Philippa Kaur

Banks, N. C., Paini, D. R., Bayliss, K. L. & Hodda, M. The role of global trade and transport network topology in the human-mediated dispersal of alien species. Ecol. Lett. 18, 188–199 (2015).
Google Scholar 
Epanchin-Niell, R. et al. Controlling invasive species in complex social landscapes. Front. Ecol. Environ. 8, 210–216 (2009).
Google Scholar 
Charles, H. & Dukes, J. S. in Biological Invasions (ed. Nentwig, W.) 217–237 (Springer, 2007). https://doi.org/10.1007/978-3-540-36920-2_13Gallardo, B., Clavero, M., Sánchez, M. & Vilà, M. Global ecological impacts of invasive species in aquatic ecosystems. Glob. Change Biol. 22, 151–163 (2016).
Google Scholar 
Diagne, C. et al. High and rising economic costs of biological invasions worldwide. Nature 592, 571–576 (2021).CAS 

Google Scholar 
Sardain, A., Sardain, E. & Leung, B. Global forecasts of shipping traffic and biological invasions to 2050. Nat. Sustain. 2, 274–282 (2019).
Google Scholar 
Epanchin-Niell, R. S. & Hastings, A. Controlling established invaders: integrating economics and spread dynamics to determine optimal management. Ecol. Lett. 13, 528–541 (2010).
Google Scholar 
Chades, I. et al. General rules for managing and surveying networks of pests, diseases, and endangered species. Proc. Natl. Acad. Sci. USA 108, 8323–8328 (2011).CAS 

Google Scholar 
Epanchin-Niell, R. S. & Wilen, J. E. Optimal spatial control of biological invasions. J. Environ. Econ. Manag. 63, 260–270 (2012).
Google Scholar 
Epanchin-Niell, R. S. & Wilen, J. E. Individual and cooperative management of invasive species in human-mediated landscapes. Am. J. Agric. Econ. 97, 180–198 (2015).
Google Scholar 
Aadland, D., Sims, C. & Finnoff, D. Spatial dynamics of optimal management in bioeconomic systems. Comput. Econ. 45, 545–577 (2015).
Google Scholar 
Baker, C. M. Target the source: optimal spatiotemporal resource allocation for invasive species control. Conserv. Lett. 10, 41–48 (2017).
Google Scholar 
Bushaj, S., Büyüktahtakın, İ. E., Yemshanov, D. & Haight, R. G. Optimizing surveillance and management of emerald ash borer in urban environments. Nat. Res. Model. 34, e12267 (2021).
Google Scholar 
Fischer, S. M., Beck, M., Herborg, L.-M. & Lewis, M. A. Managing aquatic invasions: optimal locations and operating times for watercraft inspection stations. J. Environ. Manag. 283, 111923 (2021).
Google Scholar 
Büyüktahtakın, İ. E. & Haight, R. G. A review of operations research models in invasive species management: state of the art, challenges, and future directions. Ann. Oper. Res. 271, 357–403 (2018).
Google Scholar 
Epanchin-Niell, R. S. Economics of invasive species policy and management. Biol. Invasions 19, 3333–3354 (2017).
Google Scholar 
Bodin, Ö. et al. Improving network approaches to the study of complex social–ecological interdependencies. Nat. Sustain. 2, 551–559 (2019).CAS 

Google Scholar 
Nowzari, C., Precaido, V. M. & Pappas, G. J. Analysis and control of epidemics: a survey of spreading processes on complex networks. IEEE Control Syst. 36, 26–46 (2016).
Google Scholar 
Newman, M. E. J. Spread of epidemic disease on networks. Phys. Rev. E 66, 016128 (2002).CAS 

Google Scholar 
Kempe, D., Kleinberg, J. & Tardos, E. Maximizing the spread of influence through a social network. In Proc. 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 137–146 (ACM Press, 2003).Pastor-Satorras, R. & Vespignani, A. Immunization of complex networks. Phys. Rev. E 65, 036104 (2002).
Google Scholar 
Pastor-Satorras, R., Castellano, C., Van Mieghem, P. & Vespignani, A. Epidemic processes in complex networks. Rev. Mod. Phys. 87, 925–979 (2015).
Google Scholar 
Holme, P., Kim, B. J., Yoon, C. N. & Han, S. K. Attack vulnerability of complex networks. Phys. Rev. E 65, 056109 (2002).
Google Scholar 
Muirhead, J. R. & Macisaac, H. J. Development of inland lakes as hubs in an invasion network. J. Appl. Ecol. 42, 80–90 (2005).
Google Scholar 
de la Fuente, B., Saura, S. & Beck, P. S. Predicting the spread of an invasive tree pest: the pine wood nematode in southern europe. J. Appl. Ecol. 55, 2374–2385 (2018).
Google Scholar 
Minor, E. S. & Urban, D. L. A graph-theory framework for evaluating landscape connectivity and conservation planning. Conserv. Biol. 22, 297–307 (2008).
Google Scholar 
Morel-Journel, T., Assa, C. R., Mailleret, L. & Vercken, E. Its all about connections: hubs and invasion in habitat networks. Ecol. Lett. 22, 313–321 (2019).
Google Scholar 
Perry, G. L. W., Moloney, K. A. & Etherington, T. R. Using network connectivity to prioritise sites for the control of invasive species. J. Appl. Ecol. 54, 1238–1250 (2017).
Google Scholar 
Kvistad, J. T., Chadderton, W. L. & Bossenbroek, J. M. Network centrality as a potential method for prioritizing ports for aquatic invasive species surveillance and response in the Laurentian Great Lakes. Manag. Biol. Invasions 10, 403 (2019).
Google Scholar 
Haight, R. G., Kinsley, A. C., Kao, S.-Y., Yemshanov, D. & Phelps, N. B. Optimizing the location of watercraft inspection stations to slow the spread of aquatic invasive species. Biol. Invasions 23, 3907–3919 (2021).
Google Scholar 
McEachran, M. C. et al. Stable isotopes indicate that zebra mussels (Dreissena polymorpha) increase dependence of lake food webs on littoral energy sources. Freshw, Biol. 64, 183–196 (2019).CAS 

Google Scholar 
Karatayev, A. Y., Burlakova, L. E. & Padilla, D. K. in Invasive Aquatic Species of Europe. Distribution, Impacts and Management (eds Leppäkoski, E. et al.) 433–446 (Springer, 2002).Prescott, T. H., Claudi, R. & Prescott, K. L. Impact of Dreissenid mussels on the infrastructure of dams and hydroelectric power plants. In Quagga and Zebra Mussels (eds Nalepa, T. F. & Schloesser, D. W.) 243–258 (CRC Press, 2013).Invasive Species of Aquatic Plants and Wild Animals in Minnesota: Annual Report for 2020 (Minnesota Department of Natural Resources, 2020).Kanankege, K. S., Alkhamis, M. A., Phelps, N. B. & Perez, A. M. A probability co-kriging model to account for reporting bias and recognize areas at high risk for zebra mussels and eurasian watermilfoil invasions in Minnesota. Front. Vet. Sci. 4, 231 (2018).
Google Scholar 
Mallez, S. & McCartney, M. Dispersal mechanisms for zebra mussels: population genetics supports clustered invasions over spread from hub lakes in Minnesota. Biol. Invasions 20, 2461–2484 (2018).
Google Scholar 
Kao, S.-Y. Z. et al. Network connectivity of Minnesota waterbodies and implications for aquatic invasive species prevention. Biol. Invasions 23, 3231–3242 (2021).
Google Scholar 
Kleinberg, J. M. Authoritative sources in a hyperlinked environment. In Proc. 9th Annual ACM-SIAM Symposium on Discrete Algorithms 668–677 (1998).McDonald-Madden, E. et al. Using food-web theory to conserve ecosystems. Nat. Commun. 7, 10245 (2016).CAS 

Google Scholar 
Bossenbroek, J. M., Kraft, C. E. & Nekola, J. C. Prediction of long-distance dispersal using gravity models: zebra mussel invasion of inland lakes. Ecol. Appl. 11, 1778–1788 (2001).
Google Scholar 
Leung, B., Bossenbroek, J. M. & Lodge, D. M. Boats, pathways, and aquatic biological invasions: estimating dispersal potential with gravity models. Biol. Invasions 8, 241–254 (2006).
Google Scholar 
Beger, M. et al. Integrating regional conservation priorities for multiple objectives into national policy. Nat. Commun. 6, 8208 (2015).Runting, R. K. et al. Larger gains from improved management over sparing–sharing for tropical forests. Nat. Sustain. 2, 53–61 (2019).
Google Scholar 
Kinsley, A. C. et al. AIS Explorer: prioritization for watercraft inspections. A decision-support tool for aquatic invasive species management. J. Environ. Manage. 314, 115037 (2022).
Google Scholar 
Vander Zanden, M. J. & Olden, J. D. A management framework for preventing the secondary spread of aquatic invasive species. Can. J. Fish. Aquat. Sci. 65, 1512–1522 (2008).
Google Scholar 
Kanankege, K. S. et al. Lessons learned from the stakeholder engagement in research: application of spatial analytical tools in one health problems. Front. Vet. Sci. 7, 254 (2020).
Google Scholar 
Kroetz, K. & Sanchirico, J. The bioeconomics of spatial-dynamic systems in natural resource management. Annu. Rev. Resour. Econ. 7, 189–207 (2015).
Google Scholar 
Cade, B. S. & Noon, B. R. A gentle introduction to quantile regression for ecologists. Front. Ecol. Environ. 1, 412–420 (2003).
Google Scholar 
Koenker, R. in Asymptotic Statistics (eds Mandl, P. & Hušková, M.) 349–359 (Springer, 1994).Ashander, J. Analysis code and data for ‘Guiding large-scale management of invasive species using network metrics’. figshare https://doi.org/10.6084/m9.figshare.14402447 (2021). More

Losey, J. E. & Vaughan, M. The economic value of ecological services provided by insects. Bioscience 56, 311–323 (2006).Article 

Google Scholar 
Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809 (2017).PubMed 
PubMed Central 
Article 
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 
PubMed 
Article 

Google Scholar 
Powney, G. D. et al. Widespread losses of pollinating insects in Britain. Nat. Commun. 10, 1–6 (2019).ADS 
CAS 
Article 

Google Scholar 
Foley, J. A. et al. Global consequences of land use. Science 309, 570–574 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Seto, K. C., Güneralp, B. & Hutyra, L. R. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc. Natl. Acad. Sci. 109, 16083–16088 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Johnson, M. T. J. & Munshi-South, J. Evolution of life in urban environments. Science 358, eaam8327 (2017).PubMed 
Article 
CAS 

Google Scholar 
Petersen, H. & Luxton, M. A comparative analysis of soil fauna populations and their role in decomposition processes. Oikos 39, 288–388 (1982).Article 

Google Scholar 
Frizzo, T. L., Souza, L. M., Sujii, E. R. & Togni, P. H. Ants provide biological control on tropical organic farms influenced by local and landscape factors. Biol. Control 151, 104378 (2020).CAS 
Article 

Google Scholar 
Elizalde, L. et al. The ecosystem services provided by social insects: Traits, management tools and knowledge gaps. Biol. Rev. 95, 1418–1441 (2020).PubMed 
Article 

Google Scholar 
Zhong, Z. et al. Soil engineering by ants facilitates plant compensation for large herbivore removal of aboveground biomass. Ecology 102, e03312 (2021).PubMed 
Article 

Google Scholar 
Ortiz, D. P., Elizalde, L. & Pirk, G. I. Role of ants as dispersers of native and exotic seeds in an understudied dryland. Ecol. Entomol. 46, 626–636 (2021).Article 

Google Scholar 
Li, X. et al. A facilitation between large herbivores and ants accelerates litter decomposition by modifying soil microenvironmental conditions. Funct. Ecol. 35, 1822–1832 (2021).Article 

