Philippa Kaur

IPBES The IPBES Assessment Report on Land Degradation and Restoration (Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, 2018).Barlow, J. et al. Anthropogenic disturbance in tropical forests can double biodiversity loss from deforestation. Nature 535, 144–147 (2016).CAS 
Article 

Google Scholar 
The State of the World’s Forests 2020. Forests, Biodiversity and People (FAO and UNEP, 2020).Pendrill, F. et al. Agricultural and forestry trade drives large share of tropical deforestation emissions. Glob. Environ. Change 56, 1–10 (2019).Article 

Google Scholar 
Geist, H. J. & Lambin, E. F. What Drives Tropical Deforestation? LUCC Report Series 4 (LUCC International Project Office, 2001).Austin, K. G., González-Roglich, M., Schaffer-Smith, D., Schwantes, A. M. & Swenson, J. J. Trends in size of tropical deforestation events signal increasing dominance of industrial-scale drivers. Environ. Res. Lett. 12, 054009 (2017).Article 

Google Scholar 
Graesser, J., Ramankutty, N. & Coomes, O. T. Increasing expansion of large-scale crop production onto deforested land in sub-Andean South America. Environ. Res. Lett. 13, 084021 (2018).Article 

Google Scholar 
Meyfroidt, P. et al. Middle-range theories of land system change. Glob. Environ. Change 53, 52–67 (2018).Article 

Google Scholar 
Verburg, P. H. et al. Land system science and sustainable development of the Earth system: a global land project perspective. Anthropocene 12, 29–41 (2015).Article 

Google Scholar 
Václavík, T. et al. Investigating potential transferability of place-based research in land system science. Environ. Res. Lett. 11, 095002 (2016).Article 

Google Scholar 
Stocks, G., Seales, L., Paniagua, F., Maehr, E. & Bruna, E. M. The geographical and institutional distribution of ecological research in the tropics. Biotropica 40, 397–404 (2008).Article 

Google Scholar 
Schröder, J. M., Ávila Rodríguez, L. P. & Günter, S. Research trends: tropical dry forests: the neglected research agenda? For. Policy Econ. 122, 102333 (2021).Article 

Google Scholar 
Rodrigues, A. S. L. et al. Boom-and-bust development patterns across the Amazon deforestation frontier. Science 324, 1435–1437 (2009).CAS 
Article 

Google Scholar 
de Jong, E. B. P., Knippenberg, L. & Bakker, L. New frontiers: an enriched perspective on extraction frontiers in Indonesia. Crit. Asian Stud. 49, 330–348 (2017).Article 

Google Scholar 
Tyukavina, A. et al. Congo Basin forest loss dominated by increasing smallholder clearing. Sci. Adv. 4, eaat2993 (2018).Article 

Google Scholar 
Pacheco, P. et al. Deforestation Fronts: Drivers and Responses in a Changing World (WWF, 2021).Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).CAS 
Article 

Google Scholar 
Oberlack, C. et al. Archetype analysis in sustainability research: meanings, motivations, and evidence-based policy making. Ecol. Soc. https://doi.org/10.5751/ES-10747-240226 (2019).Sietz, D. et al. Archetype analysis in sustainability research: methodological portfolio and analytical frontiers. Ecol. Soc. https://doi.org/10.5751/ES-11103-240334 (2019).Václavík, T., Lautenbach, S., Kuemmerle, T. & Seppelt, R. Mapping global land system archetypes. Glob. Environ. Change 23, 1637–1647 (2013).Article 

Google Scholar 
Vallejos, M. et al. Social-ecological functional types: connecting people and ecosystems in the Argentine Chaco. Ecosystems 23, 471–484 (2020).Article 

Google Scholar 
Oberlack, C., Tejada, L., Messerli, P., Rist, S. & Giger, M. Sustainable livelihoods in the global land rush? Archetypes of livelihood vulnerability and sustainability potentials. Glob. Environ. Change 41, 153–171 (2016).Article 

Google Scholar 
Miles, L. et al. A global overview of the conservation status of tropical dry forests. J. Biogeogr. 33, 491–505 (2006).Article 

Google Scholar 
Pennington, R. T., Lehmann, C. E. R. & Rowland, L. M. Tropical savannas and dry forests. Curr. Biol. 28, R541–R545 (2018).CAS 
Article 

Google Scholar 
Ribeiro, N. S., Katerere, Y., Chirwa, P. W. & Grundy, I. M. in Miombo Woodlands in a Changing Environment: Securing the Resilience and Sustainability of People and Woodlands (eds Ribeiro, N. S. et al.) 1–8 (Springer, 2020).Murphy, B. P., Andersen, A. N. & Parr, C. L. The underestimated biodiversity of tropical grassy biomes. Philos. Trans. R. Soc. B 371, 20150319 (2016).Article 

Google Scholar 
Chidumayo, E. & Marunda, C. in The Dry Forests and Woodlands of Africa (eds Chidumayo, E. N. & Gumbo, D.) 1–9 (Earthscan, 2010).Gasparri, N. I. & Grau, H. R. Deforestation and fragmentation of Chaco dry forest in NW Argentina (1972–2007). For. Ecol. Manag. 258, 913–921 (2009).Article 

Google Scholar 
Miranda, J., Börner, J., Kalkuhl, M. & Soares-Filho, B. Land speculation and conservation policy leakage in Brazil. Environ. Res. Lett. 14, 045006 (2019).Article 

Google Scholar 
Ingalls, M. L., Meyfroidt, P., To, P. X., Kenney-Lazar, M. & Epprecht, M. The transboundary displacement of deforestation under REDD+: problematic intersections between the trade of forest-risk commodities and land grabbing in the Mekong region. Glob. Environ. Change 50, 255–267 (2018).Article 

Google Scholar 
Davis, K. F. et al. Tropical forest loss enhanced by large-scale land acquisitions. Nat. Geosci. 13, 482–488 (2020).CAS 
Article 

Google Scholar 
Ordway, E. M., Asner, G. P. & Lambin, E. F. Deforestation risk due to commodity crop expansion in sub-Saharan Africa. Environ. Res. Lett. 12, 044015 (2017).Article 

Google Scholar 
Vancutsem, C. et al. Long-term (1990–2019) monitoring of forest cover changes in the humid tropics. Sci. Adv. 7, eabe1603 (2021).Article 

