Philippa Kaur

Hughes, C. E. & Atchinson, G. W. The ubiquity of alpine plant radiations: from the Andes to the Hengduan Mountains. N. Phytol. 207, 275–282 (2015).Article 

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

Google Scholar 
Antonelli, A. et al. Geological and climatic influences on mountain biodiversity. Nat. Geosci. 11, 718–725 (2018).ADS 
CAS 
Article 

Google Scholar 
Quintero, I. & Jetz, W. Global elevational diversity and diversification of birds. Nature 555, 246–250 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Merckx, V. S. F. T. et al. Evolution of endemism on a young tropical mountain. Nature 524, 347–350 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Körner, C. Alpine Plant Life (Springer, 1999).Smyčka, J. et al. Reprint of: Disentangling drivers of plant endemism and diversification in the European Alps – a phylogenetic and spatially explicit approach. Perspect. Plant Ecol. Evol. Syst. 30, 31–40 (2018).Article 

Google Scholar 
Schönswetter, P., Stehlik, I., Holderegger, R. & Tribsch, A. Molecular evidence for glacial refugia of mountain plants in the European Alps. Mol. Ecol. 14, 3547–3555 (2005).PubMed 
Article 
CAS 

Google Scholar 
Haller, A. von. Enumeratio Methodica Stirpium Helvetiae indigenarum. (Officina Academica Abrami Vandenhoek, 1742).de Candolle, A. Sur les causes de l’inégale distribution des plantes rares dans la chaîne des Alpes. Atti del Congr. Internazionale Bot. Tenuto Firenze. 92–104 (1875).Boucher, F. C., Zimmermann, N. E. & Conti, E. Allopatric speciation with little niche divergence is common among alpine Primulaceae. J. Biogeogr. 43, 591–602 (2016).Article 

Google Scholar 
Schneeweiss, G. M. et al. Molecular phylogenetic analyses identify Alpine differentiation and dysploid chromosome number changes as major forces for the evolution of the European endemic Phyteuma (Campanulaceae). Mol. Phylogenet. Evol. 69, 634–652 (2013).CAS 
PubMed 
Article 

Google Scholar 
Tkach, N. et al. Molecular phylogenetics, morphology and a revised classification of the complex genus Saxifraga (Saxifragaceae). Taxon 64, 1159–1187 (2015).Article 

Google Scholar 
Favre, A. et al. Out-of-Tibet: the spatio-temporal evolution of Gentiana (Gentianaceae). J. Biogeogr. 43, 1967–1978 (2016).Article 

Google Scholar 
Kadereit, J. W., Griebeler, E. M. & Comes, H. Quaternary diversification in European alpine plants: pattern and process. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 359, 265–274 (2004).PubMed 
PubMed Central 
Article 

Google Scholar 
Xing, Y. & Ree, R. H. Uplift-driven diversification in the Hengduan Mountains, a temperate biodiversity hotspot. Proc. Natl Acad. Sci. 114, E3444–E3451 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Lagomarsino, L. P., Condamine, F. L., Antonelli, A., Mulch, A. & Davis, C. C. The abiotic and biotic drivers of rapid diversification in Andean bellflowers (Campanulaceae). N. Phytol. 210, 1430–1442 (2016).Article 

Google Scholar 
Ding, W. N., Ree, R. H., Spicer, R. A. & Xing, Y. W. Ancient orogenic and monsoon-driven assembly of the world’s richest temperate alpine flora. Science 369, 578–581 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Roquet, C., Boucher, F. C., Thuiller, W. & Lavergne, S. Replicated radiations of the alpine genus Androsace (Primulaceae) driven by range expansion and convergent key innovations. J. Biogeogr. 40, 1874–1886 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Luebert, F. & Muller, L. A. H. Biodiversity from mountain building. Front. Genet. 6, (2015).Zachos, J. C., Dickens, G. R. & Zeebe, R. E. An early Cenozoic perspective on greenhouse warming and carbon-cycle dynamics. Nature 451, 279–283 (2008).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Haffer, J. Speciation in Colombian forest birds west of the Andes. Am. Museum Novit. 2294, 1–58 (1967).Aguilée, R., Claessen, D. & Lambert, A. Adaptive radiation driven by the interplay of eco-evolutionary and landscape dynamics. Evolution 67, 1291–1306 (2013).PubMed 
Article 

Google Scholar 
Feng, G., Mao, L., Sandel, B., Swenson, N. G. & Svenning, J. C. High plant endemism in China is partially linked to reduced glacial-interglacial climate change. J. Biogeogr. 43, 145–154 (2016).Article 

Google Scholar 
Molina-Venegas, R., Aparicio, A., Lavergne, S. & Arroyo, J. Climatic and topographical correlates of plant palaeo- and neoendemism in a Mediterranean biodiversity hotspot. Ann. Bot. 119, 229–238 (2017).PubMed 
Article 

Google Scholar 
Saladin, B. et al. Rapid climate change results in long-lasting spatial homogenization of phylogenetic diversity. Nat. Commun. 11, 1–8 (2020).Article 
CAS 

Google Scholar 
Hughes, C. & Eastwood, R. Island radiation on a continental scale: exceptional rates of plant diversification after uplift of the Andes. Proc. Natl Acad. Sci. 103, 10334–10339 (2006).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pouchon, C. et al. Phylogenomic analysis of the explosive adaptive radiation of the Espeletia complex (Asteraceae) in the tropical Andes. Syst. Biol. 67, 1041–1060 (2018).CAS 
PubMed 
Article 

Google Scholar 
Kadereit, J. W. The role of in situ species diversification for the evolution of high vascular plant species diversity in the European Alps—a review and interpretation of phylogenetic studies of the endemic flora of the Alps. Perspect. Plant Ecol. Evol. Syst. 26, 28–38 (2017).Article 

Google Scholar 
Escobar García, P. et al. Extensive range persistence in peripheral and interior refugia characterizes Pleistocene range dynamics in a widespread Alpine plant species (Senecio carniolicus, Asteraceae). Mol. Ecol. 21, 1255–1270 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Lohse, K., Nicholls, J. A. & Stone, G. N. Inferring the colonization of a mountain range-refugia vs. nunatak survival in high alpine ground beetles. Mol. Ecol. 20, 394–408 (2011).CAS 
PubMed 
Article 

Google Scholar 
Stehlik, I. Resistance or emigration? Response of alpine plants to the ice ages. Taxon 52, 499–510 (2003).Article 

Google Scholar 
Schneeweiss, G. M. & Schönswetter, P. A re-appraisal of nunatak survival in arctic-alpine phylogeography. Mol. Ecol. 20, 190–192 (2011).PubMed 
Article 

Google Scholar 
Westergaard, K. B. et al. Glacial survival may matter after all: Nunatak signatures in the rare European populations of two west-arctic species. Mol. Ecol. 20, 376–393 (2011).PubMed 
Article 

Google Scholar 
Bettin, O., Cornejo, C., Edwards, P. J. & Holderegger, R. Phylogeography of the high alpine plant Senecio halleri (Asteraceae) in the European Alps: In situ glacial survival with postglacial stepwise dispersal into peripheral areas. Mol. Ecol. 16, 2517–2524 (2007).CAS 
PubMed 
Article 

Google Scholar 
Tomasello, S., Karbstein, K., Hodač, L., Paetzold, C. & Hörandl, E. Phylogenomics unravels Quaternary vicariance and allopatric speciation patterns in temperate-montane plant species: a case study on the Ranunculus auricomus species complex. Mol. Ecol. 29, 2031–2049 (2020).PubMed 
Article 

Google Scholar 
Ozenda, P. L’endémisme au niveau de l’ensemble du Système alpin. Acta Bot. Gall. 142, 753–762 (1995).Article 

Google Scholar 
Rolland, J., Lavergne, S. & Manel, S. Combining niche modelling and landscape genetics to study local adaptation: A novel approach illustrated using alpine plants. Perspect. Plant Ecol. Evol. Syst. 17, 491–499 (2015).Article 

Google Scholar 
Alvarez, N. et al. History or ecology? Substrate type as a major driver of spatial genetic structure in Alpine plants. Ecol. Lett. 12, 632–640 (2009).PubMed 
Article 

Google Scholar 
Gao, Y.-D., Gao, X.-F. & Harris, A. Species boundaries and parapatric speciation in the complex of alpine shrubs, Rosa sericea (Rosaceae), based on population genetics and ecological tolerances. Front. Plant Sci. 10, 1–16 (2019).Article 

Google Scholar 
Knox, E. B. Adaptive radiation of African montane plants. In Adaptive Speciation (eds. Dieckmann, U., Doebeli, M., Metz, J. A. J. & Tautz, D.) 345–361 (Cambridge University Press, 2004).Segar, S. T. et al. Speciation in a keystone plant genus is driven by elevation: a case study in New Guinean Ficus. J. Evol. Biol. 30, 512–523 (2017).CAS 
PubMed 
Article 

Google Scholar 
Pouchon, C. et al. Phylogenetic signatures of ecological divergence and leapfrog adaptive radiation in Espeletia. Am. J. Bot. 108, 113–128 (2021).CAS 
PubMed 
Article 

Google Scholar 
Luebert, F. & Weigend, M. Phylogenetic insights into Andean plant diversification. Front. Ecol. Evol. 2, 1–17 (2014).Article 

Google Scholar 
Nagy, L. & Grabherr, G. The Biology of Alpine Habitats (Oxford University Press, 2009).Louca, S. & Pennell, M. W. Extant timetrees are consistent with a myriad of diversification histories. Nature 580, 502–505 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Goldberg, E. E., Lancaster, L. T. & Ree, R. H. Phylogenetic inference of reciprocal effects between geographic range evolution and diversification. Syst. Biol. 60, 451–465 (2011).PubMed 
Article 

Google Scholar 
Goldberg, E. E. & Igić, B. Tempo and mode in plant breeding system evolution. Evolution 66, 3701–3709 (2012).PubMed 
Article 

Google Scholar 
Gitzendanner, M., Soltis, P., Yi, T.-S., Li, D.-Z. & Soltis, D. Plastome Phylogenetics: 30 years of inferences into plant evolution. In Advances in Botanical Research 293–313 (Elsevier, 2018).Birks, H. H. The late-quaternary history of arctic and alpine plants. Plant Ecol. Divers. 1, 135–146 (2008).Article 

Google Scholar 
Mai, D. Tertiäre Vegetationsgeschichte Europas—Metoden und Ergebnisse. (Gustav Fischer Verlag, 1995).Svenning, J. C. Deterministic Plio-Pleistocene extinctions in the European cool-temperate tree flora. Ecol. Lett. 6, 646–653 (2003).Article 

