Philippa Kaur

Brown, J. S., Laundre, J. W. & Gurung, M. The ecology of fear: optimal foraging, game theory, and trophic interactions. J. Mammal. 80, 385–399 (1999).
Google Scholar 
Laundré, J. W., Hernández, L. & Altendorf, K. B. Wolves, elk, and bison: reestablishing the ‘landscape of fear’ in Yellowstone National Park, US.A. Can. J. Zool. 79, 1401–1409 (2001).
Google Scholar 
Atkins, J. L. et al. Cascading impacts of large-carnivore extirpation in an African ecosystem. Science 364, 173–177 (2019).CAS 

Google Scholar 
Laundre, J. W., Hernandez, L. & Ripple, W. J. The landscape of fear: ecological implications of being afraid. Open Ecol. J. 3, 1–7 (2010).
Google Scholar 
Loggins, A. A., Shrader, A. M., Monadjem, A. & McCleery, R. A. Shrub cover homogenizes small mammals’ activity and perceived predation risk. Sci. Rep. 9, 16857 (2019).
Google Scholar 
Whittingham, M. J. & Evans, K. L. The effects of habitat structure on predation risk of birds in agricultural landscapes. Ibis 146, 210–220 (2004).
Google Scholar 
Marshall, K. L. A., Philpot, K. E. & Stevens, M. Microhabitat choice in island lizards enhances camouflage against avian predators. Sci. Rep. 6, 19815 (2016).CAS 

Google Scholar 
Stevens, M., Troscianko, J., Wilson-Aggarwal, J. K. & Spottiswoode, C. N. Improvement of individual camouflage through background choice in ground-nesting birds. Nat. Ecol. Evol. 1, 1325–1333 (2017).
Google Scholar 
Wilson-Aggarwal, J. K., Troscianko, J. T., Stevens, M. & Spottiswoode, C. N. Escape distance in ground-nesting birds differs with individual level of camouflage. Am. Nat. 188, 231–239 (2016).
Google Scholar 
Troscianko, J., Wilson-Aggarwal, J., Stevens, M. & Spottiswoode, C. N. Camouflage predicts survival in ground-nesting birds. Sci. Rep. 6, 19966 (2016).CAS 

Google Scholar 
Gaston, K. J., Duffy, J. P., Gaston, S., Bennie, J. & Davies, T. W. Human alteration of natural light cycles: causes and ecological consequences. Oecologia 176, 917–931 (2014).
Google Scholar 
Gaston, K. J., Davies, T. W., Nedelec, S. L. & Holt, L. A. Impacts of artificial light at night on biological timings. Annu. Rev. Ecol. Evol. Syst. 48, 49–68 (2017).
Google Scholar 
Falchi, F. et al. The new world atlas of artificial night sky brightness. Sci. Adv. 2, e1600377 (2016).
Google Scholar 
Gaston, K. J. et al. Pervasiveness of biological impacts of artificial light at night. Integr. Comp. Biol. 61, 1098–1110 (2021).
Google Scholar 
Sanders, D., Frago, E., Kehoe, R., Patterson, C. & Gaston, K. J. A meta-analysis of biological impacts of artificial light at night. Nat. Ecol. Evol. 5, 74–81 (2021).
Google Scholar 
Kronfeld-Schor, N., Visser, M. E., Salis, L. & van Gils, J. A. Chronobiology of interspecific interactions in a changing world. Philos. Trans. R. Soc. B Biol. Sci. 372, 20160248 (2017).
Google Scholar 
Underwood, C. N., Davies, T. W. & Queir Os, A. M. Artificial light at night alters trophic interactions of intertidal invertebrates. J. Anim. Ecol. 86, 781–789 (2017).
Google Scholar 
Burger, J., Howe, M. A., Hahn, D. C. & Chase, J. Effects of tide cycles on habitat selection and habitat partitioning by migrating shorebirds. Auk 94, 743–758 (1977).
Google Scholar 
Granadeiro, J. P., Dias, M. P., Martins, R. C. & Palmeirim, J. M. Variation in numbers and behaviour of waders during the tidal cycle: implications for the use of estuarine sediment flats. Acta Oecologica 29, 293–300 (2006).
Google Scholar 
Lourenço, P. M. et al. The energetic importance of night foraging for waders wintering in a temperate estuary. Acta Oecologica 34, 122–129 (2008).
Google Scholar 
McNeil, R., Drapeau, P. & Goss-Custard, J. D. The occurrence and adaptive significance of nocturnal habits in waterfowl. Biol. Rev. 67, 381–419 (1992).
Google Scholar 
Martin, G. R. Visual fields and their functions in birds. J. Ornithol. 148, 547–562 (2007).
Google Scholar 
Martin, G. R. What is binocular vision for? A birds’ eye view. J. Vis. 9, 1–19 (2009).
Google Scholar 
Davies, T. W., Duffy, J. P., Bennie, J. & Gaston, K. J. The nature, extent, and ecological implications of marine light pollution. Front. Ecol. Environ. 12, 347–355 (2014).
Google Scholar 
Leopold, M. F., Philippart, C. J. M. & Yorio, P. Nocturnal feeding under artificial light conditions by Brown-hooded Gull (Larus maculipennis) in Puerto Madryn harbour (Chubut Province, Argentina). Hornero 25, 55–60 (2010).
Google Scholar 
Pugh, A. R. & Pawson, S. M. Artificial light at night potentially alters feeding behaviour of the native southern black-backed gull (Larus dominicanus). Notornis 63, 37–39 (2016).
Google Scholar 
Santos, C. D. et al. Effects of artificial illumination on the nocturnal foraging of waders. Acta Oecologica 36, 166–172 (2010).
Google Scholar 
Montevecchi, W. A. Influences of Artificial Light on Marine Birds. in Ecological Consequences of Artificial Night Lighting (eds. Rich, C. & Longcore, T.) 94–113 (Island Press, 2006).Dwyer, R. G., Bearhop, S., Campbell, H. A. & Bryant, D. M. Shedding light on light: benefits of anthropogenic illumination to a nocturnally foraging shorebird. J. Anim. Ecol. 82, 478–485 (2013).
Google Scholar 
Blumstein, D. T. Developing an evolutionary ecology of fear: how life history and natural history traits affect disturbance tolerance in birds. Anim. Behav. 71, 389–399 (2006).
Google Scholar 
Stankowich, T. & Blumstein, D. T. Fear in animals: a meta-analysis and review of risk assessment. Proc. R. Soc. B Biol. Sci. 272, 2627–2634 (2005).
Google Scholar 
Caro, T. Antipredator Defenses in Birds and Mammals. (University of Chicago Press, 2005).Tillmann, J. E. Fear of the dark: night-time roosting and anti-predation behaviour in the grey partridge (Perdix perdix L.). Behaviour 146, 999–1023 (2009).
Google Scholar 
IUCN. The IUCN Red List of Threatened Species. Version 2022-1. https://www.iucnredlist.org/species/22693190/117917038 (2022).Brown, D. et al. The Eurasian Curlew—the most pressing bird conservation priority in the UK? Br. Birds 108, 660–668 (2015).
Google Scholar 
Franks, S. E., Douglas, D. J. T., Gillings, S. & Pearce-Higgins, J. W. Environmental correlates of breeding abundance and population change of Eurasian Curlew Numenius arquata in Britain. Bird. Study 64, 393–409 (2017).
Google Scholar 
Desholm, M. & Kahlert, J. Avian collision risk at an offshore wind farm. Biol. Lett. 1, 296–298 (2005).
Google Scholar 
Clarke, J. A. Moonlight’s influence on predator/prey interactions between short-eared owls (Asio flammeus) and Deermice (Peromyscus maniculatus). Behav. Ecol. Sociobiol. 13, 205–209 (1983).
Google Scholar 
Mandelik, Y., Jones, M. & Dayan, T. Structurally complex habitat and sensory adaptations mediate the behavioural responses of a desert rodent to an indirect cue for increased predation risk. Evol. Ecol. Res. 5, 501–515 (2003).
Google Scholar 
Alexander, R. D. The Evolution of Social Behavior | Annual Review of Ecology, Evolution, and Systematics. Annu. Rev. Ecol. Syst. 5, 325–383 (1974).
Google Scholar 
Pulliam, H. R. On the advantages of flocking. J. Theor. Biol. 38, 419–422 (1973).CAS 

Google Scholar 
Barnard, C. J. Flock feeding and time budgets in the house sparrow (Passer domesticus L.). Anim. Behav. 28, 295–309 (1980).
Google Scholar 
Cooper, W. E. Jr. et al. Effects of risk, cost, and their interaction on optimal escape by nonrefuging Bonaire whiptail lizards, Cnemidophorus murinus. Behav. Ecol. 14, 288–293 (2003).
Google Scholar 
Lagos, P. A. et al. Flight initiation distance is differentially sensitive to the costs of staying and leaving food patches in a small-mammal prey. Can. J. Zool. 87, 1016–1023 (2009).
Google Scholar 
Ydenberg, R. C. & Dill, L. M. The economics of fleeing from predators. Adv. Study Behav. 16, 229–249 (1986).
Google Scholar 
Tucker, V. A., Tucker, A. E., Akers, K. & Enderson, J. H. Curved flight paths and sideways vision in peregrine falcons (Falco peregrinus). J. Exp. Biol. 203, 3755–3763 (2000).CAS 

