Ecology

Lerato Shikwambana from the South African National Space Agency and the University of the Witwatersrand, South Africa, and colleagues also from South Africa compared the wildfire emissions of a strong El Niño event in 2015–2016 and a pronounced La Niña event in 2010–2011. They find that both a strong El Niño and La Niña event can increase emissions from wildfires compared with average years, but they affect different regions, with the effect of La Niña reaching farther south than El Niño. Overall, emissions are stronger during the El Niño phase, mainly driven by higher air temperatures. ENSO variability is expected to increase with future warming, which would also make strong El Niño events more likely. Therefore, these findings indicate that the exposure to wildfire air pollution could grow in southern Africa. More

Jolles, J. W., King, A. J. & Killen, S. S. The Role of Individual Heterogeneity in Collective Animal Behaviour. Trends Ecol. Evol. 35, 278–291 (2020).Article 
PubMed 

Google Scholar 
Lang, S. D. J. & Farine, D. R. A multidimensional framework for studying social predation strategies. Nat. Ecol. Evol. 1, 1230–1239 (2017).Article 
PubMed 

Google Scholar 
Kissui, B. M. & Packer, C. Top–down population regulation of a top predator: lions in the Ngorongoro Crater. Proc. R. Soc. Lond. Ser. B Biol. Sci. 271, 1867–1874 (2004).Article 

Google Scholar 
Atwood, T. C. & Gese, E. M. Coyotes and recolonizing wolves: social rank mediates risk-conditional behaviour at ungulate carcasses. Anim. Behav. 75, 753–762 (2008).Article 

Google Scholar 
Pitman, R. L. & Durban, J. W. Cooperative hunting behavior, prey selectivity and prey handling by pack ice killer whales (Orcinus orca), type B, in Antarctic Peninsula waters. Mar. Mammal. Sci. 28, 16–36 (2012).Article 

Google Scholar 
Machovsky-Capuska, G. E. & Raubenheimer, D. The nutritional ecology of marine apex predators. Ann. Rev. Mar. Sci. 12, 361–387 (2020).Article 
PubMed 

Google Scholar 
Hubel, T. Y. et al. Energy cost and return for hunting in African wild dogs and cheetahs. Nat. Commun. 7, 1–13 (2016).Article 

Google Scholar 
Hubel, T. Y. et al. Additive opportunistic capture explains group hunting benefits in African wild dogs. Nat. Commun. 7, 1–11 (2016).Article 

Google Scholar 
Schaller, G. B. The Serengeti Lion.,(University of Chicago Press: Chicago, IL.). (1972).Packer, C., Pusey, A. E. & Eberly, L. E. Egalitarianism in female African lions. Science 293, 690–693 (2001).Article 
CAS 
PubMed 

Google Scholar 
Tilson, R. L. & Hamilton, W. J. III Social dominance and feeding patterns of spotted hyaenas. Anim. Behav. 32, 715–724 (1984).Article 

Google Scholar 
Frank, L. G. Social organization of the spotted hyaena Crocuta crocuta. II. Dominance and reproduction. Anim. Behav. 34, 1510–1527 (1986).Article 

Google Scholar 
Mech, L. D. & Boitani, L. Wolves: behavior, ecology, and conservation. (University of Chicago Press, 2007).Frame, L. H., Malcolm, J. R., Frame, G. W. & Van Lawick, H. Social Organization of African Wild Dog on the Serengeti Plains. Z. Tierpsychol. 50, 225–249 (1979).Article 

Google Scholar 
Bertram, B. C. R. Social factors influencing reproduction in wild lions. J. Zool. 177, 463–482 (1975).Article 

Google Scholar 
Packer, C. & Pusey, A. Asymmetric contests in social mammals: respect, manipulation and age-specific aspects. Evol. essays honour John Maynard Smith 173–186 (1985).Domenici, P., Batty, R. S., Similä, T. & Ogam, E. Killer whales (Orcinus orca) feeding on schooling herring (Clupea harengus) using underwater tail-slaps: Kinematic analyses of field observations. J. Exp. Biol. 203, 283–294 (2000).Article 
CAS 
PubMed 

Google Scholar 
Benoit-Bird, K. J. & Au, W. W. L. Cooperative prey herding by the pelagic dolphin, Stenella longirostris. J. Acoust. Soc. Am. 125, 125–137 (2009).Article 
PubMed 

Google Scholar 
Gazda, S. K. Driver-barrier feeding behavior in bottlenose dolphins (Tursiops truncatus): New insights from a longitudinal study. Mar. Mammal. Sci. 32, 1152–1160 (2016).Article 

Google Scholar 
Herbert-Read, J. E. et al. Proto-Cooperation: Group hunting sailfish improve hunting success by alternating attacks on grouping prey. Proc. R. Soc. B Biol. Sci. 283, 1–14 (2016).
Google Scholar 
Rieucau, G., Holmin, A. J., Castillo, J. C., Couzin, I. D. & Handegard, N. O. School level structural and dynamic adjustments to risk promote information transfer and collective evasion in herring. Anim. Behav. 117, 69–78 (2016).Article 

Google Scholar 
Rieucau, G., Fernö, A., Ioannou, C. C. & Handegard, N. O. Towards of a firmer explanation of large shoal formation, maintenance and collective reactions in marine fish. Rev. Fish. Biol. Fish. 25, 21–37 (2014).Article 

Google Scholar 
Ford, J. K. B. & Ellis, G. M. Transients: mammal-hunting killer whales of British Columbia, Washington, and southeastern Alaska. (UBC Press, 1999).Bailey, I., Myatt, J. P. & Wilson, A. M. Group hunting within the Carnivora: Physiological, cognitive and environmental influences on strategy and cooperation. Behav. Ecol. Sociobiol. 67, 1–17 (2013).Article 

Google Scholar 
Packer, C., Scheel, D. & Pusey, A. E. Why Lions Form Groups: Food is Not Enough. Am. Nat. 136, 1–19 (1990).Article 

Google Scholar 
Creel, S. & Creel, N. M. The African wild dog: behavior, ecology, and conservation. (Princeton University Press, 2002).Carbone, C. et al. Feeding success of African wild dogs (Lycaon pictus) in the Serengeti: The effects of group size and kleptoparasitism. J. Zool. 266, 153–161 (2005).Article 

Google Scholar 
Chakrabarti, S. & Jhala, Y. V. Selfish partners: Resource partitioning in male coalitions of Asiatic lions. Behav. Ecol. 28, 1532–1539 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Amorós, M., Gil-Sánchez, J. M., López-Pastor, B., de las, N. & Moleón, M. Hyaenas and lions: how the largest African carnivores interact at carcasses. Oikos 129, 1820–1832 (2020).Article 

Google Scholar 
Wilmers, C. C. & Stahler, D. R. Constraints on active-consumption rates in gray wolves, coyotes, and grizzly bears. Can. J. Zool. 80, 1256–1261 (2002).Article 

Google Scholar 
Schmidt, P. A. & Mech, L. D. Wolf pack size and food acquisition. Am. Nat. 150, 513–517 (1997).Article 
CAS 
PubMed 

Google Scholar 
Major, P. F. Predator-prey interactions in two schooling fishes, Caranx ignobilis and Stolephorus purpureus. Anim. Behav. 26, 760–777 (1978).Article 

Google Scholar 
Thiebault, A., Semeria, M., Lett, C. & Tremblay, Y. How to capture fish in a school? Effect of successive predator attacks on seabird feeding success. J. Anim. Ecol. 85, 157–167 (2016).Article 
PubMed 

Google Scholar 
Handegard, N. O. et al. The dynamics of coordinated group hunting and collective information transfer among schooling prey. Curr. Biol. 22, 1213–1217 (2012).Article 
CAS 
PubMed 

Google Scholar 
King, A. J., Fehlmann, G., Biro, D., Ward, A. J. & Fürtbauer, I. Re-wilding Collective Behaviour: An Ecological Perspective. Trends Ecol. Evol. 33, 347–357 (2018).Article 
PubMed 

Google Scholar 
Hansen, M. J. et al. Linking hunting weaponry to attack strategies in sailfish and striped marlin. Proc. R. Soc. B Biol. Sci. 287, 20192228 (2020).Rieucau, G. et al. Using unmanned aerial vehicle (UAV) surveys and image analysis in the study of large surface-associated marine species: a case study on reef sharks Carcharhinus melanopterus shoaling behaviour. J. Fish. Biol. 93, 119–127 (2018).Article 
PubMed 

Google Scholar 
Krause, J. The relationship between foraging and shoal position in a mixed shoal of roach (Rutilus rutilus) and chub (Leuciscus cephalus): a field study. Oecologia 93, 356–359 (1993).Article 
PubMed 

Google Scholar 
DeBlois, E. M. & Rose, G. A. Cross-shoal variability in the feeding habits of migrating Atlantic cod (Gadus morhua). Oecologia 108, 192–196 (1996).Article 
PubMed 

Google Scholar 
Hansen, M. J., Schaerf, T. M. & Ward, A. J. W. The influence of nutritional state on individual and group movement behaviour in shoals of crimson-spotted rainbowfish (Melanotaenia duboulayi). Behav. Ecol. Sociobiol. 69, 1713–1722 (2015).Article 

Google Scholar 
Hansen, M. J., Schaerf, T. M., Krause, J. & Ward, A. J. W. Crimson spotted rainbowfish (Melanotaenia duboulayi) change their spatial position according to nutritional requirement. PLoS One 11, 1–17 (2016).Article 

Google Scholar 
McLean, S., Persson, A., Norin, T. & Killen, S. S. Metabolic costs of feeding predictively alter the spatial distribution of individuals in fish schools. Curr. Biol. 28, 1144–1149 (2018).Article 
CAS 
PubMed 

Google Scholar 
Domenici, P. et al. How sailfish use their bills to capture schooling prey. Proc. R. Soc. B Biol. Sci. 281, 20140444 (2014).Kurvers, R. H. J. M. et al. The Evolution of Lateralization in Group Hunting Sailfish. Curr. Biol. 27, 521–526 (2017).Article 
CAS 
PubMed 

Google Scholar 
Ward, A. & Webster, M. Sociality: The behaviour of group-living animals. (Springer, 2016).Wiley, D. et al. Underwater components of humpback whale bubble-net feeding behaviour Published by: Brill Stable URL: http://www.jstor.org/stable/23034261 REFERENCES Linked references are available on JSTOR for this article: You may need to log in to JSTOR to access th. 148, 575–602 (2017).D’Vincent, C. G., Nilson, R. M. & Hanna, R. E. Vocalization and coordinated feeding behavior of the humpback whale Megaptera novaeangliae in Southeastern Alaska, USA. Sci. Rep. Whale Res. Inst. Tokyo 36, 41–47 (1985).
Google Scholar 
Jurasz, C. M. & Jurasz, V. P. Feeding modes of the humpback whale, Megaptera novaeangliae, in southeast Alaska. Sci. Rep. Whales Res. Inst. 31, 69–83 (1979).
Google Scholar 
Similä, T. & Ugarte, F. Surface and underwater observations of cooperatively feeding killer whales in northern Norway. Can. J. Zool. 71, 1494–1499 (1993).Article 

Google Scholar 
Clua, É. & Grosvalet, F. Mixed-species feeding aggregation of dolphins, large tunas and seabirds in the Azores. Aquat. Living Resour. 14, 11–18 (2001).Article 

Google Scholar 
Uchiyama, J. H. & Kazama, T. K. Updated weight-on-length relationships for pelagic fishes caught in the central North Pacific Ocean and bottomfishes from the northwestern Hawaiian Islands. (2003).Ponce-Díaz, G., Ortega-García, S. & González-Ramírez, P. G. Analysis of sizes and weight-length relation of the striped marlin, Tetrapturus sudax (Philippi, 1887) in Baja California Sur, Mexico. Cienc. Mar. 17, 69–82 (1991).Article 

Google Scholar 
Abitı́a-Cárdenas, L. A., Muhlia-Melo, A., Cruz-Escalona, V. & Galván-Magaña, F. Trophic dynamics and seasonal energetics of striped marlin Tetrapturus audax in the southern Gulf of California, Mexico. Fish. Res. 57, 287–295 (2002).Article 

Google Scholar 
R Core Team. (2021). R: A Language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/Hansen, Matthew Mechanisms prey Div. a Mar. group-Hunt. Predat., Dryad, Dataset https://doi.org/10.5061/dryad.b2rbnzshx (2022).Article 