Google Scholar 
Fauquette, S. et al. The Alps: a geological, climatic and human perspective on vegetation history and modern plant diversity. In Mountains, Climate and Biodiversity (eds. Hoorn, C., Perrigo, A. & Antonelli, A.) 413 (Wiley-Blackwell, 2018).Mráz, P. et al. Vascular plant endemism in the Western Carpathians: spatial patterns, environmental correlates and taxon traits. Biol. J. Linn. Soc. 119, 630–648 (2016).Article 

Google Scholar 
Puşcaş, M. et al. Post-glacial history of the dominant alpine sedge Carex curvula in the European Alpine System inferred from nuclear and chloroplast markers. Mol. Ecol. 17, 2417–2429 (2008).PubMed 
Article 
CAS 

Google Scholar 
Puşcaş, M., Taberlet, P. & Choler, P. No positive correlation between species and genetic diversity in European alpine grasslands dominated by Carex curvula. Divers. Distrib. 14, 852–861 (2008).Article 

Google Scholar 
Magyari, E. K. et al. Late Pleniglacial vegetation in eastern-central Europe: are there modern analogues in Siberia? Quat. Sci. Rev. 95, 60–79 (2014).ADS 
Article 

Google Scholar 
Prodon, R., Thibault, J. C. & Dejaifve, P. A. Expansion vs. compression of bird altitudinal ranges on a Mediterranean island. Ecology 83, 1294–1306 (2002).Article 

Google Scholar 
Moen, D. & Morlon, H. Why does diversification slow down? Trends Ecol. Evol. 29, 190–197 (2014).PubMed 
Article 

Google Scholar 
Aguilée, R., Gascuel, F., Lambert, A. & Ferriere, R. Clade diversification dynamics and the biotic and abiotic controls of speciation and extinction rates. Nat. Commun. 9, 1–13 (2018).Article 
CAS 

Google Scholar 
Vargas, P. Molecular evidence for multiple diversification patterns of alpine plants in Mediterranean Europe. Taxon 52, 463–476 (2003).Article 

Google Scholar 
Kruckeberg, A. R. An essay: the stimulus of unusual geologies for plant speciation. Syst. Bot. 11, 455–463 (1986).Article 

Google Scholar 
Cowling, R. M. & Holmes, P. M. Endemism and speciation in a lowland flora from the Cape Floristic Region. Biol. J. Linn. Soc. 47, 367–383 (1992).Article 

Google Scholar 
Lexer, C. et al. Genomics of the divergence continuum in an African plant biodiversity hotspot, I: drivers of population divergence in Restio capensis (Restionaceae). Mol. Ecol. 23, 4373–4386 (2014).CAS 
PubMed 
Article 

Google Scholar 
Anacker, B. L. & Strauss, S. Y. The geography and ecology of plant speciation: range overlap and niche divergence in sister species. Proc. R. Soc. B Biol. Sci. 281, 20132980 (2014).Article 

Google Scholar 
Moore, A. J. & Kadereit, J. W. The evolution of substrate differentiation in Minuartia series Laricifoliae (Caryophyllaceae) in the European Alps: in situ origin or repeated colonization? Am. J. Bot. 100, 2412–2425 (2013).PubMed 
Article 

Google Scholar 
Guggisberg, A. et al. The genomic basis of adaptation to calcareous and siliceous soils in Arabidopsis lyrata. Mol. Ecol. 27, 5088–5103 (2018).PubMed 
Article 

Google Scholar 
Gigon, A. Vergleich alpiner Rasen auf Silikat- und auf Karbonatboden—Konkurrenz—und Stickstofformenversuche sowie standortskundliche Untersuchungen im Nardetum und im Seslerietum bei Davos. (ETH Zuerich, 1971).Davies, M. S. & Snaydon, R. W. Physiological differences among populations of Anthoxanthum odoratum L. collected from the park grass experiment, Rothamsted. I. Response to calcium. J. Appl. Ecol. 10, 33–45 (1973).Article 

Google Scholar 
Snaydon, R. W. Rapid population differentiation in mosaic environment. I. The response of Anthoxantum odoratum populations to soils. Evolution 24, 257–269 (1970).CAS 
PubMed 
Article 

Google Scholar 
Zohlen, A. & Tyler, G. Soluble inorganic tissue phosphorus and calcicole-calcifuge behaviour of plants. Ann. Bot. 94, 427–432 (2004).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kassen, R., Llewellyn, M. & Rainey, P. B. Ecological contraints on diversification in a model adaptive radiation. Nature 431, 984–988 (2004).ADS 
CAS 
PubMed 
Article 

Google Scholar 
MacLean, R. C., Bell, G. & Rainey, P. B. The evolution of a pleiotropic fitness tradeoff in Pseudomonas fluorescens. Proc. Natl Acad. Sci. USA 101, 8072–8077 (2004).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rabosky, D. L. & Goldberg, E. E. Model inadequacy and mistaken inferences of trait-dependent speciation. Syst. Biol. 64, 340–355 (2015).CAS 
PubMed 
Article 

Google Scholar 
Kolář, F. et al. Northern glacial refugia and altitudinal niche divergence shape genome-wide differentiation in the emerging plant model Arabidopsis arenosa. Mol. Ecol. 25, 3929–3949 (2016).PubMed 
Article 

Google Scholar 
Dentant, C. & Lavergne, S. Plantes de haute montagne: état des lieux, évolution et analyse diachronique dans le massif des Écrins (France). Bull. Soc. linn. Provence 64, 83–98 (2013).
Google Scholar 
Dentant, C. The highest vascular plants on Earth. Alp. Bot. 128, 97–106 (2018).Article 

Google Scholar 
Boucher, F. C. et al. Reconstructing the origins of high‐alpine niches and cushion life form in the genus Androsace sl (Primulaceae). Evolution 66, 1255–1268 (2012).PubMed 
Article 

Google Scholar 
Boucher, F. C., Lavergne, S., Basile, M., Choler, P. & Aubert, S. Evolution and biogeography of the cushion life form in angiosperms. Perspect. Plant Ecol. Evol. Syst. 20, 22–31 (2016).Article 

Google Scholar 
Schönswetter, P. & Schneeweiss, G. M. Is the incidence of survival in interior Pleistocene refugia (nunataks) underestimated? Phylogeography of the high mountain plant Androsace alpina (Primulaceae) in the European Alps revisited. Ecol. Evol. 9, 4078–4086 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Aeschimann, D., Rasolofo, N. & Theurillat, J. P. Analyse de la flore des Alpes. 2: Diversité et chorologie. Candollea 66, 225–253 (2011).Article 

Google Scholar 
Ebersbach, J. et al. In and out of the Qinghai-Tibet Plateau: divergence time estimation and historical biogeography of the large arctic-alpine genus Saxifraga L. J. Biogeogr. 44, 900–910 (2017).Article 

Google Scholar 
Hannon, G. FASTX. http://hannonlab.cshl.edu/fastx_toolkit/ (2014).Coissac, E. The ORGanelle ASseMbler 1.0.3. https://git.metabarcoding.org/org-asm/org-asm/wikis/home (2016).Shaw, J. et al. Chloroplast DNA sequence utility for the lowest phylogenetic and phylogeographic inferences in angiosperms: the tortoise and the hare IV. Am. J. Bot. 101, 1987–2004 (2014).PubMed 
Article 

Google Scholar 
Mansion, G. et al. How to handle speciose clades? Mass taxon-sampling as a strategy towards illuminating the natural history of Campanula (Campanuloideae). PLoS ONE 7, e50076 (2012).Rossi, M. Taxonomy, phylogeny and reproductive ecology of Gentiana lutea L (University in Bologna, 2011).Hämmerli, M. Molecular Aspects in Systematics of Gentiana Sect. Calathianae Froel (Université de Neuchâtel, 2007).Hungerer, K. B. & Kadereit, J. W. The phylogeny and biogeography of Gentiana L. sect. Ciminalis (Adans.) Dumort.: A historical interpretation of distribution ranges in the European high mountains. Perspect. Plant Ecol. Evol. Syst. 1, 121–135 (1998).Article 

Google Scholar 
Ranwez, V., Harispe, S., Delsuc, F. & Douzery, E. J. P. MACSE: Multiple alignment of coding SEquences accounting for frameshifts and stop codons. PLoS One 6, e22594 (2011).Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552 (2000).CAS 
PubMed 
Article 

Google Scholar 
Kück, P. & Meusemann, K. FASconCAT: convenient handling of data matrices. Mol. Phylogenet. Evol. 56, 1115–1118 (2010).PubMed 
Article 
CAS 

Google Scholar 
Katoh, K., Kuma, K. I., Toh, H. & Miyata, T. MAFFT version 5: Improvement in accuracy of multiple sequence alignment. Nucleic Acids Res. 33, 511–518 (2005).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bouckaert, R. et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10, 1–6 (2014).Article 
CAS 

Google Scholar 
Bouckaert, R. R. & Drummond, A. J. bModelTest: Bayesian phylogenetic site model averaging and model comparison. BMC Evol. Biol. 17, 1–11 (2017).Article 

Google Scholar 
Morlon, H. Phylogenetic approaches for studying diversification. Ecol. Lett. 17, 508–525 (2014).PubMed 
Article 

Google Scholar 
Aeschimann, D., Lauber, K., Moser, D. M. & Theurillat, J. P. Flora Alpina (Editions Belin, 2004).Castroviejo, S. Flora Iberica (Real Jardin Botanico CSIC, 2012).Goliášová, K. & Michalková, E. Flóra Slovenska (Vydavateľstvo Slovenskej akadémie vied, 2012).Speta, E. & Rákosy, L. Wildpflanzen Siebenbürgen (Naturhistorisches Museum Wien, 2010).Sarić, M. Flora Srbije (Srpska akademija nauka i umetnosti, 1992).Schönswetter, P. & Schneeweiss, G. M. Androsace komovensis sp. nov., a long mistaken local endemic from the southern Balkan Peninsula with biogeographic links to the Eastern Alps. Taxon 58, 544–549 (2009).Article 

Google Scholar 
Schönswetter, P., Magauer, M. & Schneeweiss, G. M. Androsace halleri subsp. nuria Schönsw. & Schneew. (Primulaceae), a new taxon from the eastern Pyrenees (Spain, France). Phytotaxa 201, 227–232 (2015).Article 

Google Scholar 
Schneeweiss, G. M. & Schonswetter, P. The wide but disjunct range of the European mountain plant Androsace lactea L. (Primulaceae) reflects Late Pleistocene range fragmentation and post-glacial distributional stasis. J. Biogeogr. 37, 2016–2025 (2010).
Google Scholar 
Webb, D. A. & Gornall, R. J. Saxifrages of Europe (Timber Press, 1989).GBIF. https://www.gbif.org/ (2018).Körner, C. et al. A global inventory of mountains for bio-geographical applications. Alp. Bot. 127, 1–15 (2017).Article 