Google Scholar 
Carr, J. M. & Lima, S. L. Wintering birds avoid warm sunshine: predation and the costs of foraging in sunlight. Oecologia 174, 713–721 (2014).
Google Scholar 
van den Hout, P. J. & Martin, G. R. Extreme head-tilting in shorebirds: predator detection and sun avoidance. Wader Study Group Bull. 118, 18–21 (2011).
Google Scholar 
Ferguson, J. W. H., Galpin, J. S. & de Wet, M. J. Factors affecting the activity patterns of black-backed jackals Canis mesomelas. J. Zool. 214, 55–69 (1988).
Google Scholar 
Pyke, G. H. Optimal foraging theory: a critical review. Annu. Rev. Ecol. Syst. 15, 523–575 (1984).
Google Scholar 
Stephens, D. W. & Krebs, J. R. Foraging Theory. (Princeton University Press, 1986).Mouritsen, K. N. Predator avoidance in night-feeding dunlins calidris alpina: a matter of concealment. Ornis Scand. 23, 195–198 (1992).
Google Scholar 
Blumstein, D. T. Flight-initiation distance in birds is dependent on intruder starting distance. J. Wildl. Manag. 67, 852–857 (2003).
Google Scholar 
Troscianko, J. OSpRad; an open-source, low-cost, high-sensitivity spectroradiometer (p. 2022.12.09.519768). bioRxiv https://doi.org/10.1101/2022.12.09.519768 (2022).Article 

Google Scholar 
Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.4.4. http://florianhartig.github.io/DHARMa/ (2022).Core Team, R. R: a Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, 2022).
Google Scholar  More

Butchart, S. H. M. et al. Global biodiversity: Indicators of recent declines. Science 328, 1164–1168 (2010).ADS 
CAS 

Google Scholar 
McGill, B. J., Dornelas, M., Gotelli, N. J. & Magurran, A. E. Fifteen forms of biodiversity trend in the Anthropogene. Trends Ecol. Evol. 30, 104–113 (2015).
Google Scholar 
Bradshaw, C. J. A., Sodhi, N. S. & Brook, B. W. Tropical turmoil: A biodiversity tragedy in progress. Front. Ecol. Environ. 7, 79–87 (2009).
Google Scholar 
Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).ADS 
CAS 

Google Scholar 
Loreau, M. et al. Biodiversity and ecosystem functioning: Current knowledge and future challenges. Science 294, 804–808 (2001).ADS 
CAS 

Google Scholar 
Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: A consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).
Google Scholar 
Hooper, D. U. et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108 (2012).ADS 
CAS 

Google Scholar 
Balvanera, P. et al. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecol. Lett. 9, 1146–1156 (2006).
Google Scholar 
Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).ADS 
CAS 

Google Scholar 
Pasari, J. R., Levi, T., Zavaleta, E. S. & Tilman, D. Several scales of biodiversity affect ecosystem multifunctionality. Proc. Natl. Acad. Sci. U.S.A. 110, 10219–10222 (2013).ADS 
CAS 

Google Scholar 
Tilman, D., Isbell, F. & Cowles, J. M. Biodiversity and ecosystem functioning. Annu. Rev. Ecol. Evol. Syst. 45, 471–493 (2014).
Google Scholar 
Murphy, G. E. P. & Romanuk, T. N. A meta-analysis of declines in local species richness from human disturbances. Ecol. Evol. 4, 91–103 (2014).
Google Scholar 
Johnson, C. N. et al. Biodiversity losses and conservation responses in the Anthropocene. Science 356, 270–275 (2017).ADS 
CAS 

Google Scholar 
de Coster, G., Banks-Leite, C. & Metzger, J. P. Atlantic forest bird communities provide different but not fewer functions after habitat loss. Proc. R. Soc. B 282, 20142844 (2015).
Google Scholar 
Riemann, J. C., Ndriantsoa, S. H., Rödel, M.-O. & Glos, J. Functional diversity in a fragmented landscape—habitat alterations affect functional trait composition of frog assemblages in Madagascar. Global Ecol. Conserv. 10, 173–183 (2017).
Google Scholar 
McKinney, M. L. & Lockwood, J. L. Biotic homogenization: A few winners replacing many losers in the next mass extinction. Trends Ecol. Evol. 14, 450–453 (1999).CAS 

Google Scholar 
Socolar, J. B., Gilroy, J. J., Kunin, W. E. & Edwards, D. P. How should beta-diversity inform biodiversity conservation?. Trends Ecol. Evol. 31, 67–80 (2016).
Google Scholar 
van der Plas, F. et al. Biotic homogenization can decrease landscape-scale forest multi-functionality. Proc. Natl. Acad. Sci. U.S.A. 113, 3557–3562 (2016).ADS 

Google Scholar 
Mori, A. S., Isbell, F. & Seidl, R. β-diversity, community assembly, and ecosystem functioning. Trends Ecol. Evol. 33, 549–564 (2018).
Google Scholar 
Dehling, J. M. & Dehling, D. M. Conserving ecological functions of frog communities in Borneo requires diverse forest landscapes. Global Ecol. Conserv. 26, e01481 (2021).
Google Scholar 
Hector, A. & Bagchi, R. Biodiversity and ecosystem multifunctionality. Nature 448, 188–190 (2007).ADS 
CAS 

Google Scholar 
Isbell, F. et al. High plant diversity is needed to maintain ecosystem services. Nature 477, 199–202 (2011).ADS 
CAS 

Google Scholar 
Loreau, M., Mouquet, N. & Gonzalez, A. Biodiversity as spatial insurance in heterogeneous landscapes. Proc. Natl. Acad. Sci. U.S.A. 100, 12765–12770 (2003).ADS 
CAS 

Google Scholar 
Seibold, S. et al. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature 574, 671–674 (2019).ADS 
CAS 

Google Scholar 
Felipe-Lucia, M. R. et al. Land-use intensity alters networks between biodiversity, ecosystem functions, and services. Proc. Natl. Acad. Sci. U.S.A. 117, 28140–28149 (2020).ADS 
CAS 

Google Scholar 
Tilman, D. Functional diversity in Encyclopedia of biodiversity, Vol. 3. (ed. Levin S. A.) 109–120 (Academic Press, 2001)Cadotte, M. W., Carscadden, K. & Mirotchnick, N. Beyond species: functional diversity and the maintenance of ecological processes and services. J. Appl. Ecol. 48, 1079–1087 (2011).
Google Scholar 
Flynn, D. F. B., Mirotchnick, N., Jain, M., Palmer, M. I. & Naeem, S. Functional and phylogenetic diversity as predictors of biodiversity-ecosystem function relationships. Ecology 92, 1573–1581 (2011).
Google Scholar 
Lean, C. & Maclaurin, J. The value of phylogenetic diversity in Biodiversity conservation and phylogenetic systematics. Topics in Biodiversity and Conservation 14. (eds. Pellens, R., Grandcolas, P.) 19–38 (Springer, 2016).Owen, N. R., Gumbs, R., Gray, C. L. & Faith, D. P. Global conservation of phylogenetic diversity captures more than just functional diversity. Nat. Commun. 10, 859 (2019).ADS 

Google Scholar 
Gumbs, R., Williams, R. C., Lowney, A. M. & Smith, D. Spatial and species-level metrics reveal global patterns of irreplaceable and imperiled gecko phylogenetic diversity. Israel J. Ecol. Evolut. 66, 239–252 (2020).
Google Scholar 
Brooks, D. R., Mayden, R. L. & McLennan, D. A. Phylogeny and biodiversity: Conserving our evolutionary legacy. Trends Ecol. Evol. 7, 55–59 (1992).CAS 

Google Scholar 
Phillimore, A. B. et al. Biogeographical basis of recent phenotypic divergence among birds: a global study of subspecies richness. Evolution 61, 942–957 (2007).
Google Scholar 
Miraldo, A. et al. An Anthropocene map of genetic diversity. Science 353, 1532–1535 (2016).ADS 
CAS 

Google Scholar 
Smith, B. T., Seeholzer, G. F., Harvey, M. G., Cuervo, A. M. & Brumfield, R. T. A latitudinal phylogeographic diversity gradient in birds. PLoS Biol. 15, e2001073 (2017).
Google Scholar 
Tucker, C. M. et al. Assessing the utility of conserving evolutionary history. Biol. Rev. 94, 1740–1760 (2019).
Google Scholar 
Flynn, D. F. B. et al. Loss of functional diversity under land use intensification across multiple taxa. Ecol. Lett. 12, 22–33 (2009).
Google Scholar 
Villéger, S., Miranda, J. R., Hernández, D. F. & Mouillot, D. Contrasting changes in taxonomic vs. functional diversity of tropical fish communities after habitat degradation. Ecological Applications 20, 1512–1522 (2010).Gibbons, J. W. et al. Remarkable amphibian biomass and abundance in an isolated wetland: Implications for wetland conservation. Conserv. Biol. 20, 1457–1465 (2006).
Google Scholar 
Hocking, D. J. & Babbitt, K. J. Amphibian contributions to ecosystem services. Herpetol. Conserv. Biol. 9, 1–17 (2014).
Google Scholar 
Beebee, T. J. C. Amphibian breeding and climate change. Nature 374, 219–220 (1995).ADS 
CAS 

Google Scholar 
Kiesecker, J. M., Blaustein, A. R. & Belden, L. K. Complex causes of amphibian population declines. Nature 410, 681–684 (2001).ADS 
CAS 

Google Scholar 
Cheng, T. L., Rovito, S. M., Wake, D. B. & Vredenburg, V. T. Coincident mass extirpation of neotropical amphibians with the emergence of the infection fungal pathogen Batrachochytrium dendrobatidis. Proc. Natl. Acad. Sci. U.S.A. 108, 9502–9507 (2011).ADS 
CAS 

Google Scholar 
Wake, D. B. & Vredenburg, V. T. Are we in the midst of the sixth mass extinction? A view from the world of amphibians. Proc. Natl. Acad. Sci. U.S.A. 105, 11466–11473 (2008).ADS 
CAS 