Google Scholar 
Sunderland, T. et al. Global dry forests: a prologue. Int. For. Rev. 17, 1–9 (2015).
Google Scholar 
Grau, H. R. & Aide, M. Globalization and land-use transitions in Latin America. Ecol. Soc. https://doi.org/10.5751/es-02559-130216 (2008).le Polain de Waroux, Y. et al. Rents, actors, and the expansion of commodity frontiers in the Gran Chaco. Ann. Am. Assoc. Geogr. 108, 204–225 (2018).
Google Scholar 
Romero-Muñoz, A. et al. Fires scorching Bolivia’s Chiquitano forest. Science 366, 1082 (2019).Article 
CAS 

Google Scholar 
Hoang, N. T. & Kanemoto, K. Mapping the deforestation footprint of nations reveals growing threat to tropical forests. Nat. Ecol. Evol. 5, 845–853 (2021).Article 

Google Scholar 
Eigenbrod, F. et al. Identifying agricultural frontiers for modeling global cropland expansion. One Earth 3, 504–514 (2020).Article 

Google Scholar 
Nolte, C., le Polain de Waroux, Y., Munger, J., Reis, T. N. P. & Lambin, E. F. Conditions influencing the adoption of effective anti-deforestation policies in South America’s commodity frontiers. Glob. Environ. Change 43, 1–14 (2017).Article 

Google Scholar 
Volante, J. N. & Seghezzo, L. Can’t see the forest for the trees: can declining deforestation trends in the Argentinian Chaco region be ascribed to efficient law enforcement? Ecol. Econ. 146, 408–413 (2018).Article 

Google Scholar 
Chirwa, P. W. & Adeyemi, O. in Zero Hunger: Encyclopedia of the UN Sustainable Development Goals (eds Leal Filho, W. et al.) 1–15 (Springer, 2019).Pacheco, P. Actor and frontier types in the Brazilian Amazon: assessing interactions and outcomes associated with frontier expansion. Geoforum 43, 864–874 (2012).Article 

Google Scholar 
García, A. K., Meyfroidt, P., Abeygunawardane, D. & Sitoe, A. Waves and legacies: the making of an investment frontier in Niassa, Mozambique. Ecol. Soc. 27, 40 (2022).Leal, I. R., Da Silva, J. M. C., Tabarelli, M. & Lacher, T. E.Jr Changing the course of biodiversity conservation in the Caatinga of northeastern Brazil. Conserv. Biol. 19, 701–706 (2005).Article 

Google Scholar 
Osabuohien, E. S. & Karakara, A. A. in The Palgrave Handbook of Agricultural and Rural Development in Africa (ed. Osabuohien, E. S.) 627–640 (Springer, 2020).Gautier, D., Garcia, C., Negi, S. & Wardell, D. A. The limits and failures of existing forest governance standards in semi-arid contexts. Int. For. Rev. 17, 114–126 (2015).
Google Scholar 
Brandt, M. et al. An unexpectedly large count of trees in the West African Sahara and Sahel. Nature 587, 78–82 (2020).Article 
CAS 

Google Scholar 
Bastin, J. F. et al. The extent of forest in dryland biomes. Science 356, 635–638 (2017).CAS 
Article 

Google Scholar 
Fagan, M. E. A lesson unlearned? Underestimating tree cover in drylands biases global restoration maps. Glob. Change Biol. 26, 4679–4690 (2020).CAS 
Article 

Google Scholar 
Bey, A. & Meyfroidt, P. Improved land monitoring to assess large-scale tree plantation expansion and trajectories in Northern Mozambique. Environ. Res. Commun. https://doi.org/10.1088/2515-7620/ac26ab (2021).Harris, N., Goldman, E. D. & Gibbes, S. Spatial Database of Planted Trees (SDPT Version 1.0) (World Resources Institute, accessed 21 November 2021).Timberlake, W. J., Chidumayo, E. & Sawadogo, L. in The Dry Forests and Woodlands of Africa (eds Chidumayo, E. N. & Gumbo, D.) 11–41 (Earthscan, 2010).Portillo-Quintero, C. A. & Sánchez-Azofeifa, G. A. Extent and conservation of tropical dry forests in the Americas. Biol. Conserv. 143, 144–155 (2010).Article 

Google Scholar 
Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. BioScience 67, 534–545 (2017).Article 

Google Scholar 
Murphy, P. G. & Lugo, A. E. Ecology of tropical dry forest. Annu. Rev. Ecol. Syst. 17, 67–88 (1986).Article 

Google Scholar 
Lock, J. M. in Neotropical Savannas and Seasonally Dry Forests (eds Pennington, R. T. & Ratter, J. A.) 449–467 (CRC Press, 2006).Malhi, Y. et al. Megafauna and ecosystem function from the Pleistocene to the Anthropocene. Proc. Natl Acad. Sci. USA 113, 838–846 (2016).CAS 
Article 

Google Scholar 
Baldi, G., Veron, S. R. & Jobbagy, E. G. The imprint of humans on landscape patterns and vegetation functioning in the dry subtropics. Glob. Change Biol. 19, 441–458 (2013).Article 

Google Scholar 
Lahsen, M., Bustamante, M. M. C. & Dalla-Nora, E. L. Undervaluing and overexploiting the Brazilian Cerrado at our peril. Environ. Sci. Policy Sustain. Dev. 58, 4–15 (2016).Article 

Google Scholar 
Sitoe, A., Chidumayo, E. & Alberto, M. in The Dry Forests and Woodlands of Africa (eds Chidumayo, E. N. & Gumbo, D.) 131–153 (Earthscan, 2010).Ozdogan, M. & Woodcock, C. E. Resolution dependent errors in remote sensing of cultivated areas. Remote Sens. Environ. 103, 203–217 (2006).Article 

Google Scholar 
Estes, L. et al. A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses. Glob. Change Biol. 24, 322–337 (2018).Article 

Google Scholar 
Dlamini, W. M. Mapping forest and woodland loss in Swaziland: 1990–2015. Remote Sens. Appl. Soc. Environ. 5, 45–53 (2017).
Google Scholar 
Geist, H. J. & Lambin, E. F. Proximate causes and underlying driving forces of tropical deforestation: tropical forests are disappearing as the result of many pressures, both local and regional, acting in various combinations in different geographical locations. BioScience 52, 143–150 (2002).Article 

Google Scholar 
Walker, R. Mapping process to pattern in the landscape change of the Amazonian frontier. Ann. Assoc. Am. Geogr. 93, 376–398 (2003).Article 