Google Scholar  More

Study speciesTo increase our ability to generalize the results, we conducted two multispecies experiments34. The experiments were designed independently, but, as they used similar treatments, we analyzed them jointly to further increase generalizability. For the experiment in China, we selected eight species that are either native or non-native in China (Supplementary Table 1). For the experiment in Germany, we selected 16 species that are either native or non-native in Germany (Supplementary Table 1). All 24 species, representing seven families, are herbaceous, mainly occur in grasslands, and are common in the respective regions. To control for phylogenetic non-independence of species, we selected at least one non-native and one native species in each of the seven families. All non-native species are fully established (i.e. naturalized sensu Richardson et al.35) in the country where the respective experiment was conducted, and, as they are common, most of them could be considered invasive36,37. We classified the species as naturalized non-native or native to China or Germany based on the following databases: (1) “The Checklist of the Alien Invasive Plants in China”38, (2) the Flora of China (www.efloras.org), and (3) BiolFlor (www.ufz.de/biolflor). Seeds or stem fragments of the study species were obtained from local botanical gardens, local commercial seed companies, or from wild populations (Supplementary Table 1).The experiment in ChinaFrom 21 May to 27 June 2020, we planted or sowed the eight study species into plastic trays filled with potting soil (Pindstrup Plus, Pindstrup Mosebrug A/S, Denmark). We sowed the species at different times (Supplementary Table 1) because they were known to require different times until germination. Three species were grown from stem fragments because they mainly rely on clonal propagation, and the others were propagated from seeds (Supplementary Table 1).On 13 July 2020, we transplanted the cuttings or seedlings into 2.5-L circular plastic pots filled with a mixture of sand and vermiculite (1:1 v/v). Three competition treatments were imposed: (1) competition-free, in which plants were grown alone; (2) intraspecific competition, in which two individuals of the same species were grown together; (3) interspecific competition, in which two individuals, each from a different species were grown together. We grew all eight species without competition, in intraspecific competition, and in all 28 possible pairs of interspecific competition. For the competition-free and intraspecific-competition treatments, we replicated each species seven times (i.e. we had seven technical replicates). For the interspecific-competition treatment, for which we had many pairs of species (i.e. biological replicates), we replicated each pair two times.The experiment took place in a greenhouse at the Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences (Changchun, China). The greenhouse had a transparent plastic film on the top, which reduced the ambient light intensity by 12%. It was open on the sides so that insects and other organisms could enter. To vary nutrient availability, we applied to each pot either 5 g (low-nutrient treatment) or 10 g (high-nutrient treatment) of a slow-release fertilizer (Osmocote® Exact Standard, Everris International B.V., Geldermalsen, The Netherlands; 15% N + 9% P2O5 + 12% K2O + 2% MgO + trace elements). To vary light availability, we used two cages (size: 9 m × 4.05 m × 1.8 m). One of them was covered with two layers of black netting material, which reduced the light intensity by 71% (low light-intensity treatment, where the light intensity was on average 233.5 μmol m−2 s−1, measured on a sunny day). The other was left uncovered (high light-intensity treatment, where the light intensity was on average 826.7 μmol m−2 s−1).The experiment included a total of 672 pots ([8 no-competition × 7 replicates + 8 intraspecific-competition × 7 replicates + 28 interspecific-competition × 2 replicates]×2 nutrient treatments × 2 light treatments). The pots were randomly assigned to positions and were randomized once on 15 August within each block (i.e. the low or high light-intensity treatment). The initial height of each plant was measured on 15 July 2020, two days after the transplanting. We watered the plants daily to avoid water limitations. On 1 September 2020, we harvested the aboveground biomass of all plants. The biomass was dried at 65°C for 72 h to constant weight and then weighed to the nearest mg.The experiment in GermanyOn 15 June 2020, we sowed seeds of the 16 species into plastic trays filled with potting soil (Topferde, Einheitserde Co). On 6 July 2020, we transplanted the seedlings into 1.5-L pots filled with a mixture of potting soil and sand (1:1 v/v). Like the experiment in China, we imposed three competition treatments: competition-free, intraspecific competition, and interspecific competition. However, in this experiment, which had two times more species than the experiment in China, we only included 24 randomly chosen species pairs for the interspecific-competition treatment, and all of these pairs consisted of one naturalized non-native and one native species. For the competition-free treatment, we replicated each species two times (i.e. we had two technical replicates). For the competition treatments, we did not use technical replicates for any of the species combinations for logistic reasons. However, as we had a large number of species pairs in the inter-specific competition treatment, we had many biological replicates.The experiment took place outdoors in the Botanical Garden of the University of Konstanz (Konstanz, Germany). To vary nutrient availability, we applied to each pot once a week either 100 ml of a low-concentration liquid fertilizer (low-nutrient treatment; 0.5‰ Universol ® Blue oxide fertilizer, 18% N + 11% P + 18% K + 2.5% MgO + trace elements) or 100 ml of a high-concentration of the same liquid fertilizer (high-nutrient treatment; 1‰). In total, pots in the low- and high-nutrient treatment received 0.4 and 0.8 g fertilizer, respectively. To vary light availability, we used eight metal wire cages (size: 2 m × 2 m × 2 m). Four of the cages were covered with one layer of white and one layer of green netting material, which reduced the ambient light intensity by 84% (low light-intensity treatment; where the light intensity was on average 219.0 μmol m−2 s−1, measured on a sunny day). The remaining four cages were covered only with one layer of the white netting material, which served as a positive control for the effect of netting and reduced light intensity by 53% (high light-intensity treatment; where the light intensity was on average 678.4 μmol m−2 s−1). In other words, the low light-intensity treatment received 34% (66% reduction) of the light intensity in the high light-intensity treatment.The experiment included a total of 320 pots ([16 no-competition × 2 replicates + 16 intraspecific-competition + 32 interspecific-competition]×2 nutrient treatments × 2 light treatments). The eight cages were randomly assigned to fixed positions in the botanical garden. The pots were randomly assigned to the eight cages (40 pots in each cage) and were re-randomized once within and across cages of the same light treatment on 3 August 2020. Besides the weekly fertilization, we watered the plants two or three times a week to avoid water limitations. On 7 and 8 September 2020, we harvested the aboveground biomass of all plants. The biomass was dried at 70 °C for 96 h to constant weight and then weighed to the nearest 0.1 mg.Statistical analysesAll analyses were performed using R version 3.6.139. To test whether resource availability affected competitive outcomes between native and non-native species, we applied linear mixed-effects models to analyze the biomass of the plants in the two experiments jointly and separately, using the nlme package40. For the model used to analyze the two experiments jointly, we excluded interspecific competition between two non-natives and interspecific competition between two natives from the experiment in China, because non-native-non-native and native-non-native combinations were not included in the experiment in Germany. When we analyzed each experiment separately, the results were overall similar to the results of the joint analysis. Therefore, we focus in the manuscript on the joint analysis and present the results of the separate analyses in Supplementary Note 2.Because plant mortality was low and mainly happened after transplanting, we excluded pots in which plants had died. The final dataset contained 1180 individuals from 871 pots. In the model, we included the aboveground biomass of individuals as the response variable. We included the origin of the species (non-native or native), competition treatment (see below for details), nutrient treatment, light treatment and their interactions as fixed effects; study site (China or Germany), and identity and family of the species as random effects. In addition, we allowed each species to respond differently to the nutrient and light treatments (i.e. we included random slopes). To account for pseudoreplication41, we also included pots as random effects and cages (ten cages, eight from Germany and two from China) as random block effects. In the competition treatment, we had three levels: (1) no competition, (2) intraspecific competition, and (3) interspecific competition between native and non-native species. To split them into two contrasts, we created two variables42 testings (1) the effect of the presence of competitors, and (2) the difference between intra- and interspecific competition (see Supplementary Note 3 for details). To improve the normality of the residuals, we natural-log-transformed aboveground biomass. To improve the homoscedasticity of the residuals, we allowed the species and competition treatment to have different variances by using the varComb and varIdent functions43. Significances of the fixed effects were assessed with likelihood-ratio tests (type II) with the car package44.To determine the ‘competitive outcome’, i.e. which species will exclude or dominate over the other species at the endpoint for the community45,46, one should ideally conduct a long-term study. Alternatively, one could vary the density of each species, which mimics the dynamics of species populations across time (see refs. 47,48 for examples). However, applying this space-for-time-substitution method would have largely increased the size of the experiment, especially when combined with the light and nutrient treatments. Still, by growing plants alone, in intraspecific competition and in interspecific competition, our experiments meet the minimal requirement for measuring competitive outcome, at least in terms of short-term biomass production46,49.In the linear mixed-effects model of individual biomass, a significant effect of origin would indicate that native and naturalized non-native species differed in their biomass production, across all competition and resource-availability (light and nutrients) treatments. This would tell us the competitive outcome between non-natives and natives across different resource availabilities. For example, an overall higher level of biomass production of non-native species would indicate that non-natives would dominate when competing with natives. A significant interaction between a resource-availability treatment and the origin of the species would indicate that resource availability affects the biomass production of native and non-native species differently, averaged across all competition treatments. In other words, it would indicate that resource availability affects the competitive outcome between natives and non-natives. A significant interaction between a resource-availability treatment and the competition treatment would indicate that resource availabilities modify the effect of competition (e.g. no competition vs. competition). Other studies frequently have inferred competitive outcomes from the effect of competition by calculating the relative interaction intensity50. However, while the competitive outcome and effect of competition are often related, they are not equivalent45. This is because the competitive outcome is both determined by the effect of competition and intrinsic growth rate48,49. For example, a plant species that strongly suppress other species but has a low intrinsic growth rate still cannot dominate the community.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Hayes, S. M. & McCullough, E. A. Critical minerals: A review of elemental trends in comprehensive criticality studies. Resour. Policy 59, 192–199 (2018).
Google Scholar 
Saatz, J., Vetterlein, D., Mattusch, J., Otto, M. & Daus, B. The influence of gadolinium and yttrium on biomass production and nutrient balance of maize plants. Environ. Pollut. 204, 32–38 (2015).CAS 
PubMed 

Google Scholar 
Gonzalez, V., Vignati, D. A. L., Leyval, C. & Giamberini, L. Environmental fate and ecotoxicity of lanthanides: Are they a uniform group beyond chemistry? Environ. Int. 71, 148–157 (2014).CAS 
PubMed 

Google Scholar 
Kovarikova, M., Tomaskova, I. & Soudek, P. Rare earth elements in plants. Biol. Plant. 63, 20–32 (2019).CAS 

Google Scholar 
Thomas, P. J., Carpenter, D., Boutin, C. & Allison, J. E. Rare earth elements (REEs): Effects on germination and growth of selected crop and native plant species. Chemosphere 96, 57–66 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Ramos, S. J. et al. Rare earth elements in the soil environment. Curr. Pollut. Rep. 2, 28–50 (2016).CAS 

Google Scholar 
Carpenter, D., Boutin, C., Allison, J. E., Parsons, J. L. & Ellis, D. M. Uptake and effects of six rare earth elements (REEs) on selected native and crop species growing in contaminated soils. PLoS ONE 10, e0129936 (2015).PubMed 
PubMed Central 

Google Scholar 
Kotelnikova, A., Fastovets, I., Rogova, O. & Volkov, D. S. La, Ce and Nd in the soil-plant system in a vegetation experiment with barley (Hordeum vulgare L.). Ecotoxicol. Environ. Saf. 206, 111193 (2020).CAS 
PubMed 

Google Scholar 
Hu, Z., Richter, H., Sparovek, G. & Schnug, E. Physiological and biochemical effects of rare earth elements on plants and their agricultural significance: A review. J. Plant Nutr. 27, 183–220 (2004).CAS 

Google Scholar 
Tao, Y. et al. Distribution of rare earth elements (REEs) and their roles in plant growth: A review. Environ. Pollut. 298, 118540 (2022).CAS 
PubMed 

Google Scholar 
Tyler, G. Rare earth elements in soil and plant systems—A review. Plant Soil 267, 191–206 (2004).CAS 

Google Scholar 
Ding, S. et al. Fractionation mechanisms of rare earth elements (REEs) in hydroponic wheat: An application for metal accumulation by plants. Environ. Sci. Technol. 40, 2686–2691 (2006).ADS 
CAS 
PubMed 

Google Scholar 
Grosjean, N. et al. Accumulation and fractionation of rare earth elements are conserved traits in the Phytolacca genus. Sci. Rep. 9, 18458 (2019).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Yuan, M. et al. Accumulation and fractionation of rare earth elements (REEs) in the naturally grown Phytolacca americana L. in southern China. Int. J. Phytoremediat. 20, 415–423 (2018).CAS 

Google Scholar 
Yuan, M. et al. The accumulation and fractionation of rare earth elements in hydroponically grown Phytolacca americana L.. Plant Soil 421, 67–82 (2017).CAS 

Google Scholar 
Liu, C. et al. Element case studies: Rare earth elements. In Agromining: Farming for Metals (eds Van der Ent, A. et al.) 297–308 (Springer, 2018).
Google Scholar 
Purwadi, I., Nkrumah, P. N., Paul, A. L. D. & van der Ent, A. Uptake of yttrium, lanthanum and neodymium in Melastoma malabathricum and Dicranopteris linearis from Malaysia. Chemoecology 31, 335–342 (2021).CAS 

Google Scholar 
Shan, X. et al. Accumulation and uptake of light rare earth elements in a hyperaccumulator Dicropteris dichotoma. Plant Sci. 165, 1343–1353 (2003).CAS 

Google Scholar 
Wu, J., Chen, A., Peng, S., Wei, Z. & Liu, G. Identification and application of amino acids as chelators in phytoremediation of rare earth elements lanthanum and yttrium. Plant Soil 373, 329–338 (2013).CAS 

Google Scholar 
Zhenggui, W. et al. Rare earth elements in naturally grown fern Dicranopteris linearis in relation to their variation in soils in South-Jiangxi region (Southern China). Environ. Pollut. 114, 345–355 (2001).
Google Scholar 
Okoroafor, P. U., Ogunkunle, C. O., Heilmeier, H. & Wiche, O. Phytoaccumulation potential of nine plant species for selected nutrients, rare earth elements (REEs), germanium (Ge), and potentially toxic elements (PTEs) in soil. Int. J. Phytoremediat. 24, 1310–1320 (2022).CAS 

Google Scholar 
Taggart, R. K. et al. Differences in bulk and microscale yttrium speciation in coal combustion fly ash. Environ. Sci. Process. Impacts 20, 1390–1403 (2018).CAS 
PubMed 

Google Scholar 
Fehlauer, T. et al. Uptake patterns of critical metals in alpine plant species growing in an unimpaired natural site. Chemosphere 287, 132315 (2022).ADS 
CAS 
PubMed 

Google Scholar 
Liu, W.-S. et al. Spatially resolved localization of lanthanum and cerium in the rare earth element hyperaccumulator fern Dicranopteris linearis from China. Environ. Sci. Technol. 54, 2287–2294 (2020).ADS 
CAS 
PubMed 

Google Scholar 
Saatz, J. et al. Location and speciation of gadolinium and yttrium in roots of Zea mays by LA-ICP-MS and ToF-SIMS. Environ. Pollut. 216, 245–252 (2016).CAS 
PubMed 

Google Scholar 
Mantienne, J. L. Minéralisation thallifère de Jas Roux (Hautes-Alpes)—Alpes françaises (Université Pierre et Marie Curie—Paris VI, 1974).
Google Scholar 
Kabata-Pendias, A. Trace Elements in Soils and Plants (CRC Press, 2011).
Google Scholar 
Kastori, R., Maksimovic, I., Zeremski-Skoric, T. & Putnik-Delic, M. Rare earth elements: Yttrium and higher plants. Zb. Matice Srp. Za Prir. Nauke 118, 87–98 (2010).Salminen, R., Vos, W. D. & Tarvainen, T. Geochemical Atlas of Europe—Part 1: Background Information, Methodology and Maps (Geological Survey of Finland, 2005).
Google Scholar 
Soil Quality—Leaching Procedures for Subsequent Chemical and Ecotoxicological Testing of Soil and Soil-Like Materials—Part 2: Batch Test Using a Liquid to Solid Ratio of 10 l/kg Dry Matter. https://doi.org/10.31030/3069638 (2020).R Core Team. R: A Language and Environment for Statistical Computing (2021).RStudio Team. RStudio: Integrated Development Environment for R (RStudio, PBC, 2020).
Google Scholar 
Radziemska, M., Vaverková, M. & Baryła, A. Phytostabilization—Management strategy for stabilizing trace elements in contaminated soils. Int. J. Environ. Res. Public Health 14, 958 (2017).PubMed Central 