Google Scholar 
Anacker, B. L., Whittall, J. B., Goldberg, E. E. & Harrison, S. P. Origins and consequences of serpentine endemism in the California flora. Evolution 65, 365–376 (2011).PubMed 
Article 

Google Scholar 
Morlon, H. et al. RPANDA: An R package for macroevolutionary analyses on phylogenetic trees. Methods Ecol. Evol. 7, 589–597 (2016).Article 

Google Scholar 
Burnham, K. & Anderson, D. Model Selection and Multimodel Inference (Springer, 2002).Fitzjohn, R. G., Maddison, W. P. & Otto, S. P. Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Syst. Biol. 58, 595–611 (2009).PubMed 
Article 

Google Scholar 
O’Meara, B. C. & Beaulieu, J. M. Past, future, and present of state-dependent models of diversification. Am. J. Bot. 103, 792–795 (2016).PubMed 
Article 

Google Scholar 
Beaulieu, J. M. & O’Meara, B. C. Detecting hidden diversification shifts in models of trait-dependent speciation and extinction. Syst. Biol. 65, 583–601 (2016).PubMed 
Article 

Google Scholar 
Herrera-Alsina, L., Van Els, P. & Etienne, R. S. Detecting the dependence of diversification on multiple traits from phylogenetic trees and trait data. Syst. Biol. 68, 317–328 (2019).PubMed 
Article 

Google Scholar 
Onstein, R. E. et al. To adapt or go extinct? The fate of megafaunal palm fruits under past global change. Proc. R. Soc. B Biol. Sci. 285, (2018).Rabosky, D. L. & Goldberg, E. E. FiSSE: a simple nonparametric test for the effects of a binary character on lineage diversification rates. Evolution 71, 1432–1442 (2017).PubMed 
Article 

Google Scholar 
Holland, B. R., Ketelaar-Jones, S., O’Mara, A. R., Woodhams, M. D. & Jordan, G. J. Accuracy of ancestral state reconstruction for non-neutral traits. Sci. Rep. 10, 1–10 (2020).Article 
CAS 

Google Scholar 
Ree, R. H. & Sanmartín, I. Conceptual and statistical problems with the DEC+J model of founder-event speciation and its comparison with DEC via model selection. J. Biogeogr. 45, 741–749 (2018).Article 

Google Scholar 
Schoener, T. W. Nonsynchronous spatial overlap of lizards in patchy habitats. Ecology 51, 408–418 (1970).Article 

Google Scholar 
Zhang, J. spaa: SPecies Association Analysis 0.2.2. https://cran.r-project.org/package=spaa (2016).Smyčka, J. Tempo and drivers of plant diversification in the European mountain system. multidiv, https://doi.org/10.5281/zenodo.6341727 (2022). More

Young cerebrospinal fluid probably improves the conductivity of the neurons in ageing mice.Credit: Qilai Shen/Bloomberg/Getty

Young brain fluid improves memory in old miceCerebrospinal fluid (CSF) from young mice can improve memory function in older mice, researchers report in Nature (T. Iram et al. Nature 605, 509–515; 2022).A direct brain infusion of young CSF probably improves the conductivity of the neurons in ageing mice, which improves the process of making and recalling memories.CSF is a cocktail of essential ions and nutrients that cushions the brain and spinal cord and is essential for normal brain development. But as mammals age, CSF loses some of its punch. Those changes might affect cells related to memory, says co-author Tal Iram, a neuroscientist at Stanford University in California.The researchers found that young CSF helps ageing mice to generate more early-stage oligodendrocytes, cells in the brain that produce the insulating sheath around nerve projections and help to maintain brain function.The team suggest that the improvements are largely due to a specific protein in the fluid.“This is super exciting from the perspective of basic science, but also looking towards therapeutic applications,” says Maria Lehtinen, a neurobiologist at Boston Children’s Hospital in Massachusetts.Gender bias worms its way into parasite namingA study examining the names of nearly 3,000 species of parasitic worm discovered in the past 20 years reveals a markedly higher proportion named after male scientists than after female scientists — and a growing appetite for immortalizing friends and family members in scientific names.Robert Poulin, an ecological parasitologist at the University of Otago in Dunedin, New Zealand, and his colleagues combed through papers published between 2000 and 2020 that describe roughly 2,900 new species of parasitic worm (R. Poulin et al. Proc. R. Soc. B https://doi.org/htqn; 2022). The team found that well over 1,500 species were named after their host organism, where they were found or a prominent feature of their anatomy.

Source: R. Poulin et al. Proc. R. Soc. B https://doi.org/htqn (2022)

Many others were named after people, ranging from technical assistants to prominent politicians. But just 19% of the 596 species named after eminent scientists were named after women, a percentage that barely changed over the decades (see ‘Parasite name game’). Poulin and his colleagues also noticed an upward trend in the number of parasites named after friends, family members and even pets of the scientists who formally described them. This practice should be discouraged, Poulin argues.

Sea anemones turn oxybenzone into a light-activated agent that can bleach and kill corals.Credit: Georgette Douwma/Getty

Anemones suggest why sunscreen turns toxic in seaA common but controversial sunscreen ingredient that is thought to harm corals might do so because of a chemical reaction that causes it to damage cells in the presence of ultraviolet light.Researchers have discovered that sea anemones, which are similar to corals, make the sun-blocking molecule oxybenzone water-soluble by tacking a sugar onto it. This inadvertently turns oxybenzone into a molecule that — instead of blocking UV light — is activated by sunlight to produce free radicals that can bleach and kill corals. The animals “convert a sunscreen into something that’s essentially the opposite of a sunscreen”, says Djordje Vuckovic, an environmental engineer at Stanford University in California.It’s not clear how closely these laboratory-based studies mimic the reality of reef ecosystems. The concentration of oxybenzone at a coral reef can vary widely, depending on factors such as tourist activity and water conditions. And other factors threaten the health of coral reefs; these include climate change, ocean acidification, coastal pollution and overfishing. The study, published on 5 May (D. Vuckovic et al. Science 376, 644–648; 2022) does not show where oxybenzone ranks in the list. More

Australia’s tropical rainforests are some of the oldest in the world.Credit: Alexander Schenkin

The rate of tree dying in the old-growth tropical forests of northern Australia each year has doubled since the 1980s, and researchers say climate change is probably to blame.The findings, published today in Nature1, come from an extraordinary record of tree deaths catalogued at 24 sites in the tropical forests of northern Queensland over the past 49 years.“Trees are such long-living organisms that it really requires huge amounts of data to be able to detect changes in such rare events as the death of a tree,” says lead author David Bauman, a plant ecologist at the University of Oxford, UK. The sites were initially surveyed every two years, then every three to four years, he explains, and the analysis focused on 81 key species.Bauman and his team recorded that 2,305 of these trees have died since 1971. But they calculated that, from the mid-1980s, tree mortality risk increased from an average of 1% a year to 2% a year (See ‘Increasing death rate’).

Bauman says that trees help to slow global warming because they absorb carbon dioxide, so an increase in tree deaths reduces forests’ carbon-capturing ability. “Tropical forests are critical to climate change, but they’re also very vulnerable to it,” he explains.Climate changeThe study found that the rise in death rate occurred at the same time as a long-term trend of increases in the atmospheric vapour pressure deficit, which is the difference between the amount of water vapour that the atmosphere can hold and the amount of water it does hold at a given time. The higher the deficit, the more water trees lose through their leaves. “If the evaporative demand at the leaf level can’t be matched by water absorption in fine roots, it can lead to leaves wilting, whole branches dying and, if the stress is sustained, to tree death,” Bauman says.The researchers looked at other climate-related trends — including rising temperatures and an estimate of drought stress in soils — but they found that the drying atmosphere had the strongest effect. “What we show is that this increase [in tree mortality risk] also closely followed the increase in atmospheric water stress, or the drying power of air, which is a consequence of the temperature increase due to climate change,” Bauman explains.Of the 81 tree species that the team studied, 70% showed an increase in mortality risk over the study period, including the Moreton Bay chestnut (Castanospermum australe), white aspen (Medicosma fareana) and satin sycamore (Ceratopetalum succirubrum).The authors also saw differences in mortality in the same tree species across plots, depending on how high the atmospheric vapour pressure deficit was in each plot.“This is one data set where the trees have been monitored in reasonably good detail since the early ’70s, and this is a really top-notch analysis of it,” says Belinda Medlyn, an ecosystem scientist at University of Western Sydney, Australia.But she says that more experiments are needed to determine whether the vapour pressure deficit is the biggest climate-related contributor to the increase in tree deaths. More