Google Scholar 
Baumann, M. et al. Frontier metrics for a process-based understanding of deforestation dynamics. Preprint at EarthArXiv https://doi.org/10.31223/X55S7J (2022).Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).CAS 
Article 

Google Scholar 
Lesiv, M. et al. Estimating the global distribution of field size using crowdsourcing. Glob. Change Biol. 25, 174–186 (2019).Article 

Google Scholar 
Weiss, D. J. et al. A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature 553, 333–336 (2018).CAS 
Article 

Google Scholar 
Global Agro-Ecological Zones (GAEZ v3. 0) (IIASA and FAO, accessed 24 July 2020).Heinimann, A. et al. A global view of shifting cultivation: recent, current, and future extent. PLoS ONE 12, e0184479 (2017).Article 
CAS 

Google Scholar 
Shamseer, L. et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ 349, g7647 (2015).Article 

Google Scholar  More

Petropoulos, G. A. Fenugreek © 2002. (2002).Megias, C. et al. Free amino acids, Including Canavanine, in the Seeds from 24 Wild Mediterranean Legumes. J. Food Chem. Nanotechnol. 2, 178–183 (2016).Article 

Google Scholar 
Legume Phylogeny Working Group. Legume phylogeny and classification in the 21st century: Progress , prospects and lessons for other species-rich clades. Taxon. 62, 217–248 (2013).Grela, E. R., Kiczorowska, B., Samolińska, W. & Matras, J. Chemical composition of leguminous seeds : part I — content of basic nutrients, amino acids, phytochemical compounds, and antioxidant activity. Eur. Food Res. Technol. 243, 1385–1395 (2017).CAS 
Article 

Google Scholar 
Bradshaw, A. D. Producing patterns in plants. New Phytol. 170, 639–641 (2006).Article 

Google Scholar 
Brunetti, C., George, R. M., Tattini, M., Field, K. & Davey, M. P. Metabolomics in plant environmental physiology. J. Exp. Bot. 64, 4011–4020 (2013).CAS 
Article 

Google Scholar 
Allevato, D. M., Kiyota, E., Mazzafera, P. & Nixon, K. C. Ecometabolomic analysis of wild populations of Pilocarpus pennatifolius (Rutaceae ) Using Unimodal Analyses. Front. Plant Sci. 10 (2019).Chen, W., Hou, L., Zhang, Z., Pang, X. & Li, Y. Genetic diversity, population structure, and linkage disequilibrium of a core collection of Ziziphus jujuba assessed with genome-wide SNPs developed by genotyping-by-sequencing and SSR. Markers. 8, 1–14 (2017).
Google Scholar 
Aljuhaimi, F., Şimşek, Ş., Özcan, M. M., Ghafoor, K. & Babiker, E. E. Effect of location on chemical properties, amino acid and fatty acid compositions of fenugreek (Trigonella foenum-graecum L.) seed and oils. J. Food Process. Preserv. 42, e13569 (2018).Kapoor, N. & Pande, V. Antioxidative defense to salt stress in Trigonella foenum-graecum L. Curr. discov. 2, 123–127 (2015).
Google Scholar 
Kyani, A. & Niknam, V. Comparative responses of two Trigonella species to salinity and drought stresses in vitro. Prog. Biol. Sci. 5, 233–248 (2015).
Google Scholar 
Saberali, S. F. & Moradi, M. Effect of salinity on germination and seedling growth of Trigonella foenum-graecum, Dracocephalum moldavica, Satureja hortensis and Anethum graveolens. J. Saudi Soc. Agric. Sci. 18, 316–323 (2019).
Google Scholar 
Ahari, D. S., Kashi, A. K., Hassandokht, M. R., Amri, A. & Alizadeh, K. Assessment of drought tolerance in Iranian fenugreek landraces. J. Food Agric. Environ. 7, 414–419 (2009).Meena, S. et al. Water stress induced biochemical changes in fenugreek (Trigonella foenum graecum L .) genotypes. International J. Seed Spices. 6, 61–70 (2016).
Google Scholar 
Nour, A. A. M. & Magboul, B. I. Chemical and amino acid composition of fenugreek seeds grown in Sudan. Food Chem. 22, 1–5 (1986).CAS 
Article 

Google Scholar 
Hassanzadeh, E., Chaichi, M. R., Mazaheri, D., Rezazadeh, S. & Badi, H. A. N. Physical and chemical variabilities among domestic Iranian Fenugreek (Trigonella foenum-graceum) seeds. Asian J. Plant Sci. 10, 323–330 (2011).Article 

Google Scholar 
Nagulapalli Venkata, K. C., Swaroop, A., Bagchi, D. & Bishayee, A. A small plant with big benefits: Fenugreek (Trigonella foenum-graecum Linn.) for disease prevention and health promotion. Mol. Nutr. Food Res. 61 (2017).Robinson, A. R., Ukrainetz, N. K., Kang, K., Mansfield, S. D. & Mansfield, S. D. Metabolite profiling of Douglas-fir (Pseudotsuga menziesii ) field trials reveals strong environmental and weak genetic variation. New Phytol . 174, 762–773 (2003).Article 

Google Scholar 
Wang, C. et al. Extraction of sensitive bands for monitoring the winter wheat (Triticum aestivum) growth status and yields based on the spectral reflectance. PLoS ONE. 12, 1–16 (2017).
Google Scholar 
Mehrafarin, A. et al. Bioengineering of important secondary metabolites and metabolic pathways in fenugreek (Trigonella foenum-graecum L.). J. Med. Plants 9, 1–18 (2010).CAS 

Google Scholar 
Bhutia, P. H. & Sharangi, A. B. Influence of dates of sowing and irrigation scheduling on phenology, growth and yield dynamics of fenugreek (Trigonella foenum greacum L .). Legume Res. 41, 275–280 (2018).
Google Scholar 
Guillermo A. A. Dosio, Luis A. N. Aguirreza´bal,* Fernando H. Andrade & ABSTRACT, V. R. P. Solar Radiation Intercepted during Seed Filling and Oil Production in Two Sunflower Hybrids. Crop Sci. 40, 1637–1644 (2000).Ishimaru, T. et al. High temperature and low solar radiation during ripening differentially affect the composition of milky-white grains in rice (Oryza sativa L.). Plant Prod. Sci. 21, 370–379 (2018).Larsson, S., Wirén, A., Lundgren, L. & Ericsson, T. Effects of light and nutrient stress on leaf phenolic chemistry in salix dasyclados and susceptibility to galerucella lineola (Coleoptera). Oikos. 47, 205–210 (1986).CAS 
Article 