Google Scholar 
Somogyi, A. et al. Optical design and multi-length-scale scanning spectro-microscopy possibilities at the Nanoscopium beamline of Synchrotron Soleil. J. Synchrotron Radiat. 22, 1118–1129 (2015).CAS 
PubMed 

Google Scholar 
Sancho-Tomás, M. et al. Geochemical evidence for arsenic cycling in living microbialites of a high altitude Andean Lake (Laguna Diamante, Argentina). Chem. Geol. 549, 11 (2020).
Google Scholar 
Medjoubi, K. et al. Development of fast, simultaneous and multi-technique scanning hard X-ray microscopy at Synchrotron Soleil. J. Synchrotron Radiat. 20, 293–299 (2013).CAS 
PubMed 

Google Scholar 
Aubineau, J. et al. Microbially induced potassium enrichment in Paleoproterozoic shales and implications for reverse weathering on early Earth. Nat. Commun. 10, 2670 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
Schindelin, J. et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).CAS 
PubMed 

Google Scholar 
Solé, V. A., Papillon, E., Cotte, M., Walter, Ph. & Susini, J. A multiplatform code for the analysis of energy-dispersive X-ray fluorescence spectra. Spectrochim. Acta B At. Spectrosc. 62, 63–68 (2007).ADS 

Google Scholar 
Hahsler, M., Piekenbrock, M. & Doran, D. dbscan: Fast density-based clustering with R. J. Stat. Softw. 91, 1 (2019).
Google Scholar 
Hennig, C. fpc: Flexible Procedures for Clustering (2020).Kassambara, A. & Mundt, F. factoextra: Extract and Visualize the Results of Multivariate Data Analyses (2020).Lê, S., Josse, J. & Husson, F. FactoMineR: A package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).
Google Scholar 
Revelle, W. psych: Procedures for Psychological, Psychometric, and Personality Research (2021).Wei, T. & Simko, V. R Package ‘corrplot’: Visualization of a Correlation Matrix (2021).van der Ent, A. et al. (eds) Agromining: Farming for Metals: Extracting Unconventional Resources Using Plants (Springer, 2021).
Google Scholar 
Liu, C. et al. Simultaneous hyperaccumulation of rare earth elements, manganese and aluminum in Phytolacca americana in response to soil properties. Chemosphere 282, 131096 (2021).ADS 
CAS 
PubMed 

Google Scholar 
Han, F. et al. Organic acids promote the uptake of lanthanum by barley roots. New Phytol. 165, 481–492 (2005).CAS 
PubMed 

Google Scholar 
Ruíz-Herrera, L. F., Sánchez-Calderón, L., Herrera-Estrella, L. & López-Bucio, J. Rare earth elements lanthanum and gadolinium induce phosphate-deficiency responses in Arabidopsis thaliana seedlings. Plant Soil 353, 231–247 (2012).
Google Scholar 
González-Guerrero, M., Escudero, V., Saéz, Á. & Tejada-Jiménez, M. Transition metal transport in plants and associated endosymbionts: Arbuscular mycorrhizal fungi and rhizobia. Front. Plant Sci. 7, 1088 (2016).PubMed 
PubMed Central 

Google Scholar 
Jogawat, A., Yadav, B., Chhaya, & Narayan, O. P. Metal transporters in organelles and their roles in heavy metal transportation and sequestration mechanisms in plants. Physiol. Plant. 173, 259–275. https://doi.org/10.1111/ppl.13370 (2021).Article 
CAS 
PubMed 

Google Scholar 
Krämer, U., Talke, I. N. & Hanikenne, M. Transition metal transport. FEBS Lett. 581, 2263–2272 (2007).PubMed 

Google Scholar 
Tuduri, J. et al. Lumière sur la géologie des terres rares, pourquoi tant d’attraits? Géologues 204, 48–54 (2020).
Google Scholar 
Tiziani, R. et al. Root handling affects carboxylates exudation and phosphate uptake of white lupin roots. Front. Plant Sci. 11, 584568 (2020).PubMed 
PubMed Central 

Google Scholar 
Lambers, H., Hayes, P. E., Laliberté, E., Oliveira, R. S. & Turner, B. L. Leaf manganese accumulation and phosphorus-acquisition efficiency. Trends Plant Sci. 20, 83–90 (2015).CAS 
PubMed 

Google Scholar 
Wen, Z. et al. In addition to foliar manganese concentration, both iron and zinc provide proxies for rhizosheath carboxylates in chickpea under low phosphorus supply. Plant Soil 465, 31–46 (2021).CAS 

Google Scholar 
Wiche, O., Kummer, N.-A. & Heilmeier, H. Interspecific root interactions between white lupin and barley enhance the uptake of rare earth elements (REEs) and nutrients in shoots of barley. Plant Soil 402, 235–245 (2016).CAS 

Google Scholar 
Chen, A., Husted, S., Salt, D. E., Schjoerring, J. K. & Persson, D. P. The intensity of manganese deficiency strongly affects root endodermal suberization and ion homeostasis. Plant Physiol. 181, 729–742 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rengel, Z. et al. (eds) Marschner’s Mineral Nutrition of Higher Plants (Elsevier, 2012).
Google Scholar 
Brioschi, L. et al. Transfer of rare earth elements (REE) from natural soil to plant systems: Implications for the environmental availability of anthropogenic REE. Plant Soil 366, 143–163 (2013).CAS 

Google Scholar 
Bojórquez-Quintal, E., Escalante-Magaña, C., Echevarría-Machado, I. & Martínez-Estévez, M. Aluminum, a friend or foe of higher plants in acid soils. Front. Plant Sci. 8, 1767 (2017).PubMed 
PubMed Central 

Google Scholar 
St-Cyr, L. & Campbell, P. G. C. Metals (Fe, Mn, Zn) in the root plaque of submerged aquatic plants collected in situ: Relations with metal concentrations in the adjacent sediments and in the root tissue. Biogeochemistry 33, 969 (1996).
Google Scholar 
Tripathi, R. D. et al. Roles for root iron plaque in sequestration and uptake of heavy metals and metalloids in aquatic and wetland plants. Metallomics 6, 1789–1800 (2014).CAS 
PubMed 

Google Scholar 
Pourret, O. et al. The ‘europium anomaly’ in plants: Facts and fiction. Plant Soil 476, 721–728 (2022).CAS 

Google Scholar 
Liu, C. et al. The limited exclusion and efficient translocation mediated by organic acids contribute to rare earth element hyperaccumulation in Phytolacca americana. Sci. Total Environ. 805, 150335 (2022).ADS 
CAS 
PubMed 

Google Scholar 
Poschenrieder, C., Busoms, S. & Barceló, J. How plants handle trivalent (+3) elements. Int. J. Mol. Sci. 20, 3984 (2019).CAS 
PubMed Central 

Google Scholar 
Ma, J. F. & Hiradate, S. Form of aluminium for uptake and translocation in buckwheat (Fagopyrum esculentum Moench). Planta 211, 355–360 (2000).CAS 
PubMed 

Google Scholar 
Rellán-Álvarez, R. et al. Identification of a tri-iron(III), tri-citrate complex in the xylem sap of iron-deficient tomato resupplied with iron: New insights into plant iron long-distance transport. Plant Cell Physiol. 51, 91–102 (2010).PubMed 

Google Scholar 
Ding, S. et al. Role of ligands in accumulation and fractionation of rare earth elements in plants: Examples of phosphate and citrate. Biol. Trace Elem. Res. 107, 073–086 (2005).CAS 

Google Scholar 
Wu, J., Wei, Z., Zhao, H., Li, H. & Hu, F. The role of amino acids in the long-distance transport of La and Y in the xylem sap of tomato. Biol. Trace Elem. Res. 129, 239–250 (2009).CAS 
PubMed 

Google Scholar 
Singh, S. Guttation: New insights into agricultural implications. In Advances in Agronomy Vol. 128 (ed. Sparks, D. L.) 97–135 (Elsevier, 2014).
Google Scholar 
Hossain, Md. B., Sawada, A., Noda, K. & Kawasaki, M. Hydathode function and changes in contents of elements in eddo exposed to zinc in hydroponic solution. Plant Prod. Sci. 20, 423–433 (2017).CAS 

Google Scholar 
Singh, S. Guttation: Path, principles and functions. Aust. J. Bot. 61, 497 (2013).
Google Scholar 
Wightman, R., Wallis, S. & Aston, P. Leaf margin organisation and the existence of vaterite-producing hydathodes in the alpine plant Saxifraga scardica. Flora 241, 27–34 (2018).
Google Scholar 
Brüggemann, W., Maas-Kantel, K. & Moog, P. R. Iron uptake by leaf mesophyll cells: The role of the plasma membrane-bound ferric-chelate reductase. Planta 190, 196606 (1993).
Google Scholar 
Ma, J. F., Ryan, P. R. & Delhaize, E. Aluminium tolerance in plants and the complexing role of organic acids. Trends Plant Sci. 6, 273–278 (2001).CAS 
PubMed 

Google Scholar 
Tolrà, R. et al. Localization of aluminium in tea (Camellia sinensis) leaves using low energy X-ray fluorescence spectro-microscopy. J. Plant Res. 124, 165–172 (2011).PubMed 

Google Scholar  More

Lucas, S. G. Permian tetrapod extinction events. Earth Sci. Rev. 170, 31–60 (2017).
Google Scholar 
Rampino, M. R. & Shen, S.-Z. The end-Guadalupian (259.8 Ma) biodiversity crisis: the sixth major mass extinction? Hist. Biol. 33, 716–722 (2019).
Google Scholar 
Day, M. O. & Rubidge, B. S. The late capitanian mass extinction of terrestrial vertebrates in the Karoo Basin of South Africa. Front. Earth Sci. 9, 631198 (2021).
Google Scholar 
Bordy, E. M. & Paiva, F. Stratigraphic architecture of the karoo river channels at the end-capitanian. Front. Earth Sci. 8, 521766 (2021).
Google Scholar 
Erwin, D. H., Bowring, S. A. & Yugan, J. In Catastrophic events and mass extinctions: impacts and beyond (eds. Koeberl, C. & MacLeod, K. G.) 363–383 (Geological Society of America, 2002).Fielding, C. R. et al. Age and pattern of the southern high-latitude continental end-Permian extinction constrained by multiproxy analysis. Nat. Commun. 10, 385 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Viglietti, P. A. et al. Evidence from South Africa for a protracted end-Permian extinction on land. Proc. Natl Acad. Sci. USA 118, e2017045118 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rubidge, B. S. Did mammals originate in Africa? South African fossils and the Russian connection. Syd. Haughton Meml. Lect. 4, 1–14 (1995).
Google Scholar 
Day, M. O. & Rubidge, B. S. A brief lithostratigraphic review of the Abrahamskraal and Koonap formations of the Beaufort Group, South Africa: towards a basin-wide stratigraphic scheme for the Middle Permian Karoo. J. Afr. Earth Sci. 100, 227–242 (2014).
Google Scholar 
Day, M., Ramezani, J., Frazer, R. & Rubidge, B. U-Pb zircon age constraints on the vertebrate assemblages and palaeomagnetic record of the Guadalupian Abrahamskraal Formation, Karoo Basin, South Africa. J. Afr. Earth Sci. 186, 104435 (2022).CAS 

Google Scholar 
Koch, N. M., Garwood, R. & Parry, L. Fossils improve phylogenetic analyses of morphological characters. Proc. R. Soc. B Biol. Sci. 288, 1–8 (2021).
Google Scholar 
McLoughlin, S. Glossopteris: insights into the architecture and relationships of an iconic Permian Gondwanan plant. J. Bot. Soc. Bengal 65, 93–106 (2011).
Google Scholar 
Slater, B. J., McLoughlin, S. & Hilton, J. A high-latitude Gondwanan lagerstätte: the Permian permineralised peat biota of the Prince Charles Mountains, Antarctica. Gondwana Res. 27, 1446–1473 (2015).
Google Scholar 
Plumstead, E. P. Three thousand million years of plant life in Africa. (Geological Society of South Africa, 1969).Lacey, W. S., van Dijk, D. E. & Gordon-Gray, K. D. Fossil plants from the Upper Permian in the Mooi River district of Natal, South Africa. Ann. Natal. Mus. 22, 349–420 (1975).
Google Scholar 
Anderson, J. M. & Anderson, H. M. Palaeoflora of Southern Africa. Prodomus of South African megafloras. Devonian to Lower Cretaceous. (Balkema, 1985).Bordy, E. M. & Prevec, R. Sedimentology, palaeontology and palaeo-environments of the Middle (?) to Upper Permian Emakwezini Formation (Karoo Supergroup, South Africa). South Afr. J. Geol. 111, 429–458 (2008).Prevec, R. et al. Portrait of a Gondwanan ecosystem: a new late Permian fossil locality from KwaZulu-Natal, South Africa. Rev. Palaeobot. Palynol. 156, 454–493 (2009).
Google Scholar 
Mcloughlin, S. & Prevec, R. The architecture of Permian glossopterid ovuliferous reproductive organs. Alcheringa Australas. J. Palaeontol. 43, 480–510 (2019).
Google Scholar 
McLoughlin, S. & Prevec, R. The reproductive biology of glossopterid gymnosperms—a review. Rev. Palaeobot. Palynol. 295, 104527 (2021).
Google Scholar 
Riek, E. F. New Upper Permian insects from Natal, South Africa. Ann. Natal. Mus. 22, 755–789 (1976).
Google Scholar 
Riek, E. F. Fossil insects from the Middle Ecca (Lower Permian) of southern Africa. Palaeontol. Afr. 19, 145–148 (1976).
Google Scholar 
Riek, E. F. An entomobryid collembolan (Hexapoda: Collembola) from the Lower Permian of Southern Africa. Palaeontol. Afr. 19, 141–143 (1976).
Google Scholar 
McLachlan, I. R. & Anderson, A. M. Fossil insect wings from the Early Permian White Band Formation, South Africa. Palaeontol. Afr. 20, 83–86 (1977).
Google Scholar 
Pinto, I. D. & Pinto De Ornellas, L. New fossil insects from the White Band Formation (Permian), South Africa. Pesqui. Zool. 10, 96–104 (1978).
Google Scholar 
van Dijk, D. E. & Geertsema, H. Permian insects from the Beaufort Group of Natal, South Africa. Ann. Natal. Mus. 40, 137–171 (1999).
Google Scholar 
Geertsema, H., van Dijk, D. E. & van den Heever, A. J. Palaeozoic insects of southern Africa: a review. Palaeontol. Afr. 38, 19–25 (2002).
Google Scholar 
Rubidge, B. S., Erwin, D. H., Ramezani, J., Bowring, S. A. & de Klerk, W. J. High-precision temporal calibration of Late Permian vertebrate biostratigraphy: U-Pb zircon constraints from the Karoo Supergroup, South Africa. Geology 41, 363–366 (2013).CAS 