DataAll data was processed and analyzed using R (R Core Team, Version 4.0.3).Dengue case data were collected and shared by the Alcaldía de Medellín, Secretaría de Salud. In Medellin, dengue case surveillance is conducted by public health institutions that classify and report all cases that meet the WHO clinical dengue case criteria for a probable case to Medellin’s Secretaría de Salud through SIVIGILA (“el Sistema Nacional de Vigilancia en Salud Publica). All case data were de-identified and aggregated to the SIT Zone level.Human public transit usage and movement data were collected and shared by the Área Metropolitana del Valle de Aburrá for 50–200 respondents per SIT Zone. The “Encuestas Origen Destino” (Origen Destination Surveys) were conducted in 2005, 2011, and 2016 and published in 2006, 2012, and 2017, with survey methods described by the Área Metropolitana del Valle de Aburrá25. Survey respondents include a randomly selected subset of all Medellin residents in each SIT zone regardless of whether they use public transit or not. Survey respondents reported the start and end locations, purpose for travel, and mode of travel for all movement over the last 24 h from the time the survey was administered. Respondents reported all modes of movement, including public transit, private transit, and movement on foot. The results of the survey published in 2017 are published online by the Área Metropolitana del Valle de Aburrá26, and select data are available through the geodata-Medellin open data portal27. The results and data of the survey published in 2012 are not publicly available and were obtained directly from the Área Metropolitana del Valle de Aburrá.The public transit usage survey data were also used to extract socioeconomic data to the SIT zone; surveyors also reported basic demographic data including household Estrato, which was averaged per SIT zone to estimate zone socioeconomic status. “Estrato” measures socioeconomic status on a scale from 1 (lowest) to 6 (highest). This system is used by the government of Colombia to allocate public services and subsidies (Law 142, 1994). Data from the public transit usage survey were used to extract socioeconomic status data because it is the only location available where the spatial scale of the data matched the spatial scale of the SIT zone.Data on the location of Medellín public transit lines was downloaded as shape files from the geodata-Medellín open data portal27 and subset for each year to the set of transit lines that was available in that year. Data on the opening date of each Medellín public transit line was taken from the Medellín metro website28.Because census data at the zone level were not available for this study and only exists for 2005 and 2018, we used population estimates for each year downloaded from the WorldPop project29 and aggregated by SIT zone. The accuracy of WorldPop estimates were checked against available census data for 2005 and 2018 at the comuna level, accessed via the geodata- Medellín open data portal27.Ethical considerationsNo human subjects research was conducted. All data used was de-identified, and the analysis was conducted on a database of cases meeting the clinical criteria for dengue with no intervention or modification of biological, physical, psychological, or social variables. All methods were performed in accordance with the relevant guidelines and regulations.Data analysisQuantifying public transit usage and distance from nearest transit lineTo quantify public transit usage, we determined if each respondent reported using the metro, metroplus, or ruta alimentadora (supplementary bus route system integrated with the metro system) in the last 24 h. We then calculated the percent of respondents using the public transit system at least once for each SIT zone.To quantify the distance to the nearest public transit line, we calculated the distance from the center point of each zone to the closest metro, metroplus, tranvía, metrocable, ruta alimentadora, or escalera eléctrica. This was recalculated for each year, including new transit lines that were added within that year.Spatial autoregressive models of dengue incidenceDengue incidence per year at the level of the SIT zone was modeled using a fixed effects spatial panel model by maximum likelihood (R package splm30) as described in31. Our fixed effects were socioeconomic status, distance from public transit, a two-way interaction between these factors, and year. To weight dengue cases by population per SIT zone, the model contained a log offset of population per zone per year. Dengue case counts were log transformed after adding one to account for zones with zero dengue cases in a given year. Year was analyzed as a categorical variable to avoid smoothing epidemic years. All continuous variables were scaled to enable comparison of effect size. Because these panel models require balanced data across time, data was truncated to SIT zones that had data for all years available (247 remaining of 291). Spatial dependency was evaluated, and the model was selected using the Hausman specification test and locally robust panel Lagrange Multiplier tests for spatial dependence. Based on a significant Hausman specification test result, which indicates a poor specification of the random effect model, a fixed effect model was chosen. This result is supported by the fact that we had a nearly exhaustive sample of SIT zones in the Medellin metro area. Lagrange multiplier tests were used to determine the most appropriate spatial dependency specifications. Based on the results of the Lagrange multiplier tests, a Spatial Autoregressive (SAR) model was the most appropriate to incorporate spatial dependency; a SAR model considers that the number of dengue cases in a SIT zone depends on the number in neighboring zones.Because public transit usage was a measurement taken during just two of the study years, we constructed an additional fixed effects spatial panel model by maximum likelihood model of dengue incidence in just 2011 and 2016 that included ridership as an additional predictor variable. Our fixed effects were year, socioeconomic status, distance from public transit, a two-way interaction between socioeconomic status and distance from public transit, percent utilizing public transit, and a two-way interaction between socioeconomic status and percent utilizing public transit. As in our model of all years, the model contained a log offset of population per zone per year and dengue case counts were log transformed after adding one to account for zones with zero dengue cases in a given year, year was analyzed as a categorical variable, and all continuous variables were scaled to enable comparison of effect size. The data was truncated to SIT zones that had data for all years available (251 remaining of 291). We used the same model selection process, and again a fixed effect model was chosen, and based on the results of the Lagrange multiplier tests, a Spatial Autoregressive (SAR) model was determined the most appropriate to incorporate spatial dependency. More

Kelly, A. E. & Goulden, M. L. Rapid shifts in plant distribution with recent climate change. Proc. Natl. Acad. Sci. U.S.A. 105, 11823–11826. https://doi.org/10.1073/pnas.0802891105 (2008).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Wiens, J. J. Climate-related local extinctions are already widespread among plant and animal species. PLoS Biol. 14, e2001104. https://doi.org/10.1371/journal.pbio.2001104 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Swinnen, J., Burkitbayeva, S., Schierhorn, F., Prishchepov, A. V. & Müller, D. Production potential in the “bread baskets” of Eastern Europe and Central Asia. Global Food Secur. 14, 38–53. https://doi.org/10.1016/j.gfs.2017.03.005 (2017).Article 

Google Scholar 
Henry, R. J. Innovations in plant genetics adapting agriculture to climate change. Curr. Opin. Plant Biol. 56, 168–173. https://doi.org/10.1016/j.pbi.2019.11.004 (2020).Article 
PubMed 

Google Scholar 
Stokes, C. & Howden, M. Adapting Agriculture to Climate Change: Preparing Australian Agriculture, Forestry and Fisheries for the Future (Csiro Publishing, 2010).Book 

Google Scholar 
Bräutigam, K. et al. Epigenetic regulation of adaptive responses of forest tree species to the environment. Ecol. Evol. 3, 399–415. https://doi.org/10.1002/ece3.461 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Yaish, M. W., Colasanti, J. & Rothstein, S. J. The role of epigenetic processes in controlling flowering time in plants exposed to stress. J. Exp. Bot. 62, 3727–3735. https://doi.org/10.1093/jxb/err177 (2011).CAS 
Article 
PubMed 

Google Scholar 
Yaish, M. W. DNA methylation-associated epigenetic changes in stress tolerance of plants. In Molecular Stress Physiology of Plants (eds Rout, G. R. & Das, A. B.) 427–440 (Springer India, 2013).Chapter 

Google Scholar 
Suji, K. K. & Joel, A. J. An epigenetic change in rice cultivars underwater stress conditions. Electron. J. Plant Breed. 1, 1142–1143 (2010).
Google Scholar 
Peng, H. & Zhang, J. Plant genomic DNA methylation in response to stresses: Potential applications and challenges in plant breeding. Prog. Nat. Sci. 19, 1037–1045. https://doi.org/10.1016/j.pnsc.2008.10.014 (2009).CAS 
Article 

Google Scholar 
Baduel, P. & Colot, V. The epiallelic potential of transposable elements and its evolutionary significance in plants. Philos. Trans. R. Soc. B 376, 20200123. https://doi.org/10.1098/rstb.2020.0123 (2021).CAS 
Article 

Google Scholar 
Labra, M. et al. Analysis of cytosine methylation pattern in response to water deficit in pea root tips. Plant Biol. 4, 694–699. https://doi.org/10.1055/s-2002-37398 (2002).CAS 
Article 

Google Scholar 
Wang, W.-S. et al. Drought-induced site-specific DNA methylation and its association with drought tolerance in rice (Oryza sativa L.). J. Exp. Bot. 62, 1951–1960. https://doi.org/10.1093/jxb/erq391 (2011).CAS 
Article 
PubMed 

Google Scholar 
Šmarda, P., Bureš, P., Horová, L., Foggi, B. & Rossi, G. Genome size and GC content evolution of Festuca: Ancestral expansion and subsequent reduction. Ann. Bot. 101, 421–433. https://doi.org/10.1093/aob/mcm307 (2008).CAS 
Article 
PubMed 

Google Scholar 
Tomczyk, P. P., Kiedrzyński, M., Jedrzejczyk, I., Rewers, M. & Wasowicz, P. The transferability of microsatellite loci from a homoploid to a polyploid hybrid complex: An example from fine-leaved Festuca species (Poaceae). PeerJ 8, e9227. https://doi.org/10.7717/peerj.9227 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Piękoś-Mirkowa, H. & Mirek, Z. Distribution patterns and habitats of endemic vascular plants in the Polish Carpathians. Acta Soc. Bot. Pol. 78, 321–326 (2009).Article 

Google Scholar 
Kiedrzyński, M., Zielińska, K. M., Rewicz, A. & Kiedrzyńska, E. Habitat and spatial thinning improve the Maxent models performed with incomplete data. J. Geophys. Res. Biogeosci. 122(6), 1359–1370. https://doi.org/10.1002/2016JG003629 (2017).Article 

Google Scholar 
Rewicz, A. et al. Morphometric traits in the fine-leaved fescues depend on ploidy level: The case of Festuca amethystina L. PeerJ 6, e5576. https://doi.org/10.7717/peerj.5576 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Kiedrzyński, M. et al. Tetraploids expanded beyond the mountain niche of their diploid ancestors in the mixed-ploidy grass Festuca amethystina L. Sci. Rep. 11, 18735 (2021).ADS 
Article 

Google Scholar 
Mounger, J. et al. Epigenetics and the success of invasive plants. Philos. Trans. R. Soc. B 376, 20200117. https://doi.org/10.1098/rstb.2020.0117 (2021).CAS 
Article 

Google Scholar 
Bewick, A. J. & Schmitz, R. J. Epigenetics in the wild. Elife 4, e07808. https://doi.org/10.7554/eLife.07808 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Sahu, P. P. et al. Epigenetic mechanisms of plant stress responses and adaptation. Plant Cell Rep. 32(8), 1151–1159. https://doi.org/10.1007/s00299-013-1462-x (2013).CAS 
Article 
PubMed 

Google Scholar 
Alonso, C. et al. Interspecific variation across angiosperms in global DNA methylation: Phylogeny, ecology and plant features in tropical and Mediterranean communities. New Phytol. 224(2), 949–960. https://doi.org/10.1111/nph.16046 (2019).CAS 
Article 
PubMed 

Google Scholar 
Angers, B., Castonguay, E. & Massicotte, R. Environmentally induced phenotypes and DNA methylation: How to deal with unpredictable conditions until the next generation and after. Mol. Ecol. 19(7), 1283–1295. https://doi.org/10.1111/j.1365-294X.2010.04580.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Batog, J. & Wawro, A. Process of obtaining bioethanol from sorghum biomass using genome shuffling. Cellul. Chem. Technol. 53, 459–467 (2019).CAS 
Article 

Google Scholar 
Richards, C. L., Schrey, A. W. & Pigliucci, M. Invasion of diverse habitats by few Japanese knotweed genotypes is correlated with epigenetic differentiation. Ecol. Lett. 15, 1016–1025. https://doi.org/10.1111/j.1461-0248.2012.01824.x (2012).Article 
PubMed 

Google Scholar 
Li, N. et al. DNA methylation repatterning accompanying hybridization, whole genome doubling and homoeolog exchange in nascent segmental rice allotetraploids. New Phytol. 223(2), 979–992. https://doi.org/10.1111/nph.15820 (2019).CAS 
Article 
PubMed 

Google Scholar 
Róis, A. S. et al. Epigenetic rather than genetic factors may explain phenotypic divergence between coastal populations of diploid and tetraploid Limonium spp. (Plumbaginaceae) in Portugal. BMC Plant Biol. 13(1), 205. https://doi.org/10.1186/1471-2229-13-205 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Li, A. et al. DNA methylation in genomes of several annual herbaceous and woody perennial plants of varying ploidy as detected by MSAP. Plant Mol. Biol. Rep. 29, 784–793. https://doi.org/10.1007/s11105-010-0280-3 (2011).ADS 
CAS 
Article 

Google Scholar 
Sokolova, D. A., Vengzhen, G. S. & Kravets, A. P. An Analysis of the correlation between the changes in satellite DNA methylation patterns and plant cell responses to the stress. Cell Bio 2, 163–171. https://doi.org/10.4236/cellbio.2013.23018 (2013).CAS 
Article 

