Ecology

Peixoto, R. S., Harkins, D. M. & Nelson, K. E. Advances in microbiome research for animal health. Annu. Rev. Anim. Biosci. 9, 289–311 (2021).Article 

Google Scholar 
Amato, K. R. et al. Habitat degradation impacts black howler monkey (Alouatta pigra) gastrointestinal microbiomes. ISME J. 7, 1344 (2013).Article 

Google Scholar 
West, A. G. et al. The microbiome in threatened species conservation. Biol. Conserv. 229, 85–98 (2019).Article 

Google Scholar 
Robinson, J. M., Mills, J. G. & Breed, M. F. Walking ecosystems in microbiome-inspired green infrastructure: An ecological perspective on enhancing personal and planetary health. Challenges 9, 40 (2018).Article 

Google Scholar 
Mills, J. G. et al. Urban habitat restoration provides a human health benefit through microbiome rewilding: The Microbiome Rewilding Hypothesis. Restor. Ecol. 25, 866–872 (2017).Article 

Google Scholar 
Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: A call for the consideration of host-associated microbiota in wildlife management practices. Proc. R. Soc. B 286, 20182448 (2019).Article 

Google Scholar 
Dallas, J. W. & Warne, R. W. Captivity and animal microbiomes: Potential roles of microbiota for influencing animal conservation. Microb. Ecol. https://doi.org/10.1007/s00248-022-01991-0 (2022).Article 

Google Scholar 
Bornbusch, S. L. et al. Gut microbiota of ring-tailed lemurs (Lemur catta) vary across natural and captive populations and correlate with environmental microbiota. Anim. Microbiome 4, 1–19 (2022).Article 

Google Scholar 
Greene, L. K. et al. Gut microbiota of frugo-folivorous sifakas across environments. Anim. Microbiome 3, 39 (2021).Article 

Google Scholar 
McKenzie, V. J. et al. The effects of captivity on the mammalian gut microbiome. Integr. Comp. Biol. 57, 690–704 (2017).Article 

Google Scholar 
Bornbusch, S. L. & Drea, C. M. Antibiotic resistance genes in lemur gut and soil microbiota along a gradient of anthropogenic disturbance. Front. Ecol. Evol. 9, 514 (2021).Article 

Google Scholar 
Hyde, E. R. et al. The oral and skin microbiomes of captive komodo dragons are significantly shared with their habitat. mSystems 1, e00046-e116 (2016).Article 

Google Scholar 
LaFleur, M., Clarke, T. A., Reuter, K. E. & Schaefer, M. S. Illegal trade of wild-captured Lemur catta within Madagascar. Folia Primatol. 90, 199–214 (2019).Article 

Google Scholar 
Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174–180 (2011).Article 

Google Scholar 
Choo, J. M., Leong, L. E. & Rogers, G. B. Sample storage conditions significantly influence faecal microbiome profiles. Sci. Rep. 5, 16350 (2015).Article 
ADS 

Google Scholar 
Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012).Article 

Google Scholar 
Hasan, N. A. et al. Microbial community profiling of human saliva using shotgun metagenomic sequencing. PLoS ONE 9, e97699 (2014).Article 
ADS 

Google Scholar 
Bornbusch, S. L. et al. Stable and transient structural variation in lemur vaginal, labial and axillary microbiomes: Patterns by species, body site, ovarian hormones and forest access. FEMS Microbiol. Ecol. 96, fiaa090 (2020).Article 

Google Scholar 
Bolyen, E. et al. QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science. PeerJ 37, 852–857 (2018).
Google Scholar 
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581 (2016).Article 

Google Scholar 
Trosvik, P., Rueness, E. K., de Muinck, E. J., Moges, A. & Mekonnen, A. Ecological plasticity in the gastrointestinal microbiomes of Ethiopian Chlorocebus monkeys. Sci. Rep. 8, 1–10 (2018).Article 

Google Scholar 
Wills, M. O. et al. Host species and captivity distinguish the microbiome compositions of a diverse zoo-resident non-human primate population. Diversity 14, 715 (2022).Article 

Google Scholar 
Katoh, K., Misawa, K., Kuma, K. & Miyata, T. MAFFT: A novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).Article 

Google Scholar 
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).Article 
ADS 

Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).Article 

Google Scholar 
Yarza, P. et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat. Rev. Microbiol. 12, 635 (2014).Article 

Google Scholar 
Aitchison, J. The statistical analysis of compositional data. J. R. Stat. Soc. Ser. B 44, 139–160 (1982).MathSciNet 
MATH 

Google Scholar 
Quinn, T. P., Erb, I., Richardson, M. F. & Crowley, T. M. Understanding sequencing data as compositions: An outlook and review. Bioinformatics 34, 2870–2878 (2018).Article 

Google Scholar 
Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome datasets are compositional: And this is not optional. Front. Microbiol. 8, 2224 (2017).Article 

Google Scholar 
Ottesen, A. et al. Enrichment dynamics of Listeria monocytogenes and the associated microbiome from naturally contaminated ice cream linked to a listeriosis outbreak. BMC Microbiol. 16, 1–11 (2016).Article 

Google Scholar 
Lax, S. et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science 345, 1048–1052 (2014).Article 
ADS 

Google Scholar 
Shenhav, L. et al. FEAST: Fast expectation-maximization for microbial source tracking. Nat. Methods 16, 627 (2019).Article 

Google Scholar 
Barelli, C. et al. The gut microbiota communities of wild arboreal and ground-feeding tropical primates are affected differently by habitat disturbance. mSystems 5, e00061 (2020).Article 

Google Scholar 
Frankel, J. S., Mallott, E. K., Hopper, L. M., Ross, S. R. & Amato, K. R. The effect of captivity on the primate gut microbiome varies with host dietary niche. Am. J. Primatol. 81, e23061 (2019).Article 

Google Scholar 
Bornbusch, S. L. et al. Antibiotics and fecal transfaunation differentially affect microbiota recovery, associations, and antibiotic resistance in lemur guts. Anim. Microbiome 3, 65 (2021).Article 

Google Scholar 
Amato, K. R. et al. Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes. ISME J. 13, 576–587 (2019).Article 

Google Scholar 
Bornbusch, S. L. et al. A comparative study of gut microbiomes in captive nocturnal strepsirrhines. Am. J. Primatol. 81, e22986 (2019).Article 

Google Scholar 
Nishida, A. H. & Ochman, H. A great-ape view of the gut microbiome. Nat. Rev. Genet. 20, 195–206 (2019).Article 

Google Scholar 
Nagpal, R. et al. Gut microbiome composition in non-human primates consuming a Western or Mediterranean diet. Front. Nutr. 5, 28 (2018).Article 

Google Scholar 
Deng, H. et al. Bacteroides fragilis prevents Clostridium difficile infection in a mouse model by restoring gut barrier and microbiome regulation. Front. Microbiol. 9, 2976 (2018).Article 

Google Scholar 
Wang, C. et al. Roles of intestinal bacteroides in human health and diseases. Crit. Rev. Food Sci. Nutr. 61, 3518–3536 (2021).Article 

Google Scholar 
Townsend, G. E. et al. Dietary sugar silences a colonization factor in a mammalian gut symbiont. Proc. Natl. Acad. Sci. USA 116, 233–238 (2019).Article 
ADS 

Google Scholar 
LaFleur, M. et al. Drug-resistant tuberculosis in pet ring-tailed lemur, Madagascar. Emerg. Infect. Dis. 27, 977 (2021).Article 

Google Scholar 
Gálvez, E. J. C. et al. Distinct polysaccharide utilization determines interspecies competition between intestinal Prevotella spp. Cell Host Microbe 28, 838–852 (2020).Article 

Google Scholar 
Costea, P. I. et al. Enterotypes in the landscape of gut microbial community composition. Nat. Microbiol. 3, 8–16 (2018).Article 

Google Scholar 
Roager, H. M., Licht, T. R., Poulsen, S. K., Larsen, T. M. & Bahl, M. I. Microbial enterotypes, inferred by the prevotella-to-bacteroides ratio, remained stable during a 6-month randomized controlled diet intervention with the new nordic diet. Appl. Environ. Microbiol. 80, 1142–1149 (2014).Article 
ADS 

Google Scholar 
Hjorth, M. F. et al. Pretreatment Prevotella-to-Bacteroides ratio and markers of glucose metabolism as prognostic markers for dietary weight loss maintenance. Eur. J. Clin. Nutr. 74, 338–347 (2020).Article 

Google Scholar 
Hjorth, M. F. et al. Pre-treatment microbial Prevotella-to-Bacteroides ratio, determines body fat loss success during a 6-month randomized controlled diet intervention. Int. J. Obes. 42, 580–583 (2018).Article 

Google Scholar 
DeMartino, P. & Cockburn, D. W. Resistant starch: Impact on the gut microbiome and health. Curr. Opin. Biotechnol. 61, 66–71 (2020).Article 

Google Scholar 
Wang, K. et al. Diet with a high proportion of rice alters profiles and potential function of digesta-associated microbiota in the ileum of goats. Animals 10, 1261 (2020).Article 

Google Scholar 
Greene, L. K., McKenney, E. A., O’Connell, T. M. & Drea, C. M. The critical role of dietary foliage in maintaining the gut microbiome and metabolome of folivorous sifakas. Sci. Rep. 8, 14482 (2018).Article 
ADS 

Google Scholar 
Allen, H. K. et al. Call of the wild: Antibiotic resistance genes in natural environments. Nat. Rev. Microbiol. 8, 251–259 (2010).Article 

Google Scholar 
Daszak, P., Cunningham, A. A. & Hyatt, A. D. Anthropogenic environmental change and the emergence of infectious diseases in wildlife. Acta Trop. 78, 103–116 (2001).Article 

Google Scholar 
Shapira, M. Gut microbiotas and host evolution: Scaling up symbiosis. Trends Ecol. Evol. 31, 539–549 (2016).Article 

Google Scholar 
Sbihi, H. et al. Thinking bigger: How early-life environmental exposures shape the gut microbiome and influence the development of asthma and allergic disease. Allergy 74, 2103–2115 (2019).Article 

Google Scholar 
Bendiks, M. & Kopp, M. V. The relationship between advances in understanding the microbiome and the maturing hygiene hypothesis. Curr. Allergy Asthma Rep. 13, 487–494 (2013).Article 

Google Scholar 
Alexandre-Silva, G. M. et al. The hygiene hypothesis at a glance: Early exposures, immune mechanism and novel therapies. Acta Trop. 188, 16–26 (2018).Article 

Google Scholar 
Yao, R. et al. The, “wildness” of the giant panda gut microbiome and its relevance to effective translocation. Glob. Ecol. Conserv. 18, e00644 (2019).Article 

Google Scholar  More

Charlesworth, B., Charlesworth, D. & Barton, N. H. The effects of genetic and geographic structure on neutral variation. Annu. Rev. Ecol. Evol. Syst. 34(1), 99–125 (2003).Article 

Google Scholar 
Bradburd, G. S., Ralph, P. L. & Coop, G. M. Disentangling the effects of geographic and ecological isolation on genetic differentiation. Evolution 67(11), 3258–3273 (2013).Article 

Google Scholar 
Orsini, L., Vanoverbeke, J., Swillen, I., Mergeay, J. & De Meester, L. Drivers of population genetic differentiation in the wild: Isolation by dispersal limitation, isolation by adaptation and isolation by colonization. Mol. Ecol. 22(24), 5983–5999 (2013).Article 

Google Scholar 
Ronce, O. How does it feel to be like a rolling stone? Ten questions about dispersal evolution. Annu. Rev. Ecol. Evol. Syst. 38, 231–253 (2007).Article 

Google Scholar 
Broquet, T. & Petit, E. J. Molecular estimation of dispersal for ecology and population genetics. Annu. Rev. Ecol. Evol. Syst. 40, 193–216 (2009).Article 

Google Scholar 
Sexton, J. P., McIntyre, P. J., Angert, A. L. & Rice, K. J. Evolution and ecology of species range limits. Annu. Rev. Ecol. Evol. Syst. 40, 415–436 (2009).Article 

Google Scholar 
Qiao, H., Saupe, E. E., Soberón, J., Peterson, A. T. & Myers, C. E. Impacts of niche breadth and dispersal ability on macroevolutionary patterns. Am. Nat. 188(2), 149–162 (2016).Article 

Google Scholar 
Mayr, E. Ecological factors in speciation. Evolution 1(4), 263–288 (1947).
Google Scholar 
Hua, X. & Wiens, J. J. How does climate influence speciation?. Am. Nat. 182(1), 1–12 (2013).Article 

Google Scholar 
Rundle, H. D. & Nosil, P. Ecological speciation. Ecol. Lett. 8(3), 336–352 (2005).Article 

Google Scholar 
Schluter, D. Evidence for ecological speciation and its alternative. Science 323(5915), 737–741 (2009).Article 
ADS 

Google Scholar 
Wielstra, B. et al. Corresponding mitochondrial DNA and niche divergence for crested newt candidate species. PLoS ONE 7(9), e46671 (2012).Article 
ADS 

Google Scholar 
Wiens, J. J. Speciation and ecology revisited: Phylogenetic niche conservatism and the origin of species. Evolution 58(1), 193–197 (2004).
Google Scholar 
Manel, S., Schwartz, M. K., Luikart, G. & Taberlet, P. Landscape genetics: combining landscape ecology and population genetics. Trends Ecol. Evol. 18(4), 189–197 (2003).Article 

Google Scholar 
Alvarado-Serrano, D. F. & Hickerson, M. J. Spatially explicit summary statistics for historical population genetic inference. Methods Ecol. Evol. 7(4), 418–427 (2016).Article 

Google Scholar 
Rissler, L. J. Union of phylogeography and landscape genetics. PNAS 113(29), 8079–8086 (2016).Article 
ADS 

Google Scholar 
Pinho, C. & Hey, J. Divergence with gene flow: Models and data. Annu. Rev. Ecol. Evol. Syst. 41, 215–230 (2010).Article 

Google Scholar 
Sobel, J. M., Chen, G. F., Watt, L. R. & Schemske, D. W. The biology of speciation. Evolution 64(2), 295–315 (2010).Article 

Google Scholar 
Richards, C. L., Carstens, B. C. & Knowles, L. L. Distribution modelling and statistical phylogeography: An integrative framework for generating and testing alternative biogeographical hypotheses. J. Biogeogr. 34(11), 1833–1845 (2007).Article 

Google Scholar 
Alvarado-Serrano, D. F. & Knowles, L. L. Ecological niche models in phylogeographic studies: applications, advances and precautions. Mol. Ecol. 14(2), 233–248 (2014).Article 

Google Scholar 
Wang, I. J. Examining the full effects of landscape heterogeneity on spatial genetic variation: A multiple matrix regression approach for quantifying geographic and ecological isolation. Evolution 67(12), 3403–3411 (2013).Article 

Google Scholar 
Wright, S. Isolation by distance. Genetics 28(2), 114–138 (1943).Article 

Google Scholar 
Sexton, J. P., Hangartner, S. B. & Hoffmann, A. A. Genetic isolation by environment or distance: which pattern of gene flow is most common?. Evolution 68(1), 1–15 (2014).Article 

Google Scholar 
Wang, I. J. & Bradburd, G. S. Isolation by environment. Mol. Ecol. 23(23), 5649–5662 (2014).Article 

Google Scholar 
Lee, C. R. & Mitchell-Olds, T. Quantifying effects of environmental and geographical factors on patterns of genetic differentiation. Mol. Ecol. 20(22), 4631–4642 (2011).Article 

Google Scholar 
Moreira-Muñoz, A. Plant Geography of Chile Vol. 10, 978–990 (Springer, 2011).Book 

Google Scholar 
Orme, A. R. Tectonism, climate, and landscape change. Phys. Geogr. South Am. 1, 23–44 (2007).
Google Scholar 
Morando, M. et al. Diversification and evolutionary histories of Patagonian steppe lizards. in Lizards of Patagonia (pp. 217–254). (Springer, 2020).Rull, V. Neotropical diversification: historical overview and conceptual insights. In Neotropical Diversification: Patterns and Processes (eds Rull, V. & Carnaval, A. C.) (Springer, 2020).Chapter 

Google Scholar 
Lessa, E. P., D’Elía, G. & Pardiñas, U. F. J. Mammalian biogeography of Patagonia and Tierra del Fuego. In Bones, Clones and Biomes: The History and Recent Geography of Neotropical Animals (eds Patterson, B. D. & Costa, L. P.) 379–398 (University of Chicago Press, 2012).Chapter 

Google Scholar 
Pardiñas, U. F., D’Elía, G. & Lessa, E. P. The evolutionary history of sigmodontine rodents in Patagonia and Tierra del Fuego. Biol. J. Linn. Soc. 2(103), 495–513 (2011).Article 

Google Scholar 
Alarcón, O., D’Elía, G., Lessa, E. P. & Pardiñas, U. Phylogeographic structure of the Fossorial Long-Clawed Mouse Chelemys macronyx (Cricetidae: Sigmodontinae). Zool. Stud. 50(5), 682–688 (2011).
Google Scholar 
Lessa, E. P., D’Elía, G. & Pardiñas, U. F. J. Genetic footprints of late Quaternary climate change in the diversity of Patagonian-Fueguian rodents. Mol. Ecol. 19(15), 3031–3037 (2010).Article 