Google Scholar 
Chua, I. Y. P., King, P. J. H., Ong, K. H., Sarbini, S. R. & Yiu, P. H. Influence of light intensity and temperature on antioxidant activity in Premna serratifolia L. J. Soil Sci. Plant Nutr. 15, 605–614 (2015).
Google Scholar 
Sharma, A., Shahzad, B., Rehman, A., Bhardwaj, R., Landi, M. Response of phenylpropanoid pathway and the role of polyphenols in plants under abiotic stress. Molecules. 4, 2452. https://www.mdpi.com/1420-3049/24/13/2452Vaast, P. et al. Shade: A key factor for coffee sustainability and quality. 20th Int. Conf. Coffee Sci. 4, 887–896 (2005).Borges, C. V., Minatel, I. O., Gomez-Gomez, H. A. & Lima, G. P. P. Medicinal plants: Influence of environmental factors on the content of secondary metabolites. Med. Plants Environ. Challenges 259–277 (2017). https://doi.org/10.1007/978-3-319-68717-9_15Hanifah, A., Maharijaya, A., Putri, S. P., Laviña, W. A. & Sobir. Untargeted metabolomics analysis of eggplant (Solanum melongena L.) fruit and its correlation to fruit morphologies. Metabolites 8, (2018).Szakiel, A. & Henry, M. Influence of environmental biotic factors on the content of saponins in plants Influence of environmental abiotic factors on the content of saponins in plants. Phytochem Rev. 10, (2011). https://doi.org/10.1007/s11101-010-9177-xObata, T. & Fernie, A. R. The use of metabolomics to dissect plant responses to abiotic stresses. Cell. Mol. Life Sci. 69, 3225–3243 (2012).CAS 
Article 

Google Scholar 
Hamidou, M. et al. Genetic Variability and its implications on early generation sorghum lines selection for yield, Yield contributing traits, and resistance to sorghum midge. 2018, (2018).Tierno, R. & Galarreta, J. I. R. De. Heritability of target bioactive compounds and hydrophilic antioxidant capacity in purple- and red- fl eshed tetraploid potatoes. Crop Pasture Sci. 67, 1309–1317 (2016).Culley, D. Variation of anthocyanin and carotenoid contents and associated antioxidant values in potato breeding Lines. J. Am. Soc. Hortic. Sci. 130 (2005). https://doi.org/10.21273/JASHS.130.2.174Stephens, M. J., Hall, H. K. & Alspach, P. A. Variation and heritabilities of antioxidant activity and total phenolic content estimated from a red raspberry factorial experiment. J. Am. Soc. Hortic. Sci. 130, 403–411 (2015). https://doi.org/10.21273/JASHS.130.3.403Antoine, M., Nicolas, Y., Noubissié, T. J., Marcel, R. & Martin, J. Genetics of seed flavonoid content and antioxidant activity in cowpea (Vigna unguiculata L . Walp .). Crop J. 4, 391–397 (2016).Matros, A. et al. Genome-metabolite associations revealed low heritability, high genetic complexity, and causal relations for leaf metabolites in winter wheat (Triticum aestivum L.). J. Exp. Bot
.
68, 415–428 (2017).Labarrere, B., Prinzing, A., Dorey, T., Chesneau, E., Hennion, F. Variations of secondary metabolites among natural suggest functional redundancy and versatility. Plants. 19, 234 (2019).Ghaffari, M. R., Shahinnia, F. & Schreiber, F. The metabolic signature of biomass formation in barley. Plant Cell Physiol. 57, 1943–1960 (2016).Aryal S, Baniya MK, Danekhu K, Kunwar P, Gurung R, Koirala N. Total phenolic content, flavonoid content and antioxidant potential of wild vegetables from Western Nepal. Plants. 11, 96 (2019).Praksh, R., Singh, D., Meena, B. L., Kumari, R. & Meena, S. K. Assessment of genetic variability, heritability and genetic advance for quantitative traits in Fenugreek (Trigonella foenum-graecum L.). Int. J. Curr. Microbiol. App.Sci. 6, 2389–2399 (2017).Haefelé, C., Bonfils, C. & Sauvaire, Y. Characterization of a dioxygenase from Trigonella foenum-graecum involved in 4-hydroxyisoleucine biosynthesis. Phytochemistry 44, 563–566 (1997).Article 

Google Scholar 
Zafar, M. I. & Gao, F. 4-Hydroxyisoleucine: A Potential New Treatment for Type 2 Diabetes Mellitus. BioDrugs 30, 255–262 (2016).CAS 
Article 

Google Scholar 
Hosamath, J. V., Hegde, R. V & Venugopal, C. K. Studies on genetic variability, heritability and genetic advance in Fenugreek (Trigonella foenum-graecum L .). Int. J. Curr. Microbiol. App.Sci. 6, 4029–4036 (2017).Al-Naggar AM, El-Salam R, Badran AE, Boulos ST, El-Moghazi M. Heritability and genetic advance from selection for morphological, biochemical and anatomical traits of Chenopodium quinoa under water stress. Bionature. 38, 66–85 (2018).Yadav, T. C., Meena, R. S. & Dhakar, L. Genetic variability analysis in Fenugreek (Trigonella foenum-graecum L.) Genotypes. Int. J. Curr. Microbiol. App. Sci. 7, 2998–3003 (2018).Di Martino, C., Delfine, S., Pizzuto, R., Loreto, F. & Fuggi, A. Free amino acids and glycine betaine in leaf osmoregulation of spinach responding to increasing salt stress. New Phytol. 158, 455–463 (2003).Article 

Google Scholar 
Haji, M. H., Sadat, E. S., Amanzadeh, Y., Izaddoust, M., Givi, E. Identification and quantitative determination of 4-hydroxyisoleucine in Trigonella foenum-graecum L. from Iran. J. Med. Plants 9, 29–34 (2010).Zhuo, R., Wang, L., Wang, L., Xiao, H. & Cai, S. Determination of trigonelline in Trigonella foenum-graecum L. by hydrophilic interaction chromatography. Se pu. 28, 379—382 (2010).CAS 
PubMed 

Google Scholar 
Kim, D. O., Jeong, S. W. & Lee, C. Y. Antioxidant capacity of phenolic phytochemicals from various cultivars of plums. Food Chem. 81, 321–326 (2003).CAS 
Article 