Google Scholar 
Johnson, L. I. & Tricker, P. J. Epigenomic plasticity within populations: Its evolutionary significance and potential. Heredity 105, 113–121. https://doi.org/10.1038/hdy.2010.25 (2010).CAS 
Article 
PubMed 

Google Scholar 
Zheng, X. et al. Transgenerational variations in DNA methylation induced by drought stress in two rice varieties with distinguished difference to drought resistance. PLoS One 8(11), e80253. https://doi.org/10.1371/journal.pone.0080253 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Karan, R., DeLeon, T., Biradar, H. & Subudhi, P. K. Salt Stress induced variation in DNA methylation pattern and its influence on gene expression in contrasting rice genotypes. PLoS One 7(6), e40203. https://doi.org/10.1371/journal.pone.0040203 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richards, C. L. & Pigliucci, M. Epigenetic inheritance. A decade into the extended evolutionary synthesis. Paradigmi 38, 463–494. https://doi.org/10.30460/99624 (2020).Article 

Google Scholar 
Chelaifa, H., Monnier, A. & Ainouche, M. Transcriptomic changes following recent natural hybridization and allopolyploidy in the salt marsh species Spartina × townsendii and Spartina anglica (Poaceae). New Phytol. 186(1), 161–174. https://doi.org/10.1111/j.1469-8137.2010.03179.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Al-Lawati, A., Al-Bahry, S., Victor, R., Al-Lawati, A. H. & Yaish, M. W. Salt stress alters DNA methylation levels in alfalfa (Medicago spp.). Genet. Mol. Res. 15, 15018299. https://doi.org/10.4238/gmr.15018299 (2016).CAS 
Article 
PubMed 

Google Scholar 
Lewandowska-Gnatowska, E. et al. Is DNA methylation modulated by wounding-induced oxidative burst in maize?. Plant Physiol. Biochem. 82, 202–208. https://doi.org/10.1016/j.plaphy.2014.06.003 (2014).CAS 
Article 
PubMed 

Google Scholar 
Marfil, C. et al. Changes in grapevine DNA methylation and polyphenols content induced by solar ultraviolet-B radiation, water deficit and abscisic acid spray treatments. Plant Physiol. Biochem. 135, 287–294. https://doi.org/10.1016/j.plaphy.2018.12.021 (2019).CAS 
Article 
PubMed 

Google Scholar 
Zedek, F. et al. Endopolyploidy is a common response to UV-B stress in natural plant populations, but its magnitude may be affected by chromosome type. Ann. Bot. 126(5), 883–889. https://doi.org/10.1093/aob/mcaa109 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Pandey, N. & Pandey-Rai, S. Deciphering UV-B-induced variation in DNA methylation pattern and its influence on regulation of DBR2 expression in Artemisia annua L. Planta 242(4), 869–879. https://doi.org/10.1007/s00425-015-2323-3 (2015).CAS 
Article 
PubMed 

Google Scholar 
Molinier, J. Genome and epigenome surveillance processes underlying UV exposure in plants. Genes 8(11), 316. https://doi.org/10.3390/genes8110316 (2017).CAS 
Article 
PubMed Central 

Google Scholar 
Niederhuth, C. E. et al. Widespread natural variation of DNA methylation within angiosperms. Genome Biol. 17, 194. https://doi.org/10.1186/s13059-016-1059-0 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Lira-Medeiros, C. F. et al. Epigenetic variation in mangrove plants occurring in contrasting natural environment. PLoS One 5, e10326. https://doi.org/10.1371/journal.pone.0010326 (2010).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richards, C. L., Verhoeven, K. J. F. & Bossdorf, O. Evolutionary significance of epigenetic variation. In Plant Genome Diversity Vol. 1 (eds Wendel, J. F. et al.) 257–274 (Springer Vienna, 2012).Chapter 

Google Scholar 
Paun, O. et al. Stable epigenetic effects impact adaptation in allopolyploid orchids (Dactylorhiza: Orchidaceae). Mol. Biol. Evol. 27, 2465–2473. https://doi.org/10.1093/molbev/msq150 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Xie, H. et al. Global DNA methylation patterns can play a role in defining terroir in grapevine (Vitis vinifera cv. Shiraz). Front. Plant Sci. 8, 130398. https://doi.org/10.3389/fpls.2017.01860 (2017).Article 

Google Scholar 
Herrera, C. M. & Bazaga, P. Epigenetic differentiation and relationship to adaptive genetic divergence in discrete populations of the violet Viola cazorlensis. New Phytol. 187(3), 867–876. https://doi.org/10.1111/j.1469-8137.2010.03298.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Portis, E., Acquadro, A., Comino, C. & Lanteri, S. Analysis of DNA methylation during germination of pepper (Capsicum annuum L.) seeds using methylation-sensitive amplification polymorphism (MSAP). Plant Sci. 166, 169–178. https://doi.org/10.1016/j.plantsci.2003.09.004 (2004).CAS 
Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. http://www.R-project.org (R Foundation for Statistical Computing, 2013).Schloerke, B. et al. GGally: Extension to “ggplot2” R package version 2.1.0. https://CRAN.R-project.org/package=GGally (2021).StatSoft, Inc. STATISTICA (Data Analysis Software System), Version 10. http://www.statsoft.com (2011).Tomczyk, P. Phenotypic measurement of inbreeding depression in grasses—An overview of traits (Fenotypowe miary depresji wsobnej u traw—przegląd cech). Wiad. Bot. https://doi.org/10.5586/wb.2019.005 (2019).Article 

Google Scholar 
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37(12), 4302–4315. https://doi.org/10.1002/joc.5086 (2017).Article 

Google Scholar 
Fox, J. & Weisberg, S. An {R} Companion to Applied Regression (Sage Publications, 2019).
Google Scholar  More

Dobson, A., Lafferty, K. D., Kuris, A. M., Hechinger, R. F. & Jetz, W. Homage to Linnaeus: How many parasites? How many hosts?. Proc. Natl. Acad. Sci. 105, 11482–11489 (2008).ADS 
CAS 
Article 

Google Scholar 
Kuris, A. M. et al. Ecosystem energetic implications of parasite and free-living biomass in three estuaries. Nature 454, 515–518 (2008).ADS 
CAS 
Article 

Google Scholar 
Seabloom, E. W. et al. The community ecology of pathogens: Coinfection, coexistence and community composition. Ecol. Lett. 18, 401–415 (2015).Article 

Google Scholar 
French, R. K. & Holmes, E. C. An ecosystems perspective on virus evolution and emergence. Trends Microbiol. 28, 165–175 (2020).CAS 
Article 

Google Scholar 
Hudson, P. J., Dobson, A. P. & Lafferty, K. D. Is a healthy ecosystem one that is rich in parasites?. Trends Ecol. Evol. 21, 381–385 (2006).Article 

Google Scholar 
Raffel, T. R., Martin, L. B. & Rohr, J. R. Parasites as predators: Unifying natural enemy ecology. Trends Ecol. Evol. 23, 610–618 (2008).Article 

Google Scholar 
Johnson, P. T. J. et al. When parasites become prey: Ecological and epidemiological significance of eating parasites. Trends Ecol. Evol. 25, 362–371 (2010).Article 

Google Scholar 
Frainer, A., McKie, B. G., Amundsen, P. A., Knudsen, R. & Lafferty, K. D. parasitism and the biodiversity-functioning relationship. Trends Ecol. Evol. 33, 260–268 (2018).Article 

Google Scholar 
Jephcott, T. G., Sime-Ngando, T., Gleason, F. H. & Macarthur, D. J. Host-parasite interactions in food webs: Diversity, stability, and coevolution. Food Webs 6, 1–8 (2016).Article 

Google Scholar 
Rohr, J. R. et al. Towards common ground in the biodiversity–disease debate. Nat. Ecol. Evol. 4, 24–33 (2020).Article 

Google Scholar 
Johnson, P. T. J., De Roode, J. C. & Fenton, A. Why infectious disease research needs community ecology. Science 349, 1259504 (2015).Article 

Google Scholar 
Marcogliese, D. J. & Cone, D. K. Food webs: A plea for parasites. Trends Ecol. Evol. 12, 320–325 (1997).CAS 
Article 

Google Scholar 
Chen, H.-W. et al. Network position of hosts in food webs and their parasite diversity. Oikos 117, 1847–1855 (2008).Article 

Google Scholar 
Lafferty, K. D., Dobson, A. P. & Kuris, A. M. Parasites dominate food web links. Proc. Natl. Acad. Sci. USA 103, 11211–11216 (2006).ADS 
CAS 
Article 

Google Scholar 
Lafferty, K. D. et al. Parasites in food webs: The ultimate missing links. Ecol. Lett. 11, 533–546 (2008).Article 

Google Scholar 
Dunne, J. A. The network structure of food webs. In Ecological Networks: Linking Structure to Dynamics (eds Pascual, M. & Dunne, J. A.) 27–28 (Oxford University Press, 2005).
Google Scholar 
Dunne, J. A., Williams, R. J. & Martinez, N. D. Network structure and biodiversity loss in food webs: Robustness increases with connectance. Ecol. Lett. 5, 558–567 (2002).Article 

Google Scholar 
Hudson, P. J., Rizzoli, A., Grenfell, B. T., Heesterbeek, H. & Dobson, A. P. The Ecology of Wildlife Diseases. (Oxford University Press, Oxford, 2002).
Google Scholar 
Anderson, R. M. & May, R. M. Infectious Diseases of Humans: Dynamics and Control (Oxford University Press, 1992).
Google Scholar 
McCallum, H. & Dobson, A. Detecting disease and parasite threats to endangered species and ecosystems. Trends Ecol. Evol. 10, 190–194 (1995).CAS 
Article 

Google Scholar 
De Castro, F. & Bolker, B. M. Parasite establishment and host extinction in model communities. Oikos 111, 501–513 (2005).Article 

Google Scholar 
McQuaid, C. F. & Britton, N. F. Parasite species richness and its effect on persistence in food webs. J. Theor. Biol. 364, 377–382 (2015).ADS 
Article 

Google Scholar 
Holt, R. D., Dobson, A. P., Begon, M., Bowers, R. G. & Schauber, E. M. Parasite establishment in host communities. Ecol. Lett. 6, 837–842 (2003).
Article 

Google Scholar 
Hatcher, M. J. & Dunn, A. M. Parasites in Ecological Communities: From Interactions to Ecosystems (Cambridge University Press, 2011).Book 

Google Scholar 
Dobson, A. Population dynamics of pathogens with multiple host species. Am. Nat. 164, S64–S78 (2004).Article 

Google Scholar 
McCann, K., Hastings, A. & Huxel, G. R. Weak trophic interactions and the balance of nature. Nature 395, 794–798 (1998).ADS 
CAS 
Article 