Google Scholar 
Valdez, L. & D’Elía, G. Genetic diversity and demographic history of the Shaggy Soft-Haired Mouse Abrothrix hirta (Cricetidae; Abrotrichini). Front. Genet. 12, 184 (2021).Article 

Google Scholar 
Valdez, L., Quiroga-Carmona, M. & D’Elía, G. Genetic variation of the Chilean endemic long-haired mouse Abrothrix longipilis (Rodentia, Supramyomorpha, Cricetidae) in a geographical and environmental context. PeerJ 8, e9517 (2020).Article 

Google Scholar 
Valdez, L. & D’Elía, G. Local persistence of Mann’s soft-haired mouse Abrothrix manni (Rodentia, Sigmodontinae) during Quaternary glaciations in southern Chile. PeerJ 6, e6130 (2018).Article 

Google Scholar 
Quiroga-Carmona, M., Abud, C., Lessa, E. P. & D’Elía, G. The mitochondrial genetic diversity of the olive field mouse Abrothrix olivacea (Cricetidae; Abrotrichini) is latitudinally structured across its geographic distribution. J. Mamm. Evol. 29, 431–433 (2022).Article 

Google Scholar 
Cañón, C., D’Elía, G., Pardiñas, U. F. & Lessa, E. P. Phylogeography of Loxodontomys micropus with comments on the alpha taxonomy of Loxodontomys (Cricetidae: Sigmodontinae). J. Mamm. 91(6), 1449–1458 (2010).Article 

Google Scholar 
Palma, R. E., Boric-Bargetto, D., Torres-Perez, F., Hernández, C. E. & Yates, T. L. Glaciation effects on the phylogeographic structure of Oligoryzomys longicaudatus (Rodentia: Sigmodontinae) in the Southern Andes. PLoS ONE 7(3), e32206 (2012).Article 
ADS 

Google Scholar 
Rodríguez-Serrano, E., Cancino, R. & Palma, R. E. Molecular phylogeography of Abrothrix olivaceus (Rodentia: Sigmodontinae) in Chile. J. Mamm. 87(5), 971–980 (2006).Article 

Google Scholar 
Rodríguez-Serrano, E., Hernandez, C. & Palma, R. E. A new record and an evaluation of the phylogenetic relationships of Abrothrix olivaceus markhami (Rodentia: Sigmodontinae). Mamm. Biol. 73(4), 309–317 (2008).Article 

Google Scholar 
Sánchez, J., Poljak, S., Teta, P., Lanusse, L. & Lizarralde, M. S. A contribution to the knowledge of the taxonomy of the subgenus Abrothrix (Angelomys) (Rodentia, Cricetidae) in southernmost South America. Polar Biol. 45(4), 601–614 (2022).Article 

Google Scholar 
Patton, J., Pardiñas, U. F. & D’Elía, G. Mammals of South America Vol. 2 (The University of Chicago Press, 2015).Book 

Google Scholar 
Patterson, B. D., Smith, M. F. & Teta, P. Genus Abrothrix Waterhouse, 1837. In Mammals of South America Vol. 2 (eds Patton, J. L. et al.) 109–127 (The University of Chicago Press, 2015).
Google Scholar 
Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).Article 

Google Scholar 
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high-resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25(15), 1965–1978 (2005).Article 

Google Scholar 
Quantum GIS Development Team (2021) Quantum GIS Geographic Information System. Version 3.18.2-ZürichHijmans, R. J. et al. Package ‘raster’. R package. (2015).Kuhn, M. caret: Classification and Regression Training. (2019) https://CRAN.R-project.org/package=caret.Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5–7. (2020). https://CRAN.R-project.org/package=vegan.Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35(6), 1547–1549 (2018).Article 

Google Scholar 
Wang, C. et al. Comparing spatial maps of human population-genetic variation using Procrustes analysis. Stat. Appl. Genet. Mol. Biol. 9(1), 13 (2010).Article 
MathSciNet 

Google Scholar 
Wang, C., Zöllner, S. & Rosenberg, N. A. A quantitative comparison of the similarity between genes and geography in worldwide human populations. PLoS Genet. 8(8), e1002886 (2012).Article 

Google Scholar 
Bivand, R., Keitt, T. & Rowlingson, B. rgdal: Bindings for the ‘Geospatial’ Data Abstraction Library. R package version 1.5–28. (2021). https://CRAN.R-project.org/package=rgdal.Kierepka, M. E. & Latch, K. E. Performance of partial statistics in individual-based landscape genetics. Mol. Ecol. 15(3), 512–525 (2015).Article 

Google Scholar 
Legendre, P. & Legendre, L. Numerical Ecology (Elsevier, 2012).MATH 

Google Scholar 
Lê, S., Josse, J. & Husson, F. FactoMineR: An R package for multivariate analysis. J. Stat. Soft. 25(1), 1–8 (2008).Article 

Google Scholar 
Barria, A. M. et al. The importance of intraspecific variation for niche differentiation and species distribution models: the ecologically diverse frog Pleurodema thaul as study case. Evol. Biol. 47(3), 206–219 (2020).Article 

Google Scholar 
Blonder, B., Lamanna, C., Violle, C. & Enquist, B. J. The n-dimensional hypervolume. Glob. Ecol. Biol. 23(5), 595–609 (2014).Article 

Google Scholar 
Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. & Anderson, R. P. spThin: An R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38(5), 541–545 (2015).Article 

Google Scholar 
Peterson, A. T. et al. Ecological Niches and Geographic Distributions (Princeton University Press, 2011).Book 

Google Scholar 
Viale, M. et al. Contrasting climates at both sides of the Andes in Argentina and Chile. Front. Environ. Sci. 7, 69 (2019).Article 

Google Scholar 
Pacifici, M. et al. Global correlates of range contractions and expansions in terrestrial mammals. Nat. Commun. 11(1), 1–9 (2020).Article 

Google Scholar 
Di Marco, M., Pacifici, M., Maiorano, L. & Rondinini, C. Drivers of change in the realised climatic niche of terrestrial mammals. Ecography 44(8), 1180–1190 (2021).Article 

Google Scholar 
Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. Opening the black box: An open-source release of Maxent. Ecography 40(7), 887–893 (2017).Article 

Google Scholar 
Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model 190(3–4), 231–259 (2006).Article 

Google Scholar 
Phillips, S. J., Dudík, M. & Schapire, R. E. Maxent Software for Modeling Species Niches and Distributions. (American Museum of Natural History, 2018) http://biodiversityinformatics.amnh.org/opensource/maxent/.Muscarella, R. et al. ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol. Evol. 5(11), 1198–1205 (2014).Article 

Google Scholar 
Radosavljevic, A. & Anderson, R. P. Making better Maxent models of species distributions: complexity, overfitting and evaluation. J. Biogeogr. 41(4), 629–643 (2014).Article 

Google Scholar 
Warren, D. L. & Seifert, S. N. Ecological niche modeling in Maxent: The importance of model complexity and the performance of model selection criteria. Ecol. Appl. 21(2), 335–342 (2011).Article 

Google Scholar 
Warren, D. L., Wright, A. N., Seifert, S. N. & Shaffer, H. B. Incorporating model complexity and spatial sampling bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concern. Diver. Dist. 20(3), 334–343 (2014).Article 

Google Scholar 
Franklin, J. Mapping Species Distributions: Spatial Inference and Prediction (Cambridge University Press, 2010).Book 

Google Scholar 
Merow, C., Smith, M. J. & Silander, J. A. A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter. Ecography 36(10), 1058–1069 (2013).Article 

Google Scholar 
Elith, J., Kearney, M. & Phillips, S. The art of modelling range-shifting species. Methods Ecol. Evol. 1(4), 330–342 (2010).Article 

Google Scholar 
Osorio-Olvera, L. et al. ntbox: An r package with graphical user interface for modelling and evaluating multidimensional ecological niches. Methods Ecol. Evol. 11(10), 1199–1206 (2020).Article 

Google Scholar 
Guevara, L., Gerstner, B. E., Kass, J. M. & Anderson, R. P. Toward ecologically realistic predictions of species distributions: A cross-time example from tropical montane cloud forests. Glob. Change Biol. 24, 1511–1522 (2018).Article 
ADS 

Google Scholar 
Otto-Bliesner, B. L., Marshall, S. J., Overpeck, J. T., Miller, G. H. & Hu, A. Simulating arctic climate warmth and icefield retreat in the last interglaciation. Science 311(5768), 1751–1753 (2008).Article 
ADS 

Google Scholar 
Watanabe, S. et al. MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev. 4(4), 845 (2011).Article 
ADS 

Google Scholar 
Knowles, L. L., Massatti, R., He, Q., Olson, L. E. & Lanier, H. C. Quantifying the similarity between genes and geography across Alaska’s alpine small mammals. J. Biogeogr. 43(7), 1464–1476 (2016).Article 

Google Scholar 
McGaughran, A., Morgan, K. & Sommer, R. J. Environmental variables explain genetic structure in a beetle-associated nematode. PLoS ONE 9(1), e87317 (2014).Article 
ADS 

Google Scholar 
Wang, I. J. Choosing appropriate genetic markers and analytical methods for testing landscape genetic hypotheses. Mol. Ecol. 20(12), 2480–2482 (2011).Article 

Google Scholar 
Bohonak, A. J. & Vandergast, A. G. The value of DNA sequence data for studying landscape genetics. Mol. Ecol. 20(12), 2477–2479 (2011).Article 

Google Scholar 
Vandergast, A. G., Bohonak, A. J., Weissman, D. B. & Fisher, R. N. Understanding the genetic effects of recent habitat fragmentation in the context of evolutionary history: Phylogeography and landscape genetics of a southern California endemic Jerusalem cricket (Orthoptera: Stenopelmatidae: Stenopelmatus). Mol. Ecol. 16(5), 977–992 (2007).Article 

Google Scholar 
Pearson, O. P. & Smith, M. F. Genetic similarity between Akodon olivaceus and Akodon xanthorhinus (Rodentia: Muridae) in Argentina. J. Zool. 247(1), 43–52 (1999).Article 

Google Scholar 
Smith, M. F., Kelt, D. A. & Patton, J. L. Testing models of diversification in mice in the Abrothrix olivaceus/xanthorhinus complex in Chile and Argentina. Mol. Ecol. 10(2), 397–405 (2001).Article 

Google Scholar 
Palma, R. E., Marquet, P. A. & Boric-Bargetto, D. Inter- and intraspecific phylogeography of small mammals in the Atacama Desert and adjacent areas of northern Chile. J. Biogeogr. 32(11), 1931–1941 (2005).Article 

Google Scholar 
Arroyo, M. T. K., Squeo, F. A., Armesto, J. J. & Villagran, C. Effects of aridity on plant diversity in the northern Chilean Andes: Results of a natural experiment. Ann. Mol. Bot. Gard. 1, 55–78 (1988).Article 

Google Scholar 
Del Pozo, A. H., Fuentes, E. R., Hajek, E. R. & Molina, J. D. Zonación microclimática por efecto de los manchones de arbustos en el matorral de Chile central. Rev. Chil. Hist. Nat. 62, 85–94 (1989).
Google Scholar 
Armesto, J. J., Vidiella, P. E. & Gutiérrez, J. R. Plant communities of the fog-free coastal desert of Chile: Plant strategies in a fluctuating environment. Rev. Chil. Hist. Nat. 66, 271–282 (1993).
Google Scholar 
Veblen, T. T., Young, K. R. & Orme, A. R. The Physical Geography of South America (Oxford University Press, 2015).
Google Scholar 
Kelt, D. A. et al. Community structure of desert small mammals: Comparisons across four continents. Ecology 77(3), 746–761 (1996).Article 

Google Scholar 
Shenbrot, G. B., Krasnov, B. R. & Rogovin, K. A. Spatial Ecology of Desert Rodent Communities (Springer, 1999).Book 

Google Scholar 
Van Strien, M. J., Holderegger, R. & Van Heck, H. J. Isolation-by-distance in landscapes: considerations for landscape genetics. Heredity 114(1), 27–37 (2015).Article 

Google Scholar 
Diniz-Filho, J. A. F. et al. Mantel test in population genetics. Genet. Mol. Biol. 36(4), 475–485 (2013).Article 

Google Scholar 
Blier, P. U., Dufresne, F. & Burton, R. S. Natural selection and the evolution of mtDNA-encoded peptides: Evidence for intergenomic co-adaptation. Trends Genet. 17(7), 400–406 (2001).Article 

Google Scholar 
Meiklejohn, C. D., Montooth, K. L. & Rand, D. M. Positive and negative selection on the mitochondrial genome. Trends Genet. 23(6), 259–263 (2007).Article 

Google Scholar 
Giorello, F. M. et al. An association between differential expression and genetic divergence in the Patagonian olive mouse (Abrothrix olivacea). Mol. Ecol. 27(16), 3274–3286 (2018).Article 

Google Scholar 
Soberón, J. Grinnellian and Eltonian niches and geographic distributions of species. Ecol. Lett. 10(12), 1115–1123 (2007).Article 

Google Scholar 
Holt, R. D. Bringing the Hutchinsonian niche into the 21st century: Ecological and evolutionary perspectives. PNAS 106(Supplement 2), 19659–19665 (2009).Article 
ADS 

Google Scholar 
Soberón, J. & Nakamura, M. Niches and distributional areas: Concepts, methods, and assumptions. PNAS 106(Supplement 2), 19644–19650 (2009).Article 
ADS 

Google Scholar 
Kearney, M. & Porter, W. P. Mapping the fundamental niche: Physiology, climate, and the distribution of a nocturnal lizard. Ecology 85(11), 3119–3131 (2004).Article 

Google Scholar 
Kearney, M. & Porter, W. P. Mechanistic niche modelling: Combining physiological and spatial data to predict species’ ranges. Ecol. Lett. 12(4), 334–350 (2009).Article 

Google Scholar 
Bonetti, M. F. & Wiens, J. J. Evolution of climatic niche specialization: A phylogenetic analysis in amphibians. Proc. R. Soc. B. 281(1795), 20133229 (2014).Article 

Google Scholar 
Sexton, J. P., Montiel, J., Shay, J. E., Stephens, M. R. & Slatyer, R. A. Evolution of ecological niche breadth. Annu. Rev. Ecol. Evol. Syst. 48, 183–206 (2017).Article 

Google Scholar 
Holt, R. D. On the evolutionary ecology of species’ ranges. Evol. Ecol. Res. 5(2), 159–178 (2003).
Google Scholar 
Merilä, J. & Hendry, A. P. Climate change, adaptation, and phenotypic plasticity: The problem and the evidence. Evol. Appl. 7(1), 1–14 (2014).Article 

Google Scholar 
Schmid, M. & Guillaume, F. The role of phenotypic plasticity on population differentiation. Heredity 119(4), 214–225 (2017).Article 

Google Scholar 
Novoa, F., Rivera, A., Rosenmann, M. & Sabat, P. Intraspecific differences in metabolic rate of Chroeomys olivaceus (Rodentia: Muridae): The effect of thermal acclimation in arid and mesic habitats. Rev. Chil. Hist. Nat. 78, 207–214 (2005).Article 

Google Scholar 
Bozinovic, F., Rojas, J. M., Maldonado, K., Sabat, P. & Naya, D. E. Between-population differences in digestive flexibility in the olivaceous field mouse. Zool 113(6), 373–377 (2010).Article 

Google Scholar 
Bozinovic, F., Rojas, J. M., Gallardo, P. A., Palma, R. E. & Gianoli, E. Body mass and water economy in the South American olivaceous field mouse along a latitudinal gradient: Implications for climate change. J. Arid. Environ. 75(5), 411–415 (2011).Article 
ADS 

Google Scholar 
Naya, D. E. et al. Digestive morphology of two species of Abrothrix (Rodentia, Cricetidae): Comparison of populations from contrasting environments. J. Mammal. 95(6), 1222–1229 (2014).Article 

Google Scholar 
Warren, D. L., Glor, R. E. & Turelli, M. Environmental niche equivalency versus conservatism: Quantitative approaches to niche evolution. Evolution 62(11), 2868–2883 (2008).Article 

Google Scholar 
Goudarzi, F. et al. Geographic separation and genetic differentiation of populations are not coupled with niche differentiation in threatened Kaiser’s spotted newt (Neurergus kaiseri). Sci. Rep. 9(1), 1–12 (2019).Article 

Google Scholar 
Pyron, R. A., Costa, G. C., Patten, M. A. & Burbrink, F. T. Phylogenetic niche conservatism and the evolutionary basis of ecological speciation. Biol. Rev. 90(4), 1248–1262 (2015).Article 

Google Scholar 
Latorre, C. et al. Late Quaternary environments and paleoclimate. In The Geology of Chile (eds Moreno, T. & Gibbons, W.) 309–328 (Geological Society, 2007).Chapter 

Google Scholar 
Kaplan, M. R., Moreno, P. I. & Rojas, M. Glacial dynamics in southernmost South America during Marine Isotope Stage 5e to the Younger Dryas chron: A brief review with a focus on cosmogenic nuclide measurements. J. Quat. Sci. 23(6–7), 649–658 (2008).Article 