Google Scholar 
Wendt, C. F. et al. Local environmental variables are key drivers of ant taxonomic and functional beta-diversity in a Mediterranean dryland. Sci. Rep. 11, 1–10 (2021).ADS 
Article 
CAS 

Google Scholar 
Lach, L. Invasive ant establishment, spread, and management with changing climate. Curr. Opin. Insect Sci. 47, 119–124 (2021).PubMed 
Article 

Google Scholar 
Buczkowski, G. & Richmond, D. S. The effect of urbanization on ant abundance and diversity: A temporal examination of factors affecting biodiversity. PLoS ONE 7, e41729 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Holway, D. A. & Suarez, A. V. Homogenization of ant communities in mediterranean California: The effects of urbanization and invasion. Biol. Conserv. 127, 319–326 (2006).Article 

Google Scholar 
Miguelena, J. G. & Baker, P. B. Effects of urbanization on the diversity, abundance, and composition of ant assemblages in an arid city. Environ. Entomol. 48, 836–846 (2019).PubMed 
Article 

Google Scholar 
Nielsen, A. B., van den Bosch, M., Maruthaveeran, S. & van den Bosch, C. K. Species richness in urban parks and its drivers: A review of empirical evidence. Urban Ecosyst. 17, 305–327 (2014).Article 

Google Scholar 
Clarke, K. M., Fisher, B. L. & LeBuhn, G. The influence of urban park characteristics on ant (Hymenoptera, Formicidae) communities. Urban Ecosyst. 11, 317–334 (2008).Article 

Google Scholar 
Peng, M.-H., Hung, Y.-C., Liu, K.-L. & Neoh, K.-B. Landscape configuration and habitat complexity shape arthropod assemblage in urban parks. Sci. Rep. 10, 16043 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Santos, M. N., Delabie, J. H. & Queiroz, J. M. Biodiversity conservation in urban parks: A study of ground-dwelling ants (Hymenoptera: Formicidae) in Rio de Janeiro City. Urban Ecosyst. 22, 927–942 (2019).Article 

Google Scholar 
McKinney, M. L. Effects of urbanization on species richness: A review of plants and animals. Urban Ecosyst. 11, 161–176 (2008).Article 

Google Scholar 
Lahr, E. C., Dunn, R. R. & Frank, S. D. Getting ahead of the curve: Cities as surrogates for global change. Proc. R. Soc. B Biol. Sci. 285, 20180643 (2018).Article 
CAS 

Google Scholar 
Abdel-Dayem, M. S. et al. Ant diversity and composition patterns along the urbanization gradients in an arid city. J. Nat. Hist. 55, 2521–2547 (2021).Article 

Google Scholar 
Nooten, S. S., Lee, R. H. & Guénard, B. Evaluating the conservation value of sacred forests for ant taxonomic, functional and phylogenetic diversity in highly degraded landscapes. Biol. Conserv. 261, 109286 (2021).Article 

Google Scholar 
Bhagwat, S. A. & Rutte, C. Sacred groves: Potential for biodiversity management. Front. Ecol. Environ. 4, 519–524 (2006).Article 

Google Scholar 
Ballullaya, U. P. et al. Stakeholder motivation for the conservation of sacred groves in south India: An analysis of environmental perceptions of rural and urban neighbourhood communities. Land Use Policy 89, 104213 (2019).Article 

Google Scholar 
Lowman, M. D. & Sinu, P. A. Can the spiritual values of forests inspire effective conservation?. Bioscience 67, 688–690 (2017).Article 

Google Scholar 
Rajesh, T. P., Ballullaya, U. P., Unni, A. P., Parvathy, S. & Sinu, P. A. Interactive effects of urbanization and year on invasive and native ant diversity of sacred groves of South India. Urban Ecosyst. 23, 1335–1348 (2020).Article 

Google Scholar 
Rajesh, T. P., Unni, A. P., Ballullaya, U. P., Manoj, K. & Sinu, P. A. An insight into the quality of sacred groves–an island habitat–using leaf-litter ants as an indicator in a context of urbanization. J. Trop. Ecol. 37, 82–90 (2021).Article 

Google Scholar 
Holway, D. A., Lach, L., Suarez, A. V., Tsutsui, N. D. & Case, T. J. The causes and consequences of ant invasions. Annu. Rev. Ecol. Syst. 33, 181–233 (2002).Article 

Google Scholar 
Plowes, R. M., Dunn, J. G. & Gilbert, L. E. The urban fire ant paradox: Native fire ants persist in an urban refuge while invasive fire ants dominate natural habitats. Biol. Invasions 9, 825–836 (2007).Article 

Google Scholar 
Rajesh, T. P., Ballullaya, U. P., Surendran, P. & Sinu, P. A. Ants indicate urbanization pressure in sacred groves of southwest India: A pilot study. Curr. Sci. 113, 317–322 (2017).Article 

Google Scholar 
Wetterer, J. K. Worldwide distribution and potential spread of the long-legged ant, Anoplolepis gracilipes (Hymenoptera: Formicidae). Sociobiology 45, 77–97 (2005).
Google Scholar 
Bhagwat, S. A., Kushalappa, C. G., Williams, P. H. & Brown, N. D. A landscape approach to biodiversity conservation of sacred groves in the Western Ghats of India. Conserv. Biol. 19, 1853–1862 (2005).Article 

Google Scholar 
Chandrashekara, U. M. & Sankar, S. Ecology and management of sacred groves in Kerala, India. For. Ecol. Manag. 112, 165–177 (1998).Article 

Google Scholar 
Asha, G., Navya, K. K., Rajesh, T. P. & Sinu, P. A. Roller dung beetles of dung piles suggest habitats are alike, but that of guarding pitfall traps suggest habitats are different. J. Trop. Ecol. 37, 209–213 (2021).Article 

Google Scholar 
Manoj, K. et al. Diversity of Platygastridae in leaf litter and understory layers of tropical rainforests of the Western Ghats Biodiversity Hotspot, India. Environ. Entomol. 46, 685–692 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Hariraveendra, M., Rajesh, T. P., Unni, A. P. & Sinu, P. A. Prey–predator interaction suggests sacred groves are not functionally different from neighbouring used lands. J. Trop. Ecol. 36, 220–224 (2020).Article 

Google Scholar 
Bingham, C. T. The fauna of British India, including Ceylon and Burma. Hymenoptera, Vol. II. Ants and Cuckoo-wasps. (1903).Bolton, B. Identification Guide to the Ant Genera of the World (Harvard University Press, 1994).
Google Scholar 
Bellow, J. G. & Nair, P. K. R. Comparing common methods for assessing understory light availability in shaded-perennial agroforestry systems. Agric. For. Meteorol. 114, 197–211 (2003).ADS 
Article 

Google Scholar 
Dobson, A. J. & Barnett, A. G. An Introduction to Generalized Linear Models (Chapman and Hall/CRC, 2018).MATH 

Google Scholar 
Fox, J. et al. Package ‘car’, Vol. 16, (R Foundation for Statistical Computing, 2012).Hsieh, T. C., Ma, K. H. & Chao, A. iNEXT: An R package for rarefaction and extrapolation of species diversity (H ill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016).Article 

Google Scholar 
Kim, T. N., Savannah, B., Bill, D. W., Douglas, A. L. & Claudio, G. Disturbance differentially affects alpha and beta diversity of ants in tallgrass prairies. Ecosphere 9, e02399 (2018).Article 

Google Scholar 
Hartig, F. & Hartig, M. F. Package ‘DHARMa’. R package (2017).Nash, J. C. On best practice optimization methods in R. J. Stat. Softw. 60, 1–14 (2014).Article 

Google Scholar 
Berman, M., Andersen, A. N. & Ibanez, T. Invasive ants as back-seat drivers of native ant diversity decline in New Caledonia. Biol. Invasions 15, 2311–2331 (2013).Article 

Google Scholar 
Melliger, R. L., Braschler, B., Rusterholz, H.-P. & Baur, B. Diverse effects of degree of urbanisation and forest size on species richness and functional diversity of plants, and ground surface-active ants and spiders. PLoS ONE 13, e0199245 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Guénard, B., Cardinal-De Casas, A. & Dunn, R. R. High diversity in an urban habitat: Are some animal assemblages resilient to long-term anthropogenic change?. Urban Ecosyst. 18, 449–463 (2015).Article 

Google Scholar 
Slipinski, P., Zmihorski, M. & Czechowski, W. Species diversity and nestedness of ant assemblages in an urban environment. Eur. J. Entomol. 109, 197 (2012).Article 

Google Scholar 
Heterick, B. E., Lythe, M. & Smithyman, C. Urbanisation factors impacting on ant (Hymenoptera: Formicidae) biodiversity in the Perth metropolitan area, Western Australia: Two case studies. Urban Ecosyst. 16, 145–173 (2013).Article 

Google Scholar 
Theodorou, P. et al. Urban areas as hotspots for bees and pollination but not a panacea for all insects. Nat. Commun. 11, 1–13 (2020).Article 
CAS 

Google Scholar 
Goodman, M. & Warren, R. J. II. Non-native ant invader displaces native ants but facilitates non-predatory invertebrates. Biol. Invasions 21, 2713–2722 (2019).Article 

Google Scholar 
Philpott, S. M. & Armbrecht, I. Biodiversity in tropical agroforests and the ecological role of ants and ant diversity in predatory function. Ecol. Entomol. 31, 369–377 (2006).Article 

Google Scholar 
Philpott, S. M., Perfecto, I. & Vandermeer, J. Effects of management intensity and season on arboreal ant diversity and abundance in coffee agroecosystems. Biodivers. Conserv. 15, 139–155 (2006).Article 

Google Scholar 
García-Cárdenas, R., Montoya-Lerma, J. & Armbrecht, I. Ant diversity under three coverages in a Neotropical coffee landscape. Rev. Biol. Trop. 66, 1373–1389 (2018).Article 

Google Scholar 
Sinu, P. A. et al. Invasive ant (Anoplolepis gracilipes) disrupts pollination in pumpkin. Biol. Invasions 19, 2599–2607 (2017).Article 

Google Scholar 
Tsang, T. P., Dyer, E. E. & Bonebrake, T. C. Alien species richness is currently unbounded in all but the most urbanized bird communities. Ecography 42, 1426–1435 (2019).Article 

Google Scholar 
D’ettorre, P. Invasive eusocieties: commonalities between ants and humans. In Human Dispersal and Species Movement (eds Boivin, N. et al.) (Cambridge University Press, 2017).
Google Scholar 
Wetterer, J. K. Worldwide spread of the longhorn crazy ant, Paratrechina longicornis (Hymenoptera: Formicidae). Myrmecol. News 11, 137–149 (2008).
Google Scholar 
Lizon à l’Allemand, S. & Witte, V. sophisticated, modular communication contributes to ecological dominance in the invasive ant Anoplolepis gracilipes. Biol. invasions 12, 3551–3561 (2010).Article 

Google Scholar 
Silverman, J. & Buczkowski, G. Behaviours mediating ant invasions. In Biological Invasions and Animal Behaviour (eds Weis, J. S. & Sol, D.) (Cambridge University Press, 2016).
Google Scholar  More

Cremers, G. Presence of 10 models of plant architecture in Euphorbes-Malgaches. Comptes Rendus Hebd. des. Seances de. L Academie des. Sci. Ser. D. 281, 1575–1578 (1975).
Google Scholar 
Balduzzi, M. et al. Reshaping plant biology: qualitative and quantitative descriptors for plant morphology. Front. Plant Sci. 8, 117 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Albert, C. H. et al. A multi-trait approach reveals the structure and the relative importance of intra- vs. interspecific variability in plant traits. Funct. Ecol. 24, 1192–1201 (2010).Article 

Google Scholar 
Farnsworth, K. D. & Niklas, K. J. Theories of optimization, form and function in branching architecture in plants. Funct. Ecol. 9, 355–363 (1995).Article 