Google Scholar 
Ernst, R. & Rödel, M.-O. Patterns of community composition in two tropical tree frog assemblages: Separating spatial structure and environmental effects in disturbed and undisturbed forests. J. Trop. Ecol. 24, 111–120 (2008).
Google Scholar 
Gardner, T. A. et al. The value of primary, secondary, and plantation forests for a Neotropical Herpetofauna. Conserv. Biol. 21, 775–787 (2007).
Google Scholar 
Gardner, T. A., Fitzherbert, E. B., Drewes, R. C., Howell, K. M. & Caro, T. Spatial and temporal patterns of abundance and diversity of an East African leaf litter amphibian fauna. Biotropica 39, 105–113 (2007).
Google Scholar 
Gillespie, G. R. et al. Conservation of amphibians in Borneo: relative value of secondary tropical forest and non-forest habitats. Biol. Cons. 152, 136–144 (2012).
Google Scholar 
Angarita-M., O., Montes-Correa, A. C. & Renjifo, J. M. Amphibians and reptiles of an agroforestry system in the Colombian Caribbean. Amphibian & Reptile Conservation 8, 33–52 (2015).Jiménez-Robles, O., Guayasamin, J. M., Ron, S. R. & De la Riva, I. Reproductive traits associated with species turnover of amphibians in Amazonia and its Andean slopes. Ecol. Evol. 7, 2489–2500 (2017).
Google Scholar 
Ernst, R., Linsenmair, K. E. & Rödel, M.-O. Diversity erosion beyond the species level: dramatic loss of functional diversity after selective logging in two tropical amphibian communities. Biol. Cons. 133, 143–155 (2006).
Google Scholar 
Oda, F. H. et al. Anuran species richness, composition, and breeding habitat preferences: a comparison between forest remnants and agricultural landscapes in Southern Brazil. Zool. Stud. 55, 34 (2016).
Google Scholar 
Sinsch, U., Lümkemann, K., Rosar, K., Schwarz, C. & Dehling, J. M. Acoustic niche partitioning in an anuran community inhabiting an Afromontane wetland (Butare, Rwanda). African Zool. 47, 60–73 (2012).
Google Scholar 
Tumushimire, L., Mindje, M., Sinsch, U. & Dehling, J. M. The anuran diversity of cultivated wetlands in Rwanda: Melting pot of generalists?. Salamandra 56, 99–112 (2020).
Google Scholar 
REMA. Rwanda State of Environment and Outlook Report 2017 – Achieving Sustainable Urbanization. (Rwanda Environment Management Authority, Government of Rwanda, 2017).Su, J. C., Debinski, D. M., Jakubauskas, M. E. & Kindscher, K. Beyond species richness: Community similarity as a measure of cross-taxon congruence for coarse-filter conservation. Conserv. Biol. 18, 167–173 (2004).
Google Scholar 
Gibson, L. et al. Primary forests are irreplaceable for sustaining tropical biodiversity. Nature 478, 378–381 (2011).ADS 
CAS 

Google Scholar 
Zimkus, B. M., Rödel, M.-O. & Hillers, A. Complex patterns of continental speciation: Molecular phylogenetics and biogeography of sub-Saharan puddle frogs (Phrynobatrachus). Mol. Phylogenet. Evol. 55, 883–900 (2010).
Google Scholar 
Dehling, J. M. & Sinsch, U. Partitioning of morphospace in larval and adult reed frogs (Anura: Hyperoliidae: Hyperolius) of the Central African Albertine Rift. Zool. Anz. 280, 65–77 (2019).
Google Scholar 
Mazel, F. et al. Prioritizing phylogenetic diversity captures functional diversity unreliably. Nat. Commun. 9, 2888 (2018).ADS 

Google Scholar 
Haddad, C. F. B. & Prado, C. P. A. Reproductive modes and their unexpected diversity in the Atlantic forest of Brazil. Bioscience 55, 207–217 (2005).
Google Scholar 
Capinha, C., Essl, F., Seebens, H., Moser, D. & Pereira, H. M. The dispersal of alien species redefines biogeography in the Anthropocene. Science 348, 1248–1251 (2015).ADS 
CAS 

Google Scholar 
Alroy, J. Effects of habitat disturbance on tropical forest biodiversity. Proc. Natl. Acad. Sci. U.S.A. 114, 6056–6061 (2017).ADS 
CAS 

Google Scholar 
Dehling, J. M. & Sinsch, U. Diversity of Ptychadena in Rwanda and taxonomic status of P. chrysogaster Laurent, 1954 (Amphibia, Anura, Ptychadenidae). ZooKeys 356, 69–102 (2013).IUCN. The IUCN Red List of Threatened Species. Version 2020–1. https://www.iucnredlist.org (2020).Portillo, F., Greenbaum, E., Menegon, M., Kusamba, C. & Dehling, J. M. Phylogeography and species boundaries of Leptopelis (Anura: Arthroleptidae) from the Albertine Rift. Mol. Phylogenet. Evol. 82, 75–86 (2015).
Google Scholar 
Channing, A., Dehling, J. M., Lötters, S. & Ernst, R. Species boundaries and taxonomy of the African River Frogs (Anura: Pyxicephalidae: Amietia). Zootaxa 4155, 1–76 (2016).CAS 

Google Scholar 
Rödel, M.-O. & Ernst, R. Measuring and monitoring amphibian diversity in tropical forests. I. An evaluation of methods with recommendations for standardization. Ecotropica 10, 1–14 (2004).Channing, A. & Howell, K. M. Amphibians of East Africa. (Chimaira, 2006).Jetz, W. & Pyron, R. A. The interplay of past diversification and evolutionary isolation with present imperilment across the amphibian tree of life. Nat. Ecol. Evolut. 2, 850–858 (2018).
Google Scholar 
Villéger, S., Mason, N. W. & Mouillot, D. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology 89, 2290–2301 (2008).
Google Scholar 
Maire, E., Grenouillet, G., Brosse, S. & Villéger, S. How many dimensions are needed to accurately assess functional diversity? A pragmatic approach for assessing the quality of functional spaces. Glob. Ecol. Biogeogr. 24, 728–740 (2015).
Google Scholar 
Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Cons. 61, 1–10 (1992).
Google Scholar 
Dehling, D. M. et al. Functional and phylogenetic diversity and assemblage structure of frugivorous birds along an elevational gradient in the tropical Andes. Ecography 37, 1047–1055 (2014).
Google Scholar 
Baselga, A. et al. betapart: partitioning beta diversity into turnover and nestedness components. R package version 1.5.6. https://CRAN.R-project.org/package=betapart (2022).Dehling, D. M. et al. Specialists and generalists fulfil important and complementary functional roles in ecological processes. Funct. Ecol. 35, 1810–1821 (2021).CAS 

Google Scholar 
Dehling, D. M., Barreto, E. & Graham, C. H. The contribution of mutualistic interactions to functional and phylogenetic diversity. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2022.05.006 (2022).Article 

Google Scholar 
R Core Team. R: a language and environment for statistical computing. (R Foundation for Statistical Computing, 2021). More

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Hoffmann, A. A. & Sgrò, C. M. Nature 470, 479–485 (2011).Article 
CAS 

Google Scholar 
Taylor, S. A. & Larson, E. L. Nat. Ecol. Evol. 3, 170–177 (2019).Article 

Google Scholar 
Brauer, C. J. et al. Nat. Clim. Change https://doi.org/10.1038/s41558-022-01585-1 (2023).Article 

Google Scholar 
Grinnell, J. Auk 34, 427–433 (1917).Article 

Google Scholar 
Peterson, A. T. et al. Ecological Niches and Geographic Distributions (Princeton Univ. Press, 2011).Wiens, J. A., Stralberg, D., Jongsomjit, D., Howell, C. A. & Snyder, M. A. Proc. Natl Acad. Sci. USA 106, 19729–19736 (2009).Article 
CAS 

Google Scholar 
Aguirre-Liguori, J. A., Ramírez-Barahona, S. & Gaut, B. S. Nat. Ecol. Evol. 5, 1350–1360 (2021).Article 

Google Scholar 
Fitzpatrick, M. C. & Keller, S. R. Ecol. Lett. 18, 1–16 (2015).Article 

Google Scholar 
Bay, R. A. et al. Science 359, 83–86 (2018).Article 
CAS 

Google Scholar 
Capblancq, T., Fitzpatrick, M. C., Bay, R. A., Exposito-Alonso, M. & Keller, S. R. Annu. Rev. Ecol. Evol. Syst. 51, 245–269 (2020).Article 

Google Scholar 
Rellstab, C., Dauphin, B. & Exposito‐Alonso, M. Evol. Appl. 14, 1202–1212 (2021).Article 

Google Scholar 
Allendorf, F. W., Leary, R. F., Spruell, P. & Wenburg, J. K. Trends Ecol. Evol. 16, 613–622 (2001).Article 

Google Scholar 
Rhymer, J. M. & Simberloff, D. Annu. Rev. Ecol. Syst. 27, 83–109 (1996).Article 

Google Scholar 
Todesco, M. et al. Evol. Appl. 9, 892–908 (2016).Article 
CAS 

Google Scholar  More

Habitat loss is one of main threats to biodiversity worldwide and in general is perceived as something to be avoided. However, the prevalence of negative effects of forest fragmentation is less clear. Fragmentation creates edges between once-pristine forest and the adjacent non-forest system or systems (for example, agricultural lands, cities or water reservoirs), but the effects of these edges on biodiversity are not always clear. By performing a robust study of the interaction between insect pollinators and flowering plants at forest edges and within the forest, Ren et al.1 add a new piece to this puzzle by showing that forest edges can have a positive buffering effect on interaction networks. More

Millard, J. et al. Global effects of land-use intensity on local pollinator biodiversity. Nat. Commun. 12, 2902 (2021).Article 
CAS 