Google Scholar 
Mcloughlin, S., Prevec, R. & Slater, B. J. Arthropod interactions with the Permian Glossopteris flora. J. Palaeosciences 70, 43–133 (2021).
Google Scholar 
Shcherbakov, D. E. On Permian and Triassic insect faunas in relation to biogeography and the Permian-Triassic crisis. Paleontol. J. 42, 15–31 (2008).
Google Scholar 
Nel, A. et al. The earliest known holometabolous insects. Nature 503, 257–261 (2013).CAS 
PubMed 

Google Scholar 
Nicholson, D. B., Mayhew, P. J. & Ross, A. J. Changes to the fossil record of insects through fifteen years of discovery. PLoS ONE 10, 1421–1435 (2015).
Google Scholar 
Glenister, B. F., Wardlaw, B. R., Lambert, L. L., Spinosa, C. & Bowring, S. A. Proposal of Guadalupian and component Roadian. Wordian Capitanian Stages Int. Stand. middle Permian Ser. Permophiles 34, 3–11 (1999).
Google Scholar 
Allison, P. A. Konservat-Lagerstätten: cause and classification. Paleobiology 14, 331–344 (1988).
Google Scholar 
Grimaldi, D. & Engel, M. S. Evolution of the Insects. (Cambridge University Press, 2005).Tian, Q. et al. Experimental investigation of insect deposition in lentic environments and implications for formation of Konservat Lagerstätten. Palaeontology 63, 565–578 (2020).
Google Scholar 
McCurry, M. R. et al. A Lagerstätte from Australia provides insight into the nature of Miocene mesic ecosystems. Sci. Adv. 8, 1–11 (2022).
Google Scholar 
Beckemeyer, R. J. & Hall, J. D. The entomofauna of the Lower Permian fossil insect beds of Kansas and Oklahoma, USA. Afr. Invertebr. 48, 17 (2007).
Google Scholar 
Jell, P. A. The fossil insects of Australia. Mem. Qld. Mus. 50, 1–124 (2004).
Google Scholar 
Wickens, H., de, V. & Cole, D. I. Lithostratigraphy of the Skoorsteenberg Formation (Ecca Group, Karoo Supergroup), South Africa. South Afr. J. Geol. 120, 433–446 (2017).
Google Scholar 
Rubidge, B. S., Hancox, P. J. & Catuneaunu, O. Sequence analysis of the Ecca–Beaufort contact in the southern Karoo of South Africa. South Afr. J. Geol. 103, 81–96 (2000).
Google Scholar 
Lanci, L., Tohver, E., Wilson, A. & Flint, S. Upper Permian magnetic stratigraphy of the lower Beaufort Group, Karoo Basin. Earth Planet. Sci. Lett. 375, 123–134 (2013).CAS 

Google Scholar 
Belica, M. E. et al. Refining the chronostratigraphy of the Karoo Basin, South Africa: magnetostratigraphic constraints support an early Permian age for the Ecca Group. Geophys. J. Int. 211, 1354–1374 (2017).CAS 

Google Scholar 
Rubidge, B. S. & Day, M. O. Biostratigraphy of the Eodicynodon Assemblage Zone (Beaufort Group, Karoo Supergroup), South Africa. South Afr. J. Geol. 123, 141–148 (2020).
Google Scholar 
Nel, A., Garrouste, R. & Prevec, R. The first Permian Gondwanan damselfly-like Protozygoptera (Insecta, Odonatoptera). Hist. Biol. https://doi.org/10.1080/08912963.2022.2067996 (2022).Cawood, R. et al. The first ‘Grylloblattida’ of the family Liomopteridae from the Middle Permian in the Onder Karoo, South Africa (Insecta: Polyneoptera). Comptes Rendus Palevol. https://doi.org/10.5852/cr-palevol2022v21a22 (2022).Surange, K. R. & Chandra, S. Morphology of the gymnospermous fructifications of the Glossopteris flora and their relationships. Palaeontogr. B 149, 153–180 (1975).
Google Scholar 
White, M. E. Reproductive structures of the Glossopteridales in the plant fossil collection of the Australian Museum. Rec. Aust. Mus. 31, 473–504 (1978).
Google Scholar 
Nishida, H., Pigg, K. B. & DeVore, M. L. In Transformative Paleobotany, Ch. 8 (eds. Krings, M., Harper, C. J., Cúneo, N. R. & Rothwell, G. W.) 145–154 (Academic Press, 2018).McLoughlin, S. New records of Bergiopteris and glossopterid fructifications from the Permian of Western Australia and Queensland. Alcheringa Australas. J. Palaeontol. 19, 175–192 (1995).
Google Scholar 
McLoughlin, S. In Gondwana Eight (eds. Findlay, R. H., Unrug, R., Banks, M. R. & Veevers, J. J.) 253–264 (Balkema, 1993).Nishida, H., Pigg, K. B., Kudo, K. & Rigby, J. F. New evidence of the reproductive organs of Glossopteris based on permineralized fossils from Queensland, Australia. II: pollen-bearing organ Ediea gen. nov. J. Plant Res. 127, 233–240 (2014).PubMed 

Google Scholar 
Tomescu, A. M. F., Bomfleur, B., Bippus, A. C. & Savoretti, A. In Transformative Paleobotany (eds. Krings, M., Harper, C. J., Cuneo, N. R. & Rothwell, G. W.) 375–416 (Elsevier Academic Press, 2018).Bomfleur, B. et al. Diverse bryophyte mesofossils from the Triassic of Antarctica. Lethaia 47, 120–132 (2014).
Google Scholar 
Nel, A., Bechly, G., Prokop, J., Béthoux, O. & Fleck, G. Systematics and evolution of Paleozoic and Mesozoic damselfly-like Odonatoptera of the ‘protozygopteran’ grade. J. Paleontol. 86, 81–104 (2012).
Google Scholar 
Riek, E. F. Fossil insects from the Upper Permian of Natal, South Africa. Ann. Natal. Mus. 21, 513–532 (1973).
Google Scholar 
Gallego, O. F. et al. The most ancient Platyperlidae (Insecta, Perlida= Plecoptera) from early Late Triassic deposits in southern South America. Ameghiniana 48, 447–461 (2011).
Google Scholar 
Martins-Neto, R. G., Gallego, O. F. & Melchor, R. N. The Triassic insect fauna from South America (Argentina, Brazil and Chile): a checklist (except Blattoptera and Coleoptera) and descriptions of new taxa. Acta Zool. Cracoviensia 46, 229–256 (2003).
Google Scholar 
van Dijk, D. E. & Geertsema, H. A new genus of Permian Plecoptera (Afroperla) from KwaZulu-Natal, South Africa. Palaeontogr. B 12, 268–270 (2004).
Google Scholar 
Béthoux, O., Cui, Y., Kondratieff, B., Stark, B. & Ren, D. At last, a Pennsylvanian stem-stonefly (Plecoptera) discovered. BMC Evol. Biol. 11, 248 (2011).PubMed 
PubMed Central 

Google Scholar 
Schubnel, T., Perdu, L., Roques, P., Garrouste, R. & Nel, A. Two new stem-stoneflies discovered in the Pennsylvanian Avion locality, Pas-de-Calais, France (Insecta: ‘Exopterygota’). Alcheringa Australas. J. Palaeontol. 43, 1–6 (2019).
Google Scholar 
Sharov, A. G. In Fundamentals of Paleontology: Arthropoda, Tracheata, Chelicerata. (eds. Rohdendorf, B. B. & Davis, D. R.) vol. 9 173–179 (Smithsonian Institution Libraries and NSCF, 1991).Sinitshenkova, N. D. In History of insects. (eds. Rasnitsyn, A. P. & Quicke, D. L. J.) Ch. 3.3, 388–426 (Kluwer Academic Publishers, 2002).Hayes, P. A. & Collinson, M. E. The Flora of the insect limestone (latest Eocene) from the Isle of Wight, southern England. Earth Environ. Sci. Trans. R. Soc. Edinb. 104, 245–261 (2014).
Google Scholar 
Zhang, Q. et al. Mayflies as resource pulses in Jurassic lacustrine ecosystems. Geology 50, 1043–1047 (2022).CAS 

Google Scholar 
Prokop, J. et al. Ecomorphological diversification of the Late Palaeozoic Palaeodictyopterida reveals different larval strategies and amphibious lifestyle in adults. R. Soc. Open Sci. 6, 190460 (2019).PubMed 
PubMed Central 

Google Scholar 
Prokop, J., Nel, A., Engel, M. S., Pecharová, M. & Hörnschemeyer, T. New Carboniferous fossils of Spilapteridae enlighten postembryonic wing development in Palaeodictyoptera. Syst. Entomol. 41, 178–190 (2016).
Google Scholar 
Dos Santos, T. B., de Souza Pinheiro, E. R. & Iannuzzi, R. First evidence of seed predation by arthropods from Gondwana and its early Paleozoic history (Rio Bonito Formation, Paraná Basin, Brazil). PALAIOS 35, 292–301 (2020).
Google Scholar 
Nel, A., Garrouste, R. & Prokop, J. The first African Anthracoptilidae (Insecta: Paoliida) near the Permian—Triassic boundary in Kenya. Zootaxa 3925, 145 (2015).PubMed 

Google Scholar 
Riek, E. F. An unusual immature insect from the Upper Permian of Natal. Ann. Natal. Mus. 22, 271–274 (1974).
Google Scholar 
Dunlop, J. A., Penney, D., Tetlie, O. E. & Anderson, L. I. How many species of fossil arachnids are there? J. Arachnol. 36, 267–272 (2008).
Google Scholar 
Rasnitsyn, A. P. et al. Sequence and scale of changes in the terrestrial biota during the Cretaceous (based on materials from fossil resins). Cretac. Res. 61, 234–255 (2016).
Google Scholar 
Manum, S. B., Bose, M. N. & Sawyer, R. T. Clitellate cocoons in freshwater deposits since the Triassic. Zool. Scr. 20, 347–366 (1991).
Google Scholar 
Struck, T. H. et al. Phylogenomic analyses unravel annelid evolution. Nature 471, 95–98 (2011).CAS 
PubMed 

Google Scholar 
Parry, L., Tanner, A. & Vinther, J. The origin of annelids. Palaeontology 57, 1091–1103 (2014).
Google Scholar 
Mikulic, D. G., Briggs, D. E. G. & Kluessendorf, J. A Silurian soft-bodied biota. Science 228, 715–717 (1985).CAS 
PubMed 

Google Scholar 
Prokop, J., Szwedo, J., Lapeyrie, J., Garrouste, R. & Nel, A. New Middle Permian insects from Salagou Formation of the Lodève Basin in southern France (Insecta: Pterygota). Ann. Soci.été Entomol. Fr. NS 51, 14–51 (2015).
Google Scholar 
Cai, C. et al. Integrated phylogenomics and fossil data illuminate the evolution of beetles. R. Soc. Open Sci. 9, 211771 (2022).CAS 
PubMed 
PubMed Central 

Google Scholar 
Srivastava, A. K. & Agnihotri, D. Dilemma of late Palaeozoic mixed floras in Gondwana. Palaeogeogr. Palaeoclimatol. Palaeoecol. 298, 54–69 (2010).
Google Scholar 
Raff, R. A. Written in stone: fossils, genes and evo–devo. Nat. Rev. Genet. 8, 911–920 (2007).CAS 
PubMed 

Google Scholar 
Cunningham, J. A., Liu, A. G., Bengtson, S. & Donoghue, P. C. J. The origin of animals: can molecular clocks and the fossil record be reconciled? BioEssays 39, 1–12 (2017).PubMed 

Google Scholar 
McCulloch, G. A., Wallis, G. P. & Waters, J. M. A time-calibrated phylogeny of southern hemisphere stoneflies: Testing for Gondwanan origins. Mol. Phylogenet. Evol. 96, 150–160 (2016).PubMed 

Google Scholar 
Cui, Y. et al. Rhythms of Insect Evolution. (John Wiley & Sons, Ltd, 2019).Letsch, H. et al. Combining molecular datasets with strongly heterogeneous taxon coverage enlightens the peculiar biogeographic history of stoneflies (Insecta: Plecoptera). Syst. Entomol. 46, 952–967 (2021).
Google Scholar 
Raja, N. B. et al. Colonial history and global economics distort our understanding of deep-time biodiversity. Nat. Ecol. Evol. 6, 145–154 (2022).PubMed 

Google Scholar 
Beattie, R. The geological setting and palaeoenvironmental and palaeoecological reconstructions of the Upper Permian insect beds at Belmont, New South Wales, Australia. Afr. Invertebr. 48, 18 (2007).
Google Scholar 
Bernardi, M. et al. Late Permian (Lopingian) terrestrial ecosystems: a global comparison with new data from the low-latitude Bletterbach Biota. Earth Sci. Rev. 175, 18–43 (2017).
Google Scholar 
Jackson, S. E., Pearson, N. J., Griffin, W. L. & Belousova, E. A. The application of laser ablation-inductively coupled plasma-mass spectrometry to in situ U–Pb zircon geochronology. Chem. Geol. 211, 47–69 (2004).CAS 

Google Scholar 
Sláma, J. et al. Plešovice zircon—a new natural reference material for U–Pb and Hf isotopic microanalysis. Chem. Geol. 249, 1–35 (2008).
Google Scholar 
Wiedenbeck, M. et al. Three natural zircon standards for U‐Th‐Pb, Lu‐Hf, trace element and REE analyses. Geostand. Newsl. 19, 1–23 (2007).
Google Scholar 
Horstwood, M. S. A. et al. Community‐derived standards for LA ‐ ICP ‐ MS U‐(Th‐)Pb geochronology—uncertainty propagation, age interpretation and data reporting. Geostand. Geoanal. Res. 40, 311–332 (2016).CAS 

Google Scholar 
Paton, C., Hellstrom, J., Paul, B., Woodhead, J. & Hergt, J. Iolite: freeware for the visualisation and processing of mass spectrometric data. J. Anal. Spectrom. 26, 2508–2518 (2011).CAS 

Google Scholar 
Petrus, J. A. & Kamber, B. S. VizualAge: a novel approach to laser ablation ICP-MS U-Pb geochronology data reduction. Geostand. Geoanal. Res. 36, 247–280 (2012).CAS 