Google Scholar 
Neutel, A. M., Heesterbeek, J. A. P. & de Ruiter, P. C. Stability in real food webs: Weak links in long loops. Science 296, 1120–1123 (2002).ADS 
CAS 
Article 

Google Scholar 
Chen, X. & Cohen, J. E. Transient dynamics and food–web complexity in the Lotka–Volterra cascade model. Proc. R. Soc. Lond. Ser. B Biol. Sci. 268, 869–877 (2001).CAS 
Article 

Google Scholar 
May, R. M. Stability in multispecies community models. Math. Biosci. 12, 59–79 (1971).MathSciNet 
Article 

Google Scholar 
May, R. M. Will a large complex system be stable?. Nature 238, 413–414 (1972).ADS 
CAS 
Article 

Google Scholar 
Hilker, F. M. & Schmitz, K. Disease-induced stabilization of predator-prey oscillations. J. Theor. Biol. 255, 299–306 (2008).ADS 
MathSciNet 
Article 

Google Scholar 
Hethcote, H. W., Wang, W., Han, L. & Ma, Z. A predator–prey model with infected prey. Theor. Popul. Biol. 66, 259–268 (2004).Article 

Google Scholar 
Kooi, B. W., van Voorn, G. A. K. & Das, K. P. Stabilization and complex dynamics in a predator-prey model with predator suffering from an infectious disease. Ecol. Complex. 8, 113–122 (2011).Article 

Google Scholar 
Winemiller, K. O. Spatial and temporal variation in tropical fish trophic networks. Ecol. Monogr. 60, 331–367 (1990).Article 

Google Scholar 
Paine, R. T. Food-web analysis through field measurement of per capita interaction strength. Nature 355, 73–75 (1992).ADS 
Article 

Google Scholar 
Wootton, J. T. Estimates and tests of per capita interaction strength: Diet, abundance, and impact of intertidally foraging birds. Ecol. Monogr. 67, 45–64 (1997).Article 

Google Scholar 
Cohen, J. E., Briand, F. & Newman, C. M. Community Food Webs: Data and Theory (Springer, 1990).Book 

Google Scholar 
Mougi, A. Diversity of biological rhythm and food web stability. Biol. Lett. 17, 20200673 (2021).Article 

Google Scholar  More

Sol, D., Bacher, S., Reader, S. M. & Lefebvre, L. Brain size predicts the success of mammal species introduced into novel environments. Am. Nat. 172(Suppl. 1), S63–S71 (2008).PubMed 
Article 

Google Scholar 
González-Lagos, C., Sol, D. & Reader, S. M. Large-brained mammals live longer. J. Evol. Biol. 23, 1064–1074 (2010).PubMed 
Article 

Google Scholar 
Gonda, A., Herczeg, G. & Merilä, J. Evolutionary ecology of intraspecific brain size variation: A review. Ecol. Evol. 3(8), 2751–2764 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Benson-Amram, S., Dantzer, B., Stricker, G., Swanson, E. M. & Holekamp, K. E. Brain size predicts problem-solving ability in mammalian carnivores. PNAS 113(9), 2532–2537 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Näslund, J., Aarestrup, K., Thomassen, S. T. & Johnsson, J. I. Early enrichment effects on brain development in hatchery-reared Atlantic salmon (Salmo salar): No evidence for a critical period. Can. J. Fish. Aquat. Sci. 69(9), 1481–1490 (2012).Article 

Google Scholar 
Logan, C. J., Kruuk, L. E. B., Stanley, R., Thompson, A. M. & Clutton-Brock, T. H. Endocranial volume is heritable and is associated with longevity and fitness in a wild mammal. R. Soc. Open Sci. 3(12), 160622 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yamaguchi, N., Kitchener, A. C., Gilissen, E. & MacDonald, D. W. Brain size of the lion (Panthera leo) and the tiger (P. tigris): Implications for intrageneric phylogeny, intraspecific differences and the effects of captivity. Biol. J. Linn. Soc. 98, 85–93 (2009).Article 

Google Scholar 
Turschwell, M. P. & White, C. R. The effects of laboratory housing and spatial enrichment on brain size and metabolic rate in the eastern mosquitofish Gambusia holbrooki. Biol. Open. 5(3), 205–210 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Welniak-Kaminska, M. et al. Volumes of brain structures in captive wild-type and laboratory rats: 7T magnetic resonance in vivo automatic atlas-based study. PLoS ONE 14(4), e0215348 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Guay, P. J., Parrott, M. & Selwood, L. Captive breeding does not alter brain volume in a marsupial over a few generations. Zoo Biol. 31, 82–86 (2012).PubMed 
Article 

Google Scholar 
Isler, K. et al. Endocranial volumes of primate species: Scaling analyses using a comprehensive and reliable data set. J. Hum. Evol. 55(6), 967–978 (2008).PubMed 
Article 

Google Scholar 
Burns, J. G., Saravanan, A. & Rodd, F. H. Rearing environment affects the brain size of guppies: Lab-reared guppies have smaller brains than wild-caught guppies. Ethol. 115(2), 122–133 (2009).Article 

Google Scholar 
Kruska, D. On the evolutionary significance of encephalization in some eutherian mammals: Effects of adaptive radiation, domestication, and feralization. Brain Behav. Evol. 65(2), 73–108 (2005).PubMed 
Article 

Google Scholar 
Logan, C. J. & Clutton-Brock, T. H. Validating methods for estimating endocranial volume in individual red deer (Cervus elaphus). Behav. Processes. 92, 143–146 (2013).PubMed 
Article 

Google Scholar 
Colby, A. E., Kimock, C. M. & Higham, J. P. Endocranial volume is variable and heritable, but not related to fitness, in a free-ranging primate. Sci. Rep. 11, 1–11 (2021).Article 
CAS 

Google Scholar 
Stuermer, I. W. & Wetzel, W. Early experience and domestication affect auditory discrimination learning, open field behaviour and brain size in wild Mongolian gerbils and domesticated Laboratory gerbils (Meriones unguiculatus forma domestica). Behav. Brain Res. 173, 11–21 (2006).PubMed 
Article 

Google Scholar 
Agnvall, B., Bélteky, J. & Jensen, P. Brain size is reduced by selection for tameness in red junglefowl-correlated effects in vital organs. Sci. Rep. 7(3306), 1–7 (2017).CAS 

Google Scholar 
Röhrs, M. & Ebinger, P. Wild is not really wild: Brain weight of wild and domestic mammals. Berl. Munch. Tierarztliche Wochenschrift. 112(6–7), 234–238 (1999).
Google Scholar 
Smith, B. P., Lucas, T. A., Norris, R. M. & Henneberg, M. Brain size/body weight in the dingo (Canis dingo): Comparisons with domestic and wild canids. Aust. J. Zool. 65(5), 292–301 (2017).Article 

Google Scholar 
Roberts, T., McGreevy, P. & Valenzuela, M. Human induced rotation and reorganization of the brain of domestic dogs. PLoS ONE 5(7), e11946 (2010).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Pollen, A. A. et al. Environmental complexity and social organization sculpt the brain in Lake Tanganyikan cichlid fish. Brain Behav. Evol. 70, 21–39 (2007).PubMed 
Article 

Google Scholar 
Kihslinger, R. L., Lema, S. C. & Nevitt, G. A. Environmental rearing conditions produce forebrain differences in wild Chinook salmon Oncorhynchus tshawytscha. Comp. Biochem. Physiol. 145(2), 145–151 (2006).CAS 
Article 

Google Scholar 
Guay, P. J. & Iwaniuk, A. N. Captive breeding reduces brain volume in waterfowl (Anseriformes). Condor 110(2), 276–284 (2008).Article 

Google Scholar 
Diamond, M. C., Ingham, C. A., Johnson, R. E., Bennett, E. L. & Rosenzweig, M. R. Effects of environment on morphology of rat cerebral cortex and hippocampus. J. Neurobiol. 7, 75–85 (1976).CAS 
PubMed 
Article 

Google Scholar 
Courtney Jones, S. K., Munn, A. J. & Byrne, P. G. Effect of captivity on morphology: Negligible changes in external morphology mask significant changes in internal morphology. R. Soc. Open Sci. 5(5), 1–13 (2018).Article 

Google Scholar 
Kruska, D. & Röhrs, M. Comparative-quantitative investigations on brains of feral pigs from the Galapagos Islands and of European domestic pigs. Z. Anat. Entwicklungsgesch. 144(1), 61–73 (1974).CAS 
PubMed 
Article 

Google Scholar 
Kruska, D. Changes of brain size in Tylopoda during phylogeny and caused by domestication. Verh. Dtsch. Zool. Ges. 75, 173–183 (1982).
Google Scholar 
Groves, C. P. Skull-changes due to captivity in certain Equidae. Z. Säugetierkd. 31, 44–46 (1966).
Google Scholar 
Groves, C. P. The skulls of Asian rhinoceroses: Wild and captive. Zoo Biol. 1, 251–261 (1982).Article 

Google Scholar 
Hollister, N. Some effects of environment and habit on captive lions. Proc. US. Natl. Mus. 53, 177–193 (1917).Article 

Google Scholar 
Price, E. O. Behavioral development in animals undergoing domestication. Appl. Anim. Behav. Sci. 65(3), 245–271 (1999).Article 

Google Scholar 
Wolff, J. Das Gesetz der Transformation der Knochen (A. Hirchwild, 1892).
Google Scholar 
Herring, S. W. Formation of the vertebrate face: Epigenetic and functional influences. Am. Zool. 33, 472–483 (1993).Article 

Google Scholar 
Wroe, S. & Milne, N. Convergence and remarkably consistent constraint in the evolution of carnivore skull shape. Evol. 61(5), 1251–1260 (2007).Article 

Google Scholar 
Damasceno, E. M., Hingst-Zaher, E. & Astúa, D. Bite force and encephalization in the Canidae (Mammalia: Carnivora). J. Zool. 290(4), 246–254 (2013).Article 

Google Scholar 
Van Valkenburgh, B. Deja vu: the evolution of feeding morphologies in the Carnivora. Integr. Comp. Biol. 47, 147–163 (2007).PubMed 
Article 

Google Scholar 
Van Valkenburgh, B. Carnivore dental adaptations and diet: A study of trophic diversity within guilds in Carnivore behavior, ecology, and evolution (ed. Gittleman, J. L.) 410–436 (Springer Science & Business Media, 1989).Slater, G. J., Dumont, E. R. & Van Valkenburgh, B. Implications of predatory specialization for cranial form and function in canids. J. Zool. 278(3), 181–188 (2009).Article 

Google Scholar 
Michaud, M., Veron, G. & Fabre, A. C. Phenotypic integration in feliform carnivores: Covariation patterns and disparity in hypercarnivores versus generalists. Evol. 74(12), 2681–2702 (2020).Article 