Google Scholar 
Enquist, B. J. et al. in Advances in Ecological Research (eds Pawar, S.et al.), 249–318 (Academic Press, 2015).Niklas, K. J. & Spatz, H. C. Allometric theory and the mechanical stability of large trees: proof and conjecture. Am. J. Bot. 93, 824–828 (2006).PubMed 
Article 

Google Scholar 
Price, C. A. et al. The metabolic theory of ecology: prospects and challenges for plant biology. N. Phytol. 188, 696–710 (2010).Article 

Google Scholar 
Martone, P. T. et al. Mechanics without muscle: biomechanical inspiration from the plant world. Integr. Comp. Biol. 50, 888–907 (2010).PubMed 
Article 

Google Scholar 
West, G. B. & Brown, J. H. The origin of allometric scaling laws in biology from genomes to ecosystems: towards a quantitative unifying theory of biological structure and organization. J. Exp. Biol. 208, 1575–1592 (2005).PubMed 
Article 

Google Scholar 
Enquist, B. J. Universal scaling in tree and vascular plant allometry: toward a general quantitative theory linking plant form and function from cells to ecosystems. Tree Physiol. 22, 1045–1064 (2002).PubMed 
Article 

Google Scholar 
Anfodillo, T. et al. An allometry-based approach for understanding forest structure, predicting tree-size distribution and assessing the degree of disturbance. Proc. R. Soc. Lond. B Biol. Sci. 280, 20122375 (2013).
Google Scholar 
Duncanson, L. I., Dubayah, R. O. & Enquist, B. J. Assessing the general patterns of forest structure: quantifying tree and forest allometric scaling relationships in the United States. Glob. Ecol. Biogeogr. 24, 1465–1475 (2015).Article 

Google Scholar 
West, G. B., Brown, J. H. & Enquist, B. J. The fourth dimension of life: Fractal geometry and allometric scaling of organisms. Science 284, 1677–1679 (1999).CAS 
PubMed 
Article 

Google Scholar 
Winter, C. L. & Tartakovsky, D. M. Theoretical foundation for conductivity scaling. Geophys. Res. Lett. 28, 4367–4369 (2001).Article 

Google Scholar 
Reich, P. B. et al. Universal scaling of respiratory metabolism, size and nitrogen in plants. Nature 439, 457–461 (2006).CAS 
PubMed 
Article 

Google Scholar 
Choi, S. et al. Application of the metabolic scaling theory and water–energy balance equation to model large‐scale patterns of maximum forest canopy height. Glob. Ecol. Biogeogr. 25, 1428–1442 (2016).Article 

Google Scholar 
Osler, G. H. R., West, P. W. & Downes, G. M. Effects of bending stress on taper and growth of stems of young Eucalyptus regnans trees. Trees 10, 239–246 (1996).
Google Scholar 
Berthier, S. et al. Irregular heartwood formation in maritime pine (Pinus pinaster Ait): consequences for biomechanical and hydraulic tree functioning. Ann. Bot. 87, 19–25 (2001).Article 

Google Scholar 
Fournier, M. et al. Integrative biomechanics for tree ecology: beyond wood density and strength. J. Exp. Bot. 64, 4793–4815 (2013).CAS 
PubMed 
Article 

Google Scholar 
Sone, K., Noguchi, K. & Terashima, I. Dependency of branch diameter growth in young Acer trees on light availability and shoot elongation. Tree Physiol. 25, 39–48 (2005).PubMed 
Article 

Google Scholar 
Anten, N. P. & Schieving, F. The role of wood mass density and mechanical constraints in the economy of tree architecture. Am. Nat. 175, 250–260 (2010).PubMed 
Article 

Google Scholar 
Jelonek, T. et al. The biomechanical formation of trees (Prace Naukowe, Doniesienia, Komunikaty, 2019).Muller‐Landau, H. C. et al. Testing metabolic ecology theory for allometric scaling of tree size, growth and mortality in tropical forests. Ecol. Lett. 9, 575–588 (2006).PubMed 
Article 

Google Scholar 
McMahon, T. A. & Kronauer, R. E. Tree structures: deducing the principle of mechanical design. J. Theor. Biol. 59, 443–466 (1976).CAS 
PubMed 
Article 

Google Scholar 
Alméras, T. & Fournier, M. Biomechanical design and long-term stability of trees: morphological and wood traits involved in the balance between weight increase and the gravitropic reaction. J. Theor. Biol. 256, 370–381 (2009).PubMed 
Article 

Google Scholar 
West, G. B., Brown, J. H. & Enquist, B. J. A general model for the origin of allometric scaling laws in biology. Science 276, 122–126 (1997).CAS 
PubMed 
Article 

Google Scholar 
Mäkelä, A. & Valentine, H. T. Crown ratio influences allometric scaling in trees. Ecol 87, 2967–2972 (2006).Article 

Google Scholar 
Duursma, R. A. et al. Self‐shading affects allometric scaling in trees. Funct. Ecol. 24, 723–730 (2010).Article 

Google Scholar 
Pretzsch, H. & Dieler, J. Evidence of variant intra-and interspecific scaling of tree crown structure and relevance for allometric theory. Oecologia 169, 637–649 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Lin, Y. et al. Plant interactions alter the predictions of metabolic scaling theory. PloS One 8, e57612 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cheng, D. et al. Scaling relationship between tree respiration rates and biomass. Biol. Lett. 6, 715–717 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
Ogawa, K. Scaling relations based on the geometric and metabolic theories in woody plant species: A review. Perspect. Plant Ecol. Evol. Syst. 40, 125480 (2019).Article 

Google Scholar 
Risto, S. et al. Functional–structural plant models: a growing paradigm for plant studies. Ann. Bot. 114, 599–603 (2014).Article 

Google Scholar 
Jackson, T. et al. Finite element analysis of trees in the wind based on terrestrial laser scanning data. Agric. Meteorol. 265, 137–144 (2019).Article 

Google Scholar 
Disney, M. Terrestrial LiDAR: a three‐dimensional revolution in how we look at trees. N. Phytol. 222, 1736–1741 (2019).Article 

Google Scholar 
Malhi, Y. et al. New perspectives on the ecology of tree structure and tree communities through terrestrial laser scanning. Interface Focus 8, 20170052 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Bayer, D., Seifert, S. & Pretzsch, H. Structural crown properties of Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica [L.]) in mixed versus pure stands revealed by terrestrial laser scanning. Trees 27, 1035–1047 (2013).Article 

Google Scholar 
Lin, Y. & Herold, M. Tree species classification based on explicit tree structure feature parameters derived from static terrestrial laser scanning data. Agric. Meteorol. 216, 105–114 (2016).Article 

Google Scholar 
Tanago, J. G. et al. Estimation of above‐ground biomass of large tropical trees with terrestrial LiDAR. Methods Ecol. Evol. 9, 223–234 (2018).Article 

Google Scholar 
Takoudjou, S. M. et al. Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach. Methods Ecol. Evol. 9, 905–916 (2018).Article 

Google Scholar 
Dassot, M., Fournier, M. & Deleuze, C. Assessing the scaling of the tree branch diameters frequency distribution with terrestrial laser scanning: methodological framework and issues. Ann. Sci. 76, 66 (2019).Article 

Google Scholar 
Klockow, P. A. et al. Allometry and structural volume change of standing dead southern pine trees using non-destructive terrestrial LiDAR. Remote Sens. Environ. 241, 111729 (2020).Article 

Google Scholar 
Stovall, A. E., Anderson-Teixeira, K. J. & Shugart, H. H. Assessing terrestrial laser scanning for developing non-destructive biomass allometry. Ecol. Manag. 427, 217–229 (2018).Article 

Google Scholar 
Dai, J. et al. Drought-modulated allometric patterns of trees in semi-arid forests. Commun. Biol. 3, 1–8 (2020).Article 

Google Scholar 
Ogawa, K., Hagihara, A. & Hozumi, K. Growth analysis of a seedling community of Chamaecyparis obtusa. VI. Estimation of individual gross primary production by the summation method. In Transactions of the 30th Meeting of Chubu Branch of Japanese Forestry Society, 179–181 (Honda Kiyoshi, 1985).Yokota, T. & Hagihara, A. Dependence of the aboveground CO2 exchange rate on tree size in field-grown hinoki cypress (Chamaecyparis obtusa). J. Plant Res. 109, 177–184 (1996).Article 

Google Scholar 
Enquist, B. J. et al. Biological scaling: does the exception prove the rule? Nature 445, E9–E10 (2007).CAS 
PubMed 
Article 

Google Scholar 
Lau, A. et al. Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling. Ecol. Manag. 439, 132–145 (2019).Article 

Google Scholar 
Li, Y. et al. Retrieval of tree branch architecture attributes from terrestrial laser scan data using a Laplacian algorithm. Agric. Meteorol. 284, 107874 (2020).Article 

Google Scholar 
Noyer, E. et al. Biomechanical control of beech pole verticality (Fagus sylvatica) before and after thinning: theoretical modelling and ground‐truth data using terrestrial LiDAR. Am. J. Bot. 106, 187–198 (2019).PubMed 
Article 

Google Scholar 
Jackson, T. et al. A new architectural perspective on wind damage in a natural forest. Front. Glob. Chang. 1, 13 (2019).Article 

Google Scholar 
Jackson, T. Strain Measurements on 21 Trees in Wytham Woods, UK. NERC Environmental Information Data Centre. https://doi.org/10.5285/533d87d3-48c1-4c6e-9f2f-fda273ab45bc (2018).Kozłowski, J. & Konarzewski, M. Is West, Brown and Enquist’s model of allometric scaling mathematically correct and biologically relevant? Funct. Ecol. 18, 283–289 (2004).Article 

Google Scholar 
Kleiber, M. Body size and metabolic rate. Physiol. Rev. 27, 511–541 (1947).CAS 
PubMed 
Article 

Google Scholar 
Hay, M. J. M. et al. Branching responses of a plagiotropic clonal herb to localised incidence of light simulating that reflected from vegetation. Oecologia 127, 185–190 (2001).CAS 
PubMed 
Article 

Google Scholar 
Cordero, R. A., Fetcher, N. & Voltzow, J. Effects of wind on the allometry of two species of plants in an elfin cloud forest. Biotropica 39, 177–185 (2010).Article 

Google Scholar 
Anfodillo, T. et al. Allometric trajectories and “stress”: a quantitative approach. Front. Plant Sci. 7, 1681 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Louarn, G. & Song, Y. Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology. Ann. Bot. 126, 501–509 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Poorter, H. & Sack, L. Pitfalls and possibilities in the analysis of biomass allocation patterns in plants. Front. Plant Sci. 3, 259 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Thomas, S. C. Reproductive allometry in Malaysian rain forest trees: biomechanics versus optimal allocation. Evol. Ecol. 10, 517–530 (1996).Article 

Google Scholar 
Kempes, C. P. et al. Predicting maximum tree heights and other traits from allometric scaling and resource limitations. PLoS One 6, e20551 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Blanchard, E. et al. Contrasted allometries between stem diameter, crown area, and tree height in five tropical biogeographic areas. Trees 30, 1953–1968 (2016).Article 

Google Scholar 
Swetnam, T. L., O’Connor, C. D. & Lynch, A. M. Tree morphologic plasticity explains deviation from metabolic scaling theory in semi-arid conifer forests, southwestern USA. PLoS One 11, e0157582 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Loehle, C. Biomechanical constraints on tree architecture. Trees 30, 2061–2070 (2016).Article 

Google Scholar 
Guillon, T., Dumont, Y. & Fourcaud, T. Numerical methods for the biomechanics of growing trees. Comput. Math. Appl. 64, 289–309 (2012).Article 

Google Scholar 
Olson, M. E., Rosell, J. A., Muñoz, S. Z. & Castorena, M. Carbon limitation, stem growth rate and the biomechanical cause of Corner’s rules. Ann. Bot. 122, 583–592 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
West, G. B., Enquist, B. J. & Brown, J. H. A general quantitative theory of forest structure and dynamics. Proc. Natl Acad. Sci. USA 106, 7040–7045 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