Google Scholar 
Rees, P. Mc. A., Gibbs, M. T., Ziegler, A. M., Kutzbach, J. E. & Behling, P. J. Permian climates: evaluating model predictions using global paleobotanical data. Geology 27, 891 (1999).
Google Scholar 
Walter, H. Vegetation of the Earth and ecological systems of the geo-biosphere. (Springer-Verlag, 1985).Lucas, S. G., Schneider, J. W. & Cassinis, G. Non-marine Permian biostratigraphy and biochronology: an introduction. Geol. Soc. Lond. Spec. Publ. 265, 1–14 (2006).
Google Scholar 
Scotese, C. In Atlas of Permo-Triassic Paleogeographic Maps (Mollweide Projection), Maps 43–52, Volumes 3 & 4 of the PALEOMAP Atlas for ArcGIS. (PALEOMAP Project, 2014). More

Experimental spidersExperimental spiders were maintained as previously reported37. Briefly, spiders were the F1 to F4 offspring of mated females collected from hallways of the Burnaby campus of Simon Fraser University (Burnaby, BC, CA). Upon hatching, juvenile spiders were housed individually in petri dishes (100 mm × 20 mm) and provisioned with the vinegar flies Drosophila melanogaster. Subadult spiders were fed with larvae of the mealworm beetle Tenebrio molitor. Each adult female spider was kept in a separate translucent 300-mL plastic cup (Western Family, CA) maintained at 22 °C under a reversed light cycle (12:12 h). Adult males and females were fed with black blow flies, Phormia regina. All spiders had access to water in cotton wicks. Water and food were provided once per week. Laboratory experiments were run during a reversed scotophase (0900 to 1700).Identification of contact pheromone components: Preparation of web extracts (summer 2017; spring and summer 2018)Each of the 100 spiders was allowed to build her web for three days on a wooden triangular prism scaffold (30 cm × 25 cm × 22 cm)44 of bamboo skewers (GoodCook, CA, USA) (Fig. 1b). After the spiders were removed from the scaffold, their webs were reeled up with a glass rod (10 cm × 0.5 cm) and deposited in a 1.5-mL glass vial. Per web, 50 µL of methanol (99.9% HPLC grade, Fisher Chemical, ON, Canada) were added and the silk was extracted for 24 h at room temperature. Prior to analysis, the silk was removed and the sample was concentrated under a steady nitrogen stream to the desired concentration.Identification of contact pheromone components: analyses of web extracts by gas chromatography–mass spectrometry (GC-MS)Aliquots (2 µL) of pooled and concentrated web extract (100 webs in 400 µL of solvent) were analysed by GC–MS, using a Varian Saturn Ion trap 2000 (Varian Inc., now Agilent Technologies Inc., Santa Clara, CA 95051, USA) and an Agilent 7890B GC coupled to a 5977 A MSD, both fitted with a DB-5 GC-MS column (30 m × 0.25 mm ID, film thickness 0.25 µm). The injector port was set to 250 °C, the MS source to 230 °C, and the MS quadrupole to 150 °C. Helium was used as a carrier gas at a flow rate of 35 cm s−1, with the following temperature programme: 50 °C held for 5 min, 10 °C min−1 to 280 °C (held for 10 min). Compounds were identified by comparing their mass spectra and retention indices (relative to aliphatic alkanes67) with those of authentic standards that were purchased or synthesised in our laboratory (Supplementary Table 1).Identification of contact pheromone components: high-performance liquid chromatography (HPLC) of web extractsWeb extract of virgin adult female S. grossa was fractionated by high-performance liquid chromatography (HPLC), using a Waters HPLC system (Waters Corporation, Milford, MA, USA; 600 Controller, 2487 Dual Absorbance Detector, Delta 600 pump) fitted with a Synergy Hydro Reverse Phase C18 column (250 mm × 4.6 mm, 4 µ; Phenomenex, Torrance, CA, USA). The column was eluted with a 1-mL/min flow of a solvent gradient, starting with 80% water (HPLC grade, EMD Millipore Corp., Burlington, MA, USA) and 20% acetonitrile (99.9% HPLC grade, Fisher Chemical, Ottawa, CA) and ending with acetonitrile after 10 min. A 60-web-equivalent extract was injected and 20 1-min fractions were collected. Each HPLC fraction (containing 20 web-equivalents) was tested in T-rod bioassays (Fig. 1c) for the presence of contact pheromone components. All eight fractions that elicited courtship responses by males (Supplementary Fig. 1) were analysed by HPLC-tandem MS/MS.Identification of contact pheromone components: HPLC-tandem MS/MS of bioactive HPLC fractionsThe bioactive HPLC fractions were analysed on a Bruker maXis Impact Quadrupole Time-of-Flight HPLC/MS System. The system consists of an Agilent 1200 HPLC fitted with a spursil C18 column (30 mm × 3.0 mm, 3 µ; Dikma Technologies, Foothill Ranch, CA, USA) and a Bruker maXis Impact Ultra-High Resolution tandem TOF (UHR-Qq-TOF) mass spectrometer. The LC-MS conditions were as follows: The mass spectrometer was set to positive electrospray ionisation (+ESI) with a gas temperature of 200 °C and a gas flow of 9 L/min. The nebuliser was set to 4 bar and the capillary voltage to 4200 V. The column was eluted with a 0.4-mL/min flow of a solvent gradient, starting with 80% water and 20% acetonitrile and ending with 100% acetonitrile after 4 min. The solvent contained 0.1% formic acid to improve peak shape.Identification of contact pheromone components: 1H NMR analyses of a bioactive fractionIn HPLC-MS analyses, a single bioactive fraction (9–10 min) appeared to contain only a single compound. This fraction was then further investigated using 1H NMR spectroscopy. The 1H NMR spectrum was recorded on a Bruker Advance 600 equipped with a QNP (600 MHz) using CDCl3. Signal positions (δ) are given in parts per million from tetramethylsilane (δ 0) and were measured relative to the signal of the solvent (1H NMR: CDCl3: δ 7.26).Identification of contact pheromone components: syntheses of candidate pheromone componentsThe syntheses of candidate pheromone components and synthetic intermediates are reported in the SI.Identification of contact pheromone components: T-rod bioassays (general procedures)The T-rod apparatus37 (Fig. 1c) consisted of a horizontal beam (25 cm × 0.4 cm) and a vertical beam (30 cm × 0.4 cm) held together by labelling tape (3 cm × 1.9 cm, Fisher Scientific, Ottawa, ON, CA). A piece of filter paper (2 cm2) was attached to each distal end of the horizontal beam. For each bioassay, an aliquot of web extract (in methanol), or a blend of synthetic candidate pheromone components, was applied to the randomly assigned treatment filter paper, whereas methanol was applied to the control filter paper. The solvent was allowed to evaporate for 1 min before the onset of a 15-min bioassay. A randomly selected naïve male spider was placed at the base of the vertical beam and the time he spent courting on each filter paper was recorded. In response to the presence of female-produced or synthetic pheromone on a filter paper, the male engaged in courtship, pulling silk with his hindlegs from his spinnerets and adding it to the paper. Sensing contact pheromone, the male essentially behaves as if he were courting on the web of a female. On a web, the male engages in web reduction prior to copulation, a behaviour that entails cutting sections of the female’s web with his chelicerae and wrapping the dismantled web bundle with his own silk pulled from his spinnerets41,56. Each T-rod apparatus was used only once. Replicates of experiments as part of specific research objectives were run in parallel to eliminate day effects on the responses of spiders. The sample size for each experiment was set to 20 unless otherwise stated.Identification of contact pheromone components: T-rod bioassays (specific experiments) (fall 2017; spring and summer 2018)Experiment 1 (fall 2017) tested a synthetic blend of volatile compounds 5–11 unique to mature S. grossa females (Fig. 1c and Supplementary Table 1) vs a solvent control. Parallel experiment 2 tested one web equivalent of virgin female web extract, followed by testing each of the 20 HPLC fractions in six replicates for the occurrence of courtship (spring 2018).Parallel experiments 3–6 (summer 2018) tested web extract at one female web equivalent (1 FWE) (Exp. 3), a ternary blend of the candidate contact pheromone components 12, 16 and 17 (Fig. 2d, Exp. 4), the same ternary blend (12, 16 and 17) in combination with the volatile compounds 5–11 (Exp. 5), and 5–11 on their own (Exp. 6).Parallel dose-response experiments 7–11 (summer 2018) tested the ternary blend of 12, 16 and 17 at five FWEs: 0.001 (Exp. 7); 0.01 (Exp. 8); 0.1 (Exp. 9); 1.0 (Exp. 10); and 10 (Exp. 11).Parallel experiments 12–15 tested the ternary blend, and all possible binary blends, of 12, 16 and 17. Parallel experiments 16–18 tested 12 and 16 in binary combination (Exp. 16) and singly (Exps. 17, 18).Origin of contact pheromone components (fall 2020)To trace the origin of contact pheromone component 12 (and coeluting 16), cold-euthanized female spiders were dissected in saline solution55 (25 mL of water and 25 mL of methanol, 160 mM NaCl, 7.5 mM KCl, 1 mM MgCl2, 4 mM NaHCO3, 4 mM CaCl2, 20 mM glucose, pH 7.4). Samples were homogenised (Kimble Pellet Pestle Motor, Kimble Kontes, USA) in methanol for 1 min, kept 24 h at room temperature for pheromone extraction, and then centrifuged (12,500 rpm, 3 °C for 20 min; Hermle Z 360 K refrigerated centrifuge; B. Hermle AG, Wehingen, DE) to obtain the supernatant for HPLC-MS analyses (see above) for the presence of 12 and 16. Three sequential sets of dissections aimed to determine (1) the pheromone-containing body tagma, (2) the pheromone-containing tissues or glands in that tagma and (3) the specific gland or tissue producing 12 & 16.To identify the pheromone-containing tagma, 11 spiders were severed at the pedicel, generating two tagmata: the cephalothorax with four pairs of legs and the abdomen. Each tagma was then extracted separately in 100 µL of methanol. Eight of 11 abdomen samples contained 12 and 16, whereas only one of 11 thorax samples contained 12 and 16 (Exp. 19), albeit at only trace amounts. With 12 and 16 being present in the abdomen, 20 additional abdomens were dissected68 to obtain separate samples of (i) haemolymph (25 µL), (ii) ventral cuticle (~0.5 cm2 near the pedicel, (iii) the ovaries, (iv) all silk glands combined, and (v) the gut (with anus, cloaca and Malpighian tubules). The remaining spider tissues (vi) were pooled as one sample, and 20 µL of the dissection buffer solution (vii) was obtained to detect potential pheromone bleeding. To each tissue sample, 50 µL of methanol were added. Only silk gland samples contained 12 and 16 (Exp. 20). Having established that only silk gland samples contained 12 and 16, the silk glands of 30 additional spiders were excised in the following order: (i) major ampullate gland, (ii) minor ampullate gland, (iii) anterior aggregate gland, (iv) posterior aggregate gland, (v) tubuliform, (vi) aciniform and flagelliform glands combined and (vii) pyriform gland. The glands from three spiders were combined in each sample and extracted in 30 µL methanol. Seven of ten posterior aggregate gland samples contained 12 and 16, with other silk gland samples not containing 12 and 16 or in only trace amounts (Exp. 21).Transition of contact pheromone components to mate attractant pheromone components: evidence for hydrolysis of contact pheromone components (12, 16 and 17) (spring 2021)To test for the hydrolysis of the contact pheromone components 12, 16 and 17, we compared their breakdown ratio (18/(12 + 16 + 17 + 18) on independent webs aged 0 days and 14 days (Exp. 24). Each of 140 spiders was allowed to spin a web on bamboo scaffolds for three days. Then, the spiders were removed and webs—by random assignment—were extracted immediately (0-day-old webs) or after 14 days of aging (14-day-old webs). On each web, the amount of contact pheromone components 12, 16 and 17, and of amide 18 as a breakdown product, was quantified using HPLC–MS, with 12 and 18 at 25 and 50 ng/µL as external standards.Transition of contact pheromone components to mate attractant pheromone components: Y-tube olfactometer bioassays (general procedures)The attraction of male spiders to web extracts and to candidate mate attractant pheromone components was tested in Y-tube olfactometers56 (Fig. 4a) lined with bamboo sticks to provide grip for the bioassay spider. Test stimuli were presented in translucent oven bags (30 cm × 31 cm; Toppits, Mengen, DE) secured to the orifice of side-arms. Test stimuli consisted of a triangular bamboo prism scaffold (each side 8.5 cm long) bearing a spider’s web, or bearing artificial webbing30 (40 ± 2 mg; Bling Star, CN) that was treated with web extract or synthetic chemicals in methanol (100 µL) as the treatment stimulus or with methanol (100 µL) as the control stimulus. For each experimental replicate, a male spider was introduced into a glass holding tube and allowed 2 min to acclimatise. Then, the holding tube was attached via a glass joint to the Y-tube olfactometer and an air pump was connected to the holding tube, drawing air at 100 mL/min through the olfactometer. Air entered the olfactometer through a glass tube secured to the oven bags’ second opening. A male that entered the olfactometer within the 5-min bioassay period was classed a responder and his first choice of oven bag (the oven bag he reached first) was recorded. Whenever a set of 30 replicates was completed by the same observer, using 30 separate Y-tubes, the Y-tubes were cleaned with hot water and soap (Sparkleen, Thermo Fisher Scientific, MA, United States) and dried in an oven at 100 °C for 3 h, whereas the bamboo sticks and the oven bags were discarded.Transition of contact pheromone components to mate attractant pheromone components: Y-tube olfactometer bioassays (specific experiments) (summer 2018)In experiments 22, 23 and 25–27, males were offered a choice between a solvent control stimulus and a treatment stimulus. The treatment stimulus consisted of (i) virgin female web-extract (1 web-equivalent) (Exp. 22, N = 24), (ii) the volatile compounds 5–11 unique to sexually mature females (Fig. 1d) (Exp. 23, N = 24), (iii) all breakdown products of the contact pheromone components 12, 16 and 17, consisting of the amide N-4-methylvaleroyl-l-serine (18) and the corresponding carboxylic acids 19, 20 and 21 (Exp. 25, N = 30), (iv) a blend of the acids 19, 20 and 21 (Exp. 26, N = 30) and (v) the amide 18 as a single compound (Exp. 27, N = 30). Compounds were tested at quantities as determined in virgin female web extract (50 webs in 150 μL of dichloromethane), following silyl-ester derivatization69 of acids in the extract, with valeric acid (200 ng; ≥99%, Sigma Aldrich, St. Louis, USA) added as an internal standard. Per web equivalent, there were 103 ng of 19, 3 ng of 20 and 54 ng of 21. The amide 18 was present at 200 ng per web equivalent, as determined using N-3-methylbutnaoyl-l-serine methyl ester as an external standard.Transition of contact pheromone components to mate attractant pheromone components: hallway of buildings experiment (fall 2018)As the ternary blend of the carboxylic acids 19, 20 and 21 attracted male spiders in Y-tube olfactometers (see Results), we aimed to confirm their functional role as mate attractant pheromone components also in ‘field’ settings (Exp. 28). To this end, we set up ten replicates of paired traps in building hallways on the Burnaby campus of Simon Fraser University. Adhesive-coated traps (Bell Laboratories Inc., Madison, WI, USA) were spaced 0.5 m within pairs and 20 m between pairs. By random assignment, one trap in each pair was baited with the carboxylic acids 19, 20 and 21 formulated in 200 µL of mineral oil (Anachemia, Montreal, CA; 2.8 mg of 19, 0.112 mg of 20 and 1.52 mg of 21), whereas the control trap received mineral oil only. Test stimuli were disseminated from a 400-μL microcentrifuge tube (Evergreen Scientific, Ranco Dominguez, CA, USA) with a hole in its lid punctured by a No. 3 insect pin (Hamilton Bell, Montvale, NJ, USA). Every week for 4 months (September to December 2018), traps were checked, lures were replaced, and the position of the treatment and the control trap within each trap pair was re-randomised.Communication function of amide breakdown product 18 (fall 2018)As the amide 18 did not attract males in Y-tube olfactometer experiments (see Results), we tested its alternate potential function as a contact pheromone component which, if active, would induce courtship by males. Using the T-rod apparatus (Fig. 1c), we treated one piece of filter paper with a solvent control and the other with a blend comprising both the contact pheromone components 12, 16 and 17 and the amide 18 (Exp. 29), a blend of 12, 16 and 17 (Exp. 30), and 18 alone (Exp. 31).Mechanisms underlying the transition of contact pheromone components to mate attractant pheromone components: relationship between web pH and breakdown rates of contact pheromone components (summer 2020)We allowed each of the 70 spiders to spin two webs, using one web to quantify the amide breakdown product (18) of the contact pheromone components (see above), and the other web to determine its pH according to the slurry method57 (Exp. 32). To this end, we first measured the pH of 50 µL water (HPLC grade, EMD Millipore Corp., Burlington, MA, USA) and then of a web with the water functioning as a conductor for the pH metre (LAQUAtwin pH 22 (Horiba, Kyoto, JP). Between web measurements, the pH metre was rinsed with water and regularly re-calibrated using a pH 7 and a pH 4 buffer (Horiba, Kyoto, JP).Mechanisms underlying the transition of contact pheromone components to mate attractant pheromone components: testing for pH-dependent saponification of contact pheromone components (12, 16 and 17) (summer 2021)To test whether pH alone catalyses saponification of the ester bond of contact pheromone components (12, 16 and 17), synthetic 12 was added to a 40% aqueous pH 7 buffer solution (Exp. 34), a pH 4 buffer solution (Exp. 34), and to acetonitrile (Exp. 35) as a polar aprotic solvent control (N = 12; 100 ng/µL each). pH-Dependent breakdown of 12 over time was assessed by analysing (HPLC-MS) diluted aqueous aliquots (2.5 ng/µl) of each sample at day 0 and after 14 days of storage at room temperature.Mechanisms underlying the transition of contact pheromone components to mate attractant pheromone components: testing for the presence of a carboxylesterhydrolase (CEH) (summer 2021)To test for the presence of a carboxylesterhydrolase (CEH), for each of three replicates we extracted (i) five webs of adult virgin female L. hesperus (positive control, known to have a CEH45), (ii) 20 webs of subadult S. grossa (deemed to have not yet produced a CEH) and (iii) ten webs of adult virgin female S. grossa, accounting for the different amounts of silk produced by these three groups of spiders. For each replicate, webs were extracted in 200 µL 0.05 M Sørensen buffer58 and analysed by Bioinformatics Solutions (Waterloo, ON, CA). After web samples were incubated for 20 min at 60 °C in 2× sample volumes of 10% SDS (lauryl sulfate; protein-denaturing anionic detergent), they were sonicated for 20 min. Then, the supernatant was withdrawn, reduced with dithiothreitol (DTT), and alkylated with iodoacetamide (IAA). Alkylated samples were treated further with a protein solvent (S-Trap kit; Protifi, Farmingdale, NY, USA). Briefly, samples were acidified by phosphoric acid to pH ≤1. Then 6× of sample volume S-trap buffer was mixed in. The mixture was loaded by centrifugation onto an S-Trap Micro Spin Column and washed 3× with S-trap buffer. Using the serine protease trypsin, protein digestions were carried out at 47 °C for 1 h in 50 mM triethylamonium bicarbonate (TEAB) buffer within the S-Trap Micro Spin column. Digestion products were eluted sequentially with 40 µL 50 mM TEAB and 0.2% formic acid. Eluates were dried and re-suspended in 0.1% formic acid.Eluates were analysed by HPLC-MS/MS in positive ion mode on a Thermo Scientific Orbitrap Fusion Lumos Tribrid mass spectrometer (Thermo Fisher, San Jose, CA, USA), equipped with a nanospray ionisation source and a Thermo Fisher Ultimate 3000 RSLCnano HPLC System (Thermo Fisher). Peptide mixtures were loaded onto a PEPMAP100 C18 trap column (75 µm × 20 mm, 5 µm particle size; Thermo Fisher) at a constant flow of 30 μL/min and 60 °C isothermal. Peptides were eluted at a rate of 0.2 μL/min and separated using a Reprosil C18 analytical column (75 μm × 15 mm, 1.9 μm particle size; PepSep, DK) with a 60-min solvent gradient: 0–45 min: 4–35% acetonitrile + 0.1% formic acid; 45–55 min: 90% acetonitrile + 0.1% formic acid; 55–60 min: 4% acetonitrile + 0.1% formic acid.MS data were acquired in data-dependent mode with a cycle time of 3 s. MS1 scan data were acquired with the Orbitrap mass analyser, using a mass range of 400–1600 m/z, with the resolution set to 120,000. The automatic gain control (AGC) was set to 4e5, with a maximum ion injection time of 50 ms, and the radio frequency (RF) lens was set to 30%. Isolations for MS2 scans were run using a quadrupole mass analyser, with an isolation window of 0.7. MS2 scan data were acquired with the Orbitrap mass analyser at a resolution of 15,000 m/z, with a maximum ion injection time of 22 ms, and the AGC target set to 5e4. Higher energy collisional dissociation (HCD; fixed normalised collision energy: 30%) was used for generating MS2 spectra, with the number of microscans set to 1.Statistics and reproducibilityData (Supplementary Table 2) were analysed statistically using R70. Data of experiments 1–18 and 29–31 (testing courtship by male spiders in response to contact pheromone components) were analysed with a Wilcoxon test or Kruskal–Wallis two-tailed rank-sum test with Benjamini–Hochberg correction to adjust for multiple comparison. Data of experiments 19–21 (revealing the presence of contact pheromone components in the abdomen, silk glands, and posterior aggregate silk gland) were analysed with two-tailed, rather than one-tailed, Wilcoxon test or Kruskal–Wallis rank tests because we had no strong assumption as to whether or not pheromone would be present in any of these potential pheromone sources. The p values were adjusted for multiple comparison using the Benjamini–Hochberg method. Y-tube olfactometer data of experiments 22, 23 and 25–27, as well as the hallway experiment 28 (revealing attraction of male spiders to volatile pheromone components) were analysed using an one-tailed71 binomial test, anticipating attraction of spiders to volatile mate attractant pheromone components rather than to solvent control stimuli. Data of experiment 32 (revealing a correlation between web pH and breakdown of web-borne contact pheromone components) were analysed using generalised linear models. Data of experiments 33–35 (showing pH-dependent breakdown of synthetic contact pheromone) were compared using a two-tailed Kruskal–Wallis test with Benjamini–Hochberg correction.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Ceballos, G. & Ehrlich, P. R. Mammal population losses and the extinction crisis. Science 296, 904–907 (2002).CAS 
PubMed 