Google Scholar 
Haddad, N. M. et al. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci. Adv. 1, e1500052 (2015).Article 

Google Scholar 
Valiente-Banuet, A. et al. Beyond species loss: the extinction of ecological interactions in a changing world. Funct. Ecol. 29, 299–307 (2015).Article 

Google Scholar 
Rybicki, J., Abrego, N. & Ovaskainen, O. Habitat fragmentation and species diversity in competitive communities. Ecol. Lett. 23, 506–517 (2020).Article 

Google Scholar 
Chase, J. M., Blowes, S. A., Knight, T. M., Gerstner, K. & May, F. Ecosystem decay exacerbates biodiversity loss with habitat loss. Nature 584, 238–243 (2020).Article 
CAS 

Google Scholar 
Ewers, R. M. & Didham, R. K. Confounding factors in the detection of species responses to habitat fragmentation. Biol. Rev. 81, 117–142 (2006).Article 

Google Scholar 
Didham, R. K. Ecological consequences of habitat fragmentation. In Encyclopedia of Life Sciences (ed Jansson, R.), 61, 1–39 (Wiley, UK2010).Aizen, M. A., Sabatino, M. & Tylianakis, J. M. Specialization and rarity predict nonrandom loss of interactions from mutualist networks. Science 335, 1486–1489 (2012).Article 
CAS 

Google Scholar 
Spiesman, B. J. & Inouye, B. D. Habitat loss alters the architecture of plant-pollinator interaction networks. Ecology 94, 2688–2696 (2013).Article 

Google Scholar 
Aizen, M. A. et al. The phylogenetic structure of plant-pollinator networks increases with habitat size and isolation. Ecol. Lett. 19, 29–36 (2016).Article 

Google Scholar 
Emer, C. et al. Seed-dispersal interactions in fragmented landscapes-a metanetwork approach. Ecol. Lett. 21, 484–493 (2018).Article 

Google Scholar 
Fortuna, M. A. & Bascompte, J. Habitat loss and the structure of plant-animal mutualistic networks. Ecol. Lett. 9, 278–283 (2006).Article 

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).Article 

Google Scholar 
Glenn R. Matlack & John A. Litvaitis. Forest edges. In Maintaining Biodiversity in Forest Ecosystems (ed Hunter, M.) 6, 210–233 (Cambridge Univ. Press, 1999).Hadley, A. S. & Betts, M. G. The effects of landscape fragmentation on pollination dynamics: absence of evidence not evidence of absence. Biol. Rev. 87, 526–544 (2012).Article 

Google Scholar 
Ibanez, I., Katz, D. S. W., Peltier, D., Wolf, S. M. & Barrie, B. T. C. Assessing the integrated effects of landscape fragmentation on plants and plant communities: the challenge of multiprocess-multiresponse dynamics. J. Ecol. 102, 882–895 (2014).Article 

Google Scholar 
Morreale, L. L., Thompson, J. R., Tang, X., Reinmann, A. B. & Hutyra, L. R. Elevated growth and biomass along temperate forest edges. Nat. Commun. 12, 7181 (2021).Article 
CAS 

Google Scholar 
Martinez-Ramos, M., Alvarez-Buylla, E. & Sarukhan, J. Tree demography and gap dynamics in a tropical rain forest. Ecology 70, 555–558 (1989).Article 

Google Scholar 
Yamamoto, S. I. Forest gap dynamics and tree regeneration. J. For. Res. 5, 223–229 (2000).Article 

Google Scholar 
Schnitzer, S. A. & Carson, W. P. Treefall gaps and the maintenance of species diversity in a tropical forest. Ecology 82, 913–919 (2001).Article 

Google Scholar 
Kricher, J. A Shifting Mosaic: Rain Forest Development and Dynamics. In Tropical Ecology 6, 188–226 (Princeton Univ. Press, 2011).Gayer, C. et al. Flowering fields, organic farming and edge habitats promote diversity of plants and arthropods on arable land. J. Appl. Ecol. 58, 1155–1166 (2021).Article 

Google Scholar 
Bailey, S. et al. Distance from forest edge affects bee pollinators in oilseed rape fields. Ecol. Evol. 4, 370–380 (2014).Article 

Google Scholar 
Thebault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856 (2010).Article 
CAS 

Google Scholar 
Hagen, M. et al. Biodiversity, species interactions and ecological networks in a fragmented world. Adv. Ecol. Res. 46, 89–210 (2012).Article 

Google Scholar 
Traveset, A., Castro-Urgal, R., Rotllan-Puig, X. & Lazaro, A. Effects of habitat loss on the plant-flower visitor network structure of a dune community. Oikos 127, 45–55 (2018).Article 

Google Scholar 
Rezende, E. L., Lavabre, J. E., Guimaraes, P. R., Jordano, P. & Bascompte, J. Non-random coextinctions in phylogenetically structured mutualistic networks. Nature 448, 925–928 (2007).Article 
CAS 

Google Scholar 
Staddon, P., Lindo, Z., Crittenden, P. D., Gilbert, F. & Gonzalez, A. Connectivity, non-random extinction and ecosystem function in experimental metacommunities. Ecol. Lett. 13, 543–552 (2010).Article 

Google Scholar 
Wardle, D. A., Bardgett, R. D., Callaway, R. M. & Van der Putten, W. H. Terrestrial ecosystem responses to species gains and losses. Science 332, 1273–1277 (2011).Article 
CAS 

Google Scholar 
Sargent, R. D. & Ackerly, D. D. Plant-pollinator interactions and the assembly of plant communities. Trends Ecol. Evol. 23, 123–130 (2008).Article 

Google Scholar 
Bastolla, U. et al. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458, 1018–1020 (2009).Article 
CAS 

Google Scholar 
Rohr, R. P., Saavedra, S. & Bascompte, J. On the structural stability of mutualistic systems. Science 345, 1253497 (2014).Article 

Google Scholar 
Dunne, J. A., Williams, R. J. & Martinez, N. D. Network structure and biodiversity loss in food webs: robustness increases with connectance. Ecol. Lett. 5, 558–567 (2002).Article 

Google Scholar 
Pawar, S. Why are plant-pollinator networks nested? Science 345, 383–383 (2014).Article 
CAS 

Google Scholar 
Kaiser-Bunbury, C. N., Muff, S., Memmott, J., Muller, 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).Article 

Google Scholar 
Evans, D. M., Pocock, M. J. O. & Memmott, J. The robustness of a network of ecological networks to habitat loss. Ecol. Lett. 16, 844–852 (2013).Article 

Google Scholar 
Ponisio, L. C., Gaiarsa, M. P. & Kremen, C. Opportunistic attachment assembles plant-pollinator networks. Ecol. Lett. 20, 1261–1272 (2017).Article 

Google Scholar 
Wilson, M. C. et al. Habitat fragmentation and biodiversity conservation: key findings and future challenges. Landsc. Ecol. 31, 219–227 (2016).Article 

Google Scholar 
Zhong, L., Didham, R. K., Liu, J., Jin, Y. & Yu, M. Community re-assembly and divergence of woody plant traits in an island-mainland system after more than 50 years of regeneration. Divers. Distrib. 27, 1435–1448 (2021).Article 

Google Scholar 
Liu, J. et al. The asymmetric relationships of the distribution of conspecific saplings and adults in forest fragments. J. Plant Ecol. 13, 398–404 (2020).Article 
CAS 

Google Scholar 
Ewers, R. M., Bartlam, S. & Didham, R. K. Altered species interactions at forest edges: contrasting edge effects on bumble bees and their phoretic mite loads in temperate forest remnants. Insect Conserv. Divers. 6, 598–606 (2013).Article 

Google Scholar 
Wardhaugh, C. W. The spatial and temporal distributions of arthropods in forest canopies: uniting disparate patterns with hypotheses for specialisation. Biol. Rev. Camb. Philos. Soc. 89, 1021–1041 (2015).Article 

Google Scholar 
Lowman, M. Life in the treetops – an overview of forest canopy science and its future directions. Plants People Planet 3, 16–21 (2021).Article 

Google Scholar 
Nakamura, A. et al. Forests and their canopies: achievements and horizons in canopy science. Trends Ecol. Evol. 32, 438–451 (2017).Article 

Google Scholar 
Lennartsson, T. Extinction thresholds and disrupted plant-pollinator interactions in fragmented plant populations. Ecology 83, 3060–3072 (2002).
Google Scholar 
Aguilar, R., Ashworth, L., Galetto, L. & Aizen, M. A. Plant reproductive susceptibility to habitat fragmentation: review and synthesis through a meta-analysis. Ecol. Lett. 9, 968–980 (2006).Article 

Google Scholar 
Kremen, C. et al. Pollination and other ecosystem services produced by mobile organisms: a conceptual framework for the effects of land-use change. Ecol. Lett. 10, 299–314 (2007).Article 

Google Scholar 
Goulson, D., Nicholls, E., Botias, C. & Rotheray, E. L. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347, 1255957 (2015).Article 

Google Scholar 
Gathmann, A. & Tscharntke, T. Foraging ranges of solitary bees. J. Anim. Ecol. 71, 757–764 (2002).Article 

Google Scholar 
Winfree, R., Bartomeus, I. & Cariveau, D. P. Native pollinators in anthropogenic habitats. Annu. Rev. Entomol. 42, 1–22 (2011).
Google Scholar 
Torné-Noguera, A. et al. Determinants of spatial distribution in a bee community: nesting resources, flower resources, and body size. PLoS ONE 9, e97255 (2014).Article 

Google Scholar 
Roswell, M., Dushoff, J. & Winfree, R. A conceptual guide to measuring species diversity. Oikos 130, 321–338 (2021).Article 

Google Scholar 
Schoereder, J. H. et al. Should we use proportional sampling for species-area studies? J. Biogeogr. 31, 1219–1226 (2004).Article 

