, L. M. et al. Advancing the integration of spatial data to map human and natural drivers on coral reefs. PLoS One 13, e0189792 (2018).Article 

Google Scholar 
Nguyen, T., Liquet, B., Mengersen, K. & Sous, D. Mapping of coral reefs with multispectral satellites: a review of recent papers. Remote Sens. 13, 4470 (2021).Article 

Google Scholar 
Wicaksono, P., Aryaguna, P. A. & Lazuardi, W. Benthic habitat mapping model and cross validation using machine-learning classification algorithms. Remote Sens. 11, 1279 (2019).Article 

Google Scholar  More

Biomass yield and WUEBiomass increased with precipitation, as expected and reported in Lee3. There was less water uptake in intercropping compared to sole oat and pea. In general, intercropping represented the median of the two sole cropping treatments, where oat had the highest biomass and WUE while pea had the lowest, and where pea had the highest mineral content and oat had the lowest3. Intercropping resulted in advantages in forage yield stability and was not associated with changes to the AMF community.Alpha diversityWe found differences in AMF species richness estimates in the roots across treatment combinations (i.e., intercropping systems × N fertilizer rate) in 2019 (Chao1, p  More