Google Scholar 
Morrison, J. C., Sechrest, W., Dinerstein, E., Wilcove, D. S. & Lamoreux, J. F. Persistence of large mammal faunas as indicators of global human impacts. J. Mammal. 88, 1363–1380 (2007).
Google Scholar 
Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343, 1241484 (2014).PubMed 

Google Scholar 
Finnegan, S. P. et al. Reserve size, dispersal and population viability in wide ranging carnivores: the case of jaguars in Emas National Park, Brazil. Anim. Conserv. 24, 3–14 (2021).
Google Scholar 
Wang, T. et al. Amur tigers and leopards returning to China: direct evidence and a landscape conservation plan. Landsc. Ecol. 31, 491–503 (2016).
Google Scholar 
Gilbert, M. et al. Distemper, extinction, and vaccination of the Amur tiger. Proc. Natl. Acad. Sci. 117, 31954–31962 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Smith, K. F., Acevedo-Whitehouse, K. & Pedersen, A. B. The role of infectious diseases in biological conservation. Anim. Conserv. 12, 1–12 (2009).
Google Scholar 
Wolf, C. & Ripple, W. J. Range contractions of the world’s large carnivores. R. Soc. Open Sci. 4, 170052 (2017).PubMed 
PubMed Central 

Google Scholar 
Courchamp, F. et al. Inverse density dependence and the Allee effect. Trends Ecol. Evol. 14, 405–410 (1999).CAS 
PubMed 

Google Scholar 
Wittmann, M. J., Stuis, H. & Metzler, D. Genetic Allee effects and their interaction with ecological Allee effects. J. Anim. Ecol. 87, 11–23 (2018).PubMed 

Google Scholar 
Estes, J. A. et al. Trophic Downgrading of Planet Earth. Science 333, 301–306 (2011).CAS 
PubMed 

Google Scholar 
Stein, A. B. et al. IUCN Red List of Threatened Species: Panthera pardus. IUCN Red List Threat. Species (2020).Vitkalova, A. V. et al. Transboundary cooperation improves endangered species monitoring and conservation actions: A case study of the global population of Amur leopards. Conserv. Lett. 11, e12574 (2018).
Google Scholar 
Wang, T. et al. A science-based approach to guide Amur leopard recovery in China. Biol. Conserv. 210, 47–55 (2017).
Google Scholar 
Lewis, J. et al. Assessing the health risks of reintroduction: The example of the Amur leopard, Panthera pardus orientalis. Transbound. Emerg. Dis. 67, 1177–1188 (2020).PubMed 

Google Scholar 
Terio, K. A. & Craft, M. E. Canine distemper virus (CDV) in another big cat: should CDV be renamed carnivore distemper virus? mBio 4, e00702–e00713 (2013).PubMed 
PubMed Central 

Google Scholar 
Adhikari, R. B., Shrestha, M., Puri, G., Regmi, G. R. & Ghimire, T. R. Canine Distemper Virus (CDV): an emerging threat to Nepal’s wildlife. Appl. Sci. Technol. Ann. 1, 149–154 (2020).
Google Scholar 
Roelke-Parker, M. E. et al. A canine distemper virus epidemic in Serengeti lions (Panthera leo). Nature 379, 441–445 (1996).CAS 
PubMed 
PubMed Central 

Google Scholar 
Mulia, B. H. et al. Exposure of Wild Sumatran Tiger (Panthera tigris sumatrae) to Canine Distemper Virus. J. Wildl. Dis. 57, 464–466 (2021).PubMed 

Google Scholar 
Gordon, C. H. et al. Canine distemper in endangered Ethiopian wolves. Emerg. Infect. Dis. 824–832 (2015) https://doi.org/10.3201/eid2105.141920.Timm, S. F. et al. A suspected canine distemper epidemic as the cause of a catastrophic decline in Santa Catalina Island foxes (Urocyon littoralis catalinae). J. Wildl. Dis. 45, 333–343 (2009).PubMed 

Google Scholar 
Sulikhan, N. S. et al. Canine distemper virus in a wild Far Eastern leopard (Panthera pardus orientalis). J. Wildl. Dis. 54, 170–174 (2018).PubMed 

Google Scholar 
Gilbert, M. et al. Canine distemper virus as a threat to wild tigers in Russia and across their range. Integr. Zool. 10, 329–343 (2015).PubMed 

Google Scholar 
Almberg, E. S., Cross, P. C. & Smith, D. W. Persistence of canine distemper virus in the Greater Yellowstone Ecosystem’s carnivore community. Ecol. Appl. 20, 2058–2074 (2010).PubMed 

Google Scholar 
Cleaveland, S. et al. The conservation relevance of epidemiological research into carnivore viral diseases in the Serengeti. Conserv. Biol. 21, 612–622 (2007).PubMed 

Google Scholar 
Haydon, D. T. et al. Low-coverage vaccination strategies for the conservation of endangered species. Nature 443, 692–695 (2006).CAS 
PubMed 

Google Scholar 
Hebblewhite, M., Miquelle, D. G., Murzin, A. A., Aramilev, V. V. & Pikunov, D. G. Predicting potential habitat and population size for reintroduction of the Far Eastern leopards in the Russian Far East. Biol. Conserv. 144, 2403–2413 (2011).
Google Scholar 
Jiang, G. et al. New hope for the survival of the Amur leopard in China. Sci. Rep. 5, 15475 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Licht, D. S., Moen, R. A. & Romanski, M. Modeling viability of a potential Canada lynx reintroduction to Isle Royale national park. Nat. Areas J. 37, 170–177 (2017).
Google Scholar 
Menges, E. S. Population viability analysis for an endangered plant. Conserv. Biol. 4, 52–62 (1990).
Google Scholar 
Beissinger, S. R. & McCullough, D. R. Population viability analysis. J. Wildl. Manag. 67, 481–506 (2003).
Google Scholar 
Aresu, M. et al. Assessing the effects of different management scenarios on the conservation of small island vulture populations. Bird. Conserv. Int. 31, 111–128 (2021).
Google Scholar 
Benson, J. F. et al. Extinction vortex dynamics of top predators isolated by urbanization. Ecol. Appl. 29, e01868 (2019).PubMed 

Google Scholar 
Franklin, A. D., Lacy, R. C., Bauman, K. L., Traylor-Holzer, K. & Powell, D. M. Incorporating drivers of reproductive success improves population viability analysis. Anim. Conserv. 24, 386–400 (2021).
Google Scholar 
McCallum, H. Models for managing wildlife disease. Parasitology 143, 805–820 (2016).PubMed 