Climate and land cover dataOur study of tropical dry season dynamics required climatic variables with high temporal resolution (i.e., daily) and full coverage of tropic regions. To reduce uncertainties associated with the choice of precipitation (P) and evapotranspiration (Ep or E) datasets, we used an ensemble of eight precipitation products, three reanalysis-based products for Ep, and one satellite-based land E product. These precipitation datasets were derived four gauge-based or satellite observation (CHIRPS58, GPCC59, CPC-U60 and PERSIANN-CDR61), three reanalyses (ERA-562, MERRA-263, and PGF64) and a multi-source weighted ensemble product (MSWEP v2.865). The potential evapotranspiration (Ep) was calculated using the FAO Penman–Monteith equation66 (Eqs. (1, 2)), which requires meteorological inputs of wind speed, net radiation, air temperature, specific humidity, and surface pressure. We derived these meteorological variables from the three reanalysis products (ERA-5, MERRA-2, and GLDAS-2.067). Since PGF reanalysis lacked upward short- and long-wave radiation output and thus net radiation, we used available meteorological outputs from GLDAS-2.0 instead, which was forced entirely with the PGF input data.$${Ep}=frac{0.408cdot triangle cdot left({R}_{n}-Gright)+gamma cdot frac{900}{T+273}cdot {u}_{2}cdot left({e}_{s}-{e}_{a}right)}{triangle +{{{{{rm{gamma }}}}}}cdot left(1+0.34cdot {u}_{2}right)}$$
(1)
$${VPD}={e}_{s}-{e}_{a}=0.6108cdot {e}^{frac{17.27cdot T}{T+237.3}}cdot left(1-frac{{RH}}{100}right)$$
(2)
Where Ep is the potential evapotranspiration (mm day−1). Rn is net radiation at the surface (MJ m−2 day−1), T is mean daily air temperature at 2 m height (°C), ({u}_{2}) is wind speed at 2 m height (m s−1), ((,{e}_{s}-{e}_{a})) is the vapor pressure deficit of the air (kPa), ({RH}) is the relative air humidity near surface (%), ∆ is the slope of the saturation vapor pressure-temperature relationship (kPa °C−1), γ is the psychrometric constant (kPa °C−1), G is the soil heat flux (MJ m−2 day−1, is often ignored for daily time steps G ≈ 0).We derived the daily evapotranspiration data from the Global Land Evaporation Amsterdam Model (GLEAM v3.3a68), which is a set of algorithms dedicated to developing terrestrial evaporation and root-zone soil moisture data. GLEAM fully assimilated the satellite-based soil moisture estimates from ESA CCI, microwave L-band vegetation optical depth (VOD), reanalysis-based temperature and radiation, and multi-source precipitation forcings. The direct assimilation of observed soil moisture allowed us to detect true soil moisture dynamic and its impacts on evapotranspiration. Besides, the incorporation of VOD, which is closely linked to vegetation water content69,70, allowed us to detect the effect of water stress, heat stress, and vegetation phenological constraints on evaporation. Other observation-driven ET products from remote-sensing physical estimation and flux-tower are not included due to their low temporal resolution (i.e., monthly)71 or short duration72,73. ET outputs of reanalysis products are not considered in our analysis, because the assimilation systems lack explicit representation of inter-annual variability of vegetation activities and thus may not fully capture hydrological response to vegetation changes62,63,67.We used land cover maps for the year 2001 from the Moderate-Resolution Imaging Spectroradiometer (MODIS, MCD12C1 C574) based on the IGBP classification scheme to exclude water-dominated and sparely-vegetated pixels (like Sahara, Arabian Peninsula). All climate and land cover datasets mentioned above were remapped to a common 0.25° × 0.25° grid and unified to daily resolution. The main characteristics of the datasets mentioned above are summarized in Supplementary Table 1.Outputs of CMIP6 simulationsTo understand how modeled dry season changes compare with observed changes, we analyzed outputs from the “historical” (1983-2014) runs of 34 coupled models participating in the 6th Coupled Model Inter-comparison Project75 (CMIP6, Supplementary Table 3). We used these models because they offered daily outputs of all climatic variables needed for our analysis, including precipitation, latent heat (convert to E), and multiple meteorological variables for Ep (air temperature, surface specific humidity, wind speed, and net radiation). All outputs were remapped to a common 1.0° × 1.0° grid and unified to daily resolution.Defining dry season length and timingFor each grid cell and each dry season definition (P  More

Brondizio, E. S., Settele, J., Díaz, S. & Ngo, H. T. IPBES (2019): Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES Secretariat, 2019).Urban, M. C. Accelerating extinction risk from climate change. Science 348, 571–573 (2015).CAS 
PubMed 

Google Scholar 
Warren, R., Price, J., Graham, E., Forstenhaeusler, N. & VanDerWal, J. The projected effect on insects, vertebrates, and plants of limiting global warming to 1.5 °C rather than 2 °C. Science 360, 791–795 (2018).CAS 
PubMed 

Google Scholar 
Schloss, C. A., Nuñez, T. A. & Lawler, J. J. Dispersal will limit ability of mammals to track climate change in the Western Hemisphere. Proc. Natl Acad. Sci. USA 109, 8606–8611 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Travis, J. M. J. Climate change and habitat destruction: a deadly anthropogenic cocktail. Proc. Biol. Sci. 270, 467–473 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Hill, J. K. et al. Impacts of landscape structure on butterfly range expansion. Ecol. Lett. 4, 313–321 (2001).
Google Scholar 
Guo, F., Lenoir, J. & Bonebrake, T. C. Land-use change interacts with climate to determine elevational species redistribution. Nat. Commun. 9, 1315 (2018).PubMed 
PubMed Central 

Google Scholar 
McLaughlin, J. F., Hellmann, J. J., Boggs, C. L. & Ehrlich, P. R. Climate change hastens population extinctions. Proc. Natl Acad. Sci. USA 99, 6070–6074 (2002).CAS 
PubMed 
PubMed Central 

Google Scholar 
Jetz, W., Wilcove, D. S. & Dobson, A. P. Projected impacts of climate and land-use change on the global diversity of birds. PLoS Biol. 5, e157 (2007).PubMed 
PubMed Central 

Google Scholar 
Mantyka-Pringle, C. S. et al. Climate change modifies risk of global biodiversity loss due to land-cover change. Biol. Conserv. 187, 103–111 (2015).
Google Scholar 
Conradie, S. R., Woodborne, S. M., Cunningham, S. J. & McKechnie, A. E. Chronic, sublethal effects of high temperatures will cause severe declines in southern African arid-zone birds during the 21st century. Proc. Natl Acad. Sci. USA 116, 14065–14070 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Forister, M. L. et al. Compounded effects of climate change and habitat alteration shift patterns of butterfly diversity. Proc. Natl Acad. Sci. USA 107, 2088–2092 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Oliver, T. H. & Morecroft, M. D. Interactions between climate change and land use change on biodiversity: attribution problems, risks, and opportunities. Wiley Interdiscip. Rev. Clim. Change 5, 317–335 (2014).
Google Scholar 
MacLean, S. A. & Beissinger, S. R. Species’ traits as predictors of range shifts under contemporary climate change: a review and meta-analysis. Glob. Change Biol. 23, 4094–4105 (2017).
Google Scholar 
Pacifici, M. et al. Species’ traits influenced their response to recent climate change. Nat. Clim. Change 7, 205–208 (2017).
Google Scholar 
Root, T. Energy constraints on avian distributions and abundances. Ecology 69, 330–339 (1988).
Google Scholar 
Whitfield, M. C., Smit, B., McKechnie, A. E. & Wolf, B. O. Avian thermoregulation in the heat: scaling of heat tolerance and evaporative cooling capacity in three southern African arid-zone passerines. J. Exp. Biol. 218, 1705–1714 (2015).PubMed 

Google Scholar 
McKechnie, A. E. et al. Avian thermoregulation in the heat: evaporative cooling in five Australian passerines reveals within-order biogeographic variation in heat tolerance. J. Exp. Biol. 220, 2436–2444 (2017).PubMed 

Google Scholar 
Platts, P. J. et al. Habitat availability explains variation in climate-driven range shifts across multiple taxonomic groups. Sci. Rep. 9, 15039 (2019).PubMed 
PubMed Central 

Google Scholar 
Pearson, R. G. Climate change and the migration capacity of species. Trends Ecol. Evol. 21, 111–113 (2006).PubMed 

Google Scholar 
Partners in Flight. Avian Conservation Assessment Database Version 2021 (accessed 5 February 2021); http://pif.birdconservancy.org/ACADHill, M. J. & Guerschman, J. P. The MODIS global vegetation fractional cover product 2001–2018: characteristics of vegetation fractional cover in grasslands and savanna woodlands. Remote Sens. (Basel) 12, 406 (2020).
Google Scholar 
Wiebe, K. L. & Gerstmar, H. Influence of spring temperatures and individual traits on reproductive timing and success in a migratory woodpecker. Auk 127, 917–925 (2010).
Google Scholar 
Viana, D. S. & Chase, J. M. Ecological traits underlying interspecific variation in climate matching of birds. Glob. Ecol. Biogeogr. 31, 1021–1034 (2022).
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).CAS 
PubMed 

Google Scholar 
Devictor, V. et al. Differences in the climatic debts of birds and butterflies at a continental scale. Nat. Clim. Change 2, 121–124 (2012).
Google Scholar 
Mason, L. R. et al. Population responses of bird populations to climate change on two continents vary with species’ ecological traits but not with direction of change in climate suitability. Clim. Change 157, 337–354 (2019).
Google Scholar 
Coyle, J. R., Hurlbert, A. H. & White, E. P. Opposing mechanisms drive richness patterns of core and transient bird species. Am. Nat. 181, E83–E90 (2013).PubMed 

Google Scholar 
Valiela, I. & Martinetto, P. Changes in bird abundance in eastern North America: urban sprawl and global footprint? BioScience 57, 360–370 (2007).
Google Scholar 
Smith, S. J., Edmonds, J., Hartin, C. A., Mundra, A. & Calvin, K. Near-term acceleration in the rate of temperature change. Nat. Clim. Change 5, 333–336 (2015).
Google Scholar 
Winkler, K., Fuchs, R., Rounsevell, M. & Herold, M. Global land use changes are four times greater than previously estimated. Nat. Commun. 12, 2501 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rosenberg, K. V. et al. Decline of the North American avifauna. Science 366, 120–124 (2019).CAS 
PubMed 

Google Scholar 
Currie, D. J. & Venne, S. Climate change is not a major driver of shifts in the geographical distributions of North American birds. Glob. Ecol. Biogeogr. 26, 333–346 (2017).
Google Scholar 
Socolar, J. B., Epanchin, P. N., Beissinger, S. R. & Tingley, M. W. Phenological shifts conserve thermal niches in North American birds and reshape expectations for climate-driven range shifts. Proc. Natl Acad. Sci. USA 114, 12976–12981 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Barnagaud, J.-Y. et al. Relating habitat and climatic niches in birds. PLoS ONE 7, e32819 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ponti, R., Arcones, A., Ferrer, X. & Vieites, D. R. Seasonal climatic niches diverge in migratory birds. Ibis 162, 318–330 (2020).
Google Scholar 
Zurell, D., Gallien, L., Graham, C. H. & Zimmermann, N. E. Do long-distance migratory birds track their niche through seasons? J. Biogeogr. 45, 1459–1468 (2018).
Google Scholar 
Stephens, P. A. et al. Consistent response of bird populations to climate change on two continents. Science 352, 84–87 (2016).CAS 
PubMed 

Google Scholar 
Ralston, J., DeLuca, W. V., Feldman, R. E. & King, D. I. Population trends influence species ability to track climate change. Glob. Change Biol. 23, 1390–1399 (2017).
Google Scholar 
Magurran, A. E. et al. Long-term datasets in biodiversity research and monitoring: assessing change in ecological communities through time. Trends Ecol. Evol. 25, 574–582 (2010).PubMed 