Google Scholar 
McCulloch, R. D. et al. Climatic inferences from glacial and palaeoecological evidence at the last glacial termination, southern South America. J. Quat. Sci. 15(4), 409–417 (2000).Article 

Google Scholar 
Giorello, F. M., D’Elía, G. & Lessa, E. P. Genomic footprints of Quaternary colonization and population expansion in the Patagonian-Fuegian region rules out a separate southern refugium in Tierra del Fuego. J. Biogeogr. 48(10), 2656–2670 (2021).Article 

Google Scholar 
Knowles, L. L., Carstens, B. C. & Keat, M. L. Coupling genetic and ecological-niche models to examine how past population distributions contribute to divergence. Curr. Biol. 17(11), 940–946 (2007).Article 

Google Scholar 
Diniz-Filho, J. A. F. et al. Correlation between genetic diversity and environmental suitability: Taking uncertainty from ecological niche models into account. Mol. Ecol. 15(5), 1059–1066 (2015).Article 

Google Scholar 
Guevara, L., León-Paniagua, L., Rios, J. & Anderson, R. P. Variación entre modelos de circulación global para reconstrucciones de distribuciones geográficas del Último Máximo Glacial: Relevancia en la filogeografía. Ecosistemas 27(1), 62–76 (2018).Article 

Google Scholar 
Guevara, L., Morrone, J. J. & León-Paniagua, L. Spatial variability in species’potential distributions during the Last Glacial Maximum under different Global Circulation Models: Relevance in evolutionary biology. J. Zool. Syst. Evol. Res. 57(1), 113–126 (2019).Article 

Google Scholar 
Cab-Sulub, L. & Álvarez-Castañeda, S. T. Genetic isolation between conspecific populations and their relationship to climate heterogeneity. Acta Oecol. 116, 103847 (2022).Article 

Google Scholar 
Teta, P., de la Sancha, N. U., D’Elía, G. & Patterson, B. D. Andean rain shadow effect drives phenotypic variation in a widely distributed Austral rodent. J. Biogeogr. 00, 1–12 (2022).
Google Scholar 
León-Tapia, M. A. DNA barcoding and demographic history of Peromyscus yucatanicus (Rodentia: Cricetidae) endemic to the Yucatan Peninsula, Mexico. J. Mammal. Evol. 28(2), 481–495 (2021).Article 

Google Scholar 
Lin, X. et al. Climatic-niche evolution with key morphological innovations across clades within Scutiger boulengeri (Anura: Megophryidae). Ecol. Evol. 11, 10353–10368 (2021).Article 

Google Scholar  More

Paudel, P. K., Sipos, J. & Brodie, J. F. Threatened species richness along a Himalayan elevational gradient: Quantifying the influences of human population density, range size, and geometric constraints. BMC Ecol. 18, 6. https://doi.org/10.1186/s12898-018-0162-3 (2018).Article 

Google Scholar 
Pan, K. Distribution of Coniferous Plants in Southwest China (Chengdu Cartographic Publishing House, 2021).
Google Scholar 
Zhang, Y.-B. & Ma, K.-P. Geographic distribution patterns and status assessment of threatened plants in China. Biol. Conserv. 17, 1783. https://doi.org/10.1007/s10531-008-9384-6 (2008).Article 

Google Scholar 
Shrestha, N., Xu, X., Meng, J. & Wang, Z. Vulnerabilities of protected lands in the face of climate and human footprint changes. Nat. Commun. 12, 1632. https://doi.org/10.1038/s41467-021-21914-w (2021).Article 
ADS 
CAS 

Google Scholar 
Pandey, B. et al. Energy–water and seasonal variations in climate underlie the spatial distribution patterns of gymnosperm species richness in China. Ecol. Evol. 10, 9474–9485. https://doi.org/10.1002/ece3.6639 (2020).Article 

Google Scholar 
Gao, J. & Liu, Y. Climate stability is more important than water–energy variables in shaping the elevational variation in species richness. Ecol. Evol. 8, 6872–6879. https://doi.org/10.1002/ece3.4202 (2018).Article 

Google Scholar 
Lomolino, M. V. Elevation gradients of species-density: Historical and prospective views. Glob. Ecol. Biogeogr. 10, 3–13. https://doi.org/10.1046/j.1466-822x.2001.00229.x (2001).Article 

Google Scholar 
Dakhil, M. A. et al. Richness patterns of endemic and threatened conifers in south-west China: Topographic-soil fertility explanation. Environ. Res. Lett. 16, 034017. https://doi.org/10.1088/1748-9326/abda6e (2021).Article 
ADS 
CAS 

Google Scholar 
Dakhil, M. A. et al. Potential risks to endemic conifer montane forests under climate change: Integrative approach for conservation prioritization in southwestern China. Landsc. Ecol. 36, 3137–3151. https://doi.org/10.1007/s10980-021-01309-4 (2021).Article 

Google Scholar 
Howard, C., Flather, C. H. & Stephens, P. A. A global assessment of the drivers of threatened terrestrial species richness. Nat. Commun. 11, 993. https://doi.org/10.1038/s41467-020-14771-6 (2020).Article 
ADS 
CAS 

Google Scholar 
Bhattarai, K. R. & Vetaas, O. R. Variation in plant species richness of different life forms along a subtropical elevation gradient in the Himalayas, east Nepal. Glob. Ecol. Biogeogr. 12, 327–340. https://doi.org/10.1046/j.1466-822X.2003.00044.x (2003).Article 

Google Scholar 
Currie, D. J. et al. Predictions and tests of climate-based hypotheses of broad-scale variation in taxonomic richness. Ecol. Lett. 7, 1121–1134. https://doi.org/10.1111/j.1461-0248.2004.00671.x (2004).Article 

Google Scholar 
Vetaas, O. R., Paudel, K. P. & Christensen, M. Principal factors controlling biodiversity along an elevation gradient: Water, energy and their interaction. J. Biogeogr. 46, 1652–1663. https://doi.org/10.1111/jbi.13564 (2019).Article 

Google Scholar 
Pandey, B. et al. Distribution pattern of gymnosperms’ richness in Nepal: Effect of environmental constrains along elevational gradients. Plants 9, 625. https://doi.org/10.3390/plants9050625 (2020).Article 

Google Scholar 
Kluge, J. et al. Elevational seed plants richness patterns in Bhutan, Eastern Himalaya. J. Biogeogr. 44, 1711–1722. https://doi.org/10.1111/jbi.12955 (2017).Article 

Google Scholar 
Currie, D. J. Energy and large-scale patterns of animal- and plant- species richness. Am. Nat. 137, 27–49. https://doi.org/10.1086/285144 (1991).Article 

Google Scholar 
MacArthur, R. H. & MacArthur, J. W. On bird species diversity. Ecology 42, 594–598. https://doi.org/10.2307/1932254 (1961).Article 

Google Scholar 
Kerr, J. T. & Packer, L. Habitat heterogeneity as a determinant of mammal species richness in high-energy regions. Nature 385, 252. https://doi.org/10.1038/385252a0 (1997).Article 
ADS 
CAS 

Google Scholar 
Kreft, H. & Jetz, W. Global patterns and determinants of vascular plant diversity. P. Natl. Acad. Sci. USA 104, 5925–5930. https://doi.org/10.1073/pnas.0608361104 (2007).Article 
ADS 
CAS 

Google Scholar 
Pausas, J. G. & Austin, M. P. Patterns of plant species richness in relation to different environments: An appraisal. J. Veg. Sci. 12, 153–166. https://doi.org/10.2307/3236601 (2001).Article 

Google Scholar 
Colwell, R. K. & Lees, D. C. The mid-domain effect: Geometric constraints on the geography of species richness. Trends Ecol. Evol. 15, 70–76. https://doi.org/10.1016/S0169-5347(99)01767-X (2000).Article 
CAS 

Google Scholar 
McCain, C. M. The mid-domain effect applied to elevational gradients: Species richness of small mammals in Costa Rica. J. Biogeogr. 31, 19–31. https://doi.org/10.1046/j.0305-0270.2003.00992.x (2004).Article 

Google Scholar 
Gao, D. et al. The mid-domain effect and habitat complexity applied to elevational gradients: Moss species richness in a temperate semihumid monsoon climate mountain of China. Ecol. Evol. 11, 7448–7460. https://doi.org/10.1002/ece3.7576 (2021).Article 

Google Scholar 
Wang, J.-H., Cai, Y.-F., Zhang, L., Xu, C.-K. & Zhang, S.-B. Species richness of the family Ericaceae along an elevational gradient in Yunnan, China. Forests 9, 511. https://doi.org/10.3390/f9090511 (2018).Article 

Google Scholar 
Xu, M. et al. The mid-domain effect of mountainous plants is determined by community life form and family flora on the Loess Plateau of China. Sci. Rep. 11, 10974. https://doi.org/10.1038/s41598-021-90561-4 (2021).Article 
ADS 
CAS 

Google Scholar 
Sichuan Vegetation Cooperation Group. Vegetation in Sichuan (Sichuan People’s Publishing House, 1980).
Google Scholar 
Pan, K., Wu, N., Pan, K. & Chen, Q. A discussion on the issues of the re-construction of ecological shelter zone on the upper reaches of the Yangtze River. Acta Ecol. Sin. 24, 617–629. https://doi.org/10.3321/j.issn:1000-0933.2004.03.032 (2004).Article 

Google Scholar 
Jpl, N. A. S. A. NASA shuttle radar topography mission global 1 arc second. NASA EOSDIS Land Process. DAAC https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL1.003 (2013).Liu, Y. et al. Determinants of richness patterns differ between rare and common species: Implications for Gesneriaceae conservation in China. Divers. Distrib. 23, 235–246. https://doi.org/10.1111/ddi.12523 (2017).Article 

Google Scholar 
Liao, Z. et al. Climate change jointly with migration ability affect future range shifts of dominant fir species in Southwest China. Divers. Distrib. 26, 352–367. https://doi.org/10.1111/ddi.13018 (2020).Article 

Google Scholar 
Karger, D. N. et al. Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digit. Repos. https://doi.org/10.5061/dryad.kd1d4 (2018).Running, S. W., Mu, Q. & Zhao, M. MODIS/terra net evapotranspiration 8-day L4 global 500m SIN grid V061. NASA EOSDIS Land Process. DAAC https://doi.org/10.5067/MODIS/MOD16A2.061 (2021).Mu H. et al. An Annual Global Terrestrial Human Footprint Dataset from 2000 to 2018https://doi.org/10.6084/m9.figshare.16571064.v5(2021).Zhang, D., Zhang, Y., Boufford, D. E. & Sun, H. Elevational patterns of species richness and endemism for some important taxa in the Hengduan Mountains, southwestern China. Biol. Conserv. 18, 699–716. https://doi.org/10.1007/s10531-008-9534-x (2009).Article 

Google Scholar 
Sun, L., Luo, J., Qian, L., Deng, T. & Sun, H. The relationship between elevation and seed-plant species richness in the Mt. Namjagbarwa region (Eastern Himalayas) and its underlying determinants. Glob. Ecol. Conserv. 23, e01053. https://doi.org/10.1016/j.gecco.2020.e01053 (2020).Article 

Google Scholar 
Zhou, Y. et al. The species richness pattern of vascular plants along a tropical elevational gradient and the test of elevational Rapoport’s rule depend on different life-forms and phytogeographic affinities. Ecol. Evol. 9, 4495–4503. https://doi.org/10.1002/ece3.5027 (2019).Article 

Google Scholar 
Krömer, T., Acebey, A., Kluge, J. & Kessler, M. Effects of altitude and climate in determining elevational plant species richness patterns: A case study from Los Tuxtlas, Mexico. Flora 208, 197–210. https://doi.org/10.1016/j.flora.2013.03.003 (2013).Article 

Google Scholar 
Pandey, B. et al. Contrasting gymnosperm diversity across an elevation gradient in the ecoregion of China: The role of temperature and productivity. Front. Ecol. Evol. 9, 1–7. https://doi.org/10.3389/fevo.2021.679439 (2021).Article 
CAS 

Google Scholar 
Geng, S. et al. Diversity of vegetation composition enhances ecosystem stability along elevational gradients in the Taihang Mountains, China. Ecol. Indic. 104, 594–603. https://doi.org/10.1016/j.ecolind.2019.05.038 (2019).Article 

Google Scholar 
Rosenzweig, M. L. Species Diversity in Space and Time (Cambridge University Press, 1995).Book 

Google Scholar 
Zhang, S., Chen, W., Huang, J., Bi, Y. & Yang, X. Orchid species richness along elevational and environmental gradients in Yunnan, China. PLoS ONE https://doi.org/10.1371/journal.pone.0142621 (2015).Article 

Google Scholar 
Bertuzzo, E. et al. Geomorphic controls on elevational gradients of species richness. Proc. Natl. Acad. Sci. USA 113, 1737–1742. https://doi.org/10.1073/pnas.1518922113 (2016).Article 
ADS 
CAS 

Google Scholar 
Vetaas, O. R. & Grytnes, J. A. Distribution of vascular plant species richness and endemic richness along the Himalayan elevation gradient in Nepal. Glob. Ecol. Biogeogr. 11, 291–301. https://doi.org/10.1046/j.1466-822X.2002.00297.x (2002).Article 

Google Scholar 
Antonio, T. & Robert, Z. Global Aridity Index and Potential Evapotranspiration (ET0) Climate Database v2. https://doi.org/10.6084/m9.figshare.7504448.v3 (2019).Panda, R. M., Behera, M. D., Roy, P. S. & Biradar, C. Energy determines broad pattern of plant distribution in Western Himalaya. Ecol. Evol. 7, 10850–10860. https://doi.org/10.1002/ece3.3569 (2017).Article 

Google Scholar 
Vetaas, O. R. & Ferrer-Castán, D. Patterns of woody plant species richness in the Iberian Peninsula: Environmental range and spatial scale. J. Biogeogr. 35, 1863–1878. https://doi.org/10.1111/j.1365-2699.2008.01931.x (2008).Article 

Google Scholar 
McCain, C. M. & Grytnes, J.-A. Encyclopedia of Life Sciences (ELS) (Wiley, 2010).
Google Scholar 
Tukiainen, H., Bailey, J. J., Field, R., Kangas, K. & Hjort, J. Combining geodiversity with climate and topography to account for threatened species richness. Conserv. Biol. 31, 364–375. https://doi.org/10.1111/cobi.12799 (2017).Article 

Google Scholar 
Zhang, Z., He, J.-S., Li, J. & Tang, Z. Distribution and conservation of threatened plants in China. Biol. Conserv. 192, 454–460. https://doi.org/10.1016/j.biocon.2015.10.019 (2015).Article 

Google Scholar 
Shrestha, N., Su, X., Xu, X. & Wang, Z. The drivers of high Rhododendron diversity in south-west China: Does seasonality matter?. J. Biogeogr. 45, 438–447. https://doi.org/10.1111/jbi.13136 (2017).Article 

Google Scholar 
Hawkins, B. A. et al. Energy, water, and broad-scale geographic patterns of species richness. Ecology 84, 3105–3117. https://doi.org/10.1890/03-8006 (2003).Article 

Google Scholar 
Bijlsma, R. & Loeschcke, V. Environmental stress, adaptation and evolution: An overview. J. Evol. Biol. 18, 744–749. https://doi.org/10.1111/j.1420-9101.2005.00962.x (2005).Article 
CAS 

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. https://doi.org/10.1111/jbi.12613 (2016).Article 

Google Scholar 
Zhang, X., Wang, H., Wang, R., Wang, Y. & Liu, J. Relationships between plant species richness and environmental factors in nature reserves at different spatial scales. Pol. J. Environ. Stud. 26, 2375–2384. https://doi.org/10.15244/pjoes/69032 (2017).Article 

Google Scholar 
Mu, H. et al. A global record of annual terrestrial Human Footprint dataset from 2000 to 2018. Sci. Data 9, 176. https://doi.org/10.1038/s41597-022-01284-8 (2022).Article 

Google Scholar 
Kadmon, R. & Benjamini, Y. Effects of productivity and disturbance on species richness: A neutral model. Am. Nat. 167, 939–946. https://doi.org/10.1086/504602 (2006).Article 

Google Scholar 
Olson, D. M. & Dinerstein, E. The global 200: Priority ecoregions for global conservation. Ann. Mo. Bot. Gard. 89, 199–224. https://doi.org/10.2307/3298564 (2002).Article 

Google Scholar 
Chéng, X. Y. Atlas of National Wildlife Conservation and Rare and Endangered Plants of Sichuan Province (Science Press, 2018).
Google Scholar 
Wu, Z. & Raven, P. Flora of China. Vol. 4 (Cycadaceae Through Fagaceae) (Science Press and Missouri Botanical Garden Press, 1999).
Google Scholar 
Sanders, N. J. Elevational gradients in ant species richness: Area, geometry, and Rapoport’s rule. Ecography 25, 25–32. https://doi.org/10.1034/j.1600-0587.2002.250104.x (2002).Article 

Google Scholar 
RangeModel: A Monte Carlo simulation tool for assessing geometric constraints on species richness. Version 5. User’s Guide and application (2006).Colwell, R. K. RangeModel: Tools for exploring and assessing geometric constraints on species richness (the mid-domain effect) along transects. Ecography 31, 4–7. https://doi.org/10.1111/j.2008.0906-7590.05347.x (2008).Article 