Google Scholar 
Bradshaw, C. J. A. et al. Novel coupling of individual-based epidemiological and demographic models predicts realistic dynamics of tuberculosis in alien buffalo. J. Appl. Ecol. 49, 268–277 (2012).
Google Scholar 
Shoemaker, K. T. et al. Effects of prey metapopulation structure on the viability of black-footed ferrets in plague-impacted landscapes: a metamodelling approach. J. Appl. Ecol. 51, 735–745 (2014).
Google Scholar 
Shaffer, M. L. Minimum population sizes for species conservation. BioScience 31, 131–134 (1981).
Google Scholar 
Seimon, T. A. et al. Canine distemper virus: an emerging disease in wild endangered Amur tigers (Panthera tigris altaica). mBio 4, e00410–e00413 (2013).PubMed 
PubMed Central 

Google Scholar 
Wang, T. et al. An introduction to Long-term Tiger-Leopard Observation Network based on camera traps in Northeast China. Biodivers. Sci. 28, 1059 (2020).
Google Scholar 
Gilbert, M. et al. Estimating the potential impact of canine distemper virus on the Amur tiger population (Panthera tigris altaica) in Russia. PLOS ONE 9, e110811 (2014).PubMed 
PubMed Central 

Google Scholar 
Fahrig, L. How much habitat is enough? Biol. Conserv. 100, 65–74 (2001).
Google Scholar 
Thatte, P., Joshi, A., Vaidyanathan, S., Landguth, E. & Ramakrishnan, U. Maintaining tiger connectivity and minimizing extinction into the next century: Insights from landscape genetics and spatially-explicit simulations. Biol. Conserv. 218, 181–191 (2018).
Google Scholar 
Hostetler, J. A., Onorato, D. P., Jansen, D. & Oli, M. K. A cat’s tale: the impact of genetic restoration on Florida panther population dynamics and persistence. J. Anim. Ecol. 82, 608–620 (2013).PubMed 

Google Scholar 
Johnson, W. E. et al. Genetic restoration of the Florida panther. Science 329, 1641–1645 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Sankar, K. et al. Monitoring of reintroduced tigers in Sariska Tiger Reserve, Western India: preliminary findings on home range, prey selection and food habits. Trop. Conserv. Sci. 3, 301–318 (2010).
Google Scholar 
Kelly, P., Stack, D. & Harley, J. A review of the proposed reintroduction program for the Far Eastern leopard (Panthera pardus orientalis) and the role of conservation organizations, veterinarians, and zoos. Top. Companion Anim. Med. 28, 163–166 (2013).PubMed 

Google Scholar 
Hayward, M. W. & Somers, M. J. Reintroduction of top-order predators: using science to restore one of the drivers of biodiversity. in Reintroduction of Top-Order Predators 1–9 (John Wiley & Sons, Ltd, 2009). https://doi.org/10.1002/9781444312034.ch1.Pujol, B., Zhou, S.-R., Sanchez Vilas, J. & Pannell, J. R. Reduced inbreeding depression after species range expansion. Proc. Natl Acad. Sci. 106, 15379–15383 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
He, C., Du, J., Zhu, D. & Zhang, L. Population viability analysis of small population: a case study for Asian elephant in China. Integr. Zool. 15, 350–362 (2020).PubMed 

Google Scholar 
Sugimoto, T., Aramilev, V. V., Nagata, J. & McCullough, D. R. Winter food habits of sympatric carnivores, Amur tigers and Far Eastern leopards, in the Russian Far East. Mamm. Biol. 81, 214–218 (2016).
Google Scholar 
Athreya, V., Odden, M., Linnell, J. D. C., Krishnaswamy, J. & Karanth, K. U. A cat among the dogs: leopard Panthera pardus diet in a human-dominated landscape in western Maharashtra, India. Oryx 50, 156–162 (2016).
Google Scholar 
Steinmetz, R., Seuaturien, N., Intanajitjuy, P., Inrueang, P. & Prempree, K. The effects of prey depletion on dietary niches of sympatric apex predators in Southeast Asia. Integr. Zool. 16, 19–32 (2021).CAS 
PubMed 

Google Scholar 
Appel, M. J. G. et al. Canine distemper epizootic in lions, tigers, and leopards in North America. J. Vet. Diagn. Invest. 6, 277–288 (1994).CAS 
PubMed 

Google Scholar 
Coltman, D. W., Pilkington, J. G., Smith, J. A. & Pemberton, J. M. Parasite-mediated selection against inbred Soay sheep in a free-living, island population. Evolution 53, 1259–1267 (1999).PubMed 

Google Scholar 
Fox, C. W. & Reed, D. H. Inbreeding depression increases with environmental stress: an experimental study and meta-analysis. Evolution 65, 246–258 (2011).PubMed 

Google Scholar 
Feng, L. et al. Collaboration brings hope for the last Amur leopards. Cat. N. 65, 20 (2017).
Google Scholar 
Lacy, R. C., Pollak, J. P., Miller, P. S., Hungerford, L. & Bright, P. Outbreak. Version 2.10. (2020).Lacy, R. C. & Pollak, J. P. Vortex: A stochastic simulation of the extinction process. Version 10.4. (2021).Pollak, J. P. & Lacy, R. C. Metamodel manager. Version 1.0.6. (2020).Pacioni, C., Sullivan, S., Lees, C. M., Miller, P. S. & Lacy, R. C. Outbreak user’s manual. Version 1.1. (2020).Roscoe, D. E. Epizootiology of canine-distemper in new-jersey raccoons. J. Wildl. Dis. 29, 390–395 (1993).CAS 
PubMed 

Google Scholar 
Odden, M. & Wegge, P. Spacing and activity patterns of leopards Panthera pardus in the Royal Bardia National Park, Nepal. Wildl. Biol. 11, 145–152 (2005).
Google Scholar 
Stander, P. E., Haden, P. J., Kaqece, I. & Ghau, I. The ecology of asociality in Namibian leopards. J. Zool. 242, 343–364 (1997).
Google Scholar 
Huisman, J., Kruuk, L. E. B., Ellis, P. A., Clutton-Brock, T. & Pemberton, J. M. Inbreeding depression across the lifespan in a wild mammal population. Proc. Natl Acad. Sci. 113, 3585–3590 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Morton, N. E., Crow, J. F. & Muller, H. J. An estimate of the mutational damage in man from data on consanguineous marriages. Proc. Natl Acad. Sci. 42, 855–863 (1956).CAS 
PubMed 
PubMed Central 

Google Scholar 
Balme, G. A., Slotow, R. & Hunter, L. T. B. Edge effects and the impact of non-protected areas in carnivore conservation: leopards in the Phinda–Mkhuze Complex, South Africa. Anim. Conserv. 13, 315–323 (2010).
Google Scholar 
Kumbhojkar, S., Yosef, R., Mehta, A. & Rakholia, S. A camera-trap home-range analysis of the Indian leopard (Panthera pardus fusca) in Jaipur, India. Animals 10, 1600 (2020).PubMed Central 

Google Scholar 
Rozhnov, V. V. et al. Home range structure and space use of a female Amur leopard, Panthera pardus orientalis (Carnivora, Felidae). Biol. Bull. 42, 821–830 (2015).
Google Scholar 
Ralls, K., Ballou, J. D. & Templeton, A. Estimates of lethal equivalents and the cost of inbreeding in mammals. Conserv. Biol. 2, 185–193 (1988).
Google Scholar 
Hammersley, J. M. & Handscomb, D. C. General principles of the Monte Carlo method. in Monte Carlo Methods (eds. Hammersley, J. M. & Handscomb, D. C.) 50–75 (Springer Netherlands, 1964). https://doi.org/10.1007/978-94-009-5819-7_5.Kenney, J. S., Allendorf, F. W., McDougal, C. & Smith, J. L. D. How much gene flow is needed to avoid inbreeding depression in wild tiger populations? Proc. R. Soc. B Biol. Sci. 281, 20133337 (2014).
Google Scholar 
O’Grady, J. J. et al. Realistic levels of inbreeding depression strongly affect extinction risk in wild populations. Biol. Conserv. 133, 42–51 (2006).
Google Scholar 
Miller, P. S., Lacy, R. C., Medina-Miranda, R., López-Ortiz, R. & Díaz-Soltero, H. Confronting the invasive species crisis with metamodel analysis: An explicit, two-species demographic assessment of an endangered bird and its brood parasite in Puerto Rico. Biol. Conserv. 196, 124–132 (2016).
Google Scholar  More

Doherty, T. S., Glen, A. S., Nimmo, D. G., Ritchie, E. G. & Dickman, C. R. Invasive predators and global biodiversity loss. Proc. Natl. Acad. Sci. 113, 11261–11265 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Salo, P., Korpimäki, E., Banks, P. B., Nordström, M. & Dickman, C. R. Alien predators are more dangerous than native predators to prey populations. Proc. R. Soc. B Biol. Sci. 274, 1237–1243 (2007).
Google Scholar 
Losos, J. B., Schoener, T. W. & Spiller, D. A. Predator-induced behaviour shifts and natural selection in field-experimental lizard populations. Nature 432, 505–508 (2004).ADS 
CAS 
PubMed 

Google Scholar 
Komine, H., Iwai, N. & Kaji, K. Rapid responses in morphology and performance of native frogs induced by predation pressure from invasive mongooses. Biol. Invasions 23, 1293–1305 (2021).
Google Scholar 
Nunes, A. L. et al. A global meta-analysis of the ecological impacts of alien species on native amphibians. Proc. R. Soc. B Biol. Sci. 286, 20182528 (2019).
Google Scholar 
Berthon, K. How do native species respond to invaders? Mechanistic and trait-based perspectives. Biol. Invasions 17, 2199–2211 (2015).
Google Scholar 
Strauss, S. Y., Lau, J. A. & Carroll, S. P. Evolutionary responses of natives to introduced species: What do introductions tell us about natural communities?. Ecol. Lett. 9, 354–371 (2006).
Google Scholar 
Sih, A., Ferrari, M. C. O. & Harris, D. J. Evolution and behavioural responses to human-induced rapid environmental change. Evol. Appl. 4, 367–387 (2011).PubMed 
PubMed Central 

Google Scholar 
Sih, A. et al. Predator–prey naïveté, antipredator behavior, and the ecology of predator invasions. Oikos 119, 610–621 (2010).
Google Scholar 
Gould, S. J. & Vrba, E. Exaptation—A missing term in the science of form. Paleobiology 8, 4–15 (1982).
Google Scholar 
Komine, H. et al. Rapid behavioural responses of native frogs caused by past predation pressure from invasive mongooses. J. Zool. 310, 126–134 (2020).
Google Scholar 
Hoare, J. M., Pledger, S., Nelson, N. J. & Daugherty, C. H. Avoiding aliens: Behavioural plasticity in habitat use enables large, nocturnal geckos to survive Pacific rat invasions. Biol. Conserv. 136, 510–519 (2007).
Google Scholar 
Trompeter, W. P. & Langkilde, T. Invader danger: Lizards faced with novel predators exhibit an altered behavioral response to stress. Horm. Behav. 60, 152–158 (2011).CAS 
PubMed 

Google Scholar 
Thawley, C. J., Goldy-Brown, M., McCormick, G. L., Graham, S. P. & Langkilde, T. Presence of an invasive species reverses latitudinal clines of multiple traits in a native species. Glob. Change Biol. 25, 620–628 (2019).ADS 

Google Scholar 
Melotto, A., Manenti, R. & Ficetola, G. F. Rapid adaptation to invasive predators overwhelms natural gradients of intraspecific variation. Nat. Commun. 11, 3608 (2020).ADS 
PubMed 
PubMed Central 

Google Scholar 
Langkilde, T. Invasive fire ants alter behavior and morphology of native lizards. Ecology 90, 208–217 (2009).PubMed 

Google Scholar 
Moore, R. D., Griffiths, R. A., O’Brien, C. M., Murphy, A. & Jay, D. Induced defences in an endangered amphibian in response to an introduced snake predator. Oecologia 141, 139–147 (2004).ADS 
PubMed 

Google Scholar 
Fritts, T. H. & Rodda, G. H. The role of introduced species in the degradation of island ecosystems: A case history of Guam. Annu. Rev. Ecol. Syst. 29, 113–140 (1998).
Google Scholar 
Caut, S., Angulo, E. & Courchamp, F. Dietary shift of an invasive predator: Rats, seabirds and sea turtles. J. Appl. Ecol. 45, 428–437 (2008).PubMed 

Google Scholar 
Bonnaud, E. et al. The diet of feral cats on islands: A review and a call for more studies. Biol. Invasions 13, 581–603 (2011).
Google Scholar 
Guiden, P. W., Bartel, S. L., Byer, N. W., Shipley, A. A. & Orrock, J. L. Predator–prey interactions in the Anthropocene: Reconciling multiple aspects of novelty. Trends Ecol. Evol. 34, 616–627 (2019).PubMed 

Google Scholar 
Savidge, J. A. Extinction of an island forest avifauna by an introduced snake. Ecology 68, 660–668 (1987).
Google Scholar 
Wu, N. C., Alton, L. A., Clemente, C. J., Kearney, M. R. & White, C. R. Morphology and burrowing energetics of semi-fossorial skinks (Liopholis spp.). J. Exp. Biol. 218, 2416–2426 (2015).PubMed 

Google Scholar 
Losos, J. B. The evolution of form and function: Morphology and locomotor performance in West Indian lizards. Evolution 44, 1189–1203 (1990).PubMed 

Google Scholar 
Irschick, D. J. et al. A comparative analysis of clinging ability among pad-bearing lizards. Biol. J. Linn. Soc. 59, 21–35 (1996).
Google Scholar 
Winchell, K. M., Maayan, I., Fredette, J. R. & Revell, L. J. Linking locomotor performance to morphological shifts in urban lizards. Proc. R. Soc. B Biol. Sci. 285, 20180229 (2018).
Google Scholar 
Tan, W. C., Vanhooydonck, B., Measey, J. & Herrel, A. Morphology, locomotor performance and habitat use in southern African agamids. Biol. J. Linn. Soc. 130, 166–177 (2020).
Google Scholar 
Snyder, R. C. The anatomy and function of the pelvic girdle and hindlimb in lizard locomotion. Am. J. Anat. 95, 1–45 (1954).CAS 
PubMed 

Google Scholar 
Losos, J. B., Schoener, T. W., Langerhans, R. B. & Spiller, D. A. Rapid temporal reversal in predator-driven natural selection. Science 314, 1111 (2006).ADS 
CAS 
PubMed 