Google Scholar 
Jarzyna, M. A. & Jetz, W. A near half-century of temporal change in different facets of avian diversity. Glob. Change Biol. 23, 2999–3011 (2017).
Google Scholar 
van der Bolt, B., van Nes, E. H., Bathiany, S., Vollebregt, M. E. & Scheffer, M. Climate reddening increases the chance of critical transitions. Nat. Clim. Change 8, 478–484 (2018).
Google Scholar 
Bowler, D. E., Heldbjerg, H., Fox, A. D., O’Hara, R. B. & Böhning-Gaese, K. Disentangling the effects of multiple environmental drivers on population changes within communities. J. Anim. Ecol. 87, 1034–1045 (2018).PubMed 

Google Scholar 
Zurell, D., Graham, C. H., Gallien, L., Thuiller, W. & Zimmermann, N. E. Long-distance migratory birds threatened by multiple independent risks from global change. Nat. Clim. Change 8, 992–996 (2018).
Google Scholar 
Northrup, J. M., Rivers, J. W., Yang, Z. & Betts, M. G. Synergistic effects of climate and land-use change influence broad-scale avian population declines. Glob. Change Biol. 25, 1561–1575 (2019).
Google Scholar 
Guisan, A. et al. Predicting species distributions for conservation decisions. Ecol. Lett. 16, 1424–1435 (2013).PubMed 
PubMed Central 

Google Scholar 
Pardieck, K. L., Ziolkowski, D. J. Jr, Lutmerding, M., Aponte, V. & Hudson, M.-A. R. North American Breeding Bird Survey Dataset 1966–2018 Version 2018.0. (US Geological Survey, 2019); https://www.sciencebase.gov/catalog/item/5d65256ae4b09b198a26c1d7Harris, D. J., Taylor, S. D. & White, E. P. Forecasting biodiversity in breeding birds using best practices. PeerJ 6, e4278 (2018).PubMed 
PubMed Central 

Google Scholar 
Wickham, H., Francois, R., Henry, L. & Müller, K. dplyr: a Grammar of Data Manipulation. R package version 1.0.0 https://cran.r-project.org/web/packages/dplyr/index.html (2020).Wickham, H. & Henry, L. tidyr: Tidy Messy Data. R package version 1.1.0 https://cran.r-project.org/web/packages/tidyr/index.html (2020).Hijmans, R. J. raster: Geographic Data Analysis and Modeling. R package version 3.0-12 https://cran.r-project.org/web/packages/raster/index.html (2015).Bivand, R., Pebesma, E. J. & Gómez-Rubio, V. Applied Spatial Data Analysis with R (Springer, 2013).Hijmans, R. J. geosphere: Spherical Trigonometry. R package version 1.5–10 https://cran.r-project.org/web/packages/geosphere/index.html (2019).Hart, E. M. & Bell, K. prism. R package version 0.0.6 https://github.com/ropensci/prism (2015).Senyondo, H. et al. rdataretriever: R interface to the data retriever. J. Open Source Softw. 6, 2800 (2021).
Google Scholar 
Morris, B. D. & White, E. P. The EcoData retriever: improving access to existing ecological data. PLoS ONE 8, e65848 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Senyondo, H. et al. Retriever: data retrieval tool. J. Open Source Softw. 2, 451 (2017).
Google Scholar 
Hurlbert, A. H. & White, E. P. Disparity between range map- and survey-based analyses of species richness: patterns, processes and implications. Ecol. Lett. 8, 319–327 (2005).
Google Scholar 
Harris, D. J. Generating realistic assemblages with a joint species distribution model. Methods Ecol. Evol. 6, 465–473 (2015).
Google Scholar 
Sheard, C. et al. Ecological drivers of global gradients in avian dispersal inferred from wing morphology. Nat. Commun. 11, 2463 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Eyres, A., Böhning-Gaese, K. & Fritz, S. A. Quantification of climatic niches in birds: adding the temporal dimension. J. Avian Biol. 48, 1517–1531 (2017).
Google Scholar 
Martin, A. E. & Fahrig, L. Habitat specialist birds disperse farther and are more migratory than habitat generalist birds. Ecology 99, 2058–2066 (2018).PubMed 

Google Scholar 
Sauer, J. R. & Link, W. A. Analysis of the North American Breeding Bird Survey using hierarchical models. Auk 128, 87–98 (2011).
Google Scholar 
García Molinos, J., Schoeman, D. S., Brown, C. J. & Burrows, M. T. VoCC: an R package for calculating the velocity of climate change and related climatic metrics. Methods Ecol. Evol. 10, 2195–2202 (2019).
Google Scholar 
Krenek, S., Berendonk, T. U. & Petzoldt, T. Thermal performance curves of Paramecium caudatum: a model selection approach. Eur. J. Protistol. 47, 124–137 (2011).PubMed 

Google Scholar 
Bahn, V. & McGill, B. J. Can niche-based distribution models outperform spatial interpolation? Glob. Ecol. Biogeogr. 16, 733–742 (2007).
Google Scholar 
Dobson, L. L., La Sorte, F. A., Manne, L. L. & Hawkins, B. A. The diversity and abundance of North American bird assemblages fail to track changing productivity. Ecology 96, 1105–1114 (2015).PubMed 

Google Scholar 
Roberts, D. R. et al. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40, 913–929 (2017).
Google Scholar 
Tikhonov, G. et al. Joint species distribution modelling with the R-package HMSC. Methods Ecol. Evol. 11, 442–447 (2020).PubMed 
PubMed Central 

Google Scholar 
Greenwell, B., Boehmke, B., Cunningham, J. & GBM Developers. gbm: Generalized boosted regression models. R package version 2.1.5 https://cran.r-project.org/web/packages/gbm/index.html (2019).Wood, S. N. Generalized Additive Models: an Introduction with R (CRC Press/Taylor & Francis Group, 2017).Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).CAS 
PubMed 

Google Scholar 
Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).
Google Scholar 
Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).CAS 
PubMed 

Google Scholar 
Bürkner, P.-C. brms: an R package for Bayesian multilevel models using Stan. J. Stat. Softw. 80, 1–28 (2017).
Google Scholar 
Stan Development Team. Stan Modeling Language Users Guide and Reference Manual (2020); https://mc-stan.org/users/documentation/ More

Wu, A. Social buffering of stress – Physiological and ethological perspectives. Appl. Anim. Behav. Sci. 239, 105325 (2021).
Google Scholar 
Hennessy, M. B., Kaiser, S. & Sachser, N. Social buffering of the stress response: diversity, mechanisms, and functions. Front. Neuroendocrinol. 30, 470–482 (2009).CAS 
PubMed 

Google Scholar 
Young, C., Majolo, B., Heistermann, M., Schülke, O. & Ostner, J. Responses to social and environmental stress are attenuated by strong male bonds in wild macaques. Proc. Natl Acad. Sci. USA 111, 18195–18200 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Stanton, M. E., Patterson, J. M. & Levine, S. Social influences on conditioned cortisol secretion in the squirrel monkey. Psychoneuroendocrinology 10, 125–134 (1985).CAS 
PubMed 

Google Scholar 
Caldji, C., Diorio, J. & Meaney, M. J. Variations in maternal care in infancy regulate the development of stress reactivity. Biol. Psychiatry 48, 1164–1174 (2000).CAS 
PubMed 

Google Scholar 
Novak, M. A., Hamel, A. F., Kelly, B. J., Dettmer, A. M. & Meyer, J. S. Stress, the HPA axis, and nonhuman primate well-being: a review. Appl. Anim. Behav. Sci. 143, 135–149 (2013).PubMed 
PubMed Central 

Google Scholar 
Sapolsky, R. M., Romero, L. M. & Munck, A. U. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21, 55–89 (2000).CAS 
PubMed 

Google Scholar 
Liu, D. et al. Maternal Care, hippocampal glucocorticoid receptors, and hypothalamic-pituitary-adrenal responses to stress. Sci. Ment. Heal. Stress Brain 9, 75–78 (1997).
Google Scholar 
Gjerstad, J. K., Lightman, S. L. & Spiga, F. Role of glucocorticoid negative feedback in the regulation of HPA axis pulsatility. Stress 21, 403–416 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Spiga, F., Walker, J. J., Terry, J. R. & Lightman, S. L. HPA axis-rhythms. Compr. Physiol. 4, 1273–1298 (2014).PubMed 

Google Scholar 
Sapolsky, R. M. Why Zebras Don’t Get Ulcers (Henry Holt and Company, LLC, 2004).Campos, F. A. et al. Glucocorticoid exposure predicts survival in female baboons. Sci. Adv. 7, 1–10 (2021).
Google Scholar 
Banerjee, S. B., Arterbery, A. S., Fergus, D. J. & Adkins-Regan, E. Deprivation of maternal care has long-lasting consequences for the hypothalamic-pituitary-adrenal axis of zebra finches. Proc. R. Soc. B Biol. Sci. 279, 759–766 (2012).
Google Scholar 
Hennessy, M. B., Nigh, C. K., Sims, M. L. & Long, S. J. Plasma cortisol and vocalization responses of postweaning age guinea pigs to maternal and sibling separation: evidence for filial attachment after weaning. Dev. Psychobiol. 28, 103–115 (1995).CAS 
PubMed 

Google Scholar 
Hennessy, M. B., O’Leary, S. K., Hawke, J. L. & Wilson, S. E. Social influences on cortisol and behavioral responses of preweaning, periadolescent, and adult guinea pigs. Physiol. Behav. 76, 305–314 (2002).CAS 
PubMed 

Google Scholar 
Wiener, S. G., Johnson, D. F. & Levine, S. Influence of postnatal rearing conditions on the response of squirrel monkey infants to brief perturbations in mother-infant relationships. Physiol. Behav. 39, 21–26 (1987).CAS 
PubMed 

Google Scholar 
Girard-Buttoz, C. et al. Early maternal loss leads to short-but not long-term effects on diurnal cortisol slopes in wild chimpanzees. Elife 10, e64134 (2021).Rosenbaum, S. et al. Social bonds do not mediate the relationship between early adversity and adult glucocorticoids in wild baboons. Proc. Natl Acad. Sci. USA 117, 20052–20062 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Moss, C. Elephant Memories: Thirteen Years in the Life of an Elephant Family (Univ. Chicago Press, 1988).Douglas-Hamilton, I., Bhalla, S., Wittemyer, G. & Vollrath, F. Behavioural reactions of elephants towards a dying and deceased matriarch. Appl. Anim. Behav. Sci. 100, 87–102 (2006).
Google Scholar 
Shoshani, J., Kupsky, W. J. & Marchant, G. H. Elephant brain. Part I: gross morphology, functions, comparative anatomy, and evolution. Brain Res. Bull. 70, 124–157 (2006).PubMed 

Google Scholar 
Goldenberg, S. Z. & Wittemyer, G. Orphaned female elephant social bonds reflect lack of access to mature adults. Sci. Rep. 7, 14408 (2017).PubMed 
PubMed Central 

Google Scholar 
Goldenberg, S. Z. & Wittemyer, G. Orphaning and natal group dispersal are associated with social costs in female elephants. Anim. Behav. 143, 1–8 (2018).
Google Scholar 
Lee, P. C. Allomothering among African elephants. Anim. Behav. 35, 278–291 (1987).
Google Scholar 
Parker, J. M. et al. Poaching of African elephants indirectly decreases population growth through lowered orphan survival. Curr. Biol. 31, 4156–4162.e5 (2021).Wittemyer, G. et al. Where sociality and relatedness diverge: the genetic basis for hierarchical social organization in African elephants. Proc. R. Soc. B Biol. Sci. 276, 3513–3521 (2009).
Google Scholar 
Goldenberg, S. Z., Douglas-Hamilton, I. & Wittemyer, G. Vertical transmission of social roles drives resilience to poaching in elephant metworks. Curr. Biol. 26, 75–79 (2016).CAS 
PubMed 