Google Scholar 
Sanderson, E. W. et al. The human footprint and the last of the wild. Bioscience 52, 891–904. https://doi.org/10.1641/0006-3568(2002)052[0891:THFATL]2.0.CO;2 (2002).Article 

Google Scholar 
Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4, 170122–170122. https://doi.org/10.1038/sdata.2017.122 (2017).Article 

Google Scholar 
Mu, Q., Zhao, M. & Running, S. W. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens. Environ. 115, 1781–1800. https://doi.org/10.1016/j.rse.2011.02.019 (2011).Article 
ADS 

Google Scholar 
Zhang, Z. et al. Distribution and conservation of orchid species richness in China. Biol. Conserv. 181, 64–72. https://doi.org/10.1016/j.biocon.2014.10.026 (2015).Article 

Google Scholar 
D’Agostino, R. Goodness-of-Fit-Techniques (Routledge, 2017).Book 
MATH 

Google Scholar 
Hilbe, J. M. Negative Binomial Regression (Cambridge University Press, 2011).Book 
MATH 

Google Scholar 
Legendre, P. & Legendre, L. Numerical Ecology (Elsevier, 2012).MATH 

Google Scholar 
Grace, J. B. Structural Equation Modeling and Natural Systems (Cambridge University Press, 2006).Book 

Google Scholar 
Grace, J. B. & Pugesek, B. H. A structural equation model of plant species richness and its application to a coastal wetland. Am. Nat. 149, 436–460. https://doi.org/10.1086/285999 (1997).Article 

Google Scholar 
R Development Core Team. (R Foundation for Statistical Computing, 2019).Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S 4th edn. (Springer, 2002).Book 
MATH 

Google Scholar 
Fox, J. et al. R Foundation for Statistical Computing Vol. 16 (2012).Rosseel, Y. lavaan: An R package for structural equation modeling. J. Stat. Softw. 48, 1–36. https://doi.org/10.18637/jss.v048.i02 (2012).Article 

Google Scholar  More

Vitousek, P. M., Mooney, H. A., Lubchenco, J. & Melillo, J. M. Human domination of earth’s ecosystems. Science 277, 494–499. https://doi.org/10.1126/science.277.5325.494 (1997).Article 
CAS 

Google Scholar 
Yue, T. X., Fan, Z. M. & Liu, J. Y. Scenarios of land cover in China. Glob. Planet. Change 55, 317–342. https://doi.org/10.1016/j.gloplacha.2006.10.002 (2007).Article 
ADS 

Google Scholar 
Ii, B. L. T., Lambin, E. F. & Reen Be Rg, A. The emergence of land change science for global environmental change and sustainability. Proc. Natl. Acad. Sci. USA 104, 20666–20671. https://doi.org/10.1073/pnas.0704119104 (2007).Article 

Google Scholar 
IPCC. 2006 IPCC Guidelines for National Greenhouse Gas Inventories—IPCC. https://www.ipcc.ch/report/2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/ (2006).Gallant, K., Withey, P., Risk, D., van Kooten, G. C. & Spafford, L. Measurement and economic valuation of carbon sequestration in Nova Scotian wetlands. Ecol. Econ. 171, 106619. https://doi.org/10.1016/j.ecolecon.2020.10661 (2020).Article 

Google Scholar 
Deng, C. et al. Spatiotemporal dislocation of urbanization and ecological construction increased the ecosystem service supply and demand imbalance. J. Environ. Manag. 288, 112478. https://doi.org/10.1016/j.jenvman.2021.112478 (2021).Article 

Google Scholar 
Wang, J., Zhai, T., Lin, Y., Kong, X. & He, T. Spatial imbalance and changes in supply and demand of ecosystem services in China. Sci. Total Environ. 657, 781–791. https://doi.org/10.1016/j.scitotenv.2018.12.080 (2019).Article 
ADS 
CAS 

Google Scholar 
Long, R., Li, J., Chen, H., Zhang, L. & Li, Q. Embodied carbon dioxide flow in international trade: A comparative analysis based on China and Japan. J. Environ. Manag. 209, 371–381. https://doi.org/10.1016/j.jenvman.2017.12.067 (2018).Article 

Google Scholar 
Lv, Y., Liu, J., Cheng, J. & Andreoni, V. The persistent and transient total factor carbon emission performance and its economic determinants: Evidence from China’s province-level panel data. J. Clean. Prod. 316, 128198. https://doi.org/10.1016/j.jclepro.2021.128198 (2021).Article 
CAS 

Google Scholar 
Wang, Y., Shataer, R., Zhang, Z., Zhen, H. & Xia, T. Evaluation and analysis of influencing factors of ecosystem service value change in Xinjiang under different land use types. Water 14, 1424. https://doi.org/10.3390/w14091424 (2022).Article 

Google Scholar 
Zhang, Y. et al. How can an ecological compensation threshold be determined? A discriminant model integrating the minimum data approach and the most appropriate land use scenarios. Sci. Total Environ. 852, 158377. https://doi.org/10.1016/j.scitotenv.2022.158377 (2022).Article 
ADS 
CAS 

Google Scholar 
Shi, M. et al. Cropland expansion mitigates the supply and demand deficit for carbon sequestration service under different scenarios in the future—the case of Xinjiang. Agriculture 12, 1182. https://doi.org/10.3390/agriculture12081182 (2022).Article 
CAS 

Google Scholar 
Yuan, K., Li, F., Yang, H. & Wang, Y. The influence of land use change on ecosystem service value in Shangzhou district. Int. J. Environ. Res. Public. Health 16, 1321. https://doi.org/10.3390/ijerph16081321 (2019).Article 

Google Scholar 
Millennium Ecosystem Assessment (MEA). Ecosystems and Human Well-Being: Multiscale Assessments. https://www.millenniu-massessment.org/en/Multiscale.html (Island Press, 2005).Liu, J. Y., Liu, M. L., Zhuang, D. F., Zhang, Z. X. & Deng, X. Z. Study on spatial pattern of land-use change in China during 1995–2000. Sci. China Ser. Earth Sci. 46, 373–384. https://doi.org/10.1360/03yd9033 (2003).Article 

Google Scholar 
Lambin, E. F. & Meyfroidt, P. Land use transitions: Socio-ecological feedback versus socio-economic change. Land Use Policy 27, 108–118. https://doi.org/10.1016/j.landusepol.2009.09.003 (2010).Article 

Google Scholar 
Long, H., Qu, Y., Tu, S., Zhang, Y. & Jiang, Y. Development of land use transitions research in China. J. Geogr. Sci. 30, 1195–1214. https://doi.org/10.1007/s11442-020-1777-9 (2020).Article 

Google Scholar 
Portela, R. & Rademacher, I. A dynamic model of patterns of deforestation and their effect on the ability of the Brazilian Amazonia to provide ecosystem services. Ecol. Model. 143, 115–146. https://doi.org/10.1016/S0304-3800(01)00359-3 (2001).Article 

Google Scholar 
Yin, D., Li, X., Li, G., Zhang, J. & Yu, H. Spatio-temporal evolution of land use transition and its eco-environmental effects: A case study of the Yellow River Basin, China. Land 9, 514. https://doi.org/10.3390/land9120514 (2020).Article 

Google Scholar 
Alkimim, A. & Clarke, K. C. Land use change and the carbon debt for sugarcane ethanol production in Brazil. Land Use Policy 72, 65–73. https://doi.org/10.1016/j.landusepol.2017.12.039 (2018).Article 

Google Scholar 
Wang, J. & Zhou, W. Ecosystem service flows: Recent progress and future perspectives. Acta Ecol. Sin. 39, 4213–4222. https://doi.org/10.5846/stxb201807271605 (2019).Article 

Google Scholar 
Krozer, Y., Coenen, F., Hanganu, J., Lordkipanidze, M. & Sbarcea, M. Towards innovative governance of nature areas. Sustainability 12, 10624. https://doi.org/10.3390/su122410624 (2020).Article 

Google Scholar 
Pan, X., Xu, L., Yang, Z. & Yu, B. Payments for ecosystem services in China: Policy, practice, and progress. J. Clean. Prod. 158, 200–208. https://doi.org/10.1016/j.jclepro.2017.04.127 (2017).Article 

Google Scholar 
Su, K. et al. The establishment of a cross-regional differentiated ecological compensation scheme based on the benefit areas and benefit levels of sand-stabilization ecosystem service. J. Clean. Prod. 270, 122490. https://doi.org/10.1016/j.jclepro.2020.122490 (2020).Article 

Google Scholar 
Zhai, T., Zhang, D. & Zhao, C. How to optimize ecological compensation to alleviate environmental injustice in different cities in the Yellow River Basin? A case of integrating ecosystem service supply, demand and flow. Sustain. Cities Soc. 75, 103341. https://doi.org/10.1016/j.scs.2021.103341 (2021).Article 

Google Scholar 
Zhai, T. et al. Did improvements of ecosystem services supply-demand imbalance change environmental spatial injustices?. Ecol. Indic. 111, 106068. https://doi.org/10.1016/j.ecolind.2020.106068 (2020).Article 

Google Scholar 
Chen, W. et al. Land use transitions and the associated impacts on ecosystem services in the Middle Reaches of the Yangtze River Economic Belt in China based on the geo-informatic Tupu method. Sci. Total Environ. 701, 134690. https://doi.org/10.1016/j.scitotenv.2019.134690 (2020).Article 
ADS 
CAS 

Google Scholar 
Zheng, W., Ke, X., Xiao, B. & Zhou, T. Optimising land use allocation to balance ecosystem services and economic benefits—A case study in Wuhan, China. J. Environ. Manag. 248, 109306. https://doi.org/10.1016/j.jenvman.2019.109306 (2019).Article 

Google Scholar 
Li, Z., Deng, X., Jin, G., Mohmmed, A. & Arowolo, A. O. Tradeoffs between agricultural production and ecosystem services: A case study in Zhangye, Northwest China. Sci. Total Environ. 707, 136032. https://doi.org/10.1016/j.scitotenv.2019.136032 (2020).Article 
ADS 
CAS 

Google Scholar 
Raudsepp-Hearne, C., Peterson, G. D. & Bennett, E. M. Ecosystem service bundles for analyzing tradeoffs in diverse landscapes. Proc. Natl. Acad. Sci. USA. 107, 5242–5247. https://doi.org/10.1073/pnas.0907284107 (2010).Article 
ADS 

Google Scholar 
Yuan, B. et al. Spatiotemporal change detection of ecological quality and the associated affecting factors in Dongting Lake Basin, based on RSEI. J. Clean. Prod. 302, 126995. https://doi.org/10.1016/j.jclepro.2021.126995 (2021).Article 

Google Scholar 
An, M. et al. Spatiotemporal change of ecologic environment quality and human interaction factors in three gorges ecologic economic corridor, based on RSEI. Ecol. Indic. 141, 109090. https://doi.org/10.1016/j.ecolind.2022.109090 (2022).Article 

Google Scholar 
Liu, W., Yan, Y., Wang, D. & Ma, W. Integrate carbon dynamics models for assessing the impact of land use intervention on carbon sequestration ecosystem service. Ecol. Indic. 91, 268–277. https://doi.org/10.1016/j.ecolind.2018.03.087 (2018).Article 
CAS 

Google Scholar 
Adelisardou, F. et al. Spatiotemporal change detection of carbon storage and sequestration in an arid ecosystem by integrating Google Earth Engine and InVEST (the Jiroft plain, Iran). Int. J. Environ. Sci. Technol. 19, 5929–5944. https://doi.org/10.1007/s13762-021-03676-6 (2021).Article 

Google Scholar 
Yang, F. et al. Taklimakan desert carbon-sink decreases under climate change. Sci. Bull. 65, 431–433. https://doi.org/10.1016/j.scib.2019.12.022 (2020).Article 
CAS 

Google Scholar 
Huang, L., Liu, J., Shao, Q. & Xu, X. Carbon sequestration by forestation across China: Past, present, and future. Renew. Sustain. Energy Rev. 16, 1291–1299. https://doi.org/10.1016/j.rser.2011.10.004 (2012).Article 

Google Scholar 
Hong, C. et al. Land-use emissions embodied in international trade. Science 376, 597–603. https://doi.org/10.1126/science.abj1572 (2022).Article 
ADS 
CAS 

Google Scholar 
Zhu, E. et al. Carbon emissions induced by land-use and land-cover change from 1970 to 2010 in Zhejiang, China. Sci. Total Environ. 646, 930–939. https://doi.org/10.1016/j.scitotenv.2018.07.317 (2019).Article 
ADS 
CAS 

Google Scholar 
Xiao, D., Niu, H., Guo, J., Zhao, S. & Fan, L. Carbon storage change analysis and emission reduction suggestions under land use transition: A case study of Henan province, China. Int. J. Environ. Res. Public. Health 18, 1844. https://doi.org/10.3390/ijerph18041844 (2021).Article 

Google Scholar 
Boisvenue, C., Bergeron, Y., Bernier, P. & Peng, C. Simulations show potential for reduced emissions and carbon stocks increase in boreal forests under ecosystem management. Carbon Manag. 3, 553–568. https://doi.org/10.4155/CMT.12.57 (2012).Article 
CAS 

Google Scholar 
Heimann, M. & Reichstein, M. Terrestrial ecosystem carbon dynamics and climate feedbacks. Nature 451, 289–292. https://doi.org/10.1038/nature06591 (2008).Article 
ADS 
CAS 

Google Scholar 
Li, T., Li, J. & Wang, Y. Carbon sequestration service flow in the Guanzhong-Tianshui economic region of China: How it flows, what drives it, and where could be optimized?. Ecol. Indic. 96, 548–558. https://doi.org/10.1016/j.ecolind.2018.09.040 (2019).Article 

Google Scholar 
Yan, X. et al. An overview of distribution characteristics and formation mechanisms in global arid areas. Adv. Earth Sci. 34, 826–841. https://doi.org/10.11867/j.issn.1001-8166.2019.08.0826 (2019).Article 

Google Scholar 
Abulizi, A. et al. Land-use change and its effects in Charchan Oasis, Xinjiang, China. Land Degrad. Dev. 28, 106–115. https://doi.org/10.1002/ldr.2530 (2017).Article 

Google Scholar 
Zhang, Z. et al. Spatiotemporal characteristics in ecosystem service value and its interaction with human activities in Xinjiang, China. Ecol. Indic. 110, 105826. https://doi.org/10.1016/j.ecolind.2019.105826 (2020).Article 

Google Scholar 
Xie, L., Wang, H. & Liu, S. The ecosystem service values simulation and driving force analysis based on land use/land cover: A case study in inland rivers in arid areas of the Aksu River Basin, China. Ecol. Indic. 138, 108828. https://doi.org/10.1016/j.ecolind.2022.108828 (2022).Article 
CAS 

Google Scholar 
Wang, Z. et al. Dynamic simulation of land use change and assessment of carbon storage based on climate change scenarios at the city level: A case study of Bortala, China. Ecol. Indic. 134, 108499. https://doi.org/10.1016/j.ecolind.2021.108499 (2022).Article 
CAS 

Google Scholar 
Shi, M. et al. Trade-offs and synergies of multiple ecosystem services for different land use scenarios in the Yili River Valley, China. Sustainability 13, 1577. https://doi.org/10.3390/su13031577 (2021).Article 
CAS 

Google Scholar 
Wang, C., Zhen, L., Bingzhen, D. U. & Sun, C. Assessment of the impact of Grain for Green project on farmers’ livelihood in the Loess Plateau. Chin. J. Eco-Agric. 22, 850–858. https://doi.org/10.3724/SP.J.1011.2014.30944 (2014).Article 

Google Scholar 
Yang, H., Mu, S. & Li, J. Effects of ecological restoration projects on land use and land cover change and its influences on territorial NPP in Xinjiang, China. CATENA 115, 85–95. https://doi.org/10.1016/j.catena.2013.11.020 (2014).Article 

Google Scholar 
Bahtebay, J., Zhang, F., Ariken, M., Chan, N. W. & Tan, M. L. Evaluation of the coordinated development of urbanization-resources-environment from the incremental perspective of Xinjiang. China. J. Clean. Prod. 325, 129309. https://doi.org/10.1016/j.jclepro.2021.129309 (2021).Article 

Google Scholar 
Chen, J. et al. County-level CO2 emissions and sequestration in China during 1997–2017. Sci. Data 7, 391. https://doi.org/10.1038/s41597-020-00736-3 (2020).Article 
CAS 

Google Scholar 
Zhu, H. & Li, X. Discussion on the index method of regional land use change. Acta Geogr. Sin. 58, 643–650. https://doi.org/10.3321/j.issn:0375-5444.2003.05.001 (2003).Article 

Google Scholar 
Li, Y., Cao, Z., Long, H., Liu, Y. & Li, W. Dynamic analysis of ecological environment combined with land cover and NDVI changes and implications for sustainable urban–rural development: The case of Mu Us Sandy Land, China. J. Clean. Prod. 142, 697–715. https://doi.org/10.1016/j.jclepro.2016.09.011 (2017).Article 

Google Scholar 
Zhou, Q., Li, B. & Kurban, A. Trajectory analysis of land cover change in arid environment of China. Int. J. Remote Sens. 29, 1093–1107. https://doi.org/10.1080/01431160701355256 (2008).Article 
CAS 