Google Scholar 
Molyneux, P. The use of the stable free radical diphenylpicryl- hydrazyl (DPPH) for estimating antioxidant activity. Songklanakarin J. Sci. Technol. 26, 211–216 (2004)CAS 

Google Scholar 
Wei, T. Title visualization of a correlation matrix. R Packag. 56, 1–17 (2017).
Google Scholar 
Husson, F., Josse, J. and Pages, J., 2010. Principal component methods-hierarchical clustering-partitional clustering: why would we need to choose for visualizing data. Applied Mathematics Department, 17 (2010)Hanson, C. H., Robinson, H. F. & Comstock, R. E. Biometrical studies of yield in segregating populations of Korean Lespedeza1. Agron. J. 48, 268–272 (1956).Article 

Google Scholar 
Herbert, W., Robinson, H. F. & Comstock, R. E. Estimates of Genetic and Environmental Variability in Soybeans. Agron J. 46, 314–318 (1955).
Google Scholar 
Oksanen, J. et al. Package ‘vegan’ title community ecology package. Community Ecol. Packag. 2, 1–297 (2019).
Google Scholar 
R Foundation for Statistical Computing. R: A language and environment for statistical computing. Vienna, Austria 2, (2008). More

Joly, K. et al. Sci. Rep. 9, 15333 (2019).Article 

Google Scholar 
Shaw, A. K. Evol. Ecol 30, 991–1007 (2016).Article 

Google Scholar 
Bauer, S. & Hoye, B. J. Science 344, 1242552 (2014).CAS 
Article 

Google Scholar 
Abraham, J. O., Upham, N. S., Damian-Serrano, A. & Jesmer, B. R. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01749-4 (2022).Article 

Google Scholar 
Middleton, A. D. et al. Oikos 127, 1060–1068 (2018).Article 

Google Scholar 
Hein, A. M., Hou, C. & Gillooly, J. F. Ecol. Lett. 15, 104–110 (2012).Article 

Google Scholar 
Zachos, J., Pagani, M., Sloan, L., Thomas, E. & Billups, K. Science 292, 686–693 (2001).CAS 
Article 

Google Scholar 
Edwards, E. J. et al. Science 328, 587–591 (2010).CAS 
Article 

Google Scholar 
Aikens, E. O. et al. Curr. Biol. 30, 3444–3449 (2020).CAS 
Article 

Google Scholar 
Merkle, J. A. et al. Ecol. Lett. 22, 1797–1805 (2019).Article 

Google Scholar 
Jesmer, B. R. et al. Science 361, 1023–1025 (2018).CAS 
Article 

Google Scholar 
Harris, G., Thirgood, S., Hopcraft, J. G. C., Cromsigt, J. & Berger, J. Endanger. Species Res. 7, 55–76 (2009).Article 

Google Scholar 
Aikens, E. O. et al. Glob. Change Biol. 26, 4215–4225 (2020).Article 

Google Scholar 
Doughty, C. E. et al. Ecography 43, 1107–1117 (2020).Article 

Google Scholar 
Kauffman, M. J. et al. Science 372, 566–569 (2021).CAS 
Article 

Google Scholar  More

Dobson, A. P. et al. Road will ruin Serengeti. Nature 467, 272–273 (2010).CAS 
PubMed 
Article 

Google Scholar 
Larsen, F. et al. Wildebeest migration drives tourism demand in the Serengeti. Biol. Conserv. 248, 108688 (2020).Article 

Google Scholar 
Aikens, E. O. et al. The greenscape shapes surfing of resource waves in a large migratory herbivore. Ecol. Lett. 20, 741–750 (2017).PubMed 
Article 

Google Scholar 
Bischof, R. et al. A migratory northern ungulate in the pursuit of spring: jumping or surfing the green wave? Am. Nat. 180, 407–424 (2012).PubMed 
Article 

Google Scholar 
Merkle, J. A. et al. Large herbivores surf waves of green-up during spring. Proc. Biol. Sci. 283, 20160456 (2016).PubMed 
PubMed Central 

Google Scholar 
Fryxell, J. M., Greever, J. & Sinclair, A. R. E. Why are migratory ungulates so abundant? Am. Nat.131, 781–798 (1988).Article 

Google Scholar 
Staver, A. C. & Hempson, G. P. Seasonal dietary changes increase the abundances of savanna herbivore species. Sci. Adv. 6, eabd2848 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Kauffman, M. J. et al. Causes, consequences, and conservation of ungulate migration. Annu. Rev. Ecol. Evol. Syst. 52, 453–478 (2021).Article 

Google Scholar 
Lundberg, J. & Moberg, F. Mobile link organisms and ecosystem functioning: implications for ecosystem resilience and management. Ecosystems 6, 0087–0098 (2003).Article 

Google Scholar 
Bauer, S. & Hoye, B. J. Migratory animals couple biodiversity and ecosystem functioning worldwide. Science 344, 1242552 (2014).CAS 
PubMed 
Article 

Google Scholar 
Bolger, D. T., Newmark, W. D., Morrison, T. A., & Doak, D. F. The need for integrative approaches to understand and conserve migratory ungulates. Ecol. Lett. 11, 63–77 (2007).PubMed 

Google Scholar 
Fryxell, J. M. & Holt, R. D. Environmental change and the evolution of migration. Ecology 94, 1274–1279 (2013).CAS 
PubMed 
Article 

Google Scholar 
Shaw, A. K. Drivers of animal migration and implications in changing environments. Evol. Ecol. 30, 991–1007 (2016).Article 

Google Scholar 
Hebblewhite, M. & Merrill, E. H. Trade-offs between predation risk and forage differ between migrant strategies in a migratory ungulate. Ecology 90, 3445–3454 (2009).PubMed 
Article 

Google Scholar 
Nelson, M. E. Development of migratory behavior in northern white-tailed deer. Can. J. Zool. 76, 426–432 (1998).Article 

Google Scholar 
Berg, J. E., Hebblewhite, M., St. Clair, C. C. & Merrill, E. H. Prevalence and mechanisms of partial migration in ungulates. Front. Ecol. Evol. 7, 325 (2019).Article 

Google Scholar 
Jesmer, B. R. et al. Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals. Science 361, 1023–1025 (2018).CAS 
PubMed 
Article 

Google Scholar 
Sih, A., Bell, A. & Johnson, J. C. Behavioral syndromes: an ecological and evolutionary overview. Trends Ecol. Evol. 19, 372–378 (2004).PubMed 
Article 