Google Scholar 
Gobush, K. S., Mutayoba, B. M. & Wasser, S. K. Long-term impacts of poaching on relatedness, stress physiology, and reproductive output of adult female African elephants. Conserv. Biol. 22, 1590–1599 (2008).CAS 
PubMed 

Google Scholar 
Gobush, K. S. et al. Loxodonta africana (African Savanna Elephant). Loxodonta africana: the IUCN red list of threatened species 2021 e.T181008073A181022663 https://doi.org/10.2305/IUCN.UK.2021-1.RLTS.T181008073A181022663.en (2021).Wittemyer, G. et al. Illegal killing for ivory drives global decline in African elephants. Proc. Natl Acad. Sci. USA 111, 13117–13121 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wittemyer, G., Daballen, D. & Douglas-Hamilton, I. Comparative Demography of an At-Risk African Elephant Population. PLoS ONE 8, e53726 (2013).McCormick, S. D. & Romero, L. M. Conservation endocrinology. Bioscience 67, 429–442 (2017).
Google Scholar 
Wittemyer, G. The elephant population of Samburu and Buffalo Springs National Reserves, Kenya. Afr. J. Ecol. 39, 357–369 (2001).
Google Scholar 
Cockrem, J. F. Individual variation in glucocorticoid stress responses in animals. Gen. Comp. Endocrinol. 181, 45–58 (2013).CAS 
PubMed 

Google Scholar 
Taff, C. C., Schoenle, L. A. & Vitousek, M. N. The repeatability of glucocorticoids: a review and meta-analysis. Gen. Comp. Endocrinol. 260, 136–145 (2018).CAS 
PubMed 

Google Scholar 
Hooten, M. B. & Hobbs, N. T. A guide to Bayesian model selection for ecologists. Ecol. Monogr. 85, 3–28 (2015).
Google Scholar 
Wittemyer, G. & Getz, W. M. Hierarchical dominance structure and social organization in African elephants, Loxodonta africana. Anim. Behav. 73, 671–681 (2007).
Google Scholar 
Heim, C., Ehlert, U. & Hellhammer, D. H. The potential role of hypocortisolism in the pathophysiology of stress-related bodily disorders. Psychoneuroendocrinology 25, 1–35 (2000).CAS 
PubMed 

Google Scholar 
Dickens, M. J. & Romero, L. M. A consensus endocrine profile for chronically stressed wild animals does not exist. Gen. Comp. Endocrinol. 191, 177–189 (2013).CAS 
PubMed 

Google Scholar 
Ma, D., Serbin, L. A. & Stack, D. M. How children’s anxiety symptoms impact the functioning of the hypothalamus–pituitary–adrenal axis over time: a cross-lagged panel approach using hierarchical linear modeling. Dev. Psychopathol. 31, 1–15 (2018).
Google Scholar 
Blas, J., Bortolotti, G. R., Tella, J. L., Baos, R. & Marchant, T. A. Stress response during development predicts fitness in a wild, long lived vertebrate. Proc. Natl Acad. Sci. USA 104, 8880–8884 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
Boonstra, R. Reality as the leading cause of stress: rethinking the impact of chronic stress in nature. Funct. Ecol. 27, 11–23 (2013).
Google Scholar 
Gunnar, M. R. & Vazquez, D. M. Low cortisol and a flattening of expected daytime rhythm: Potential indices of risk in human development. Dev. Psychopathol. 13, 515–538 (2001).CAS 
PubMed 

Google Scholar 
Perry, R. E. et al. Corticosterone administration targeting a hypo-reactive HPA axis rescues a socially-avoidant phenotype in scarcity-adversity reared rats. Dev. Cogn. Neurosci. 40, 100716 (2019).Fries, E., Hesse, J., Hellhammer, J. & Hellhammer, D. H. A new view on hypocortisolism. Psychoneuroendocrinology 30, 1010–1016 (2005).CAS 
PubMed 

Google Scholar 
Dorsey, C., Dennis, P., Guagnano, G., Wood, T. & Brown, J. L. Decreased baseline fecal glucocorticoid concentrations associated with skin and oral lesions in black rhinoceros (Diceros bicornis). J. Zoo. Wildl. Med. 41, 616–625 (2010).PubMed 

Google Scholar 
Pawluski, J. et al. Low plasma cortisol and fecal cortisol metabolite measures as indicators of compromised welfare in domestic horses (Equus caballus). PLoS ONE 12, 1–18 (2017).
Google Scholar 
Feng, X. et al. Maternal separation produces lasting changes in cortisol and behavior in rhesus monkeys. Proc. Natl Acad. Sci. USA 108, 14312–14317 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
González Ramírez, C. et al. The NR3C1 gene expression is a potential surrogate biomarker for risk and diagnosis of posttraumatic stress disorder. Psychiatry Res. 284, 112797 (2020).PubMed 

Google Scholar 
Cluver, L., Fincham, D. S. & Seedat, S. Posttraumatic stress in AIDS-orphaned children exposed to high levels of trauma: the protective role of perceived social support. J. Trauma. Stress 22, 106–112 (2009).PubMed 

Google Scholar 
Bastille-Rousseau, G. et al. Landscape-scale habitat response of African elephants shows strong selection for foraging opportunities in a human dominated ecosystem. Ecography 43, 149–160 (2020).
Google Scholar 
Foley, C. A. H., Papageorge, S. & Wasser, S. K. Noninvasive stress and reproductive measures of social and ecological pressures in free-ranging African elephants. Conserv. Biol. 15, 1134–1142 (2001).
Google Scholar 
Wittemyer, G., Getz, W. M., Vollrath, F. & Douglas-Hamilton, I. Social dominance, seasonal movements, and spatial segregation in African elephants: a contribution to conservation behavior. Behav. Ecol. Sociobiol. 61, 1919–1931 (2007).
Google Scholar 
Wittemyer, G., Daballen, D. & Douglas‐Hamilton, I. Differential influence of human impacts on age‐specific demography underpins trends in an African elephant population. Ecosphere 12, e03720 (2021).Brown, J. L. et al. Individual and environmental risk factors associated with fecal glucocorticoid metabolite concentrations in zoo-housed Asian and African elephants. PLoS ONE 14, 1–18 (2019).
Google Scholar 
Goldenberg, S. Z. et al. Increasing conservation translocation success by building social functionality in released populations. Glob. Ecol. Conserv. 18, e00604 (2019).Dantzer, B., Fletcher, Q. E., Boonstra, R. & Sheriff, M. J. Measures of physiological stress: a transparent or opaque window into the status, management and conservation of species? Conserv. Physiol. 2, 1–18 (2014).
Google Scholar 
Kaisin, O., Fuzessy, L., Poncin, P., Brotcorne, F. & Culot, L. A meta-analysis of anthropogenic impacts on physiological stress in wild primates. Conserv. Biol. 0, 1–14 (2020).CAS 

Google Scholar 
Ganswindt, A., Rasmussen, H. B., Heistermann, M. & Hodges, J. K. The sexually active states of free-ranging male African elephants (Loxodonta africana): defining musth and non-musth using endocrinology, physical signals, and behavior. Horm. Behav. 47, 83–91 (2005).CAS 
PubMed 

Google Scholar 
Santymire, R. M. et al. Using ACTH challenges to validate techniques for adrenocortical activity analysis in various African wildlife species. Int. J. Anim. Vet. Adv. 4, 99–108 (2012).CAS 

Google Scholar 
Watson, R. et al. Development of a versatile enzyme immunoassay for non-invasive assessment of glucocorticoid metabolites in a diversity of taxonomic species. Gen. Comp. Endocrinol. 186, 16–24 (2013).CAS 
PubMed 

Google Scholar 
Oduor, S. et al. Differing physiological and behavioral responses to anthropogenic factors between resident and non-resident African elephants at Mpala Ranch, Laikipia County, Kenya. PeerJ 8, e10010 (2020).Brown, J. L., Kersey, D. C., Freeman, E. W. & Wagener, T. Assessment of diurnal urinary cortisol excretion in Asian and African elephants using different endocrine methods. Zoo. Biol. 29, 274–283 (2010).PubMed 

Google Scholar 
Justice, C. O. et al. The moderate resolution imaging spectroradiometer (MODIS): land remote sensing for global change research. IEEE Trans. Geosci. Remote Sens. 36, 1228–1249 (1998).
Google Scholar 
Lafferty, D. J. R., Zimova, M., Clontz, L., Hackländer, K. & Mills, L. S. Noninvasive measures of physiological stress are confounded by exposure. Sci. Rep. 9, 1–6 (2019).
Google Scholar 
O’Dwyer, K., Dargent, F., Forbes, M. R. & Koprivnikar, J. Parasite infection leads to widespread glucocorticoid hormone increases in vertebrate hosts: a meta-analysis. J. Anim. Ecol. 89, 519–529 (2020).PubMed 

Google Scholar 
Parker, J. M., Goldenberg, S. Z., Letitiya, D. & Wittemyer, G. Strongylid infection varies with age, sex, movement and social factors in wild African elephants. Parasitology 147, 348–359 (2020).PubMed 

Google Scholar 
Gibbons, L., Jacobs, D. E., Fox, M. T. & Hansen, J. The RVC/FAO guide to veterinary diagnostic parasitology. McMaster egg-counting technique. http://www.rvc.ac.uk/review/Parasitology/EggCount/Purpose.htm (2004)R Core Team. A language and environment for statistical computing. https://www.r-project.org/. (2020).Rstudio Team. RStudio: integrated development for R. http://www.rstudio.com/ (2020).Plummer, M. rjags: Bayesian graphical models using MCMC. https://cran.r-project.org/package=rjags (2019).Brooks, S. P. & Gelman, A. General methods for monitoring convergence of iterative simulations. J. Comput. Graph. Stat. 7, 434–455 (1998).
Google Scholar 
Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences. Stat. Sci. 7, 457–511 (1992).
Google Scholar 
Wickham, H. ggplot2: elegant graphics for data analysis. https://ggplot2.tidyverse.org (2016).Youngflesh, C. MCMCvis: tools to visualize, manipulate, and summarize MCMC output. J. Open Source Softw. 3, 640 (2018).
Google Scholar 
Parker, J. M. The Physiological Condition of Orphaned African Elephants (Loxodonta africana). Doctoral dissertation, Colorado State University. (2021). More

The management of introduced species, whether kudzu or zebra mussels, is costly and complex. Now, a paper reports a workable, effective solution that harnesses network analyses of ecological phenomena.Invasive species can pose severe economic and environmental problems, costing more than US$1 trillion worldwide since 1970 (ref. 1). Yet managing this human-driven issue is difficult in itself. The regions involved can be vast — entire continents or countries, for instance — while budgets are typically limited. As well, the sites potentially affected and management options can be numerous. Real systems (for example, all the lakes in the United States) can have thousands of locations that could potentially be infested. By contrast, considering just 40 locations means dealing theoretically with over 1 trillion unique combinations (240) where management could be applied (for instance, to reduce the number of invasive species leaving infested areas or entering uninfested ones). Given these constraints, a key problem is how and where to deploy control measures such as invasive-species removal. While sophisticated optimization approaches exist2, which use mathematical rules to exclude most suboptimal combinations and quickly zoom in to which locations should be managed to minimize new invasions, these algorithms are generally unfeasible for very large systems. Now, writing in Nature Sustainability, Ashander et al.3 demonstrate that simpler network metrics revealing linkages between patches can provide solutions that are often comparable to the more complex optimization algorithms. More

Karlsson, O. et al. Pesticide-induced multigenerational effects on amphibian reproduction and metabolism. Sci. Total Environ. 775, 145771 (2021).ADS 
CAS 
PubMed 
Article 

Google Scholar 
IUCN. The IUCN Red List of Threatened Species. Version 2021-3. https://www.iucnredlist.org (2022).Wake, D. B. & Koo, M. S. Amphibians. Curr. Biol. 28, R1237–R1241 (2018).CAS 
PubMed 
Article 