Google Scholar 
O’Regan, H. J. & Kitchener, A. C. The effects of captivity on the morphology of captive, domesticated and feral mammals. Mamm. Rev. 35, 215–230 (2005).Article 

Google Scholar 
Kapoor, V., Antonelli, T., Parkinson, J. A. & Hartstone-Rose, A. Oral health correlates of captivity. Res. Vet. Sci. 107, 213–219 (2016).PubMed 
Article 

Google Scholar 
Mitchell, D. R., Wroe, S., Ravosa, M. J. & Menegaz, R. A. More challenging diets sustain feeding performance: Applications toward the captive rearing of wildlife. Integr. Org. Biol. 3, 1–13 (2021).
Google Scholar 
Curtis, A. A., Orke, M., Tetradis, S. & Van Valkenburgh, B. Diet-related differences in craniodental morphology between captive-reared and wild coyotes, Canis latrans (Carnivora: Canidae). Biol. J. Linn. Soc. 123(3), 677–693 (2018).Article 

Google Scholar 
Siciliano-Martina, L., Light, J. E. & Lawing, A. M. Cranial morphology of captive mammals: A meta-analysis. Front. Zool. 18(4), 1–13 (2021).
Google Scholar 
Corruccini, R. S. & Beecher, R. M. Occlusal variation related to soft diet in a nonhuman primate. Science 218, 74–75 (1982).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ramirez Rozzi, F. V., González-José, R. & Pucciarelli, H. M. Cranial growth in normal and low-protein-fed Saimiri An environmental heterochrony. J. Hum. Evol. 49(4), 515–535 (2005).PubMed 
Article 

Google Scholar 
Taylor, A. B. & van Schaik, C. P. Variation in brain size and ecology in Pongo. J. Hum. Evol. 52, 59–71 (2007).PubMed 
Article 

Google Scholar 
AZA Canid TAG. Large Canid (Canidae) Care Manual. (Association of Zoos and Aquariums, 2012).Mexican Wolf Species Survival Plan. Mexican Gray Wolf Husbandry Manual: Guidelines for Captive Management (2009 edition). (Mexican Wolf Species Survival Plan and U.S. Fish and Wildlife Service, 2009).Carrera, R. et al. Comparison of Mexican wolf and coyote diets in Arizona and New Mexico. The J. Wildl. Manag. 72(2), 376–381 (2008).Article 

Google Scholar 
Reed, J. E. et al. Diets of free-ranging Mexican gray wolves in Arizona and New Mexico. Wildl. Soc. Bull. 34(4), 1127–1133 (2006).Article 

Google Scholar 
Kazimierska, K., Biel, W. & Witkowicz, R. Mineral composition of cereal and cereal-free dry dog foods versus nutritional guidelines. Molecules 25(21), 1–24 (2020).Article 
CAS 

Google Scholar 
Pezzali, J. G. & Aldrich, C. G. Effect of ancient grains and grain-free carbohydrate sources on extrusion parameters and nutrient utilization by dogs. J. Anim. Sci. 98(2), 3758–3767 (2019).Article 

Google Scholar 
Hartstone-Rose, A., Selvey, H., Villari, J. R., Atwell, M. & Schmidt, T. The three-dimensional morphological effects of captivity. PLoS ONE 9(11), 1–15 (2014).Article 
CAS 

Google Scholar 
Siciliano-Martina, L., Light, J. E. & Lawing, A. M. Changes in canid cranial morphology induced by captivity and conservation implications. Biol. Conserv. 257, 109143 (2021).Article 

Google Scholar 
Hedrick, P. W. & Fredrickson, R. Genetic rescue guidelines with examples from Mexican wolves and Florida panthers. Conserv. Genet. 11(2), 615–626 (2010).Article 

Google Scholar 
Greely, S. E. Mexican Wolf, Canis lupus baileyi, International Studbook 2018. Palm Desert, California. (2018).Kalinowski, S. T., Hedrick, P. W. & Miller, P. S. No inbreeding depression observed in Mexican and red wolf captive breeding programs. Conserv. Biol. 13(6), 1371–1377 (1999).Article 

Google Scholar 
Sakai, S. T., Whitt, B., Arsznov, B. M. & Lundrigan, B. L. Endocranial development in the coyote (Canis latrans) and gray wolf (Canis lupus): A computed tomographic study. Brain Behav. Evol. 91(2), 1–18 (2018).Article 

Google Scholar 
Van Valkenburgh, B. Skeletal and dental predictors of body mass in carnivores in Body size in mammalian paleobiology: estimation and biological implications (eds. Damuth, J. & MacFadden, B. J.) (Cambridge University Press, 1990).Rohlf, F. J. TPSDig2: a program for landmark development and analysis (2001).Siciliano-Martina, L., Light, J. E., Riley, D. G. & Lawing, A. M. One of these wolves is not like the other: morphological effects and conservation implications of captivity in Mexican wolves. Anim. Conserv. 25, 77–90 (2021).Article 

Google Scholar 
Zelditch, M. L., Donald, L., Swiderski, H., Sheets, D. & Fink, W. L. Geometric morphometrics for biologists: a primer. (Elsevier Academic Press, 2004).Coster, A. pedigree: Pedigree functions. R package version 1.4 (2013).Traylor-Holzer, K. (ed.). PMx user’s manual. Version 1.0. Apple Valley, MN: IUCN SSC Conservation Breeding Specialist Group. (2011).Thomason, J. J. Cranial strength in relation to estimated biting forces in some Mammals. Can. J. Zool. 69, 2326–2333 (1991).Article 

Google Scholar 
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods. 9(7), 676–682 (2012).CAS 
PubMed 
Article 

Google Scholar 
R Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (2020).Cofran, Z. Brain size growth in wild and captive chimpanzees (Pan troglodytes). Am. J. Primat. 80(7), 1–8 (2018).Article 

Google Scholar 
Witzenberger, K. A. & Hochkirch, A. Ex situ conservation genetics: A review of molecular studies on the genetic consequences of captive breeding programmes for endangered animal species. Biodivers. Conserv. 20(9), 1843–1861 (2011).Article 

Google Scholar 
Gómez-Sánchez, D. et al. On the path to extinction: Inbreeding and admixture in a declining grey wolf population. Mole. Ecol. 27(18), 3599–3612 (2018).Article 

Google Scholar 
Elbroch, M. Animal skulls: a guide to North American species. (Stackpole Books, 2006).Conde, D. A., Flesness, N., Colchero, F., Jones, O. R. & Scheuerlein, A. An emerging role of zoos to conserve biodiversity. Science 331, 1390–1391 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Prado, E. L. & Dewey, K. G. Nutrition and brain development in early life. Nutr. Rev. 72(4), 267–284 (2014).PubMed 
Article 

Google Scholar 
Hecht, E. E. et al. Neuromorphological changes following selection for tameness and aggression in the Russian farm-fox experiment. J. Neurosci. 41(28), 6144–6156 (2021).CAS 
PubMed Central 
Article 

Google Scholar 
Bennett, E. L., Rosenzweig, M. R. & Diamond, M. C. Rat brain: Effects of environmental enrichment on wet and dry weights. Science 163(3869), 825–826 (1969).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Cummins, R. A., Walsh, R. N., Budtz-Olsen, O. E., Konstantinos, T. & Horsfall, C. R. Environmentally-induced changes in the brains of elderly rats. Nature 243(5409), 516–518 (1973).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Welch, B. L., Brown, D. G., Welch, A. S. & Lin, D. C. Isolation, restrictive confinement or crowding of rats for one year. I. Weight, nucleic acids and protein of brain regions. Brain Res. 75, 71–84 (1974).CAS 
PubMed 
Article 

Google Scholar  More

Baker, R. W. Membrane Technology and Applications. 3rd edn. ISBN 9780470743720. (Wiley, 2012).Wang, L. K., Chen, J. P., Hung, Y.-T., Shammas, N. K. Membrane and Desalination Technologies. ISBN 978-1-58829-940-6. (Humana Press, 2011).Mahmoudi, E. et al. Enhancing morphology and separation performance of polyamide 6,6 membranes by minimal incorporation of silver decorated graphene oxide nanoparticles. Sci. Rep. 9, 1216. https://doi.org/10.1038/s41598-018-38060-x (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Penkova, A. V., Dmitrenko, M. E., Ermakov, S. S., Toikka, A. M. & Roizard, D. Novel green PVA-fullerenol mixed matrix supported membranes for separating water-THF mixtures by pervaporation. Environ. Sci. Pollut. Res. 25, 20354–20362. https://doi.org/10.1007/s11356-017-9063-9 (2018).CAS 
Article 

Google Scholar 
Atlaskin, A. A. et al. Comprehensive experimental study of membrane cascades type of “continuous membrane column” for gases high-purification. J. Membr. Sci. 572, 92–101. https://doi.org/10.1016/j.memsci.2018.10.079 (2019).CAS 
Article 

Google Scholar 
Koyuncu, I., Sengur, R., Turken, T., Guclu, S., & Pasaoglu, M.E. Advances in water treatment by microfiltration, ultrafiltration, and nanofiltration. in Advances in Membrane Technologies for Water Treatment (eds. Basile, A., Cassano, A., Rastogi, N. K.). 83–128. (Elsevier, 2015).Van der Bruggen, B. Microfiltration, ultrafiltration, nanofiltration, reverse osmosis, and forward osmosis in Fundamental Modelling of Membrane Systems, Membrane and Process Performance (ed. Luis, P.). 25–70. (Elsevier, 2018).Al Aani, S., Mustafa, T. N. & Hilal, N. Ultrafiltration membranes for wastewater and water process engineering: A comprehensive statistical review over the past decade. J. Water Process Eng. 35, 101241. https://doi.org/10.1016/j.jwpe.2020.101241 (2020).Article 

Google Scholar 
Polotskaya, G. A., Goikhman, M. Y., Podeshvo, I. V., Polotsky, A. E. & Cherkasov, A. N. Polybenzoxazinoneimides and their prepolymers as promising membrane materials. Desalination 200, 46–48 (2006).CAS 
Article 

Google Scholar 
Ulbricht, M. Advanced functional polymer membranes. Polymer 47, 2217–2262. https://doi.org/10.1016/j.polymer.2006.01.084 (2006).CAS 
Article 

Google Scholar 
Siagian, U. W. R. et al. High-performance ultrafiltration membrane: Recent progress and its application for wastewater treatment. Curr. Pollut. Rep. 7, 448–462. https://doi.org/10.1007/s40726-021-00204-5 (2021).CAS 
Article 

Google Scholar 
Polotskaya, G. A., Meleshko, T. K., Gofman, I. V., Polotsky, A. E. & Cherkasov, A. N. Polyimide ultrafiltration membranes with high thermal stability and chemical durability. Sep. Sci. Technol. 44, 3814–3831. https://doi.org/10.1080/01496390903256166 (2009).CAS 
Article 