Google Scholar 
Jordano, P. Patterns of mutualistic interactions in pollination and seed dispersal: connectance, dependence asymmetries, and coevolution. Am. Nat. 129, 657–677 (1987).Article 

Google Scholar 
Devoto, M., Medan, D. & Montaldo, N. H. Patterns of interaction between plants and pollinators along an environmental gradient. Oikos 109, 461–472 (2005).Article 

Google Scholar 
Petanidou, T., Kallimanis, A. S., Tzanopoulos, J., Sgardelis, S. P. & Pantis, J. D. Long-term observation of a pollination network: fluctuation in species and interactions, relative invariance of network structure and implications for estimates of specialization. Ecol. Lett. 11, 564–575 (2008).Article 

Google Scholar 
Brodie, J. F. et al. Secondary extinctions of biodiversity. Trends Ecol. Evol. 29, 664–672 (2014).Article 

Google Scholar 
Vazquez, D. P. & Aizen, M. A. Asymmetric specialization: a pervasive feature of plant-pollinator interactions. Ecology 85, 1251–1257 (2004).Article 

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 
Malhi, Y., Gardner, T. A., Goldsmith, G. R., Silman, M. R. & Zelazowski, P. Tropical forests in the Anthropocene. Annu. Rev. Environ. Resour. 39, 125–159 (2014).Article 

Google Scholar 
Lewis, S. L., Edwards, D. P. & Galbraith, D. Increasing human dominance of tropical forests. Science 349, 827–832 (2015).Article 
CAS 

Google Scholar 
Fletcher, R. J. Jr et al. Is habitat fragmentation good for biodiversity? Biol. Conserv. 226, 9–15 (2018).Article 

Google Scholar 
Ren, P., Si, X. & Ding, P. Stable species and interactions in plant-pollinator networks deviate from core position in fragmented habitats. Ecography 2022, e06102 (2022).Article 

Google Scholar 
Fortuna, M. A. et al. Nestedness versus modularity in ecological networks: two sides of the same coin? J. Anim. Ecol. 79, 811–817 (2010).
Google Scholar 
Bascompte, J., Jordano, P., Melian, C. J. & Olesen, J. M. The nested assembly of plant-animal mutualistic networks. Proc. Natl Acad. Sci. USA 100, 9383–9387 (2003).Article 
CAS 

Google Scholar 
Almeida-Neto, M., Guimaraes, P., Guimaraes, 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).Article 

Google Scholar 
Ulrich, W., Almeida-Neto, M. & Gotelli, N. J. A consumer’s guide to nestedness analysis. Oikos 118, 3–17 (2009).Article 

Google Scholar 
Dicks, L. V., Corbet, S. A. & Pywell, R. F. Compartmentalization in plant-insect flower visitor webs. J. Anim. Ecol. 71, 32–43 (2002).Article 

Google Scholar 
Beckett, S. J. Improved community detection in weighted bipartite networks. R. Soc. Open Sci. 3, 140536 (2016).Article 

Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-7 (2020). https://CRAN.R-project.org/package=veganDormann, C. F. et al. bipartite: Visualising Bipartite Networks and Calculating Some (Ecological) Indices. R package version 2.16 (2021). https://CRAN.R-project.org/package=bipartitePocock, M. J. O., Evans, D. M. & Memmott, J. The robustness and restoration of a network of ecological networks. Science 335, 973–977 (2012).Article 
CAS 

Google Scholar 
Scherber, C. et al. Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment. Nature 468, 553–556 (2010).Article 
CAS 

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).Article 
CAS 

Google Scholar 
Shipley, B. Confirmatory path analysis in a generalized multilevel context. Ecology 90, 363–368 (2009).Article 

Google Scholar 
Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

Google Scholar 
Grace, J. B., Scheiner, S. M. & Schoolmaster, D. R. Jr. Structural equation modeling: building and evaluating causal models. In Ecological Statistics: From Principles to Applications (eds Fox, G. A. et al.), 8, 168–199 (Oxford Univ. Press, 2015).Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2014).
Google Scholar 
Shipley, B. The AIC model selection method applied to path analytic models compared using a d-separation test. Ecology 94, 560–564 (2013).Article 

Google Scholar 
Murphy, M. semEff: Automatic Calculation of Effects for Piecewise Structural Equation Models. R package version 0.6.0 (2021). https://CRAN.R-project.org/package=semEffDudgeon, P. A comparative investigation of confidence intervals for independent variables in linear regression. Multivar. Behav. Res. 51, 139–153 (2016).Article 

Google Scholar 
Gotelli, N. J. & Graves, G. R. Null Models in Ecology (Smithsonian Inst. Press, 1996).Jung, V., Violle, C., Mondy, C., Hoffmann, L. & Muller, S. Intraspecific variability and trait-based community assembly. J. Ecol. 98, 1134–1140 (2010).Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020). More

Ackerly, D. D. Community assembly, niche conservatism, and adaptive evolution in changing environments. Int. J. Plant Sci. 164, S165–S184 (2003).Article 

Google Scholar 
Kellermann, V., Van Heerwaarden, B., Sgrò, C. M. & Hoffmann, A. A. Fundamental evolutionary limits in ecological traits drive Drosophila species distributions. Science 325, 1244–1246 (2009).Article 
CAS 

Google Scholar 
Hansen, M. M., Olivieri, I., Waller, D. M. & Nielsen, E. E. Monitoring adaptive genetic responses to environmental change. Mol. Ecol. 21, 1311–1329 (2012).Article 

Google Scholar 
Aitken, S. N. & Whitlock, M. C. Assisted gene flow to facilitate local adaptation to climate change. Annu. Rev. Ecol. Evol. Syst. 44, 367–388 (2013).Article 

Google Scholar 
Becker, M. et al. Hybridization may facilitate in situ survival of endemic species through periods of climate change. Nat. Clim. Change 3, 1039–1043 (2013).Article 

Google Scholar 
Allendorf, F. W., Leary, R. F., Spruell, P. & Wenburg, J. K. The problems with hybrids: setting conservation guidelines. Trends Ecol. Evol. 16, 613–622 (2001).Article 

Google Scholar 
Todesco, M. et al. Hybridization and extinction. Evol. Appl. 9, 892–908 (2016).Article 
CAS 

Google Scholar 
Rhymer, J. M. & Simberloff, D. Extinction by hybridization and introgression. Annu. Rev. Ecol. Syst. 27, 83–109 (1996).Article 

Google Scholar 
Taylor, S. A. & Larson, E. L. Insights from genomes into the evolutionary importance and prevalence of hybridization in nature. Nat. Ecol. Evol. 3, 170–177 (2019).Article 

Google Scholar 
vonHoldt, B. M., Brzeski, K. E., Wilcove, D. S. & Rutledge, L. Y. Redefining the role of admixture and genomics in species conservation. Conserv. Lett. 11, e12371 (2018).Article 

Google Scholar 
Hamilton, J. A. & Miller, J. M. Adaptive introgression as a resource for management and genetic conservation in a changing climate. Conserv. Biol. 30, 33–41 (2016).Article 

Google Scholar 
Ralls, K., Sunnucks, P., Lacy, R. C. & Frankham, R. Genetic rescue: a critique of the evidence supports maximizing genetic diversity rather than minimizing the introduction of putatively harmful genetic variation. Biol. Conserv. 251, 108784 (2020).Article 

Google Scholar 
Capblancq, T., Fitzpatrick, M. C., Bay, R. A., Exposito-Alonso, M. & Keller, S. R. Genomic prediction of (mal) adaptation across current and future climatic landscapes. Annu. Rev. Ecol. Evol. Syst. 51, 245–269 (2020).Article 

Google Scholar 
Rellstab, C., Dauphin, B. & Exposito‐Alonso, M. Prospects and limitations of genomic offset in conservation management. Evol. Appl. 14, 1202–1212 (2021).Article 

Google Scholar 
Bay, R. A. et al. Genomic signals of selection predict climate-driven population declines in a migratory bird. Science 359, 83–86 (2018).Article 
CAS 

Google Scholar 
Rellstab, C. et al. Signatures of local adaptation in candidate genes of oaks (Quercus spp.) with respect to present and future climatic conditions. Mol. Ecol. 25, 5907–5924 (2016).Article 

Google Scholar 
Fitzpatrick, M. C. & Keller, S. R. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. Ecol. Lett. 18, 1–16 (2015).Article 

Google Scholar 
Exposito-Alonso, M. et al. Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana. Nat. Ecol. Evol. 2, 352–358 (2018).Article 

Google Scholar 
Kindt, R. AlleleShift: an R package to predict and visualize population-level changes in allele frequencies in response to climate change. PeerJ 9, e11534 (2021).Article 

Google Scholar 
Gain, C. & François, O. LEA 3: factor models in population genetics and ecological genomics with R. Mol. Ecol. Resour. 21, 2738–2748 (2020).Article 

Google Scholar 
Aguirre-Liguori, J. A., Ramírez-Barahona, S. & Gaut, B. S. The evolutionary genomics of species’ responses to climate change. Nat. Ecol. Evol. 5, 1350–1360 (2021).Article 

Google Scholar 
Taylor, S. A., Larson, E. L. & Harrison, R. G. Hybrid zones: windows on climate change. Trends Ecol. Evol. 30, 398–406 (2015).Article 

Google Scholar 
Hoffmann, A. A. & Sgro, C. M. Climate change and evolutionary adaptation. Nature 470, 479–485 (2011).Article 
CAS 

Google Scholar 
McGuigan, K., Franklin, C. E., Moritz, C. & Blows, M. W. Adaptation of rainbow fish to lake and stream habitats. Evolution 57, 104–118 (2003).
Google Scholar 
Smith, S., Bernatchez, L. & Beheregaray, L. RNA-seq analysis reveals extensive transcriptional plasticity to temperature stress in a freshwater fish species. BMC Genomics 14, 375 (2013).Article 
CAS 