Google Scholar 
Campbell Grant, E. H., Miller, D. A. & Muths, E. A synthesis of evidence of drivers of amphibian declines. Herpetologica 76, 101–107 (2020).Article 

Google Scholar 
Green, D. M., Lannoo, M. J., Lesbarrères, D. & Muths, E. Amphibian population declines: 30 years of progress in confronting a complex problem. Herpetologica 76, 97–100 (2020).Article 

Google Scholar 
Mason, R., Tennekes, H., Sánchez-Bayo, F. & Jepsen, P. U. Immune suppression by neonicotinoid insecticides at the root of global wildlife declines. J. Environ. Immunol. Toxicol. 1, 3–12 (2013).Article 

Google Scholar 
Adams, E., Leeb, C. & Brühl, C. A. Pesticide exposure affects reproductive capacity of common toads (Bufo bufo) in a viticultural landscape. Ecotoxicology 30, 213–223 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Frost, D. R. Amphibian species of the world 6,1, an online reference. Electron. Datab. https://doi.org/10.5531/db.vz.0001 (American Museum of Natural History, 2021).Article 

Google Scholar 
Eterovick, P. C., Souza, A. M. & Sazima, I. Anfíbios da Serra do Cipó [Amphibians from the Serra do Cipó]. http://herpeto.org/wp-content/uploads/2020/11/ANFIBIOS-DA-SERRA-DO-CIPO.pdf (PUCMINAS, 2020).Mijares, A., Rodrigues, M. T. & Baldo, D. Physalaemus cuvieri The IUCN Red List of Threatened Species, version 2014.3. http://www.iucnredlist.org (2010). Accessed 9 Jan 2015.de Sá, F. P., Zina, J. & Haddad, C. F. B. Reproductive dynamics of the Neotropical treefrog Hypsiboas albopunctatus (Anura, Hylidae). J. Herpetol. 48, 181–185 (2014).Article 

Google Scholar 
Herek, J. S. et al. Can environmental concentrations of glyphosate affect survival and cause malformation in amphibians? Effects from a glyphosate-based herbicide on Physalaemus cuvieri and P. gracilis (Anura: Leptodactylidae). Environ. Sci. Pollut. Res. 27, 22619–22630 (2020).CAS 
Article 

Google Scholar 
Silva, F. L. et al. Swimming ability in tadpoles of Physalaemus cf. cuvieri, Scinax x-signatus and Leptodactylus latrans (Amphibia: Anura) exposed to the insecticide chlorpyrifos. Ecotoxicol. Environ. Contam. 16, 13–18 (2021).
Google Scholar 
Pavan, F. A. et al. Morphological, behavioral and genotoxic effects of glyphosate and 2,4-D mixture in tadpoles of two native species of South American amphibians. Environ. Toxicol. Pharmacol. 85, 103637 (2021).CAS 
PubMed 
Article 

Google Scholar 
Simon-Delso, N. et al. Systemic insecticides (Neonicotinoids and fipronil): Trends, uses, mode of action and metabolites. Environ. Sci. Pollut. Res. 22, 5–34 (2015).CAS 
Article 

Google Scholar 
Pietrzak, D., Kania, J., Malina, G., Kmiecik, E. & Wątor, K. Pesticides from the EU first and second watch lists in the water environment. Clean 47, 1–10 (2019).
Google Scholar 
IBAMA: Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis. Relatório de comercialização de agrotóxicos 2019 [Brazilian Pesticide Marketing Report 2019] https://www.ibama.gov.br/agrotoxicos/relatorios-de-comercializacao-de-agrotoxicos#boletinsanuais (2021).IBAMA: Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis. Vendas de ingredientes ativos por UF [Active ingredient sales by UF in Brazil]. http://ibama.gov.br/phocadownload/qualidadeambiental/relatorios/2019/Vendas_ingredientes_ativos_UF_2019.x (2021).IBAMA – Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis. Boletins anuais de produção, importação, exportação e vendas de agrotóxicos no Brasil [Annual bulletins of production, import, export and sales of pesticides in Brazil]. http://ibama.gov.br/index.php?option=com_content&view=article&id=594&Itemid=54 (2021).Pietrzak, D., Kania, J., Kmiecik, E., Malina, G. & Wątor, K. Fate of selected neonicotinoid insecticides in soil–water systems: Current state of the art and knowledge gaps. Chemosphere 255, 126981 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
ANVISA: Agência Nacional de Vigilância Sanitária; Índice Monográfico I13. Imidacloprido. http://portal.anvisa.gov.br/documents/111215/117782/I13+%E2%80%93+Imidacloprido/9d08c7e5-8979-4ee9-b76c-1092899514d7 (2021).Kagabu, S. Discovery of imidacloprid and further developments from strategic molecular designs. J. Agric. Food Chem. 59, 2887–2896 (2011).CAS 
PubMed 
Article 

Google Scholar 
Tomizawa, M. & Casida, J. E. Neonicotinoid insecticide toxicology: Mechanisms of selective action. Annu. Rev. Pharmacol. Toxicol. 45, 247–268 (2005).CAS 
PubMed 
Article 

Google Scholar 
Hashimoto, F. et al. Occurrence of imidacloprid and its transformation product (imidacloprid-nitroguanidine) in rivers during an irrigating and soil puddling duration. Microchem. J. 153, 12 (2020).Article 
CAS 

Google Scholar 
Hladik, M. L. et al. Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA. Environ. Pollut. 235, 1022–1029 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Jurado, A., Walther, M. & Díaz-Cruz, M. Occurrence, fate and environmental risk assessment of the organic microcontaminants included in the Watch Lists set by EU Decisions 2015/495 and 2018/840 in the groundwater of Spain. Sci. Total Environ. 663, 285–296 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Montagner, C. C. et al. Ten years-snapshot of the occurrence of emerging contaminants in drinking, surface and ground waters and wastewaters from São Paulo State, Brazil. J. Braz. Chem. Soc. 30, 614–632 (2019).CAS 

Google Scholar 
CCME. Council of Ministers of the Environment. Canadian water quality guidelines for the protection of aquatic life. Imidacloprid. In Canadian water quality guidelines, Council of Ministers of the Environment. Winnipeg. https://ccme.ca/en/res/imidacloprid-en-canadian-water-quality-guidelines-for-the-protection-of-aquatic-life.pdf (2007).RIVM. Water quality standards for imidacloprid: Proposal for an update according to the Water Framework Directive in National Institute for Public Health and the Environment. https://www.rivm.nl/bibliotheek/rapporten/270006001.pdf (2014).PAN. Pesticide Action Network. International Consolidated List of Banned Pesticides. https://pan-international.org/pan-international-consolidated-list-of-banned-pesticides/ (2021).Brazil. Secretaria Estadual da Saúde do Rio Grande do Sul. Portaria SES RS nº 320, de 28 de abril de 2014. https://www.cevs.rs.gov.br/upload/arquivos/201705/11110603-portaria-agrotoxicos-n-320-de-28-de-abril-de-2014.pdf. (2014).Kobashi, K. et al. Comparative ecotoxicity of imidacloprid and dinotefuran to aquatic insects in rice mesocosms. Ecotoxicol. Environ. Saf. 138, 122–129 (2017).CAS 
PubMed 
Article 

Google Scholar 
Islam, M. A., Hossen, M. S., Sumon, K. A. & Rahman, M. M. Acute toxicity of imidacloprid on the developmental stages of common carp Cyprinus carpio. Toxicol. Environ. Health Sci. 11, 244–251 (2019).Article 

Google Scholar 
Pérez-Iglesias, J. M. et al. The genotoxic effects of the imidacloprid-based insecticide formulation Glacoxan Imida on Montevideo tree frog Hypsiboas pulchellus tadpoles (Anura, Hylidae). Ecotoxicol. Environ. Saf. 104, 120–126 (2014).PubMed 
Article 
CAS 

Google Scholar 
Sievers, M., Hale, R., Swearer, S. E. & Parris, K. M. Contaminant mixtures interact to impair predator-avoidance behaviours and survival in a larval amphibian. Ecotoxicol. Environ. Saf. 161, 482–488 (2018).CAS 
PubMed 
Article 

Google Scholar 
USEPA. United States Environmental Protection Agency. Aquatic Life Benchmarks and Ecological Risk Assessments for Registered Pesticides. https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/aquatic-life-benchmarks-and-ecological-risk. (2021).Feng, S., Kong, Z., Wang, X., Zhao, L. & Peng, P. Acute toxicity and genotoxicity of two novel pesticides on amphibian, Rana N. Hallwell. Chemosphere 56, 457–463 (2004).ADS 
CAS 
PubMed 
Article 

Google Scholar 
De Arcaute, C. R. et al. Genotoxicity evaluation of the insecticide imidacloprid on circulating blood cells of Montevideo tree frog Hypsiboas pulchellus tadpoles (Anura, Hylidae) by comet and micronucleus bioassays. Ecol. Indic. 45, 632–639 (2014).Article 
CAS 

Google Scholar 
Nkontcheu, D. B. K., Tchamadeu, N. N., Ngealekeleoh, F. & Nchase, S. Ecotoxicological effects of imidacloprid and lambda-cyhalothrin (insecticide) on tadpoles of the African common toad, Amietophrynus regularis (Reuss, 1833) (Amphibia: Bufonidae). Emerg. Sci. J. 1, 49–53 (2017).
Google Scholar 
Bortoluzzi, E. C. et al. Contaminação de águas superficiais por agrotóxicos em função do uso do solo numa microbacia hidrográfica de Agudo, RS. Rev. Bras. Eng. Agric. Ambient. 10, 881–887 (2006).Article 

Google Scholar 
Bortoluzzi, E. C. et al. Investigation of the occurrence of pesticide residues in rural wells and surface water following application to tobacco. Quim. Nova 30, 1872–1876 (2007)CAS 
Article 

Google Scholar 
La, N., Lamers, M., Bannwarth, M., Nguyen, V. V. & Streck, T. Imidacloprid concentrations in paddy rice fields in northern Vietnam: measurement and probabilistic modeling. Paddy Water Environ. 13, 191–203 (2015).Article 

Google Scholar 
Sweeney, M. R., Thompson, C. M. & Popescu, V. D. Sublethal, behavioral, and developmental effects of the neonicotinoid pesticide imidacloprid on larval wood frogs (Rana sylvatica). Environ. Toxicol. Chem. 40, 1838–1847 (2021).Article 
CAS 

Google Scholar 
Gibbons, D., Morrissey, C. & Mineau, P. A review of the direct and indirect effects of neonicotinoids and fipronil on vertebrate wildlife. Environ. Sci. Pollut. Res. 22, 103–118 (2015).CAS 
Article 

Google Scholar 
Morrissey, C. A. et al. Neonicotinoid contamination of global surface waters and associated risk to aquatic invertebrates: A review. Environ. Int. 74, 150920 (2015).Article 
CAS 

Google Scholar 
Stinson, S. A. et al. Agricultural surface water, imidacloprid, and chlorantraniliprole result in altered gene expression and receptor activation in Pimephales promelas. Sci. Total Environ. 806, 150920. (2022).ADS 
CAS 
PubMed 
Article 

Google Scholar 
DiGiacopo, D. G. & Hua, J. Evaluating the fitness consequences of plasticity in tolerance to pesticides. Ecol. Evol. 10, 4448–4456 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Carlson, B. E. & Langkilde, T. Body size variation in aquatic consumers causes pervasive community effects, independent of mean body size. Ecol. Evol. 7, 9978–9990 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Phung, T. X., Nascimento, J. C. S., Novarro, A. J. & Wiens, J. J. Correlated and decoupled evolution of adult and larval body size in frogs. Proc. Royal Soc. B 287, 20201474 (2020).Article 