Google Scholar 
Zhang, F. & Rusuli, Y. Spatio-temporal variation of ecosystem service value based on LUCC trajectories: A case study of Bosten Lake Watershed. J. Beijing For. Univ. 43, 88–99. https://doi.org/10.12171/j.1000-1522.20210017 (2021).Article 

Google Scholar 
Keller, A. A., Fournier, E. & Fox, J. Minimizing impacts of land use change on ecosystem services using multi-criteria heuristic analysis. J. Environ. Manag. 156, 23–30. https://doi.org/10.1016/j.jenvman.2015.03.017 (2015).Article 

Google Scholar 
Li, K. et al. Assessing the effects of ecological engineering on spatiotemporal dynamics of carbon storage from 2000 to 2016 in the Loess Plateau area using the InVEST model: A case study in Huining County, China. Environ. Dev. 39, 100641. https://doi.org/10.1016/j.envdev.2021.100641 (2021).Article 

Google Scholar 
Tang, X. et al. Carbon pools in China’s terrestrial ecosystems: New estimates based on an intensive field survey. Proc. Natl. Acad. Sci. USA. 115, 4021–4026. https://doi.org/10.1073/pnas.1700291115 (2018).Article 
ADS 
CAS 

Google Scholar 
Yang, F. et al. Impact of differences in soil temperature on the desert carbon sink. Geoderma 379, 114636. https://doi.org/10.1016/j.geoderma.2020.114636 (2020).Article 
ADS 
CAS 

Google Scholar 
Xiang, M. et al. Spatio-temporal evolution and driving factors of carbon storage in the Western Sichuan Plateau. Sci. Rep. 12, 8114. https://doi.org/10.1038/s41598-022-12175-8 (2022).Article 
ADS 
CAS 

Google Scholar 
de Groot, R. S., Wilson, M. A. & Boumans, R. M. J. A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol. Econ. 41, 393–408. https://doi.org/10.1016/S0921-8009(02)00089-7 (2002).Article 

Google Scholar 
Chen, J., Xue, M., Su, X. & Gao, J. Spatial transfer of regional ecosystem service in Nanjing City. Acta Ecol. Sin. 34, 5087–5095. https://doi.org/10.5846/stxb201308162095 (2014).Article 

Google Scholar 
Hu, X. et al. Carbon sequestration benefits of the grain for Green Program in the hilly red soil region of southern China. Int. Soil Water Conserv. Res. 9, 271–278. https://doi.org/10.1016/j.iswcr.2020.11.005 (2021).Article 

Google Scholar 
Yao, J. et al. Recent climate and hydrological changes in a mountain–basin system in Xinjiang, China. Earth-Sci. Rev. 226, 103957. https://doi.org/10.1016/j.earscirev.2022.103957 (2022).Article 

Google Scholar 
Li, J., Zuo, Q. & Ma, J. Analysis of spatial and temporal evolution characteristics of water-socioeconomic-ecosystem in Xinjiang. J. Beijing Norm. Univ. Sci. 56, 591–599. https://doi.org/10.12202/j.0476-0301.2020170 (2020).Article 

Google Scholar 
Chen, X., Chang, C., Bao, A., Wu, S. & Luo, G. Spatial pattern and characteristics of land cover change in Xinjiang since past 40 years of the economic reform and opening up. ARID LAND Geogr. 43, 1–11. https://doi.org/10.12118/j.issn.1000-6060.2020.01.01 (2020).Article 

Google Scholar 
Han, B. et al. Research progress and key issues of territory consolidation under the target of rural revitalization. J. Nat. Resour. 36, 3007–3030. https://doi.org/10.31497/zrzyxb.20211202 (2021).Article 

Google Scholar 
Ziyuan, C. et al. Carbon emissions index decomposition and carbon emissions prediction in Xinjiang from the perspective of population-related factors, based on the combination of STIRPAT model and neural network. Environ. Sci. Pollut. Res. 29, 31781–31796. https://doi.org/10.1007/s11356-021-17976-4 (2022).Article 
CAS 

Google Scholar 
Wang, C. et al. Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang. Renew. Sustain. Energy Rev. 67, 51–61. https://doi.org/10.1016/j.rser.2016.09.006 (2017).Article 

Google Scholar 
Ma, C., Chen, Q., Hu, F., Li, S. & Cong, J. Research characteristic of carbon emissions calculation in Xinjiang. Resour. Dev. Mark. 36, 233–240+267. https://doi.org/10.3969/j.issn.1005-8141.2020.03.002 (2020).Article 

Google Scholar 
Qin, Z. et al. Natural climate solutions for China: The last mile to carbon neutrality. Adv. Atmos. Sci. 38, 889–895. https://doi.org/10.1007/s00376-021-1031-0 (2021).Article 

Google Scholar 
Kong, R. et al. Increasing carbon storage in subtropical forests over the Yangtze River basin and its relations to the major ecological projects. Sci. Total Environ. 709, 136163. https://doi.org/10.1016/j.scitotenv.2019.136163 (2020).Article 
ADS 
CAS 

Google Scholar 
Chang, J. et al. Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands. Nat. Commun. 12, 118. https://doi.org/10.1038/s41467-020-20406-7 (2021).Article 
ADS 
CAS 

Google Scholar 
Wang, X. & Nuppenau, E.-A. Modelling payments for ecosystem services for solving future water conflicts at spatial scales: The Okavango River Basin example. Ecol. Econ. 184, 106982. https://doi.org/10.1016/j.ecolecon.2021.106982 (2021).Article 

Google Scholar  More

Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).Article 
CAS 

Google Scholar 
Hoegh-Guldberg, O. et al. Coral reefs under rapid climate change and ocean acidification. Science 318, 1737–1742 (2007).Article 
CAS 

Google Scholar 
Brown, B. E. Coral bleaching: causes and consequences. Coral Reefs 16, 129–138 (1997).Article 

Google Scholar 
Hoegh-Guldberg, O. Climate change, coral bleaching and the future of the world’s coral reefs. Mar. Freshw. Res. 50, 839–866 (1999).
Google Scholar 
Scheufen, T., Krämer, W. E., Iglesias-Prieto, R. & Enríquez, S. Seasonal variation modulates coral sensibility to heat-stress and explains annual changes in coral productivity. Sci. Rep. 7, 4937 (2017).Article 

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

Google Scholar 
Hughes, T. P. et al. Global warming transforms coral reef assemblages. Nature 556, 492–496 (2018).Article 
CAS 

Google Scholar 
Doney, S. C., Fabry, V. J., Feely, R. A. & Kleypas, J. A. Ocean acidification: the other CO2 problem. Annu. Rev. Mar. Sci. 1, 169–192 (2009).Article 

Google Scholar 
Warner, M. E., Fitt, W. K. & Schmidt, G. W. The effects of elevated temperature on the photosynthetic efficiency of zooxanthellae in hospite from four different species of reef coral: a novel approach. Plant Cell Environ. 19, 291–299 (1996).Article 

Google Scholar 
Iglesias-Prieto, R. Temperature-dependent inactivation of photosystem II in symbiotic dinoflagellates. in Proceedings of the 8th International Coral Reef Symposium (eds. Lessios, H. A. & MacIntyre, I. G.) Vol. 2, 1313–1318 (1997).Takahashi, S., Nakamura, T., Sakamizu, M., van Woesik, R. & Yamasaki, H. Repair machinery of symbiotic photosynthesis as the primary target of heat stress for reef-building corals. Plant Cell Physiol. 45, 251–255 (2004).Article 
CAS 

Google Scholar 
Warner, M. E., Fitt, W. K. & Schmidt, G. W. Damage to photosystem II in symbiotic dinoflagellates: a determinant of coral bleaching. Proc. Natl Acad. Sci. USA 96, 8007–8012 (1999).Article 
CAS 

Google Scholar 
Scheufen, T., Iglesias-Prieto, R. & Enríquez, S. Changes in the number of symbionts and Symbiodinium cell pigmentation modulate differentially coral light absorption and photosynthetic performance. Front. Mar. Sci. 4, 309 (2017).Gómez-Campo, K., Enríquez, S. & Iglesias-Prieto, R. A road map for the development of the bleached coral phenotype. Front. Mar. Sci. 9, 806491 (2022).Dahlhoff, E. A. & Somero, G. N. Effects of temperature on mitochondria from abalone (genus Haliotis): adaptive plasticity and its limits. J. Exp. Biol. 185, 151–168 (1993).Article 

Google Scholar 
Kajiwara, K., Nagai, A. & Ueno, S. Examination of the effect of temperature, light intensity and zooxanthellae concentration on calcification and photosynthesis of scleractinian coral Acropora pulchra. J. Sch. Mar. Sci. Technol. 40, 95–103 (1995).
Google Scholar 
Rodolfo-Metalpa, R., Huot, Y. & Ferrier-Pagès, C. Photosynthetic response of the Mediterranean zooxanthellate coral Cladocora caespitosa to the natural range of light and temperature. J. Exp. Biol. 211, 1579–1586 (2008).Article 
CAS 

Google Scholar 
Marshall, A. T. & Clode, P. Calcification rate and the effect of temperature in a zooxanthellate and an azooxanthellate scleractinian reef coral. Coral Reefs 23, 218–224 (2004).Article 

Google Scholar 
Kleypas, J. A., Buddemeier, R. W. & Gattuso, J.-P. The future of coral reefs in an age of global change. Int. J. Earth Sci. 90, 426–437 (2001).Article 
CAS 

Google Scholar 
Orr, J. C. et al. Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437, 681–686 (2005).Article 
CAS 

Google Scholar 
Ries, J. B., Cohen, A. L. & McCorkle, D. C. Marine calcifiers exhibit mixed responses to CO2-induced ocean acidification. Geology 37, 1131–1134 (2009).Article 
CAS 

Google Scholar 
Vasquez-Elizondo, R. M. & Enríquez, S. Coralline algal physiology is more adversely affected by elevated temperature than reduced pH. Sci. Rep. 6, 19030 (2016).Article 
CAS 

Google Scholar 
Anthony, K. R., Kline, D. I., Diaz-Pulido, G., Dove, S. & Hoegh-Guldberg, O. Ocean acidification causes bleaching and productivity loss in coral reef builders. Proc. Natl Acad. Sci. USA 105, 17442–17446 (2008).Article 
CAS 

Google Scholar 
Gattuso, J.-P., Allemand, D. & Frankignoulle, M. Photosynthesis and calcification at cellular, organismal and community levels in coral reefs: A review on interactions and control by carbonate chemistry. Am. Zool. 39, 160–183 (1999).Article 
CAS 

Google Scholar 
Langdon, C. & Aktinson, M. J. Effect of elevated pCO2 on photosynthesis and calcification of corals and interactions with seasonal change in temperature/irradiance and nutrient enrichment. J. Geophys. Res. 110, https://doi.org/10.1029/2004JC002576 (2005).Iglesias-Rodriguez, M. D. et al. Phytoplankton calcification in a high-CO2 world. Science 320, 336–340 (2008).Article 
CAS 

Google Scholar 
Krumhardt, K. M., Lovenduski, N. S., Iglesias-Rodriguez, M. D. & Kleypas, J. A. Coccolithophore growth and calcification in a changing ocean. Prog. Oceanogr. 159, 276–295 (2017).Article 

Google Scholar 
Kleypas, J. A. et al. Impact of Ocean Acidification on Coral Reefs and Other Marine Calcifiers: A Case Guide for Future Research Vol. 88 (2005).Comeau, S., Cornwall, C. E., DeCarlo, T. M., Krieger, E. & McCulloch, M. T. Similar controls on calcification under ocean acidification across unrelated coral reef taxa. Glob. Change Biol. 24, 4857–4868 (2018).Article 

Google Scholar 
Kroeker, K. J. et al. Impacts of ocean acidification on marine organisms: quantifying sensitivities and interaction with warming. Glob. Change Biol. 19, 1884–1896 (2013).Article 

Google Scholar 
Hoadley, K. D., Pettay, D. T., Dodge, D. & Warner, M. E. Contrasting physiological plasticity in response to environmental stress within different cnidarians and their respective symbionts. Coral Reefs 35, 529–542 (2016).Article 

Google Scholar 
Langdon, C., Albright, R., Baker, A. & Jones, P. Two threatened Caribbean coral species have contrasting responses to combined temperature and acidification stress. Limnol. Oceanogr. 63, 2450–2464 (2018).Article 
CAS 

Google Scholar 
Agostini, S. et al. The effects of thermal and high-CO2 stresses on the metabolism and surrounding microenvironment of the coral Galaxea fascicularis. C. R. Biol. 336, 384–391 (2013).Article 
CAS 

Google Scholar 
Reynaud, S. et al. Interacting effects of CO2 partial pressure and temperature on photosynthesis and calcification in a scleractinian coral. Glob. Change Biol. 9, 1660–1668 (2003).Article 

Google Scholar 
Klein, S. G. et al. Projecting coral responses to intensifying marine heatwaves under ocean acidification. Glob. Change Biol. 28, 1753–1765 (2022).Article 
CAS 

Google Scholar 
Colombo-Pallotta, M. F., Rodríguez-Román, A. & Iglesias-Prieto, R. Calcification in bleached and unbleached Montastraea faveolata: evaluating the role of oxygen and glycerol. Coral Reefs 29, 899–907 (2010).Article 

Google Scholar 
Holcomb, M., Tambutte, E., Allemand, D. & Tambutte, S. Light enhanced calcification in Stylophora pistillata: effects of glucose, glycerol and oxygen. PeerJ 2, e375 (2014).Article 

Google Scholar 
Herfort, L., Thake, B. & Taubner, I. Bicarbonate stimulation of calcification and photosynthesis in two hermatypic corals. J. Phycol. 44, 91–98 (2008).Article 
CAS 

Google Scholar 
Tremblay, P., Fine, M., Maguer, J. F., Grover, R. & Ferrier-Pagès, C. Photosynthate translocation increases in response to low seawater pH in a coral–dinoflagellate symbiosis. Biogeosciences 10, 3997–4007 (2013).Article 

Google Scholar 
Briggs, A. A. & Carpenter, R. C. Contrasting responses of photosynthesis and photochemical efficiency to ocean acidification under different light environments in a calcifying alga. Sci. Rep. 9, 3986 (2019).Suggett, D. J. et al. Light availability determines susceptibility of reef building corals to ocean acidification. Coral Reefs 32, 327–337 (2013).Article 

Google Scholar 
IPCC. Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 747–845 (2007).IPCC. Climate change 2021: The physical science basis. Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (2021).Wall, C. B., Fan, T. Y. & Edmunds, P. J. Ocean acidification has no effect on thermal bleaching in the coral Seriatopora caliendrum. Coral Reefs 33, 119–130 (2014).Article 

Google Scholar 
Kuffner, I. B., Andersson, A. J., Jokiel, P. L., Rodgers, K. S. & Mackenzie, F. T. Decreased abundance of crustose coralline algae due to ocean acidification. Nat. Geosci. 1, 114–117 (2008).Article 
CAS 

Google Scholar 
LaJeunesse, T. C. et al. Systematic revision of Symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580 (2018). e6.Article 
CAS 

Google Scholar 
Kemp, D. W. et al. Spatially distinct and regionally endemic Symbiodinium assemblages in the threatened Caribbean reef-building coral Orbicella faveolata. Coral Reefs 34, 535–547 (2015).Article 

Google Scholar 
Enríquez, S., Méndez, E. R., Hoegh-Guldberg, O. & Iglesias-Prieto, R. Key functional role of the optical properties of coral skeletons in coral ecology and evolution. Proc. Biol. Sci. 284, 20161667 (2017).Enríquez, S., Méndez, E. R. & Iglesias-Prieto, R. Multiple scattering on coral skeletons enhances light absorption by symbiotic algae. Limnol. Oceanogr. 50, 1025–1032 (2005).Article 

Google Scholar 
Skirving, W. et al. Remote sensing of coral bleaching using temperature and light: progress towards an operational algorithm. Remote Sens 10, 18 (2017).Article 

Google Scholar 
Warner, M. E., LaJeunesse, T. C., Robison, J. D. & Thur, R. M. The ecological distribution and comparative photobiology of symbiotic dinoflagellates from reef corals in Belize: Potential implications for coral bleaching. Limnol. Oceanogr. 51, 1887–1897 (2006).Article 

Google Scholar 
Krämer, W., Caamaño-Ricken, I., Richter, C. & Bischof, K. Dynamic regulation of photoprotection determines thermal tolerance of two phylotypes of Symbiodinium clade A at two photon flux densities. Photochem. Photobio. 88, 398–413 (2012).Article 

Google Scholar 
Wall, C. B., Mason, R. A. B., Ellis, W. R., Cunning, R. & Gates, R. D. Elevated pCO2 affects tissue biomass composition, but not calcification, in a reef coral under two light regimes. R. Soc. Open Sci. 4, 170683 (2017).Article 
CAS 

Google Scholar 
Baghdasarian, G. et al. Effects of temperature and pCO2 on population regulation of Symbiodinium spp. in a tropical reef coral. Biol. Bull. 232, 123–139 (2017).Article 

Google Scholar 
Cornwall, C. E. et al. Resistance of corals and coralline algae to ocean acidification: physiological control of calcification under natural pH variability. Proc. R. Soc. B Biol. Sci. 285, 20181168 (2018).Article 