Google Scholar 
Anson, J. R., Dickman, C. R., Boonstra, R. & Jessop, T. S. Stress triangle: Do introduced predators exert indirect costs on native predators and prey?. PLoS One 8, e60916 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sheriff, M. J., Peacor, S. D., Hawlena, D. & Thaker, M. Non-consumptive predator effects on prey population size: A dearth of evidence. J. Anim. Ecol. 89, 1302–1316 (2020).PubMed 

Google Scholar 
Cabrera-Pérez, M. Á., Gallo-Barneto, R., Esteve, I., Patiño-Martínez, C. & López-Jurado, L. F. The management and control of the California kingsnake in Gran Canaria (Canary Islands): Project LIFE+ Lampropeltis. Aliens Invasive Species Bull. 32, 20–28 (2012).
Google Scholar 
Hubbs, B. Common Kingsnakes: A Natural History of Lampropeltis getula (Tricolor Books, 2009).
Google Scholar 
Pyron, R. A. & Burbrink, F. T. Systematics of the common kingsnake (Lampropeltis getula; Serpentes: Colubridae) and the burden of heritage in taxonomy. Zootaxa 2241, 22–32 (2009).
Google Scholar 
Monzón-Argüello, C. et al. Snakes on an island: Independent introductions have different potentials for invasion. Conserv. Genet. 16, 1225–1241 (2015).
Google Scholar 
Piquet, J. C. & López-Darias, M. Invasive snake causes massive reduction of all endemic herpetofauna on Gran Canaria. Proc. R. Soc. B Biol. Sci. 288, 20211939 (2021).
Google Scholar 
Martín-González, E. & Sánchez-Pinto, L. Nuevos hallazgos de vertebrados fósiles de Fuerteventura: Identificación de una especie de serpiente utilizando técnicas de micro-escáner. Boletín la Asoc. Amigos del Mus. la Nat. y el Hombre Tenerife 15, 76–85 (2013).
Google Scholar 
García-Talavera, F., Rage, J.-C. & Barahona, F. The first record of snakes on the Canary Islands: A vertebra from the Upper Miocene of Lanzarote. Amphibia-Reptilia 19, 419–425 (1998).
Google Scholar 
Martín, A. & Lorenzo, J. Aves del archipiélago Canario (Francisco Lemus Editor S.L., 2001).
Google Scholar 
Nogales, M. & Medina, F. M. Trophic ecology of feral cats (Felis silvestris f. catus) in the main environments of an oceanic archipelago (Canary Islands): An updated approach. Mamm. Biol. 74, 169–181 (2009).
Google Scholar 
Salvador, A. & Pleguezuelos, J. Reptiles españoles: Identificación, historia natural y distribución (Esfagnos, 2002).
Google Scholar 
Vernet, R., Castanet, J. & Baez, M. Comparative water fux and daily energy expenditure of lizards of the genus Gallotia (Lacertidae) from the Canary Islands. Amphibia-Reptilia 16, 55–66 (1995).
Google Scholar 
Brown, R. P. Microevolution and Ecophysiology of Canary Island Skinks (Chalcides) (Thesis from the University of Aberdeen, 1990).
Google Scholar 
Penado, A. et al. Where to “rock”? Choice of retreat sites by a gecko in a semi-arid habitat. Acta Herpetol. 10, 47–54 (2015).
Google Scholar 
Brown, R. P. Thermal biology of the gecko Tarentola boettgeri: Comparisons among populations from different elevation within Gran Canaria. Herpetologica 52, 396–405 (1996).
Google Scholar 
Wiseman, K. D., Greene, H. W., Koo, M. S. & Long, D. J. Feeding ecology of generalist predator, the California kingsnake (Lampropeltis californiae): Why rare prey matter. Herpetol. Conserv. Biol. 14, 1–30 (2019).
Google Scholar 
King, R. B. Predicted and observed maximum prey size—Snake size allometry. Funct. Ecol. 16, 766–772 (2002).
Google Scholar 
Crystal-Ornelas, R. & Lockwood, J. L. The ‘known unknowns’ of invasive species impact measurement. Biol. Invasions 22, 1513–1525 (2020).
Google Scholar 
del Arco Aguilar, M. J. & Rodríguez Delgado, O. Vegetation of the Canary Islands (Springer, 2018).
Google Scholar 
AEMET. Standard climate values. AEMET (2022). http://www.aemet.es/en/serviciosclimaticos/datosclimatologicos/valoresclimatologicos?k=mur#tab2 (Accessed 9th February 2021)GESPLAN. Action A.1: Desarrollo de protocolos para la sistematización de las labores de captura y la recolección de datos. Official report (2015).Atzori, A. et al. Advances in methodologies of sexing and marking less dimorphic gekkonid lizards: The study case of the Moorish gecko, Tarentola mauritanica. Amphibia-Reptilia 28, 449–454 (2007).
Google Scholar 
Stuart, Y. E. et al. Rapid evolution of a native species following invasion by a congener. Science 346, 463–466 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Peig, J. & Green, A. J. New perspectives for estimating body condition from mass/length data: The scaled mass index as an alternative method. Oikos 118, 1883–1891 (2009).
Google Scholar 
Peig, J. & Green, A. J. The paradigm of body condition: A critical reappraisal of current methods based on mass and length. Funct. Ecol. 24, 1323–1332 (2010).
Google Scholar 
Molina-Borja, M. & Rodríguez-Domínguez, M. A. Evolution of biometric and life-history traits in lizards (Gallotia) from the Canary Islands. J. Zool. Syst. Evol. Res. 42, 44–53 (2004).
Google Scholar 
Suárez, C. R., Rodríguez-Domínguez, M. A. & Molina-Borja, M. Sexual dimorphism in morphological traits and scaling relationships in two populations of Gallotia stehlini (Fam. Lacertidae: Squamata) from Gran Canaria. Afr. J. Herpetol. 65, 1–20 (2016).
Google Scholar 
Tejangkura, T. Hybrid Zone Genetics and Within-Island Diversity of the Gecko Tarentola boettgeri (Liverpool John Moores University, 2012).
Google Scholar 
Rózsa, L., Reiczigel, J. & Majoros, G. Quantifying parasites in samples of hosts. J. Parasitol. 86, 228–232 (2000).PubMed 

Google Scholar 
Zapatero-Ramos, L. M., Gonzalez-Santiago, P. M., Solera-Puertas, M. A. & Carvajal-Gallardo, M. M. Estudio de nuevas especies de Pterigosomidae (Acari: Actinedida) sobre geckónidos de las Islas Canarias. Descripción de Geckobia canariensis n. sp. y Geckobia tinerfensis n. sp. Rev. Ibérica Parasitol. 49, 51–64 (1989).
Google Scholar 
Fain, A. & Bannert, B. Two new species of Ophionyssus Mégnin (Acari: Macronyssidae) parasitic on lizards of the genus Gallotia Boulenger (Reptilia: Lacertidae) from the Canary Islands. Int. J. Acarol. 26, 41–50 (2000).
Google Scholar 
Rosner, B. On the detection of many outliers. Technometrics 17, 221–227 (1975).MathSciNet 
MATH 

Google Scholar 
Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).
Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).
Google Scholar 
Hartig, F. DHARMa: Residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.4.1 (2021).Langsrud, Ø. ANOVA for unbalanced data: Use type II instead of type III sums of squares. Stat. Comput. 13, 163–167 (2003).MathSciNet 

Google Scholar 
Lenth, R. V. emmeans: Estimated marginal means, aka least-squares means. R package version 1.5.5-1 (2021).Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).MathSciNet 
MATH 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).
Google Scholar 
Halliday, T. R. & Verrell, P. A. Body size and age in amphibians and reptiles. J. Herpetol. 22, 253–265 (1988).
Google Scholar 
Lopez-Darias, M., Vanhooydonck, B., Cornette, R. & Herrel, A. Sex-specific differences in ecomorphological relationships in lizards of the genus Gallotia. Funct. Ecol. 29, 506–514 (2015).
Google Scholar 
Márquez, R. & Cejudo, D. Defensive behavior as an escape strategy in four species of Gallotia (Sauria, Lacertidae) from the Canary Islands. Copeia 2000, 601–605 (2000).
Google Scholar 
Moon, B. R., Penning, D. A., Segall, M. & Herrel, A. Feeding in snakes: Form, function, and evolution of the feeding system. In Feeding in Vertebrates: Evolution, Morphology, Behavior, Biomechanics (eds Bels, V. & Whishaw, I. Q.) 527–574 (Springer, 2019).
Google Scholar 
Castanet, J. & Baéz, M. Adaptation and evolution in Gallotia lizards from the Canary Islands: Age, growth, maturity and longevity. Amphibia-Reptilia 12, 81–102 (1991).
Google Scholar 
Zamora-Camacho, F. J., Reguera, S., Rubiño-Hispán, M. V. & Moreno-Rueda, G. Effects of limb length, body mass, gender, gravidity, and elevation on escape speed in the lizard Psammodromus algirus. Evol. Biol. 41, 509–517 (2014).
Google Scholar 
Glossip, D. & Losos, J. B. Ecological correlates of number of subdigital lamellae in anoles. Herpetologica 53, 192–199 (1997).
Google Scholar 
Crandell, K. E., Herrel, A., Sasa, M., Losos, J. B. & Autumn, K. Stick or grip? Co-evolution of adhesive toepads and claws in Anolis lizards. Zoology 117, 363–369 (2014).PubMed 

Google Scholar 
Landová, E., Jančúchová-Lásková, J., Musilová, V., Kadochová, Š & Frynta, D. Ontogenetic switch between alternative antipredatory strategies in the leopard gecko (Eublepharis macularius): Defensive threat versus escape. Behav. Ecol. Sociobiol. 67, 1113–1122 (2013).
Google Scholar 
Eifler, M. A., Marchand, R., Eifler, D. A. & Malela, K. Habitat use and activity patterns in the nocturnal gecko, Chondrodactylus turneri. Herpetologica 73, 43–47 (2017).
Google Scholar 
Hielen, B. Unterschiedliche Fortpflanzungsstrategien bei Geckos der Gattung Tarentola Gray, 1825. Salamandra 28, 179–194 (1993).
Google Scholar 
Magnhagen, C. Predation risk as a cost of reproduction. Trends Ecol. Evol. 6, 183–186 (1991).CAS 
PubMed 

Google Scholar 
Shine, R. ‘Costs’ of reproduction in reptiles. Oecologia 46, 92–100 (1980).ADS 
PubMed 

Google Scholar 
Moran, E. V. & Alexander, J. M. Evolutionary responses to global change: Lessons from invasive species. Ecol. Lett. 17, 637–649 (2014).PubMed 

Google Scholar 
Whittaker, R. J. & Fernández-Palacios, J. M. Island Biogeography: Ecology, Evolution, and Conservation (Oxford University Press, 2007).
Google Scholar 
Pinya, S., Tejada, S., Capó, X. & Sureda, A. Invasive predator snake induces oxidative stress responses in insular amphibian species. Sci. Total Environ. 566–567, 57–62 (2016).ADS 
PubMed 

Google Scholar 
Genovart, M. et al. The young, the weak and the sick: Evidence of natural selection by predation. PLoS One 5, e9774 (2010).ADS 
PubMed 
PubMed Central 

Google Scholar 
Sand, H., Wikenros, C., Ahlqvist, P., Strømseth, T. H. & Wabakken, P. Comparing body condition of moose (Alces alces) selected by wolves (Canis lupus) and human hunters: Consequences for the extent of compensatory mortality. Can. J. Zool. 90, 403–412 (2012).
Google Scholar 
Vedder, O., Bouwhuis, S. & Sheldon, B. C. The contribution of an avian top predator to selection in prey species. J. Anim. Ecol. 83, 99–106 (2014).PubMed 

Google Scholar 
Lopez, L. K. & Duffy, M. A. Mechanisms by which predators mediate host–parasite interactions in aquatic systems. Trends Parasitol. 37, 890–906 (2021).CAS 
PubMed 

Google Scholar 
Garrido, M. & Pérez-Mellado, V. Human pressure, parasitism and body condition in an insular population of a Mediterranean lizard. Eur. J. Wildl. Res. 61, 617–621 (2015).
Google Scholar 
Amo, L., López, P. & Martín, J. Habitat deterioration affects body condition of lizards: A behavioral approach with Iberolacerta cyreni lizards inhabiting ski resorts. Biol. Conserv. 135, 77–85 (2007).
Google Scholar 
Kindinger, T. L. & Albins, M. A. Consumptive and non-consumptive effects of an invasive marine predator on native coral-reef herbivores. Biol. Invasions 19, 131–146 (2017).
Google Scholar 
Main, A. R. & Bull, C. M. The impact of tick parasites on the behaviour of the lizard Tiliqua rugosa. Oecologia 122, 574–581 (2000).ADS 
CAS 
PubMed 

Google Scholar 
Garrido, M. & Pérez-Mellado, V. Sprint speed is related to blood parasites, but not to ectoparasites, in an insular population of lacertid lizards. Can. J. Zool. 92, 67–72 (2014).
Google Scholar 
Wirsing, A. J., Heithaus, M. R., Brown, J. S., Kotler, B. P. & Schmitz, O. J. The context dependence of non-consumptive predator effects. Ecol. Lett. 24, 113–129 (2021).PubMed 

Google Scholar 
Civantos, E., López, P. & Martín, J. Non-lethal effects of predators on body growth and health state of juvenile lizards, Psammdromus algirus. Physiol. Behav. 100, 332–339 (2010).CAS 
PubMed 

Google Scholar 
Graham, S. P., Freidenfelds, N. A., McCormick, G. L. & Langkilde, T. The impacts of invaders: Basal and acute stress glucocorticoid profiles and immune function in native lizards threatened by invasive ants. Gen. Comp. Endocrinol. 176, 400–408 (2012).CAS 
PubMed 

Google Scholar 
Donihue, C. M. et al. Hurricane-induced selection on the morphology of an island lizard. Nature 560, 88–91 (2018).ADS 
CAS 
PubMed 

Google Scholar 
Donihue, C. M. et al. Hurricane effects on Neotropical lizards span geographic and phylogenetic scales. Proc. Natl. Acad. Sci. 117, 10429–10434 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Goodman, B. A., Miles, D. B. & Schwarzkopf, L. Life on the rocks: Habitat use drives morphological and performance evolution in lizards. Ecology 89, 3462–3471 (2008).PubMed 

Google Scholar 
Hendry, A. P., Gotanda, K. M. & Svensson, E. I. Human influences on evolution, and the ecological and societal consequences. Philos. Trans. R. Soc. B Biol. Sci. 372, 20160028 (2017).
Google Scholar  More