Google Scholar 
Smith, S. et al. Latitudinal variation in climate‐associated genes imperils range edge populations. Mol. Ecol. 29, 4337–4349 (2020).Article 
CAS 

Google Scholar 
Sandoval-Castillo, J. et al. Adaptation of plasticity to projected maximum temperatures and across climatically defined bioregions. Proc. Natl Acad. Sci. USA 117, 17112–17121 (2020).Article 
CAS 

Google Scholar 
Brauer, C., Unmack, P. J., Smith, S., Bernatchez, L. & Beheregaray, L. B. On the roles of landscape heterogeneity and environmental variation in determining population genomic structure in a dendritic system. Mol. Ecol. 27, 3484–3497 (2018).Article 
CAS 

Google Scholar 
Attard, C. R. et al. Fish out of water: genomic insights into persistence of rainbowfish populations in the desert. Evolution 76, 171–183 (2022).Article 

Google Scholar 
Gates, K. et al. Environmental selection, rather than neutral processes, best explain patterns of diversity in a tropical rainforest fish. Preprint at bioRxiv https://doi.org/10.1101/2022.1105.1113.491913 (2022).Article 

Google Scholar 
McCairns, R. J. S., Smith, S., Sasaki, M., Bernatchez, L. & Beheregaray, L. B. The adaptive potential of subtropical rainbowfish in the face of climate change: heritability and heritable plasticity for the expression of candidate genes. Evol. Appl. 9, 531–545 (2016).Article 
CAS 

Google Scholar 
McGuigan, K., Zhu, D., Allen, G. & Moritz, C. Phylogenetic relationships and historical biogeography of melanotaeniid fishes in Australia and New Guinea. Mar. Freshwat. Res. 51, 713–723 (2000).Article 

Google Scholar 
Unmack, P. J. et al. Malanda Gold: the tale of a unique rainbowfish from the Atherton Tablelands, now on the verge of extinction. Fish. Sahul. 30, 1039–1054 (2016).
Google Scholar 
Moritz, C. Strategies to protect biological diversity and the evolutionary processes that sustain it. Syst. Biol. 51, 238–254 (2002).Article 

Google Scholar 
Pope, L., Estoup, A. & Moritz, C. Phylogeography and population structure of an ecotonal marsupial, Bettongia tropica, determined using mtDNA and microsatellites. Mol. Ecol. 9, 2041–2053 (2000).Article 
CAS 

Google Scholar 
Hugall, A., Moritz, C., Moussalli, A. & Stanisic, J. Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875). Proc. Natl Acad. Sci. USA 99, 6112–6117 (2002).Article 
CAS 

Google Scholar 
Moritz, C. et al. Identification and dynamics of a cryptic suture zone in tropical rainforest. Proc. R. Soc. B. 276, 1235–1244 (2009).Article 
CAS 

Google Scholar 
Phillips, B. L., Baird, S. J. & Moritz, C. When vicars meet: a narrow contact zone between morphologically cryptic phylogeographic lineages of the rainforest skink, Carlia rubrigularis. Evolution 58, 1536–1548 (2004).
Google Scholar 
Krosch, M. N., Baker, A. M., Mckie, B. G., Mather, P. B. & Cranston, P. S. Deeply divergent mitochondrial lineages reveal patterns of local endemism in chironomids of the Australian Wet Tropics. Austral Ecol. 34, 317–328 (2009).Article 

Google Scholar 
Williams, S. E., Bolitho, E. E. & Fox, S. Climate change in Australian tropical rainforests: an impending environmental catastrophe. Proc. R. Soc. B. 270, 1887–1892 (2003).Article 

Google Scholar 
Whitehead, P. et al. Temporal development of the Atherton Basalt Province, north Queensland. Aust. J. Earth Sci. 54, 691–709 (2007).Article 
CAS 

Google Scholar 
Moy, K. G., Unmack, P. J., Lintermans, M., Duncan, R. P. & Brown, C. Barriers to hybridisation and their conservation implications for a highly threatened Australian fish species. Ethology 125, 142–152 (2019).Article 

Google Scholar 
Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).Article 
CAS 

Google Scholar 
Buerkle, C. A. Maximum‐likelihood estimation of a hybrid index based on molecular markers. Mol. Ecol. Notes 5, 684–687 (2005).Article 
CAS 

Google Scholar 
Anderson, E. & Thompson, E. A model-based method for identifying species hybrids using multilocus genetic data. Genetics 160, 1217–1229 (2002).Article 
CAS 

Google Scholar 
Dorion, S. & Landry, J. Activation of the mitogen-activated protein kinase pathways by heat shock. Cell Stress Chaperones 7, 200 (2002).Article 
CAS 

Google Scholar 
Blumstein, M. et al. Protocol for projecting allele frequency change under future climate change at adaptive-associated loci. STAR Protoc. 1, 100061 (2020).Article 

Google Scholar 
Gougherty, A. V., Keller, S. R. & Fitzpatrick, M. C. Maladaptation, migration and extirpation fuel climate change risk in a forest tree species. Nat. Clim. Change 11, 166–171 (2021).Article 

Google Scholar 
Blumstein, M. et al. A new perspective on ecological prediction reveals limits to climate adaptation in a temperate tree species. Curr. Biol. 30, 1447–1453. e1444 (2020).Article 
CAS 

Google Scholar 
Razgour, O. et al. Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections. Proc. Natl Acad. Sci. USA 116, 10418–10423 (2019).Article 
CAS 

Google Scholar 
Goicoechea, P. G. et al. Adaptive introgression promotes fast adaptation in oaks marginal populations. Preprint available at bioRxiv https://doi.org/10.1101/731919 (2019).Lavergne, S. & Molofsky, J. Increased genetic variation and evolutionary potential drive the success of an invasive grass. Proc. Natl Acad. Sci. USA 104, 3883–3888 (2007).Article 
CAS 

Google Scholar 
De Carvalho, D. et al. Admixture facilitates adaptation from standing variation in the European aspen (Populus tremula L.), a widespread forest tree. Mol. Ecol. 19, 1638–1650 (2010).Article 

Google Scholar 
De-Kayne, R. et al. Genomic architecture of adaptive radiation and hybridization in Alpine whitefish. Nat. Commun. 13, 4479 (2022).Article 
CAS 

Google Scholar 
Baskett, M. L. & Gomulkiewicz, R. Introgressive hybridization as a mechanism for species rescue. Theor. Ecol. 4, 223–239 (2011).Article 

Google Scholar 
Meier, J. I. et al. The coincidence of ecological opportunity with hybridization explains rapid adaptive radiation in Lake Mweru cichlid fishes. Nat. Commun. 10, 1–11 (2019).Article 
CAS 

Google Scholar 
Svardal, H. et al. Ancestral hybridization facilitated species diversification in the Lake Malawi cichlid fish adaptive radiation. Mol. Biol. Evol. 37, 1100–1113 (2020).Article 
CAS 

Google Scholar 
Racimo, F., Sankararaman, S., Nielsen, R. & Huerta-Sánchez, E. Evidence for archaic adaptive introgression in humans. Nat. Rev. Genet. 16, 359–371 (2015).Article 
CAS 

Google Scholar 
Jeong, C. et al. Admixture facilitates genetic adaptations to high altitude in Tibet. Nat. Commun. 5, 1–7 (2014).Article 

Google Scholar 
Nolte, A. W., Freyhof, J., Stemshorn, K. C. & Tautz, D. An invasive lineage of sculpins, Cottus sp. (Pisces, Teleostei) in the Rhine with new habitat adaptations has originated from hybridization between old phylogeographic groups. Proc. R. Soc. B. 272, 2379–2387 (2005).Article 

Google Scholar 
Fitzpatrick, M. C., Chhatre, V. E., Soolanayakanahally, R. Y. & Keller, S. R. Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests. Mol. Ecol. Resour. 21, 2749–2765 (2021).Article 
CAS 

Google Scholar 
Schneider, C., Cunningham, M. & Moritz, C. Comparative phylogeography and the history of endemic vertebrates in the Wet Tropics rainforests of Australia. Mol. Ecol. 7, 487–498 (1998).Article 

Google Scholar 
Hewitt, G. M. Quaternary phylogeography: the roots of hybrid zones. Genetica 139, 617–638 (2011).Article 

Google Scholar 
Pfennig, K. S., Kelly, A. L. & Pierce, A. A. Hybridization as a facilitator of species range expansion. Proc. R. Soc. B. 283, 20161329 (2016).Article 

Google Scholar 
Soulé, M. E. What is conservation biology? A new synthetic discipline addresses the dynamics and problems of perturbed species, communities, and ecosystems. Bioscience 35, 727–734 (1985).
Google Scholar 
Biermann, C. & Havlick, D. Genetics and the question of purity in cutthroat trout restoration. Restor. Ecol. 29, e13516 (2021).Article 

Google Scholar 
Fredrickson, R. J. & Hedrick, P. W. Dynamics of hybridization and introgression in red wolves and coyotes. Conserv. Biol. 20, 1272–1283 (2006).Article 

Google Scholar 
Hirashiki, C., Kareiva, P. & Marvier, M. Concern over hybridization risks should not preclude conservation interventions. Conserv. Sci. Pract. 3, e424 (2021).
Google Scholar 
Unmack, P. J., Allen, G. R. & Johnson, J. B. Phylogeny and biogeography of rainbowfishes (Melanotaeniidae) from Australia and New Guinea. Mol. Phylogenet. Evol. 67, 15–27 (2013).Article 