Google Scholar 
Found, R. & St. Clair, C. C. Behavioural syndromes predict loss of migration in wild elk. Anim. Behav. 115, 35–46 (2016).Article 

Google Scholar 
Abraham, J. O., Hempson, G. P., Faith, J. T. & Staver, A. C.Seasonal strategies differ between tropical and extratropical herbivores. J. Anim. Ecol. 91, 681–692 (2022).PubMed 
Article 

Google Scholar 
Whitehead, H., Laland, K. N., Rendell, L., Thorogood, R. & Whiten, A. The reach of gene–culture coevolution in animals. Nat. Commun. 10, 2405 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Scanlon, T. M., Caylor, K. K., Manfreda, S., Levin, S. A. & Rodriguez-Iturbe, I. Dynamic response of grass cover to rainfall variability: implications for the function and persistence of savanna ecosystems. Adv. Water Res. 28, 291–302 (2005).Article 

Google Scholar 
Staver, A. C., Wigley-Coetsee, C. & Botha, J. Grazer movements exacerbate grass declines during drought in an African savanna. J. Ecol. 107, 1482–1491 (2019).Article 

Google Scholar 
Fryxell, J. M. & Sinclair, A. R. Causes and consequences of migration by large herbivores. Trends Ecol. Evol. 3, 237–241 (1988).CAS 
PubMed 
Article 

Google Scholar 
Running, S. W. et al. A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54, 547–560 (2004).Article 

Google Scholar 
Langvatn, R., Albon, S. D., Burkey, T. & Clutton-Brock, T. H. Climate, plant phenology and variation in age of first reproduction in a temperate herbivore. J. Anim. Ecol. 65, 653–670 (1996).Article 

Google Scholar 
Webber, Q. M. R. & McGuire, L. P. Heterothermy, body size, and locomotion as ecological predictors of migration in mammals. Mamm. Rev. 52, 82–95 (2022).Article 

Google Scholar 
Mann, D. H., Groves, P., Gaglioti, B. V. & Shapiro, B. A. Climate-driven ecological stability as a globally shared cause of Late Quaternary megafaunal extinctions: the Plaids and Stripes Hypothesis. Biol. Rev. Camb. Philos. Soc. 94, 328–352 (2018).PubMed Central 
Article 

Google Scholar 
Jarman, P. J. The social organisation of antelope in relation to their ecology. Behaviour 48, 215–267 (1974).Article 

Google Scholar 
Hein, A. M., Hou, C. & Gillooly, J. F. Energetic and biomechanical constraints on animal migration distance. Ecol. Lett. 15, 104–110 (2012).PubMed 
Article 

Google Scholar 
Abraham, J. O., Hempson, G. P. & Staver, A. C. Drought-response strategies of savanna herbivores. Ecol. Evol. 9, 7047–7056 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Owen-Smith, R. N. Megaherbivores: the Influence of Very Large Body Size on Ecology (Cambridge Univ. Press, 1988).Book 

Google Scholar 
Gonzalez-Voyer, A. & von Hardenberg, A. in Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology: Concepts and Practice (ed. Garamszegi, L. Z.) 201–229 (Springer, 2014).Pérez-Barbería, F. J., Gordon, I. J. & Nores, C. Evolutionary transitions among feeding styles and habitats in ungulates. Evol. Ecol. Res. 3, 221–230 (2001).
Google Scholar 
Staver, A. C., Abraham, J. O., Hempson, G. P., Karp, A. T. & Faith, J. T. The past, present, and future of herbivore impacts on savanna vegetation. J. Ecol. 109, 2804–2822 (2021).Article 

Google Scholar 
Janis, C. M. in The Ecology of Browsing and Grazing (eds Gordon, I. J. & Prins, H. H. T.) 21–45 (Springer, 2008).Janis, C. M. Tertiary mammal evolution in the context of changing climates, vegetation, and tectonic events. Annu. Rev. Ecol. Syst. 24, 467–500 (1993).Article 

Google Scholar 
Zachos, J., Pagani, M., Sloan, L., Thomas, E. & Billups, K. Trends, rhythms, and aberrations in global climate 65 Ma to present. Science 292, 686–693 (2001).CAS 
PubMed 
Article 

Google Scholar 
Edwards, E. J. et al. The origins of C4 grasslands: integrating evolutionary and ecosystem. Science 328, 587–591 (2010).CAS 
PubMed 
Article 

Google Scholar 
Bhat, U., Kempes, C. P. & Yeakel, J. D. Scaling the risk landscape drives optimal life-history strategies and the evolution of grazing. Proc. Natl Acad. Sci. USA 117, 1580–1586 (2020).CAS 
PubMed 
Article 

Google Scholar 
Fagan, W. F. et al. Spatial memory and animal movement. Ecol. Lett. 16, 1316–1329 (2013).PubMed 
Article 

Google Scholar 
Merkle, J. A. et al. Spatial memory shapes migration and its benefits: evidence from a large herbivore. Ecol. Lett. 22, 1797–1805 (2019).PubMed 
Article 

Google Scholar 
Mueller, T., O’Hara, R. B., Converse, S. J., Urbanek, R. P. & Fagan, W. F. Social learning of migratory performance. Science 341, 999–1002 (2013).CAS 
PubMed 
Article 

Google Scholar 
Wcislo, W. T. Behavioral environments and evolutionary change. Annu. Rev. Ecol. Syst. 20, 137–169 (1989).Article 

Google Scholar 
Wyles, J. S., Kunkel, J. G. & Wilson, A. C. Birds, behavior, and anatomical evolution. Proc. Natl Acad. Sci. USA 80, 4394–4397 (1983).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yeakel, J. D., Kempes, C. P. & Redner, S. Dynamics of starvation and recovery predict extinction risk and both Damuth’s law and Cope’s rule. Nat. Commun. 9, 657 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Purdon, A., Mole, M. A., Chase, M. J. & van Aarde, R. J. Partial migration in savanna elephant populations distributed across southern Africa. Sci. Rep. 8, 11331 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Upham, N. S., Esselstyn, J. A. & Jetz, W. Inferring the mammal tree: species-level sets of phylogenies for questions in ecology, evolution, and conservation. PLoS Biol. 17, e3000494 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Abrahms, B. et al. Memory and resource tracking drive blue whale migrations. Proc. Natl Acad. Sci. USA 116, 5582–5587 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Barnosky, A. D., Koch, P. L., Feranec, R. S., Wing, S. L. & Shabel, A. B. Assessing the causes of late Pleistocene extinctions on the continents. Science 306, 70–75 (2004).CAS 
PubMed 
Article 