Google Scholar 
DeCarlo, T. M., Comeau, S., Cornwall, C. E. & McCulloch, M. T. Coral resistance to ocean acidification linked to increased calcium at the site of calcification. Proc. R. Soc. B Biol. Sci. 285, 20180564 (2018).Article 

Google Scholar 
Davies, S. W., Marchetti, A., Ries, J. B. & Castillo, K. D. Thermal and pCO2 stress elicit divergent transcriptomic responses in a resilient coral. Front. Mar. Sci. 3, 112 (2016).Article 

Google Scholar 
Hernansanz-Agustín, P. & Enríquez, J. A. Generation of reactive oxygen species by mitochondria. Antioxidants 10, 415 (2021).Article 

Google Scholar 
Acín-Pérez, R. et al. ROS-triggered phosphorylation of complex II by Fgr kinase regulates cellular adaptation to fuel use. Cell Metab. 19, 1020–1033 (2014).Article 

Google Scholar 
Burris, J. E., Porter, J. W. & Laing, W. A. Effects of carbon dioxide concentration on coral photosynthesis. Mar. Biol. 75, 113–116 (1983).Article 
CAS 

Google Scholar 
Muscatine, L., Falkowski, P. G., Dubinsky, Z., Cook, P. A. & McCloskey, L. R. The effect of external nutrient resources on the population dynamics of zooxanthellae in a reef coral. Proc. R. Soc. Lond. B Biol. Sci. 236, 311–324 (1989).Article 

Google Scholar 
Goiran, C., Al-Moghrabi, S., Allemand, D. & Jaubert, J. Inorganic carbon uptake for photosynthesis by the symbiotic coral/dinoflagellate association I. Photosynthetic performances of symbionts and dependence on sea water bicarbonate. J. Exp. Mar. Biol. Ecol. 199, 207–225 (1996).Article 
CAS 

Google Scholar 
Buxton, L., Badger, M. & Ralph, P. Effects of moderate heat stress and dissolved inorganic carbon concentration on photosynthesis and respiration of Symbiodinium sp. (Dinophyceae) in culture and in symbiosis. J. Phycol. 45, 357–365 (2009).Article 
CAS 

Google Scholar 
Lin, Z., Wang, L., Chen, M. & Chen, J. The acute transcriptomic response of coral-algae interactions to pH fluctuation. Mar. Genomics 42, 32–40 (2018).Article 

Google Scholar 
Ziegler, M. et al. Integrating environmental variability to broaden the research on coral responses to future ocean conditions. Glob. Change Biol. 27, 5532–5546 (2021).Article 
CAS 

Google Scholar 
Cornwall, C. E. et al. Global declines in coral reef calcium carbonate production under ocean acidification and warming. Proc. Natl Acad. Sci. 118, e2015265118 (2021).Article 
CAS 

Google Scholar 
Eyre, B. D. et al. Coral reefs will transition to net dissolving before end of century. Science 359, 908–911 (2018).Article 
CAS 

Google Scholar 
Cyronak, T. & Eyre, B. D. The synergistic effects of ocean acidification and organic metabolism on calcium carbonate (CaCO3) dissolution in coral reef sediments. Mar. Chem. 183, 1–12 (2016).Article 
CAS 

Google Scholar 
Eyre, B. D., Andersson, A. J. & Cyronak, T. Benthic coral reef calcium carbonate dissolution in an acidifying ocean. Nat. Clim. Change 4, 969–976 (2014).Article 
CAS 

Google Scholar 
Bedwell-Ivers, H. E. et al. The role of in hospite zooxanthellae photophysiology and reef chemistry on elevated pCO2 effects in two branching Caribbean corals: Acropora cervicornis and Porites divaricata. ICES J. Mar. Sci. 74, 1103–1112 (2016).Article 

Google Scholar 
Pierrot, D., Lewis, E. & Wallace, D. W. R. MS excel program developed for CO2 system calculations (2006).Cayabyab, N. M. & Enríquez, S. Leaf photoacclimatory responses of the tropical seagrass Thalassia testudinum under mesocosm conditions: a mechanistic scaling-up study. N. Phytol. 176, 108–123 (2007).Article 

Google Scholar 
Smith, S. V. & Kinsey, D. W. In Coral Reefs: Research Methods (eds. Stoddart, D. R. & Johannes, R. E.) 469–484 (UNESCO, 1978).Yao, W. & Byrne, R. H. Simplified seawater alkalinity analysis—application to the potentiometric titration of the total alkalinity and carbonate content in sea water. Deep Sea Res. Part Oceanogr. Res. Pap. 45, 1383–1392 (1998).Article 
CAS 

Google Scholar 
Vasquez-Elizondo, R. M. et al. Absorptance determinations on multicellular tissues. Photosynth. Res. 132, 311–324 (2017).Article 
CAS 

Google Scholar 
Whitaker, J. R. & Granum, P. E. An absolute method for protein determination based on the difference in absorbance at 235 and 280 nm. Anal. Biochem. 109, 156–159 (1980).Article 
CAS 

Google Scholar 
Iglesias-Prieto, R., Matta, J. L., Robins, W. A. & Trench, R. K. Photosynthetic response to elevated temperature in the symbiotic dinoflagellate Symbiodinium microadriaticum in culture. Proc. Natl Acad. Sci. USA 89, 10302–10305 (1992).Article 
CAS 

Google Scholar 
Jeffrey, S. W. & Humphrey, G. F. New spectrophotometric equations for determining chlorophyll a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochem. Physiol. Pflanz. 167, 191–194 (1975).Article 
CAS 

Google Scholar  More

Biskaborn, B. K. et al. Permafrost is warming at a global scale. Nat. Commun. 10, 264 (2019).Article 
ADS 

Google Scholar 
Murton, J. B. What and where are periglacial landscapes? Permaf. Periglac. Process. 32, 186–212 (2021).Article 

Google Scholar 
Woodcroft, B. J. et al. Genome-centric view of carbon processing in thawing permafrost. Nature 560, 49–54 (2018).Article 
ADS 
CAS 

Google Scholar 
Reyes, F. & Lougheed, V. L. Rapid nutrient release from permafrost thaw in Arctic aquatic ecosystems. Arct. Antarct. Alp. Res. 47, 35–48 (2015).Article 

Google Scholar 
Fouché, J., Christiansen, C. T., Lafrenière, M. J., Grogan, P. & Lamoureux, S. F. Canadian permafrost stores large pools of ammonium and optically distinct dissolved organic matter. Nat. Commun. 11, 4500 (2020).Article 
ADS 

Google Scholar 
Alley, N. F., Hore, S. B. & Frakes, L. A. Glaciations at high-latitude Southern Australia during the Early Cretaceous. Aust. J. Earth Sci. 67, 1045–1095 (2020).Article 
ADS 

Google Scholar 
Hore, S. B., Hill, S. M. & Alley, N. F. Early Cretaceous glacial environment and paleosurface evolution within the Mount Painter Inlier, northern Flinders Ranges, South Australia. Aust. J. Earth Sci. 67, 1117–1160 (2020).Article 
ADS 
CAS 

Google Scholar 
Rodríguez-López, J. P. et al. Glacial dropstones in the western Tethys during the late Aptian–early Albian cold snap: Palaeoclimate and palaeogeographic implications for the mid-Cretaceous. Palaeogeogr. Palaeoclimatol. Palaeoecol. 452, 11–27 (2016).Article 

Google Scholar 
Schneider, S. et al. Macrofauna and biostratigraphy of the Rollrock Section, northern Ellesmere Island, Canadian Arctic Islands e a comprehensive high latitude archive of the Jurassic–Cretaceous transition. Cret. Res. 114, 104508 (2020).Article 

Google Scholar 
Jeans, C. V. & Platten, I. M. The erratic rocks of the Upper Cretaceous Chalk of England: how did they get there, ice transport or other means? Acta Geol. Pol. 71, 287–304 (2021).
Google Scholar 
Wu, C. & Rodríguez-López, J. P. Cryospheric processes in Quaternary and Cretaceous hyper-arid oases. Sedimentology 68, 755–770 (2021).Article 

Google Scholar 
Grasby, S. E., McCune, G. E., Beauchamp, B. & Galloway, J. M. Lower Cretaceous cold snaps led to widespread glendonite occurrences in the Sverdrup Basin, Canadian High Arctic. GSA Bull. 129, 771–787 (2017).Article 
CAS 

Google Scholar 
Galloway, J. M. et al. Finding the VOICE: organic carbon isotope chemostratigraphy of the Late Jurassic–Early Cretaceous of Arctic Canada. Geol. Mag. 1–15 https://doi.org/10.1017/S0016756819001316 (2019).Rogov, M. et al. Database of global glendonite and ikaite records throughout the Phanerozoic. Earth Syst. Sci. Data 13, 343–356 (2021).Article 
ADS 

Google Scholar 
Price, G. D. The evidence and implications of polar ice during the Mesozoic. Earth–Sci. Rev. 48, 183–210 (1999).Article 
ADS 

Google Scholar 
Savidge, R. A. Evidence of early glaciation of southeastern Beringia. Can. J. Earth Sci. 57, 199–226 (2020).Article 
ADS 

Google Scholar 
Wang, Y. et al. Relict sand wedges suggest a high altitude and cold temperature during the Early Cretaceous in the Ordos Basin, North China. Int. Geol. Rev. https://doi.org/10.1080/00206814.2022.2081938 (2022).Nelson, D. A., Cottle, J. M., Bindeman, I. N. & Camacho, A. Ultra-depleted hydrogen isotopes in hydrated glass record Late Cretaceous glaciation in Antarctica. Nat. Commun. 13, 5209 (2022).Article 
ADS 
CAS 

Google Scholar 
Yang, W.-B. et al. Isotopic evidence for continental ice sheet in mid-latitude region in the supergreenhouse Early Cretaceous. Sci. Rep. 3, 2732 (2013).Article 

Google Scholar 
Gao, T. et al. Accelerating permafrost collapse on the eastern Tibetan Plateau. Environ. Res. Lett. 16, 054023 (2021).Article 
ADS 

Google Scholar 
Huang, Y. B. The origin and evolution of the desert in southern Ordos in early Cretaceous: Constraint from Magnetostratigraphy of Zhidan Group and magnetic susceptibility of its sediment. Doctoral Dissertation. Lanzhou University (2010).Ma, J. Sedimentary Basin Analysis of the Cretaceous Ancient Desert in the Ordos Basin. Master’s thesis, China University of Geosciences (2020).Wu, C. H., Rodríguez-López, J. P. & Santosh, M. Plateau archives of lithosphere dynamics, cryosphere and paleoclimate: the formation of Cretaceous desert basins in east Asia. Geosci. Front. 13, 101454 (2022).Article 
CAS 

Google Scholar 
Zhu, R. X., Chen, L., Wu, F. Y. & Liu, J. L. Timing, scale and mechanism of the destruction of the North China Craton. Sci. China Earth Sci. 54, 789–797 (2011).Article 
ADS 
CAS 

Google Scholar 
Rodríguez-López, J. P., Clemmensen, L. B., Lancaster, N., Mountney, N. P. & Veiga, G. D. Archean to Recent aeolian sand systems and their preserved successions: current understanding and way forward. Sedimentology 61, 1487–1534 (2014).Article 

Google Scholar 
Murton, J. B. in Encyclopedia of Quaternary Science Vol. 3 (eds Elias, S. A. & Mock, C. J.) 436–451 (Elsevier, Amsterdam, 2013).Rodríguez-López, J. P., Van Vliet-Lanöe, B., López-Martínez, J. & Martín-García, R. Scouring by rafted ice and cryogenic pattern ground preserved in a Palaeoproterozoic equatorial proglacial lagoon succession, eastern India, Nuna supercontinent. Mar. Pet. Geol. 123, 104766 (2021).Article 

Google Scholar 
Murton, J. B., Worsley, P. & Gozdzik, J. Sand veins and wedges in cold aeolian environments. Quat. Sci. Rev. 19, 899–922 (2000).Article 
ADS 

Google Scholar 
Kovács, J., Fábián, S. A., Schweitzer, F. & Varga, G. A relict sand-wedge polygon site in north-central Hungary. Permafr. Periglac. Process. 18, 379–384 (2007).Article 

Google Scholar 
Fábián, S. Á. et al. Distribution of relict permafrost features in the Pannonian Basin, Hungary. Boreas 43, 722–732 (2014).Article 

Google Scholar 
Williams, G. E. Proterozoic (pre-Ediacaran) glaciation and the high obliquity, low-latitude ice, strong seasonality (HOLIST) hypothesis: principles and tests. Earth–Sci. Rev. 87, 61–93 (2008).Article 
ADS 

Google Scholar 
Williams, G. E., Schmidt, P. W. & Young, G. M. Strongly seasonal Proterozoic glacial climate in low palaeolatitudes: radically different climate system on the pre-Ediacaran Earth. Geosci. Front. 7, 555–571 (2016).Article 

Google Scholar 
Van Vliet-Lanoë, B. Deformations in the active layer related with ice/soil wedge growth and decay in present day Arctic. Paleoclimate implications. Ann. Soc. Géol. Nord. 13, 81–95 (2005).
Google Scholar 
Remillard, A. M. et al. Chronology and palaeoenvironmental implications of the ice-wedge pseudomorphs and composite wedge casts on the Magdalen Islands (eastern Canada). Boreas 44, 658–675 (2015).Article 

Google Scholar 
Murton, J. B. Thermokarst sediments and sedimentary structures, Tuktoyaktuk Coastlands, western Arctic Canada. Glob. Planet. Change 28, 175–192 (2001).Article 
ADS 

Google Scholar 
Harris, C., Murton, J. B. & Davies, M. C. R. An analysis of mechanisms of ice-wedge casting based on geotechnical centrifuge modelling. Geomorphology 71, 328–343 (2005).Article 
ADS 

Google Scholar 
Houmark-Nielsen, M. et al. Early and Middle Valdaian glaciations, ice-dammed lakes and periglacial interstadials in northwest Russia: new evidence from the Pyoza River area. Glob. Planet. Change 31, 215–237 (2001).Article 
ADS 

Google Scholar 
Murton, J. B. & Kolstrup, E. Ice-wedge casts as indicators of palaeotemperatures: precise proxy or wishful thinking? Prog. Phys. Geogr. 27, 155–170 (2003).Article 

Google Scholar 
Harry, D. G. & Gozdzik, J. S. Ice wedges: growth, thaw transformation, and palaeoenvironmental significance. J. Quat. Sci. 3, 39–55 (1988).Article 

Google Scholar 
Wolfe, S. A., Morse, P. D., Neudorf, C. M., Kokelj, S. V., Lian, O. B. & O’Neill, H. B. Contemporary sand wedge development in seasonally frozen ground and paleoenvironmental implications. Geomorphology 308, 215–229 (2018).Article 
ADS 

Google Scholar 
Murton, J. B. & Bateman, M. D. Syngenetic sand veins and anti-syngenetic sand wedges, Tuktoyaktuk Coastlands, western Arctic Canada. Permafr. Periglac. Process. 18, 33–47 (2007).Article 

Google Scholar 
Obu, J., Westermann, S., Kääb, A., & Bartsch, A. Ground Temperature Map, 2000–2016, Northern Hemisphere Permafrost (Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, 2018)Obu, J. et al. Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale. Earth–Sci. Rev. 193, 299–316 (2019).Article 
ADS 

Google Scholar 
Hock, R. et al. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (eds Pörtner, H.-O. et al.) 131–202 (Cambridge University Press, Cambridge, UK and New York, NY, USA, 2019).Mackay, J. R. The origin of hummocks, western arctic coast, Canada. Can. J. Earth Sci. 17, 996–1006 (1980).Article 
ADS 

Google Scholar 
Kokelj, S. V., Burn, C. R. & Tarnocai, C. The structure and dynamics of earth hummocks in the subarctic forest near Inuvik, Northwest Territories, Canada. Arct. Antarct. Alp. Res. 39, 99–109 (2007).Article 

Google Scholar 
Rodríguez-López, J. P., Meléndez, N., de Boer, P. L., Soria, A. R. & Liesa, C. L. Spatial variability of multicontrolled aeolian supersurfaces in central-erg and marine erg-margin systems. Aeolian Res. 11, 141–154 (2013).Article 
ADS 

Google Scholar 
Lunt, D. J. et al. Palaeogeographic controls on climate and proxy interpretation. Clim. Past 12, 1181–1198 (2016).Article 

Google Scholar 
Cheng, G., Bai, Y. & Sun, Y. Paleomagnetic study on the tectonic evolution of the Ordos Block, North China. Seismol. Geol. 10, 81–87 (1988).
Google Scholar 
Zheng, Z. et al. The apparent polar wander path for the North China Block since the Jurassic. Geophys. J. Int. 104, 29–40 (1991).Article 
ADS 

Google Scholar 
Malinverno, A., Hildebrandt, J., Tominaga, M. & Channell, J. E. T. M-sequence geomagnetic polarity time scale (MHTC12) that steadies global spreading rates and incorporates astrochronology constraints. J. Geophys. Res. 117, B06104 (2012).ADS 