Google Scholar 
Allen, G. Rainbowfishes in Nature and the Aquarium (Tetra Publications, 1995).Seehausen, O. Hybridization and adaptive radiation. Trends Ecol. Evol. 19, 198–207 (2004).Article 

Google Scholar 
Pusey, B., Kennard, M. J. & Arthington, A. H. Freshwater Fishes of North-eastern Australia (CSIRO Publishing, 2004).Zhu, D., Degnan, S. & Moritz, C. Evolutionary distinctiveness and status of the endangered Lake Eacham rainbowfish (Melanotaenia eachamensis). Conserv. Biol. 12, 80–93 (1998).Article 

Google Scholar 
McGuigan, K., Chenoweth, S. F. & Blows, M. W. Phenotypic divergence along lines of genetic variance. Am. Nat. 165, 32–43 (2005).Article 

Google Scholar 
Sunnucks, P. & Hales, D. F. Numerous transposed sequences of mitochondrial cytochrome oxidase I-II in aphids of the genus Sitobion (Hemiptera: Aphididae). Mol. Biol. Evol. 13, 510–524 (1996).Article 
CAS 

Google Scholar 
Peterson, B., Weber, J., Kay, E., Fisher, H. & Hoekstra, H. Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS ONE 7, e37135 (2012).Article 
CAS 

Google Scholar 
Catchen, J. M., Amores, A., Hohenlohe, P., Cresko, W. & Postlethwait, J. H. Stacks: building and genotyping loci de novo from short-read sequences. G3: Genes Genomes Genet. 1, 171–182 (2011).Article 
CAS 

Google Scholar 
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).Article 
CAS 

Google Scholar 
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357 (2012).Article 
CAS 

Google Scholar 
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).Article 
CAS 

Google Scholar 
Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).Article 

Google Scholar 
Goudet, J. Hierfstat, a package for R to compute and test hierarchical F‐statistics. Mol. Ecol. Notes 5, 184–186 (2005).Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).Bailey, R. ribailey/gghybrid: gghybrid R package for Bayesian hybrid index and genomic cline estimation. v2.0.0 https://doi.org/10.5281/zenodo.3676498 (2020).Wringe, B. hybriddetective: automates the process of detecting hybrids from genetic data. R package version 0.1.0.9000 https://github.com/bwringe/hybriddetective (2016).Pickrell, J. K. & Pritchard, J. K. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012).Article 
CAS 

Google Scholar 
Malinsky, M., Matschiner, M. & Svardal, H. Dsuite‐Fast D‐statistics and related admixture evidence from VCF files. Mol. Ecol. Resour. 21, 584–595 (2021).Article 

Google Scholar 
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).Article 
CAS 

Google Scholar 
Green, R. E. et al. A draft sequence of the Neandertal genome. Science 328, 710–722 (2010).Article 
CAS 

Google Scholar 
Durand, E. Y., Patterson, N., Reich, D. & Slatkin, M. Testing for ancient admixture between closely related populations. Mol. Biol. Evol. 28, 2239–2252 (2011).Article 
CAS 

Google Scholar 
Malinsky, M. et al. Genomic islands of speciation separate cichlid ecomorphs in an East African crater lake. Science 350, 1493–1498 (2015).Article 
CAS 

Google Scholar 
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).Article 
CAS 

Google Scholar 
Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4, 1–20 (2017).Article 

Google Scholar 
Karger, D. N. et al. CHELSA climatologies at high resolution for the Earth’s land surface areas (v.1.0). https://doi.org/10.1594/WDCC/CHELSA_v1 (2016).Ackerley, D. & Dommenget, D. Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface temperatures. Geosci. Model Dev. 9, 2077–2098 (2016).Article 

Google Scholar 
Brown, J. L., Hill, D. J., Dolan, A. M., Carnaval, A. C. & Haywood, A. M. PaleoClim: high spatial resolution paleoclimate surfaces for global land areas. Sci. Data 5, 1–9 (2018).Article 

Google Scholar 
Fordham, D. A. et al. PaleoView: a tool for generating continuous climate projections spanning the last 21,000 years at regional and global scales. Ecography 40, 1348–1358 (2017).Article 

Google Scholar 
Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M. B. BIOMOD–a platform for ensemble forecasting of species distributions. Ecography 32, 369–373 (2009).Article 

Google Scholar 
Lemus-Canovas, M., Lopez-Bustins, J. A., Martin-Vide, J. & Royé, D. synoptReg: an R package for computing a synoptic climate classification and a spatial regionalization of environmental data. Environ. Model. Softw. 118, 114–119 (2019).Article 

Google Scholar 
Hao, T., Elith, J., Guillera‐Arroita, G. & Lahoz‐Monfort, J. J. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Divers. Distrib. 25, 839–852 (2019).Article 

Google Scholar 
Galpern, P., Peres‐Neto, P. R., Polfus, J. & Manseau, M. MEMGENE: spatial pattern detection in genetic distance data. Methods Ecol. Evol. 5, 1116–1120 (2014).Article 

Google Scholar 
Peres‐Neto, P. R. & Galpern, P. memgene: spatial pattern detection in genetic distance data using Moran’s eigenvector maps. R package version 1.0.1 https://cran.r-project.org/web/packages/memgene/ (2019).Oksanen, J. et al. vegan: community ecology package. R package version 2.3–0 https://cran.r-project.org/web/packages/vegan/ (2015).Forester, B. R., Jones, M. R., Joost, S., Landguth, E. L. & Lasky, J. R. Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes. Mol. Ecol. 25, 104–120 (2015).Article 

Google Scholar 
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012).Article 
CAS 

Google Scholar 
Szklarczyk, D. et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 49, D605–D612 (2021).Article 
CAS 

Google Scholar 
Brauer, C. J. et al. Data for ‘Natural hybridisation reduces vulnerability to climate change’. figshare https://doi.org/10.6084/m9.figshare.21692918 (2022).Brauer, C. J. et al. Code for ‘Natural hybridisation reduces vulnerability to climate change’. GitHub https://github.com/pygmyperch/NER (2022). More

Davis, K. F., Downs, S. & Gephart, J. A. Towards food supply chain resilience to environmental shocks. Nat. Food 2, 54–65 (2021).Article 

Google Scholar 
Lempert, R. J. & Collins, M. T. Managing the risk of uncertain threshold responses: comparison of robust, optimum, and precautionary approaches. Risk Anal. 27, 1009–1026 (2007).Article 

Google Scholar 
Garnett, P., Doherty, B. & Heron, T. Vulnerability of the United Kingdom’s food supply chains exposed by COVID-19. Nat. Food 1, 315–318 (2020).Article 
CAS 

Google Scholar 
Abson, D. J. et al. Leverage points for sustainability transformation. Ambio 46, 30–39 (2017).Article 

Google Scholar 
Westley, F. et al. Tipping toward sustainability: emerging pathways of transformation. Ambio 40, 762–780 (2011).Article 

Google Scholar 
Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O. & Ludwig, C. The trajectory of the Anthropocene: the Great Acceleration. Anthr. Rev. 2, 81–98 (2015).
Google Scholar 
Jouffray, J.-B., Blasiak, R., Norström, A. V., Österblom, H. & Nyström, M. The blue acceleration: the trajectory of human expansion into the ocean. One Earth 2, 43–54 (2020).Article 

Google Scholar 
Adger, W. N., Eakin, H. & Winkels, A. Nested and teleconnected vulnerabilities to environmental change. Front. Ecol. Environ. 7, 150–157 (2009).Article 

Google Scholar 
Nyström, M. et al. Anatomy and resilience of the global production ecosystem. Nature 575, 98–108 (2019).Article 

Google Scholar 
Mason, W. & Watts, D. J. Collaborative learning in networks. Proc. Natl Acad. Sci. USA 109, 764–769 (2012).Article 
CAS 

Google Scholar 
Helbing, D. Globally networked risks and how to respond. Nature 497, 51–59 (2013).Article 
CAS 

Google Scholar 
Worm, B. & Paine, R. T. Humans as a hyperkeystone species. Trends Ecol. Evol. 31, 600–607 (2016).Article 

Google Scholar 
Crutzen, P. J. & Stoermer, E. F. in The Future of Nature (eds Robin, L. et al.) 479–490 (Yale Univ. Press, 2017); https://doi.org/10.12987/9780300188479-041Ellis, E. C. Anthropogenic transformation of the terrestrial biosphere. Phil. Trans. R. Soc. A 369, 1010–1035 (2011).Article 

Google Scholar 
Senevirante, S. I. et al. in Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) 1513–1766 (IPCC, Cambridge Univ. Press, 2021).Frank, A. B. et al. Dealing with femtorisks in international relations. Proc. Natl Acad. Sci. USA 111, 17356–17362 (2014).Article 
CAS 

Google Scholar 
Folke, C. et al. Our future in the Anthropocene biosphere. Ambio 50, 834–869 (2021).Article 

Google Scholar 
Walker, B. & Salt, D. Resilience Practice: Building Capacity to Absorb Disturbance and Maintain Function (Island Press/Center for Resource Economics, 2012); https://doi.org/10.5822/978-1-61091-231-0Biggs, R., Schlüter, M. & Schoon, M. L. (eds) Principles for Building Resilience: Sustaining Ecosystem Services in Social–Ecological Systems (Cambridge Univ. Press, 2015); https://doi.org/10.1017/CBO9781316014240Cervantes Saavedra, M. de & Rutherford, J. Don Quixote: The Ingenious Hidalgo de la Mancha (Penguin, 2003).Coronese, M., Lamperti, F., Keller, K., Chiaromonte, F. & Roventini, A. Evidence for sharp increase in the economic damages of extreme natural disasters. Proc. Natl Acad. Sci. USA 116, 21450–21455 (2019).Article 
CAS 

Google Scholar 
Cottrell, R. S. et al. Food production shocks across land and sea. Nat. Sustain. 2, 130–137 (2019).Article 