Google Scholar 
Ohya, H., Kudryavtsev, V. V., & Semenova, S. I. Polyimide Membranes. Vol. 314. (Gordon & Breach Publishers, 1996).Liu, R., Qiao, X. & Chung, T.-S. The development of high performance P84 co-polyimide hollow fibers for pervaporation dehydration of isopropanol. Chem. Eng. Sci. 60, 6674–6686. https://doi.org/10.1016/j.ces.2005.05.066 (2005).CAS 
Article 

Google Scholar 
Yang, C. et al. Preparation and characterization of acid and solvent resistant polyimide ultrafiltration membrane. Appl. Surf. Sci. 483, 278–284. https://doi.org/10.1016/j.apsusc.2019.03.226 (2019).ADS 
CAS 
Article 

Google Scholar 
Pulyalina, AYu., Polotskaya, G. A. & Toikka, A. M. Membrane materials based on polyheteroarylenes and their application for pervaporation. Russ. Chem. Rev. 85(1), 81–98 (2016).ADS 
CAS 
Article 

Google Scholar 
Volgin, I. V. et al. Transport properties of thermoplastic R-BAPB polyimide: Molecular dynamics simulations and experiment. Polymers 11, 1775. https://doi.org/10.3390/polym11111775 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
Pulyalina, A. et al. Preparation and characterization of methanol selective membranes based on polyheteroarylene–Cu(I) complexes for purification of methyl tertiary butyl ether. Polym. Int. 66(12), 1873–1882. https://doi.org/10.1002/pi.5463 (2017).CAS 
Article 

Google Scholar 
Pulyalina, A. et al. Sorption and transport of aqueous isopropanol solutions in polyimide-poly(aniline-co-anthranilic acid) composites. Russ. J. Appl. Chem. 84(5), 840–846. https://doi.org/10.1134/S107042721105017X (2011).CAS 
Article 

Google Scholar 
Pulyalina, A. et al. Novel approach to determination of sorption in pervaporation process: A case study of isopropanol dehydration by polyamidoimide urea membranes. Sci. Rep. 7, 8415. https://doi.org/10.1038/s41598-017-08420-0 (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Helali, N., Shamaei, L., Rastgar, M. & Sadrzadeh, M. Development of layer-by-layer assembled polyamide-imide membranes for oil sands produced water treatment. Sci. Rep. 11, 8098. https://doi.org/10.1038/s41598-021-87601-4 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Polotskaya, G. et al. Asymmetric membranes based on copolyheteroarylenes with imide, biquinoline, and oxazinone units: Formation and characterization. Polymers 11(10), 1542. https://doi.org/10.3390/polym11101542 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
Volgin, I. V. Transport properties of thermoplastic R-BAPB polyimide: Molecular dynamics simulations and experiment. Polymers 11(11), 1775. https://doi.org/10.3390/polym11111775 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
White, L. S. Transport properties of a polyimide solvent resistant nanofiltration membrane. J. Membr. Sci. 205, 191–202 (2005).Article 

Google Scholar 
Barsema, J. N., Kapantaidakis, G. C., van der Vegt, N. F. A., Koops, G. H. & Wessling, M. Preparation and characterization of highly selective dense and hollow fiber asymmetric membranes based on BTDA-TDI/MDI co-polyimide. J. Membr. Sci. 216, 195–205. https://doi.org/10.1016/S0376-7388(03)00071-1 (2003).CAS 
Article 

Google Scholar 
Pulyalina, A., Polotskaya, G., Rostovtseva, V., Pientka, Z. & Toikka, A. Improved hydrogen separation using hybrid membrane composed of nanodiamonds and P84 copolyimide. Polymers 10, 828. https://doi.org/10.3390/polym10080828 (2018).CAS 
Article 
PubMed Central 

Google Scholar 
Qiao, X. & Chung, T.-S. Fundamental characteristics of sorption, swelling, and permeation of P84 co-polyimide membranes for pervaporation dehydration of alcohols. Ind. Eng. Chem. Res. 44, 8938–8943. https://doi.org/10.1021/ie050836g (2005).CAS 
Article 

Google Scholar 
Mangindaan, D. W., Shi, G. M. & Chung, T.-S. Pervaporation dehydration of acetone using P84 co-polyimide flat sheet membranes modified by vapor phase crosslinking. J. Membr. Sci. 458, 76–85 (2014).CAS 
Article 

Google Scholar 
Hua, D., Ong, Y. K., Wang, Y., Yang, T. & Chung, T.-S. ZIF-90/P84 mixed matrix membranes for pervaporation dehydration of isopropanol. J. Membr. Sci. 453, 155–167. https://doi.org/10.1016/j.memsci.2013.10.059 (2014).CAS 
Article 

Google Scholar 
Pulyalina, AYu., Putintseva, M. N., Polotskaya, G. A., Rostovtseva, V. A. & Toikka, A. M. Pervaporation purification of oxygenate from an ethyl tert-butyl ether/ethanol azeotropic mixture. Membr. Membr. Technol. 1(2), 99–106. https://doi.org/10.1134/S2517751619020082 (2019).CAS 
Article 

Google Scholar 
Ren, J. & Li, Z. Development of asymmetric BTDA-TDI/MDI (P84) copolyimide flat sheet and hollow fiber membranes for ultrafiltration: Morphology transition and membrane performance. Desalination 285, 336–344. https://doi.org/10.1016/j.desal.2011.10.024 (2012).CAS 
Article 

Google Scholar 
Ren, J., Li, Z., Wong, F.-S. & Li, D. Development of asymmetric BTDA-TDI/MDI (P84) co-polyimide hollow fiber membranes for ultrafiltration: The influence of shear rate and approaching ratio on membrane morphology and performance. J. Membr. Sci. 248, 177–188. https://doi.org/10.1016/j.memsci.2004.09.031 (2005).CAS 
Article 

Google Scholar 
Yusoff, I. I. et al. Durable pressure filtration membranes based on polyaniline-polyimide P84 blends. Polym. Eng. Sci. 5(S1), E82–E92 (2019).Article 

Google Scholar 
Grosso, V. et al. Polymeric and mixed matrix polyimide membranes. Sep. Purif. Technol. 132, 684–696 (2014).CAS 
Article 

Google Scholar 
Renner, R. Ionic liquids: An industrial cleanup solution. Environ. Sci. Technol. 35, 410a–413a (2001).ADS 
CAS 
Article 

Google Scholar 
Wanga, H. H. A novel green solvent alternative for polymeric membrane preparation via nonsolvent-induced phase separation (NIPS). J. Membr. Sci. 574, 44–54 (2019).Article 

Google Scholar 
Lessan, F. & Foudazi, R. Effect of [EMIM][BF4] ionic liquid on the properties of ultrafiltration membranes. Polymer 210, 122977 (2020).CAS 
Article 

Google Scholar 
Xing, D. Y., Peng, N. & Chung, T.-S. Formation of cellulose acetate membranes via phase inversion using ionic liquid, [BMIM]SCN, as the solvent. Ind. Eng. Chem. Res. 49, 8761–8769 (2010).CAS 
Article 

Google Scholar 
Durmaz, E. N. & Çulfaz-Emecen, P. Z. Cellulose-based membranes via phase inversion using [EMIM]OAc-DMSO mixtures as solvent. Chem. Eng. Sci. 178, 93–103 (2018).CAS 
Article 

Google Scholar 
Grekov, K. B. Electronic Waste and Safety Problems (in Rus.). ISBN 9785891601796. (SUT, 2018).Svittsov, A. A. & Abylgaziev, TZh. Micellarly enhanced (reagent) ultrafiltration. Russ. Chem. Rev. 60(11), 1280–1283 (1991).ADS 
Article 

Google Scholar 
Petrov, S. & Stoichev, P. A. Reagent ultrafiltration purification of water contaminated with reactive dyes. Filtr. Sep. https://doi.org/10.1016/S0015-1882(02)80229-4 (2002).Article 

Google Scholar 
Leonard, M. A. & West, T. S. Chelating reactions of 1,2-dihydroxyanthraquinon-3-ylmethyl-amine-NN-diacetic acid with metal cations in aqueous media. J. Chem. Soc. 866, 4477–4486. https://doi.org/10.1039/jr9600004477 (1960).Article 

Google Scholar 
Marczenko, Z., & Balcerzak, M. Fluorine. in Separation, Preconcentration and Spectrophotometry in Inorganic Analysis (ed. Kloczko, E.). 189–197. (Elsevier, 2000).Chai, J.-D. & Head-Gordon, M. Long-range corrected hybrid density functionals with damped atom–atom dispersion corrections. Phys. Chem. Chem. Phys. 10, 6615–6620. https://doi.org/10.1039/B810189B (2008).CAS 
Article 
PubMed 

Google Scholar 
Frisch, M. J. et al. Gaussian 09, Revision C.01. (Gaussian, Inc., 2010).Ochterski, J. W. Thermochemistry in Gaussian. https://gaussian.com/thermo/ (2000).Cherkasov, A. N. A rapid analysis of ultrafiltration membrane structure. Sep. Sci. Tech. 40, 2775–2801. https://doi.org/10.1080/01496390500333111 (2005).CAS 
Article 

Google Scholar 
Zheng, Q.-Z. The relationship between porosity and kinetics parameter of membrane formation in PSF ultrafiltration membrane. J. Membr. Sci. 286, 7–11 (2006).CAS 
Article 

Google Scholar 
Barton, A. F. M. CRC Handbook of Solubility Parameter. Vol. 768. (CRC Press, 1991).Tan, X. & Rodrigue, D. A review on porous polymeric membrane preparation. Part I: Production techniques with polysulfone and poly (vinylidene fluoride). Polymers 11, 1160 (2019).Article 

Google Scholar 
Mulder, M. H. V. Phase Inversion Membranes. Membrane Preparation. Vol. 3331. (Academic Press, 2000).Quijada-Maldonado, E. Pilot plant study on the extractive distillation of toluene–methylcyclohexane mixtures using NMP and the ionic liquid [hmim][TCB] as solvents. Sep. Purif. Technol. 166, 196–204 (2016).CAS 
Article 

Google Scholar 
Polotskaya, G. A. et al. Aromatic copolyamides with anthrazoline units in the backbone: Synthesis, characterization, pervaporation application. Polymers 8(10), 362. https://doi.org/10.3390/polym8100362 (2016).CAS 
Article 
PubMed Central 

Google Scholar 
Mao, J. X. Interactions in 1-ethyl-3-methyl imidazolium tetracyanoborate ion pair: Spectroscopic and density functional study. J. Mol. Struct. 1038, 12–18 (2013).ADS 
CAS 
Article 

Google Scholar  More