Google Scholar 
Zachos, J. C., Shackleton, N. J., Revenaugh, J. S., Pälike, H. & Flower, B. P. Climate response to orbital forcing across the Oligocene–Miocene boundary. Science 292, 274–278 (2001).Article 
ADS 
CAS 

Google Scholar 
Li, M. et al. Astronomical tuning of the end-Permian extinction and the Early Triassic Epoch of South China and Germany. Earth Planet. Sci. Lett. 441, 10–25 (2016).Article 
ADS 
CAS 

Google Scholar 
Westall, F. The nature of fossil bacteria: a guide to the search for extraterrestial live. J. Geophys. Res. 104, 437–16,451 (1999).
Google Scholar 
Yang, H., Chen, Z.-Q. & Papineau, D. Cyanobacterial spheroids and other biosignatures from microdigitate stromatolites of Mesoproterozoic Wumishan Formation in Jixian, North China. Precambrian Res. 368, 106496 (2022).Article 
ADS 
CAS 

Google Scholar 
Kremer, B., Kazmierczak, J., Łukomska-Kowalczyk, M. & Kempe, S. Calcification and silicification: fossilization potential of cyanobacteria from stromatolites of Niuafo’ou’s caldera lakes (Tonga) and implications for the early fossil record. Astrobiology 12, 535–548 (2012).Article 
ADS 
CAS 

Google Scholar 
Astafieva M. M. et al. Fossil Bacteria and Other Microorganisms in Terrestrial Rocks and Astromaterials (Paleontological Institute Russian Academy of Science, Moscow, 2011).Rozanov, A. Y. & Zavarzin, G. A. Bacterial paleontology. Vestn. Akad. Med. Nauk 67, 241–245 (1997).
Google Scholar 
Perez-Mon, C., Stierli, B., Plötze, M. & Frey, B. Fast and persistent responses of alpine permafrost microbial communities to in situ warming. Sci. Total Environ. 807, 150–720 (2022).Article 

Google Scholar 
Rivkina, E. et al. Earth’s perennially frozen environments as a model of cryogenic planet ecosystems. Permafr. Periglac. Process. 29, 246–256 (2018).Article 

Google Scholar 
Vishnivetskaya, T. A. et al. Insights into community of photosynthetic microorganisms from permafrost. FEMS Microbiol. Ecol. 96, fiaa229 (2020).Article 
CAS 

Google Scholar 
Hultman, J. et al. Multi-omics of permafrost, active layer and thermokarst bog soil microbiomes. Nature 521, 208–212 (2015).Article 
ADS 
CAS 

Google Scholar 
Choe, Y. H. et al. Comparing rock-inhabiting microbial communities in different rock types from a high arctic polar desert. FEMS Microbiol. Ecol. 94, fiy070 (2018).ADS 

Google Scholar 
Wu, X. et al. Comparative metagenomics of the active layer and permafrost from low-carbon soil in the Canadian High Arctic. Environ. Sci. Technol. 55, 12683–12693 (2021).Article 
ADS 
CAS 

Google Scholar 
Vickers, M. L. et al. The duration and magnitude of Cretaceous cold events: evidence from the northern high latitudes. Geol. Soc. Am. Bull. 131, 1979–1994 (2019).Article 
ADS 
CAS 

Google Scholar 
Lehmann, J. in Ammonoid Palaeobiology: From Macroevolution to Palaeogeography (eds Klug, C. De Baets, K., Kruta I. & Mapes, R. H.) 403–429 (Springer, Amsterdam, 2015).Keller, M. A. & Macquaker, J. H. S. in Studies by the U.S. Geological Survey in Alaska: US Geological Survey Professional Paper 1814-B Vol. 15 (ed Dumoulin, J. A.) 1–35 (US Geological Survey, US Department of The Interior, Reston, 2015).Cavalheiro, L. et al. Impact of global cooling on Early Cretaceous high pCO2 world during the Weissert Event. Nat. Commun. 12, 5411 (2021).Article 
ADS 
CAS 

Google Scholar 
McArthur, J. M. et al. Palaeotemperatures, polar ice-volume, and isotope stratigraphy (Mg/Ca, d18O, d13C, 87Sr/86Sr): the Early Cretaceous (Berriasian, Valanginian, Hauterivian). Palaeogeogr. Palaeoclimatol. Palaeoecol. 248, 391–430 (2007).Article 

Google Scholar 
Lini, A., Weissert, H. & Erba, E. The Valanginian carbon isotope event: a first episode of greenhouse climate conditions during the Cretaceous. Terra Nova 4, 374–384 (1992).Article 
ADS 

Google Scholar 
Li, X. et al. Carbon isotope signatures of pedogenic carbonates from SE China: rapid atmospheric pCO2 changes during middle–late Early Cretaceous time. Geol. Mag. 151, 830–849 (2014).Article 
ADS 
CAS 

Google Scholar 
O’Brien, Ch. L. et al. Cretaceous sea-surface temperature evolution: constraints from TEX86 and planktonic foraminiferal oxygen isotopes. Earth–Sci. Rev. 172, 224–247 (2017).Article 
ADS 

Google Scholar 
Price, G. D. et al. A high-resolution Belemnite geochemical analysis of early Cretaceous (Valanginian–Hauterivian) environmental and climatic perturbations. Geochem. Geophys. Geosyst. 19, 3832–3843 (2018).Article 
CAS 

Google Scholar 
Turetsky, M. R. et al. Carbon release through abrupt permafrost thaw. Nat. Geosci. 13, 138–143 (2020).Article 
ADS 
CAS 

Google Scholar 
Van der Kolk, D. A., Whalen, M. T., Wartes, M. A., Newberry, R. J. & McCarthy, P. in Arctic to the Cordillera: Unlocking the Potential. American Association of Petroleum Geologists Pacific Section Meeting, May 8–11, Anchorage, AK, USA, Search and Discovery Article 90125 (American Association of Petroleum Geologists, 2011).Walter Anthony, K. M. et al. 21st-century modeled permafrost carbon emissions accelerated by abrupt thaw beneath lakes. Nat. Commun. 9, 3262 (2018).Article 
ADS 

Google Scholar 
Cheng, F. et al. Alpine permafrost could account for a quarter of thawed carbon based on Plio-Pleistocene palaeoclimate analogue. Nat. Commun. 13, 1329 (2022).Article 
ADS 
CAS 

Google Scholar 
Brouillette, M. How microbes in permafrost could trigger a massive carbon bomb. Nature 591, 360–362 (2021).Article 
ADS 
CAS 

Google Scholar 
Murton, J. B. in Climate Change, Observed Impacts on Planet Earth, 3rd edn (ed Letcher, T.) 281–326 (Elsevier, Amsterdam, 2021).Schnyder, J., Ruffell, A., Deconinck, J. F. & Baudin, F. Conjunctive use of spectral gamma-ray logs and clay mineralogy in defining late Jurassic–early Cretaceous palaeoclimate change (Dorset, UK). Palaeogeogr. Palaeoclimatol. Palaeoecol. 229, 303–320 (2006).Article 

Google Scholar 
Li, M. et al. Astrochronology of the Anisian stage (Middle Triassic) at the guandao reference section, south china. Earth Planet. Sci. Lett. 482, 591–606 (2018).Article 
ADS 
CAS 

Google Scholar 
Li, M. et al. Palaeoclimate proxies for cyclostratigraphy: comparative analysis using a Lower Triassic marine section in South China. Earth–Sci. Rev. 189, 125–146 (2019).Article 
ADS 
CAS 

Google Scholar 
Li, M., Hinnov, L. & Kump, L. Acycle: time–series analysis software for palaeoclimate research and education. Comput. Geosci. 127, 12–22 (2019).Article 
ADS 
CAS 

Google Scholar 
Laskar, J. et al. A long–term numerical solution for the insolation quantities of the Earth. Astron. Astrophys. 428, 261–285 (2004).Article 
ADS 

Google Scholar  More

IPCC. Summary for Policymakers. In (Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield, eds) Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. In Press (2018).Malhi, Y. et al. Climate change and ecosystems: Threats, opportunities and solutions. Philos. Trans. R. Soc. B Biol. Sci. 375(1794), 20190104. https://doi.org/10.1098/rstb.2019.0104 (2020).Article 
CAS 

Google Scholar 
McElwee, P. Climate change and biodiversity loss. Curr. Hist. 120(829), 295–300. https://doi.org/10.1525/curh.2021.120.829.295 (2021).Article 

Google Scholar 
Dickinson, M. G., Orme, C. D. L., Suttle, K. B. & Mace, G. M. Separating sensitivity from exposure in assessing extinction risk from climate change. Sci. Rep. 4(1), 6898. https://doi.org/10.1038/srep06898 (2015).Article 
CAS 

Google Scholar 
UNFCCC (United Nations Framework Convention on Climate Change). Global Warming Potentials http://unfccc.int/ghg_data/items/3825.php (2014).BelhadjSlimen, I., Chniter, M., Najar, T. & Ghram, A. Meta-analysis of some physiologic, metabolic and oxidative responses of sheep exposed to environmental heat stress. Livestock Sci. 229, 179–187. https://doi.org/10.1016/j.livsci.2019.09.026 (2019).Article 

Google Scholar 
Wojtas, K., Cwynar, P. & Kołacz, R. Effect of thermal stress on physiological and blood parameters in merino sheep. Bull. Vet. Inst. Pulawy 58(2), 283–288. https://doi.org/10.2478/bvip-2014-0043 (2014).Article 

Google Scholar 
Gavojdian, D., Cziszter, L. T., Budai, C. & Kusza, S. Effects of behavioral reactivity on production and reproduction traits in Dorper sheep breed. J. Vet. Behav. 10(4), 365–368. https://doi.org/10.1016/j.jveb.2015.03.012 (2015).Article 

Google Scholar 
Mehaba, N., Coloma-Garcia, W., Such, X., Caja, G. & Salama, A. A. K. Heat stress affects some physiological and productive variables and alters metabolism in dairy ewes. J. Dairy Sci. 104(1), 1099–1110. https://doi.org/10.3168/jds.2020-18943 (2021).Article 
CAS 

Google Scholar 
Ramón, M., Díaz, C., Pérez-Guzman, M. D. & Carabaño, M. J. Effect of exposure to adverse climatic conditions on production in Manchega dairy sheep. J. Dairy Sci. 99(7), 5764–6577. https://doi.org/10.3168/jds.2016-10909 (2016).Article 
CAS 

Google Scholar 
Mahjoubi, E. et al. The effect of cyclical and severe heat stress on growth performance and metabolism in Afshari lambs1. J. Anim. Sci. 93(4), 1632–1640. https://doi.org/10.2527/jas.2014-8641 (2015).Article 
CAS 

Google Scholar 
dos Hamilton, T. R. S. et al. Evaluation of lasting effects of heat stress on sperm profile and oxidative status of ram semen and epididymal sperm. Oxid. Med. Cell. Longev. 1–12, 2016. https://doi.org/10.1155/2016/1687657 (2016).Article 
CAS 

Google Scholar 
Romo-Barron, C. B. et al. Impact of heat stress on the reproductive performance and physiology of ewes: A systematic review and meta-analyses. Int. J. Biometeorol. 63(7), 949–962. https://doi.org/10.1007/s00484-019-01707-z (2019).Article 
ADS 

Google Scholar 
Caroprese, M. et al. Glucocorticoid effects on sheep peripheral blood mononuclear cell proliferation and cytokine production under in vitro hyperthermia. J. Dairy Sci. 101(9), 8544–8551. https://doi.org/10.3168/jds.2018-14471 (2018).Article 
CAS 

Google Scholar 
Marcone, G., Kaart, T., Piirsalu, P. & Arney, D. R. Panting scores as a measure of heat stress evaluation in sheep with access and with no access to shade. Appl. Anim. Behav. Sci. 240, 105350. https://doi.org/10.1016/j.applanim.2021.105350 (2021).Article 

Google Scholar 
Van Wettere, W. H. E. J. et al. Review of the impact of heat stress on reproductive performance of sheep. J. Anim. Sci. Biotechnol. 12(1), 26. https://doi.org/10.1186/s40104-020-00537-z (2021).Article 

Google Scholar 
Belhadj Slimen, I., Najar, T., Ghram, A. & Abdrrabba, M. Heat stress effects on livestock: Molecular, cellular and metabolic aspects, a review. J. Anim. Physiol. Anim. Nutr. 100(3), 401–412. https://doi.org/10.1111/jpn.12379 (2016).Article 
CAS 

Google Scholar 
Guo, Z., Gao, S., Ouyang, J., Ma, L. & Bu, D. Impacts of heat stress-induced oxidative stress on the milk protein biosynthesis of dairy cows. Animals 11(3), 726. https://doi.org/10.3390/ani11030726 (2021).Article 

Google Scholar 
Liu, Z. et al. Heat stress in dairy cattle alters lipid composition of milk. Sci. Rep. 7(1), 961. https://doi.org/10.1038/s41598-017-01120-9 (2017).Article 
ADS 
CAS 

Google Scholar 
Krishnan, G. et al. Mitigation of the heat stress impact in Livestock reproduction. In Theriogenology (InTech, 2017).
Google Scholar 
Robertson, S. & Friend, M. Strategies to ameliorate heat stress effects on sheep reproduction. In Climate Change and Livestock Production: Recent Advances and Future Perspectives 175–183 (Springer, 2021). https://doi.org/10.1007/978-981-16-9836-1_15.Chapter 

Google Scholar 
Sawyer, G. & Narayan, E. J. A review on the influence of climate change on sheep reproduction. In Comparative Endocrinology of Animals (Intech Open, 2019). https://doi.org/10.5772/intechopen.86799.Chapter 

Google Scholar 
Maurya, V. P., Sejian, V., Kumar, D. & Naqvi, S. M. K. Biological ability of Malpura rams to counter heat stress challenges and its consequences on production performance in a semi-arid tropical environment. Biol. Rhythm. Res. 49(3), 479–493. https://doi.org/10.1080/09291016.2017.1381451 (2018).Article 

Google Scholar 
Shahat, A. M., Rizzoto, G. & Kastelic, J. P. Amelioration of heat stress-induced damage to testes and sperm quality. Theriogenology 158, 84–96. https://doi.org/10.1016/j.theriogenology.2020.08.034 (2020).Article 
CAS 

Google Scholar 
Singh, K. M. et al. Association of heat stress protein 90 and 70 gene polymorphism with adaptability traits in Indian sheep (Ovis aries). Cell Stress Chaperones 22(5), 675–684. https://doi.org/10.1007/s12192-017-0770-4 (2017).Article 
CAS 

Google Scholar 
Kim, E.-S. et al. Multiple genomic signatures of selection in goats and sheep indigenous to a hot arid environment. Heredity 116(3), 255–264. https://doi.org/10.1038/hdy.2015.94 (2016).Article 
CAS 

Google Scholar 
do Paim, T. P., Alves dos Santos, C., de Faria, D. A., Paiva, S. R. & McManus, C. Genomic selection signatures in Brazilian sheep breeds reared in a tropical environment. Livestock Sci. 258, 104865. https://doi.org/10.1016/j.livsci.2022.104865 (2022).Article 

Google Scholar 
Kusza, S. et al. Kompetitive Allele Specific PCR (KASPTM) genotyping of 48 polymorphisms at different caprine loci in French Alpine and Saanen goat breeds and their association with milk composition. PeerJ 6, e4416. https://doi.org/10.7717/peerj.4416 (2018).Article 
CAS 

Google Scholar 
Zhang, Y. et al. Technical note: Development and application of KASP assays for rapid screening of 8 genetic defects in Holstein cattle. J. Dairy Sci. 103(1), 619–624. https://doi.org/10.3168/jds.2019-16345 (2020).Article 
CAS 

Google Scholar 
Chaari, A. Molecular chaperones biochemistry and role in neurodegenerative diseases. Int. J. Biol. Macromol. 131, 396–411. https://doi.org/10.1016/j.ijbiomac.2019.02.148 (2019).Article 
CAS 

Google Scholar 
Tripathy, K., Sodhi, M., Kataria, R. S., Chopra, M. & Mukesh, M. In silico analysis of HSP70 gene family in bovine genome. Biochem. Genet. 59(1), 134–158. https://doi.org/10.1007/s10528-020-09994-7 (2021).Article 
CAS 

Google Scholar 
Rehman, S. et al. Genomic identification, evolution and sequence analysis of the heat-shock protein gene family in buffalo. Genes 11(11), 1388. https://doi.org/10.3390/genes11111388 (2020).Article 
CAS 

Google Scholar 
Huo, C. et al. Chronic heat stress negatively affects the immune functions of both spleens and intestinal mucosal system in pigs through the inhibition of apoptosis. Microbial Pathog. 136, 103672. https://doi.org/10.1016/j.micpath.2019.103672 (2019).Article 
CAS 

Google Scholar 
Morange, M. HSFs in development. In Molecular Chaperones in Health and Disease 153–169 (Springer, 2006). https://doi.org/10.1007/3-540-29717-0_7.Chapter 

Google Scholar 
Hoter, A., El-Sabban, M. & Naim, H. The HSP90 family: Structure, regulation, function, and implications in health and disease. Int. J. Mol. Sci. 19(9), 2560. https://doi.org/10.3390/ijms19092560 (2018).Article 
CAS 