Google Scholar 
Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).CAS 
PubMed 
Article 

Google Scholar 
Faith, J. T., Rowan, J. & Du, A. Early hominins evolved within non-analog ecosystems. Proc. Natl Acad. Sci. USA 116, 21478–21483 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Holdo, R. M. et al. A disease-mediated trophic cascade in the Serengeti and its implications for ecosystem C. PLoS Biol. 7, e1000210 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Janzen, D. H. & Martin, P. S. Neotropical anachronisms: the fruits the gomphotheres ate. Science 215, 19–27 (1982).CAS 
PubMed 
Article 

Google Scholar 
Dantas, V. L. & Pausas, J. G. The legacy of the extinct Neotropical megafauna on plants and biomes. Nat. Commun. 13, 129 (2022).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Harris, G., Thirgood, S., Hopcraft, J. G. C., Cromsigt, J. P. G. M. & Berger, J. Global decline in aggregated migrations of large terrestrial mammals. Endanger. Species Res. 7, 55–76 (2009).Article 

Google Scholar 
Seersholm, F. V. et al. Rapid range shifts and megafaunal extinctions associated with late Pleistocene climate change. Nat. Commun. 11, 2770 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Alroy, J. A multispecies overkill simulation of the end-Pleistocene megafaunal mass extinction. Science 292, 1893–1896 (2001).CAS 
PubMed 
Article 

Google Scholar 
Berger, J. The last mile: how to sustain long-distance migration in mammals. Conserv. Biol. 18, 320–331 (2004).Article 

Google Scholar 
Faurby, S. & Svenning, J.-C. Resurrection of the island rule: human-driven extinctions have obscured a basic evolutionary pattern. Am. Nat. 187, 812–820 (2016).PubMed 
Article 

Google Scholar 
Wilman, H. et al. EltonTraits 1.0: species-level foraging attributes of the world’s birds and mammals. Ecology 95, 2027 (2014).Article 

Google Scholar 
Smith, F. A. et al. Body mass of late Quaternary mammals. Ecology 84, 3403 (2003).Article 

Google Scholar 
IUCN. IUCN Red List of Threatened Species 2019 (IUCN, 2019).Toljagić, O., Voje, K. L., Matschiner, M., Liow, L. H. & Hansen, T. F. Millions of years behind: slow adaptation of ruminants to grasslands. Syst. Biol. 67, 145–157 (2018).PubMed 
Article 

Google Scholar 
Pinzon, J. E. & Tucker, C. J. A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote Sens. 6, 6929–6960 (2014).Article 

Google Scholar 
R Core Team. R: a Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).Article 

Google Scholar 
Blomberg, S. P., Garland, T. Jr. & Ives, A. R. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57, 717–745 (2003).PubMed 
Article 

Google Scholar 
Orme, D. The caper package: Comparative analysis of phylogenetics and evolution in R. R package version 1.0.1 https://cran.r-project.org/web/packages/caper/vignettes/caper.pdf (2018).Beaulieu, J. M. & O’Meara, B. OUwie: Analysis of evolutionary rates in an OU framework. R package version 2.6 https://rdrr.io/cran/OUwie/ (2014).Cressler, C. E., Butler, M. A. & King, A. A. Detecting adaptive evolution in phylogenetic comparative analysis using the Ornstein–Uhlenbeck model. Syst. Biol. 64, 953–968 (2015).PubMed 
Article 

Google Scholar 
Ho, L. S. & Ané, C. A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Syst. Biol. 63, 397–408 (2014).PubMed 
Article 

Google Scholar 
van der Bijl, W. phylopath: easy phylogenetic path analysis in R. PeerJ 6, e4718 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Chen, L. et al. Large-scale ruminant genome sequencing provides insights into their evolution and distinct traits. Science 364, eaav6202 (2019).CAS 
PubMed 
Article 

Google Scholar  More

Water samples were filtered twice (see Methods), first through a large filter (0.45 µm, LF or “Large Filter”) and then the filtrate was passed through a small filter (0.05 µm, UF or “Ultrafine Fraction”). Using whole genome shotgun metagenomics from four water samples (LF92 and UF92 from the 92 m depth, LF99 and UF99 from the 99 m depth) as well as one sediment sample, we provide the first comprehensive whole genome shotgun metagenomics investigation of this section of the lake and highlight both the taxonomic composition and potential metabolic strategies for survival, as well as identify areas for deeper investigation.Cell counts and dissolved nutrientsIn order to determine the habitability of the anoxic basin, the cell counts were measured in the oxycline (75 m depth) and the anoxic region (92 and 99 m depth), where oxygen content is  More

Richardson, D.M., & Rundel, P.W. Ecology and biogeography of Pinus: An introduction. in Ecology and Biogeography of Pinus (Richardson, D.M. Ed.). 3–40. (Cambridge Press, 1998).Keeley, J. E. Ecology and evolution of pine life histories. Ann. For. Sci. 69, 445–453 (2012).Article 

Google Scholar 
Agee, J.K. Fire and pine ecosystems. in Ecology and Biogeography of Pinus (Richardson, D.M. Ed.). 193–217. (Cambridge Press, 1998).Keeley, J.E., & Zedler, P.H. Evolution of life histories in Pinus. in Ecology and Biogeography of Pinus (Richardson, D.M. Ed.). 219–251. (Cambridge Press, 1998).Pausas, J. G., Bradstock, R., Keith, D. A. & Keeley, J. E. Plant functional traits in relation to fire in crown-fire ecosystems. Ecology 85, 1085–1100 (2004).Article 

Google Scholar 
Hare, R. C. Contribution of bark to fire resistance of southern trees. J. For. 63, 248–251 (1965).
Google Scholar 
Jackson, J. F., Adams, D. C. & Jackson, U. B. Allometry of constitutive defense: A model and a comparative test with tree bark and fire regime. Am. Nat. 153, 614–632 (1999).PubMed 
Article 

Google Scholar 
Stephens, S. L. & Libby, W. J. Anthropogenic fire and bark thickness in coastal and island pine populations from Alta and Baja California. J. Biogeogr. 33, 648–652 (2006).Article 

Google Scholar 
Chapman, H. H. Is the longleaf type a climax?. Ecology 13, 328–334 (1932).Article 