Google Scholar 
Elmqvist, T. et al. Response diversity, ecosystem change, and resilience. Front. Ecol. Environ. 1, 488–494 (2003).Article 

Google Scholar 
Arrow, K. J. & Fisher, A. C. Environmental preservation, uncertainty, and irreversibility. Q. J. Econ. 88, 312–319 (1974).Article 

Google Scholar 
Dixit, A. K. & Pindyck, R. S. Investment under Uncertainty (Princeton Univ. Press, 1994).Markowitz, H. Portfolio selection. J. Finance 7, 77–91 (1952).
Google Scholar 
Sharpe, W. F. Capital asset prices: a theory of market equilibrium under conditions of risk. J. Finance 19, 425–442 (1964).
Google Scholar 
Cifdaloz, O., Regmi, A., Anderies, J. M. & Rodriguez, A. A. Robustness, vulnerability, and adaptive capacity in small-scale social–ecological systems: the Pumpa Irrigation System in Nepal. Ecol. Soc. 15, art39 (2010).Article 

Google Scholar 
Levin, S. A. et al. Governance in the face of extreme events: lessons from evolutionary processes for structuring interventions, and the need to go beyond. Ecosystems 25, 697–711 (2022).Article 

Google Scholar 
Peterson, G., Allen, C. R. & Holling, C. S. Ecological resilience, biodiversity, and scale. Ecosystems 1, 6–18 (1998).Article 

Google Scholar 
Nyström, M. Redundancy and response diversity of functional groups: implications for the resilience of coral reefs. Ambio 35, 30–35 (2006).Article 

Google Scholar 
Kummu, M. et al. Interplay of trade and food system resilience: gains on supply diversity over time at the cost of trade independency. Glob. Food Secur. 24, 100360 (2020).Article 

Google Scholar 
Hedblom, M., Andersson, E. & Borgström, S. Flexible land-use and undefined governance: from threats to potentials in peri-urban landscape planning. Land Use Policy 63, 523–527 (2017).Article 

Google Scholar 
Haldane, A. Rethinking the Financial Network—Speech by Andy Haldane (Bank of England, 2009); https://www.bankofengland.co.uk/speech/2009/rethinking-the-financial-networkHaldane, A. G. & May, R. M. Systemic risk in banking ecosystems. Nature 469, 351–355 (2011).Article 
CAS 

Google Scholar 
Carpenter, S. R., Brock, W. A., Folke, C., van Nes, E. H. & Scheffer, M. Allowing variance may enlarge the safe operating space for exploited ecosystems. Proc. Natl Acad. Sci. USA 112, 14384–14389 (2015).Article 
CAS 

Google Scholar 
Mouillot, D., Graham, N. A. J., Villéger, S., Mason, N. W. H. & Bellwood, D. R. A functional approach reveals community responses to disturbances. Trends Ecol. Evol. 28, 167–177 (2013).Article 

Google Scholar 
Leslie, P. & McCabe, J. T. Response diversity and resilience in social–ecological systems. Curr. Anthropol. 54, 114–143 (2013).Article 

Google Scholar 
Biggs, R. et al. Toward principles for enhancing the resilience of ecosystem services. Annu. Rev. Environ. Resour. 37, 421–448 (2012).Article 

Google Scholar 
Anderies, J. M. Managing variance: key policy challenges for the Anthropocene. Proc. Natl Acad. Sci. USA 112, 14402–14403 (2015).Article 
CAS 

Google Scholar 
Csete, M. E. & Doyle, J. C. Reverse engineering of biological complexity. Science 295, 1664–1669 (2002).Article 
CAS 

Google Scholar 
Carlson, J. M. & Doyle, J. Highly optimized tolerance: robustness and design in complex systems. Phys. Rev. Lett. 84, 2529–2532 (2000).Article 
CAS 

Google Scholar 
Kitano, H. Biological robustness. Nat. Rev. Genet. 5, 826–837 (2004).Article 
CAS 

Google Scholar 
Csete, M. & Doyle, J. Bow ties, metabolism and disease. Trends Biotechnol. 22, 446–450 (2004).Article 
CAS 

Google Scholar 
Anderies, J. M., Rodriguez, A. A., Janssen, M. A. & Cifdaloz, O. Panaceas, uncertainty, and the robust control framework in sustainability science. Proc. Natl Acad. Sci. USA 104, 15194–15199 (2007).Article 
CAS 

Google Scholar 
Rodriguez, A. A., Cifdaloz, O., Anderies, J. M., Janssen, M. A. & Dickeson, J. Confronting management challenges in highly uncertain natural resource systems: a robustness–vulnerability trade-off approach. Environ. Model. Assess. 16, 15–36 (2011).Article 

Google Scholar 
Charpentier, A. Insurability of climate risks. Geneva Pap. Risk Insur. Issues Pract. 33, 91–109 (2008).Article 

Google Scholar 
Alfieri, L., Feyen, L. & Di Baldassarre, G. Increasing flood risk under climate change: a pan-European assessment of the benefits of four adaptation strategies. Climatic Change 136, 507–521 (2016).Article 

Google Scholar 
Isakson, S. R. Derivatives for development? Small-farmer vulnerability and the financialization of climate risk management: small-farmer vulnerability and financialization. J. Agrar. Change 15, 569–580 (2015).Article 

Google Scholar 
Müller, B. & Kreuer, D. Ecologists should care about insurance, too. Trends Ecol. Evol. 31, 1–2 (2016).Article 

Google Scholar 
Walker, B. et al. Looming global-scale failures and missing institutions. Science 325, 1345–1346 (2009).Article 
CAS 

Google Scholar 
Berkes, F. et al. Globalization, roving bandits, and marine resources. Science 311, 1557–1558 (2006).Article 
CAS 

Google Scholar 
Walker, B. H., Langridge, J. L. & McFarlane, F. Resilience of an Australian savanna grassland to selective and non-selective perturbations. Austral Ecol. 22, 125–135 (1997).Article 

Google Scholar 
Polasky, S. et al. Corridors of clarity: four principles to overcome uncertainty paralysis in the Anthropocene. BioScience 70, 1139–1144 (2020).Article 

Google Scholar 
Engström, G. et al. Carbon pricing and planetary boundaries. Nat. Commun. 11, 4688 (2020).Article 

Google Scholar 
Sun, J. C., Ugolini, S. & Vivier, E. Immunological memory within the innate immune system. EMBO J. https://doi.org/10.1002/embj.201387651 (2014).Vély, F. et al. Evidence of innate lymphoid cell redundancy in humans. Nat. Immunol. 17, 1291–1299 (2016).Article 

Google Scholar 
Grimm, N., Cook, E., Hale, R. & Iwaniec, D. in The Routledge Handbook of Urbanization and Global Environmental Change (eds Seto, K. et al.) Ch. 14 (Routledge, 2015).Jiang, B., Mak, C. N. S., Zhong, H., Larsen, L. & Webster, C. J. From broken windows to perceived routine activities: examining impacts of environmental interventions on perceived safety of urban alleys. Front. Psychol. 9, 2450 (2018).Article 

Google Scholar 
Andersson, E. et al. Urban climate resilience through hybrid infrastructure. Curr. Opin. Environ. Sustain. 55, 101158 (2022).Article 

Google Scholar 
Douglas, M. & Wildavsky, A. Risk and Culture: An Essay on the Selection of Technological and Environmental Dangers (Univ. of California Press, 1983).Weber, E. U., Ames, D. R. & Blais, A.-R. ‘How do I choose thee? Let me count the ways’: a textual analysis of similarities and differences in modes of decision-making in China and the United States. Manage. Organ. Rev. 1, 87–118 (2005).Article 

Google Scholar 
Kunreuther, H. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) Ch. 2 (IPCC, Cambridge Univ. Press, 2014); https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_chapter2.pdfMeadows, D. H. Thinking in Systems: A Primer (Earthscan, 2009).Nyborg, K. et al. Social norms as solutions. Science 354, 42–43 (2016).Article 
CAS 

Google Scholar 
Hall, P. A. & Lamont, M. (eds) Social Resilience in the Neoliberal Era (Cambridge Univ. Press, 2013).Norström, A. V. et al. Principles for knowledge co-production in sustainability research. Nat. Sustain. 3, 182–190 (2020).Article 

Google Scholar 
United Nations Conference on Trade and Development Review of Maritime Transport 2017 (United Nations, 2017).United Nations Conference on Trade and Development Review of Maritime Transport 2018 (United Nations, 2019).Bailey, R. & Wellesley, L. Chatham House Report 2017: Chokepoints and Vulnerabilities in Global Food Trade (Energy, Environment and Resources Department, Chatham House, The Royal Institute of International Affairs, 2017); https://www.chathamhouse.org/sites/default/files/publications/research/2017-06-27-chokepoints-vulnerabilities-global-food-trade-bailey-wellesley-final.pdfKhoury, C. K. et al. Increasing homogeneity in global food supplies and the implications for food security. Proc. Natl Acad. Sci. USA 111, 4001–4006 (2014).Article 
CAS 

Google Scholar 
Hendrickson, M. K. Resilience in a concentrated and consolidated food system. J. Environ. Stud. Sci. 5, 418–431 (2015).Article 

Google Scholar 
Öborn, I. et al. Restoring rangelands for nutrition and health for humans and livestock. in The XXIV International Grassland Congress / XI International Rangeland Congress (Sustainable Use of Grassland and Rangeland Resources for Improved Livelihoods) (ed. National Organizing Committee of 2021 IGC/IRC Congress) (Kenya Agricultural and Livestock Research Organization, 2022).Vulnerable Supply Chains—Interim Report (Productivity Commission, Australian Government, 2021); https://www.pc.gov.au/inquiries/completed/supply-chains/interim More