Google Scholar 
Vanselow, J., Vernunft, A., Koczan, D., Spitschak, M. & Kuhla, B. Exposure of lactating dairy cows to acute pre-ovulatory heat stress affects granulosa cell-specific gene expression profiles in dominant follicles. PLoS One 11(8), e0160600. https://doi.org/10.1371/journal.pone.0160600 (2016).Article 
CAS 

Google Scholar 
Joy, A. et al. Resilience of small ruminants to climate change and increased environmental temperature: A review. Animals 10(5), 86. https://doi.org/10.3390/ani10050867 (2020).Article 

Google Scholar 
Saravanan, K. A. et al. Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds. Genomics 113(3), 955–963. https://doi.org/10.1016/j.ygeno.2021.02.009 (2021).Article 
CAS 

Google Scholar 
Singh, A. K., Upadhyay, R. C., Malakar, D., Kumar, S. & Singh, S. V. Effect of thermal stress on HSP70 expression in dermal fibroblast of zebu (Tharparkar) and crossbred (Karan-Fries) cattle. J. Therm. Biol 43, 46–53. https://doi.org/10.1016/j.jtherbio.2014.04.006 (2014).Article 
CAS 

Google Scholar 
Verma, N., Gupta, I. D., Verma, A., Kumar, R. & Das, R. Novel SNPs in HSPB8 gene and their association with heat tolerance traits in Sahiwal indigenous cattle. Trop. Anim. Health Prod. 48(1), 175–180. https://doi.org/10.1007/s11250-015-0938-9 (2016).Article 

Google Scholar 
Al-Thuwaini, T. M., Al-Shuhaib, M. B. S. & Hussein, Z. M. A novel T177P missense variant in the HSPA8 gene associated with the low tolerance of Awassi sheep to heat stress. Trop. Anim. Health Prod. 52(5), 2405–2416. https://doi.org/10.1007/s11250-020-02267-w (2020).Article 

Google Scholar 
Onasanya, G. O. et al. Heterozygous single-nucleotide polymorphism genotypes at heat shock protein 70 gene potentially influence thermo-tolerance among four Zebu breeds of Nigeria. Front. Genet. https://doi.org/10.3389/fgene.2021.642213 (2021).Article 

Google Scholar 
Pascal, C. Researches regarding quality of sheep skins obtained from Karakul from Botosani sheep. Biotechnol. Anim. Husband. 27(3), 1123–1130. https://doi.org/10.2298/BAH1103123P (2011).Article 

Google Scholar 
Kevorkian, S. E. M., Zǎuleţ, M., Manea, M. A., Georgescu, S. E. & Costache, M. Analysis of the ORF region of the prion protein gene in the Botosani Karakul sheep breed from Romania. Turk. J. Vet. Anim. Sci. 35(2), 105–109. https://doi.org/10.3906/vet-0909-124 (2011).Article 
CAS 

Google Scholar 
Kusza, S. et al. Mitochondrial DNA variability in Gyimesi Racka and Turcana sheep breeds. Acta Biochim. Pol. 62(2), 273–280. https://doi.org/10.18388/abp.2015_978 (2015).Article 
CAS 

Google Scholar 
Gavojdian, D. et al. Effects of using indigenous heritage sheep breeds in organic and low-input production systems on production efficiency and animal welfare in Romania. Landbauforschung Volkenrode 66(4), 290–297. https://doi.org/10.3220/LBF1483607712000 (2016).Article 

Google Scholar 
Gavojdian, D. et al. Reproduction efficiency and health traits in Dorper, White Dorper, and Tsigai sheep breeds under temperate European conditions. Asian Australas. J. Anim. Sci. 28(4), 599–603. https://doi.org/10.5713/ajas.14.0659 (2015).Article 
CAS 

Google Scholar 
Kusza, S. et al. The genetic variability of Hungarian Tsigai sheep. Archiv Tierzuch 53(3), 309–317 (2010).
Google Scholar 
Kusza, S. et al. Study of genetic differences among Slovak Tsigai populations using microsatellite markers. Czeh J. Anim. Sci. 54(10), 468–474. https://doi.org/10.17221/1670-CJAS (2009).Article 
CAS 

Google Scholar 
Marcos-Carcavilla, A. et al. Polymorphisms in the HSP90AA1 5′ flanking region are associated with scrapie incubation period in sheep. Cell Stress Chaperones 15(4), 343–349. https://doi.org/10.1007/s12192-009-0149-2 (2010).Article 
CAS 

Google Scholar 
Salces-Ortiz, J. et al. Looking for adaptive footprints in the HSP90AA1 ovine gene. BMC Evol. Biol. 15(1), 7. https://doi.org/10.1186/s12862-015-0280-x (2015).Article 
CAS 

Google Scholar 
Toscano, J. H. B. et al. Innate immune responses associated with resistance against Haemonchus contortus in Morada Nova Sheep. J. Immunol. Res. 2019, 1–10. https://doi.org/10.1155/2019/3562672 (2019).Article 
CAS 

Google Scholar 
Estrada-Reyes, Z. M. et al. Signatures of selection for resistance to Haemonchus contortus in sheep and goats. BMC Genom. 20(1), 735. https://doi.org/10.1186/s12864-019-6150-y (2019).Article 
CAS 

Google Scholar 
Caroprese, M., Bradford, B. J. & Rhoads, R. P. Editorial: Impact of climate change on immune responses in agricultural animals. Front. Vet. Sci. https://doi.org/10.3389/fvets.2021.732203 (2021).Article 

Google Scholar 
FAO/IAEA. Agriculture biotechnology laboratory—handbook of laboratory exercises. Seibersdorf: IAEA Laboratories, 18 (2004).Zsolnai, A. & Orbán, L. Accelerated separation of random complex DNA patterns in gels: Comparing the performance of discontinuous and continuous buffers. Electrophoresis 20(7), 1462–1468. https://doi.org/10.1002/(SICI)1522-2683(19990601)20:7%3c1462::AID-ELPS1462%3e3.0.CO;2-0 (1999).Article 
CAS 

Google Scholar 
Cavalcanti, L. C. G. et al. Genetic characterization of coat color genes in Brazilian Crioula sheep from a conservation nucleus. Pesq. Agrop. Brasil. 52(8), 615–622. https://doi.org/10.1590/s0100-204×2017000800007 (2017).Article 

Google Scholar 
Li, Y. et al. Heat stress-responsive transcriptome analysis in the liver tissue of Hu sheep. Genes 10(5), 395. https://doi.org/10.3390/genes10050395 (2019).Article 
CAS 

Google Scholar 
Younis, F. Expression pattern of heat shock protein genes in sheep. Mansoura Vet. Med. J. 21(1), 1–5. https://doi.org/10.35943/mvmj.2020.21.001 (2020).Article 

Google Scholar 
Yeh F. C., Boyle R., Yang R. C., Ye Z., Mao J. X. & Yeh D. POPGENE version 1.32. Computer program and documentation distributed by the author. http://www.ualberta.ca/∼fyeh/popgene.html (1999).Lê, S., Josse, J. & Husson, F. FactoMineR: A package for multivariate analysis. J. Stat. Softw. 25(1), 1–18. https://doi.org/10.18637/jss.v025.i01 (2008).Article 

Google Scholar 
Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer. https://ggplot2.tidyverse.org (2016) (ISBN 978-3-319-24277-4).R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2020). More

Lavelle, P., Blanchart, E., Martin, A., Spain, A. V. & Martin, S. Impact of soil fauna on the properties of soils in the humid tropics. In Myths and Science of Soils of the Tropics (eds Lal, R. & Sanchez, P.) 157–185 (Soil Science Society of America, 1992).
Google Scholar 
Eisenhauer, N. The action of an animal ecosystem engineer: Identification of the main mechanisms of earthworm impacts on soil microarthropods. Pedobiologia 53, 343–352 (2010).Article 

Google Scholar 
Eisenhauer, N. & Eisenhauer, E. The “intestines of the soil”: The taxonomic and functional diversity of earthworms—A review for young ecologists. Preprint at https://doi.org/10.32942/osf.io/tfm5y (2020).Gates, G. E. Burmese earthworms, an introduction to the systematics and biology of megadrile oligochaetes with special reference to South-east Asia. Trans. Amer. Phil. Soc. 62, 1–326. https://doi.org/10.2307/1006214 (1972).Article 

Google Scholar 
Blakemore, R. J. Origin and means of dispersal of cosmopolitan Pontodrilus litoralis (Oligocaheta: Megascolecidae). Eur. J. Soil Biol. 443, S3–S8. https://doi.org/10.1016/j.ejsobi.2007.08.041 (2007).Article 

Google Scholar 
Seesamut, T., Sutcharit, C., Jirapatrasilp, P., Chanabun, R. & Panha, S. Morphological and molecular evidence reveal a new species of the earthworm genus Pontodrilus Perrier, 1874 (Clitellata, Megascolecidae) from Thailand and Peninsular Malaysia. Zootaxa 4496, 218–237. https://doi.org/10.11646/zootaxa.4496.1.18 (2018).Article 

Google Scholar 
Seesamut, T., Jirapatrasilp, P., Chanabun, R., Oba, Y. & Panha, S. Size variation and geographical distribution of the luminous earthworm Pontodrilus litoralis (Grube, 1855) (Clitellata, Megascolecidae) in Southeast Asia and Japan. Zookeys 862, 23–43. https://doi.org/10.3897/zookeys.862.35727 (2019).Article 

Google Scholar 
Seesamut, T., Jirapatrasilp, P., Sutcharit, C., Tongkerd, P. & Panha, S. Mitochondrial genetic population structure and variation of the littoral earthworm Pontodrilus longissimus Seesamut and Panha, 2018 along the coast of Thailand. Eur. J. Soil Biol. 93, 103091. https://doi.org/10.1016/j.ejsobi.2019.103091 (2019).Article 

Google Scholar 
Attrill, M. J. A testable linear model for diversity trends in estuaries. J. Anim. Ecol. 71, 262–269. https://doi.org/10.1046/j.1365-2656.2002.00593.x (2002).Article 

Google Scholar 
McLusky, D. S. & Elliott, M. The Estuarine Ecosystem: Ecology, Threats and Management 3rd edn. (Oxford University Press, 2004).Book 

Google Scholar 
Telesh, I. V. & Khlebovich, V. V. Principal processes within the estuarine salinity gradient: A review. Mar. Pollut. Bull. 61, 149–155. https://doi.org/10.1016/j.marpolbul.2010.02.008 (2010).Article 
CAS 

Google Scholar 
Owojori, O. J. & Reinecke, A. J. Effects of natural (flooding and drought) and anthropogenic (copper and salinity) stressors on the earthworm Aporrectodea caliginosa under field conditions. Appl. Soil Ecol. 44, 156–163. https://doi.org/10.1016/j.apsoil.2009.11.006 (2010).Article 

Google Scholar 
Guzyte, G., Sujetoviene, G. & Zaltauskaite, J. Effects of salinity on earthworm (Eisenia fetida). Environ. Eng. 8, 111 (2011).
Google Scholar 
Ganapati, P. N. & Subba Rao, B. V. S. S. R. Salinity tolerance of a littoral oligochaete, Pontodrilus bermudensis Beddard. Proc. Ind. Nat. Sci. Acad. 38, 350–354 (1972).
Google Scholar 
Subba Rao, B. V. S. S. R. Volume regulation in a euryhaline oligochaete, Pontodrilus bermudensis Beddard. Proc. Indian Acad. Sci. 87, 339–347 (1978).Article 

Google Scholar 
Owojori, O. J., Reinecke, A. J. & Rozanov, A. B. Effects of salinity on partitioning, uptake and toxicity of zinc in the earthworm Eisenia fetida. Soil Biol. Biochem. 40, 2385–2393. https://doi.org/10.1016/j.soilbio.2008.05.019 (2008).Article 
CAS 

Google Scholar 
Seesamut, T. et al. Occurrence of bioluminescent and nonbioluminescent species in the littoral earthworm genus Pontodrilus. Sci. Rep. 11, 8407 (2021).Article 
CAS 

Google Scholar 
Sivinski, J. & Forrest, T. Luminous defense in an earthworm. Fla. Entomol. 66, 517 (1983).Article 

Google Scholar 
Verdes, A. & Gruber, D. F. Glowing worms: Biological, chemical, and functional diversity of bioluminescent annelids. Integr. Comp. Biol. 57, 18–32. https://doi.org/10.1093/icb/icx017 (2017).Article 
CAS 

Google Scholar 
Shimomura, O. & Yampolsky, I. Bioluminescence: Chemical Principles and Methods 3rd edn. (World Scientific, 2019).Book 

Google Scholar 
Easton, E. G. Earthworms (Oligochaeta) from islands of the south-western Pacific, and a note on two species from Papua New Guinea. N. Z. J. Zool. 11, 111–128. https://doi.org/10.1080/03014223.1984.10423750 (1984).Article 

Google Scholar 
Shen, H.-P., Tsai, S.-C. & Tsai, C.-F. Occurrence of the earthworms Pontodrilus litoralis (Grube, 1855), Metaphire houlleti (Perrier, 1872), and Eiseniella tetraedra (Savigny, 1826) from Taiwan. Taiwania 50, 11–21 (2005).
Google Scholar 
Satheeshkumar, P., Khan, A. B. & Senthilkumar, D. Annelida, Oligochaeta, Megascolecidae, Pontodrilus litoralis (Grupe, 1985): First record from Pondicherry mangroves, southeast coast of India. Int. J. Zool. Res. 7, 406–409. https://doi.org/10.3923/ijzr.2011.406.409 (2011).Article 

Google Scholar 
Nguyen, T. T., Nguyen, D. A., Tran, T. T. B. & Blakemore, R. J. A comprehensive checklist of earthworm species and subspecies from Vietnam (Annelida: Clitellata: Oligochaeta: Almidae, Eudrilidae, Glossoscolecidae, Lumbricidae, Megascolecidae, Moniligastridae, Ocnerodrilidae, Octochaetidae). Zootaxa 4140, 1–92. https://doi.org/10.11646/zootaxa.4140.1.1 (2016).Article 

Google Scholar 
Chen, S.-Y., Hsu, C.-H. & Soong, K. How to cross the sea: Testing the dispersal mechanisms of the cosmopolitan earthworm Pontodrilus litoralis. R. Soc. Open Sci. 8, 202297. https://doi.org/10.1098/rsos.202297 (2021).Article 
ADS 

Google Scholar 
Smyth, K. & Elliott, M. Effects of changing salinity on the ecology of the marine environment. In Stressors in the Marine Environment (eds Solan, M. & Whiteley, N. M.) 161–175 (Oxford University Press, 2016).Chapter 

Google Scholar 
Veiga, M. P. T., Gutierre, S. M. M., Castellano, G. C. & Freire, C. A. Tolerance of high and low salinity in the intertidal gastropod Stramonita brasiliensis (Muricidae): Behaviour and maintenance of tissue water content. J. Molluscan Stud. 82, 154–160. https://doi.org/10.1093/mollus/eyv044 (2016).Article 

Google Scholar 
Carley, W. W., Caracciolo, E. A. & Mason, R. T. Cell and coelomic fluid volume regulation in the earthworm Lumbricus terrestris. Comp. Biochem. Physiol. 74, 569–575 (1983).Article 

Google Scholar 
Sharif, F. et al. Salinity tolerance of earthworms and effects of salinity and vermi amendments on growth of Sorghum bicolor. Arch. Agron. Soil Sci. 62, 1169–1181. https://doi.org/10.1080/03650340.2015.1132838 (2016).Article 
CAS 

Google Scholar 
Wu, Z. et al. Effects of salinity on earthworms and the product during vermicomposting of kitchen wastes. Int. J. Environ. Res. Public Health 16, 4737. https://doi.org/10.3390/ijerph16234737 (2019).Article 
CAS 

Google Scholar 
Oglesby, L. C. Volume regulation in aquatic invertebrates. J. Exp. Zool. 215, 289–301 (1981).Article 
CAS 

Google Scholar 
Generlich, O. & Giere, O. Osmoregulation in two aquatic oligochaetes from habitats with different salinity and comparison to other annelids. Hydrobiologia 334, 251–261. https://doi.org/10.1007/BF00017375 (1996).Article 

Google Scholar 
Carregosa, V. et al. Tolerance of Venerupis philippinarum to salinity: Osmotic and metabolic aspects. Comp. Biochem. Physiol. A 171, 36–43. https://doi.org/10.1016/j.cbpa.2014.02.009 (2014).Article 
CAS 

Google Scholar 
Freitas, R. et al. The effects of salinity changes on the polychaete Diopatra neapolitana: Impacts on regenerative capacity and biochemical markers. Aquat. Toxicol. 163, 167–176. https://doi.org/10.1016/j.aquatox.2015.04.006 (2015).Article 
CAS 

Google Scholar 
Rivera-Ingraham, G. A. & Lignot, J. H. Osmoregulation, bioenergetics and oxidative stress in coastal marine invertebrates: Raising the questions for future research. J. Exp. Biol. 220, 1749–1760. https://doi.org/10.1242/jeb.135624 (2017).Article 

Google Scholar 
Munnoli, P. M. & Bhosle, S. Effect of soil cow dung proportion of vermicomposting. J. Sci. Ind. Res. 68, 57–60 (2009).
Google Scholar  More