Google Scholar 
Beasley, V. R. Direct and indirect effects of environmental contaminants on amphibians. In Reference Module in Earth Systems and Environmental Sciences https://doi.org/10.1016/b978-0-12-409548-9.11274-6 (Elsevier, 2020).Toledo, L. F., Sazima, I. & Haddad, C. F. B. Behavioural defences of anurans: An overview. Ethol. Ecol. Evol. 23, 1–25 (2011).Article 

Google Scholar 
Hartmann, M. T., Hartmann, P. A. & Haddad, C. F. B. Reproductive modes and fecundity of an assemblage of anuran amphibians in the Atlantic rainforest, Brazil. Inheringia 100, 207–215 (2010).Article 

Google Scholar 
Pupin, N. C., Gasparini, J. L., Bastos, R. P., Haddad, C. F. B. & Prado, C. P. A. Reproductive biology of an endemic Physalaemus of the Brazilian Atlantic forest, and the trade-off between clutch and egg size in terrestrial breeders of the P. signifer group. Herpetol. J. 20, 147–156 (2010).
Google Scholar 
Pereira, G. & Maneyro, R. Size-fecundity relationships and reproductive investment in females of Physalaemus riograndensis Milstead, 1960 (Anura, Leiuperidae) in Uruguay. Herpetol. J. 22, 145–150 (2012).
Google Scholar 
Tolledo, J., Silva, E. T., Nunes-de-Almeida, C. H. L. & Toledo, L. F. Anomalous tadpoles in a Brazilian oceanic archipelago: implications of oral anomalies on foraging behaviour, food intake and metamorphosis. Herpetol. J. 24, 237–243 (2014).
Google Scholar 
Annibale, F. S. et al. Smooth, striated, or rough: how substrate textures affect the feeding performance of tadpoles with different oral morphologies. Zoomorphology 139, 97–110 (2020).Article 

Google Scholar 
Venesky, M. D., Wassersug, R. J. & Parris, M. J. The impact of variation in labial tooth number on the feeding kinematics of tadpoles of southern leopard frog (Lithobates sphenocephalus). Copeia 3, 481–486 (2010).Article 

Google Scholar 
Venesky, M. D. et al. Comparative feeding kinematics of tropical hylid tadpoles. J. Exp. Biol. 216, 1928–1937 (2013).PubMed 

Google Scholar 
Jones, S. K. C., Munn, A. J., Penman, T. D. & Byrne, P. G. Long-term changes in food availability mediate the effects of temperature on growth, development and survival in striped marsh frog larvae: implications for captive breeding programmes. Conserv. Physiol. 3, cov029 (2015).Article 
CAS 

Google Scholar 
Bach, N. C., Natale, G. S., Somoza, G. M. & Ronco, A. E. Effect on the growth and development and induction of abnormalities by a glyphosate commercial formulation and its active ingredient during two developmental stages of the South-American Creole frog, Leptodactylus latrans. Environ. Sci. Pollut. Res. 23, 23959–23971 (2016).CAS 
Article 

Google Scholar 
Capellán, E. & Nicieza, A. G. Non-equivalence of growth arrest induced by predation risk or food limitation: context-dependent compensatory growth in anuran tadpoles. J. Anim. Ecol. 76, 1026–1035 (2007).PubMed 
Article 

Google Scholar 
Chin, A. M., Hill, D. R., Aurora, M. & Spence, J. R. Morphogenesis and maturation of the embryonic and postnatal intestine. Semin. Cell Dev. Biol. 66, 81–93 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Sun, Y., Zhang, J., Song, W. & Shan, A. Vitamin E alleviates phoxim-induced toxic effects on intestinal oxidative stress, barrier function, and morphological changes in rats. Environ. Sci. Pollut. Res. 25, 26682–26692 (2018).
Google Scholar 
Ouellet, M. Amphibian deformities: current state of knowledge. In Ecotoxicology of Amphibians and Reptiles (eds Sparling, D. W. et al.) 617–661 (Society of Environmental Toxicology and Chemistry, 2000).Hussein, M. & Singh, V. Effect on chick embryos development after exposure to neonicotinoid insecticide imidacloprid. J. Anat. Soc. India 65, 83–89 (2016).Article 

Google Scholar 
Crosby, E. B., Bailey, J. M., Oliveri, A. N. & Levin, E. D. Neurobehavioral impairments caused by developmental imidacloprid exposure in zebrafish. Neurotoxicol. Teratol. 49, 81–90 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lonare, M. et al. Evaluation of imidacloprid-induced neurotoxicity in male rats: A protective effect of curcumin. Neurochem. Int. 78, 122–129 (2014).CAS 
PubMed 
Article 

Google Scholar 
Žegura, B., Lah, T. T. & Filipič, M. The role of reactive oxygen species in microcystin-LR-induced DNA damage. Toxicology 200, 59–68 (2004).PubMed 
Article 
CAS 

Google Scholar 
Odetti, L. M., López González, E. C., Romito, M. L., Simoniello, M. F. & Poletta, G. L. Genotoxicity and oxidative stress in Caiman latirostris hatchlings exposed to pesticide formulations and their mixtures during incubation period. Ecotoxicol. Environ. Saf. 193, 110312 (2020).CAS 
PubMed 
Article 

Google Scholar 
Rutkoski, C. F. et al. Morphological and biochemical traits and mortality in Physalaemus gracilis (Anura: Leptodactylidae) tadpoles exposed to the insecticide chlorpyrifos. Chemosphere 250, 126162 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Herek, J. S. et al. Genotoxic effects of glyphosate on Physalaemus tadpoles. Environ. Toxicol. Pharmacol. 81, 103516 (2021).CAS 
PubMed 
Article 

Google Scholar 
Natale, G. S. et al. Lethal and sublethal effects of the pirimicarb-based formulation Aficida® on Boana pulchella (Duméril and Bibron, 1841) tadpoles (Anura, Hylidae). Ecotoxicol. Environ. Saf. 147, 471–479 (2018)
Google Scholar 
Gilbert, S. F. Developmental Biology, 8th edn. (Sinauer Associates, 2006).Soto, M., García-Santisteban, I., Krenning, L., Medema, R. H. & Raaijmakers, J. A. Chromosomes trapped in micronuclei are liable to segregation errors. J. Cell Sci. 131, 214742 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Crott, J. & Fenech, M. Preliminary study of the genotoxic potential of homocysteine in human lymphocytes in vitro. Mutagenesis 16, 213–217 (2001).CAS 
PubMed 
Article 

Google Scholar 
Benvindo-Souza, M. et al. Micronucleus test in tadpole erythrocytes: Trends in studies and new paths. Chemosphere 240, 124910 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Fenech, M. The in vitro micronucleus technique. Mutat. Res. 455, 81–95 (2000).CAS 
PubMed 
Article 

Google Scholar 
Podratz, J. L. et al. Drosophila melanogaster: A new model to study cisplatin-induced neurotoxicity. Neurobiol. Dis. 43, 330–337 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Iturburu, F. G. et al. Uptake, distribution in different tissues, and genotoxicity of imidacloprid in the freshwater fish Australoheros facetus. Environ. Toxicol. Chem. 36, 699–708 (2017).CAS 
PubMed 
Article 

Google Scholar 
Vieira, C. E. D., Pérez, M. R., Acayaba, R. D. A., Raimundo, C. C. M. & Martinez, C. B. R. DNA damage and oxidative stress induced by imidacloprid exposure in different tissues of the Neotropical fish Prochilodus lineatus. Chemosphere 195, 125–134 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Sanchéz-Bayo, F., Goka, K. & Hayasaka, D. Contamination of the aquatic environment with neonicotinoids and its implication for ecosystems. Front. Environ. Sci. 4, 71 (2016).Article 

Google Scholar 
Wood, T. & Goulson, D. The environmental risks of neonicotinoid pesticides: a review of the evidence post-2013. Environ. Sci. Pollut. Res. 24, 17285–17325 (2017).CAS 
Article 

Google Scholar 
Craddock, H. A., Huang, D., Turner, P.C., Quirós-Alcalá, L. & Payne-Sturges, D. C. Trends in neonicotinoid pesticide residues in food and water in the United States, 1999–2015. Environ. Health 18, 7 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Heyer, R. et al. Leptodactylus latrans. IUCN Red List https://doi.org/10.2305/IUCN.UK.2010-2.RLTS.T57151A11592655.en (2010).Ade, C. M., Boone, M. D. & Puglis, H. J. Effects of an insecticide and potential predators on green frogs and northern cricket frogs. J. Herpetol. 44, 591–600 (2010).Article 

Google Scholar 
Sarkar, M. A., Roy, S., Kole, R. K. & Chowdhury, A. Persistence and metabolism of imidacloprid in different soils of West Bengal. Pest Manag. Sci. 57, 598–602 (2001).CAS 
PubMed 
Article 

Google Scholar 
Goulson, D. Review: An overview of the environmental risks posed by neonicotinoid insecticides. J. Appl. Ecol. 50, 977–987 (2013).Article 

Google Scholar 
Mineau, P. Neonic insecticides and invertebrate species endangerment. In Reference Module in Earth Systems and Environmental Sciences https://doi.org/10.1016/B978-0-12-821139-7.00126-4 (2021).Yamamuro, M. et al. Neonicotinoids disrupt aquatic food webs and decrease fishery yields. Science 366, 620–623 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Gosner. K. L. A simplified table for staging anuran embryos and larvae with notes on identification. Herpetologica 16, 183–190 (1960).
Google Scholar 
Percie-du-Sert, N. et al. The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLoS Biol. 18, e3000410 (2020). CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Herkovits, J. & Pérez-Coll, C. S. AMPHITOX: A customized set of toxicity tests employing amphibian embryos. Symposium on multiple stressor effects in relation to declining amphibian populations. In Multiple Stressor Effects in Relation to Declining Amphibian Populations (eds Linder, G. et al.) 46–60 (ASTM International STP 1443, 2003).Merga, L. B. & Van den Brink, P. J. Ecological effects of imidacloprid on a tropical freshwater ecosystem and subsequent recovery dynamics. Sci. Total Environ. 784, 147167 (2021).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Bonmatin, J.-M. et al. Environmental fate and exposure; neonicotinoids and fipronil. Environ. Sci. Pollut. Res. 22, 35–67 (2015).CAS 
Article 

Google Scholar 
Sumon, K. A. et al. Effects of imidacloprid on the ecology of sub-tropical freshwater microcosms. Environ. Pollut. 236, 432–441 (2018).CONCEA – Conselho Nacional de Controle e Experimentação Animal. Resolução normativa Nº 25, 29 de setembro de 2015. Guia Brasileiro de Produção, Manutenção ou Utilização de Animais para Atividades de Ensino ou Pesquisa Científica do Conselho Nacional de Controle e Experimentação Animal. http://www.mctic.gov.br/mctic/export/sites/institucional/institucional/concea/arquivos/legislacao/resolucoes_normativas/Resolucao-Normativa-CONCEA-n-27-de-23.10.2015-D.O.U.-de-27.10.2015-Secao-I-Pag.-10.pdf. (2015).Rutkoski, C. F. et al. Lethal and sublethal effects of the herbicide atrazine in the early stages of development of Physalaemus gracilis (Anura: Leptodactylidae). Arch. Environ. Contam. Toxicol. 74, 587–593 (2018).CAS 
PubMed 
Article 

Google Scholar 
Pérez-Iglesias, J. M., Soloneski, S., Nikoloff, N., Natale, G. S. & Larramendy, M. L. Toxic and genotoxic effects of the imazethapyr-based herbicide formulation Pivot H® on montevideo tree frog Hypsiboas pulchellus tadpoles (Anura, Hylidae). Ecotoxicol. Environ. Saf. 119, 15–24 (2015).PubMed 
Article 
CAS 

Google Scholar 
Montalvão, M. F. et al. The genotoxicity and cytotoxicity of tannery effluent in bullfrog (Rana catesbeianus). Chemosphere 183, 491–502 (2017).ADS 
PubMed 
Article 
CAS 

Google Scholar  More