Google Scholar 
Pile, L. S., Wang, G. G., Knapp, B. O., Liu, G. & Yu, D. Comparing morphology and physiology of southeastern US Pinus seedlings: Implications for adaptation to surface fire regimes. Ann. For. Sci. 74, 68 (2017).Article 

Google Scholar 
Rodríguez-Trejo, D. A. & Fulé, P. Z. Fire ecology of Mexican pines and a fire management proposal. Int. J. Wildl. Fire 12, 23–37 (2003).Article 

Google Scholar 
Pausas, J. G. Bark thickness and fire regime. Funct. Ecol. 29, 315–327 (2015).Article 

Google Scholar 
Little, S. & Mergen, F. External and internal changes associated with basal-crook formation in pitch and shortleaf pines. For. Sci. 12, 268–275 (1966).
Google Scholar 
Kolström, T. & Kellomäki, S. Tree survival in wildfires. Silva Fenn. 27, 277–281 (1993).Article 

Google Scholar 
Schwilk, D. W. & Ackerly, D. D. Flammability and serotiny as strategies: Correlated evolution in pines. Oikos 94, 326–236 (2001).Article 

Google Scholar 
Reyes, O. & Casal, M. Effect of high temperatures on cone opening and on the release and viability of Pinus pinaster and P. radiata seeds in NW Spain. Ann. For. Sci. 59, 327–334 (2002).Article 

Google Scholar 
Pausas, J. G. & Keeley, J. E. Epicormic resprouting in fire-prone ecosystems. Trends Plant Sci. 22, 1008–1015 (2017).CAS 
PubMed 
Article 

Google Scholar 
Fonda, R. W., Bellanger, L. A. & Burley, L. L. Burning characteristics of western conifer needles. Northwest Sci. 72, 1–9 (1998).
Google Scholar 
Fonda, R. W. Burning characteristics of needles from eight pine species. For. Sci. 47, 390–396 (2001).
Google Scholar 
Anderson, H. E. Forest fuel ignitability. Fire Tech. 6, 312–319 (1970).CAS 
Article 

Google Scholar 
Martin, R.E., et al. Assessing the flammability of domestic and wildland vegetation. in Proceedings of the 12th Conference Fire and Forest Meteorology. Jekyll Island. 130–137. (1993)Varner, J. M., Kane, J. M., Kreye, J. K. & Engber, E. The flammability of forest and wildland litter: A synthesis. Curr. For. Rep. 1, 91–99 (2015).
Google Scholar 
Fernandes, P. M. & Cruz, M. G. Plant flammability experiments offer limited insight into vegetation–fire dynamics interactions. New Phytol. 194, 606–609 (2012).PubMed 
Article 

Google Scholar 
Wenk, E. S., Wang, G. G. & Walker, J. L. Within-stand variation in understorey vegetation affects fire behaviour in longleaf pine xeric sandhills. Int. J. Wildl. Fire 20, 866–875 (2012).Article 

Google Scholar 
Whelan, A. W., Bigelow, S. W. & O’Brien, J. J. Overstory longleaf pines and hardwoods create diverse patterns of energy release and fire effects during prescribed fire. Front. For. Glob. Change. 4, 25 (2021).Article 

Google Scholar 
Mutch, R. W. Wildland fires and ecosystems—A hypothesis. Ecology 51, 1046–1051 (1970).Article 

Google Scholar 
Troumbis, A. S. & Trabaud, L. Some questions about flammability in fire ecology. Acta Oecol. 10, 167–175 (1989).
Google Scholar 
Midgley, J. J. Flammability is not selected for, it emerges. Aust. J. Bot. 61, 102–106 (2013).Article 

Google Scholar 
Snyder, J. R. The role of fire: Mutch ado about nothing?. Oikos 43, 404–405 (1984).Article 

Google Scholar 
Bond, W. J. & Midgley, J. J. Kill thy neighbour: An individualistic argument for theevolution of flammability. Oikos 73, 79–85 (1995).Article 

Google Scholar 
Gagnon, P. R. et al. Does pyrogenicity protect burning plants?. Ecology 91, 3481–3486 (2010).PubMed 
Article 

Google Scholar 
Vines, R. G. Heat transfer through bark, and the resistance of trees to fire. Aust. J. Bot. 16, 499–514 (1968).Article 

Google Scholar 
Harmon, M. E. Survival of trees after low-intensity surface fires in Great Smoky Mountains National Park. Ecology 65, 796–802 (1984).Article 

Google Scholar 
Schwilk, D. W., Gaetani, M. S. & Poulos, H. M. Oak bark allometry and fire survival strategies in the Chihuahuan Desert Sky Islands, Texas, USA. PLoS ONE 8, e79285 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Stevens, J., Kling, M., Schwilk, D., Varner, J. M. & Kane, J. M. Biogeography of fire regimes in western US conifer forests: a trait-based approach. Glob. Ecol. Biogeogr. 29, 944–955 (2020).Article 

Google Scholar 
Rosell, J. A. Bark thickness across the angiosperms: More than just fire. New Phytol. 211, 90–102 (2016).CAS 
PubMed 
Article 

Google Scholar 
Kane, J. M., Varner, J. M. & Hiers, J. K. The burning characteristics of southeastern oaks: discriminating fire facilitators from fire impeders. For. Ecol. Manag. 256, 2039–2045 (2008).Article 

Google Scholar 
Engber, E. A. & Varner, J. M. Patterns of flammability of the California oaks: The role of leaf traits. Can. J. For. Res. 42, 1965–1975 (2012).Article 

Google Scholar 
Guyette, R. P., Stambaugh, M. C., Dey, D. C. & Muzika, R. Predicting fire frequency with chemistry and climate. Ecosystems 15, 322–335 (2012).Article 

Google Scholar 
Stambaugh, M.C., Varner, J.M., & Jackson, S.T. Biogeography: An interweave of climate, fire, and humans. in Ecological Restoration and Management of Longleaf Pine Forests (Kirkman, K., Jack, S. B. Eds.). 17–38. (CRC Press, 2017).Münkemüller, T. et al. How to measure and test phylogenetic signal. Methods Ecol. Evol. 3, 743–756 (2012).Article 

Google Scholar 
Schwilk, D. W. & Caprio, A. C. Scaling from leaf traits to fire behavior: community composition predicts fire severity in a temperate forest. J. Ecol. 99, 970–980 (2011).Article 

Google Scholar 
Ormeño, E. et al. The relationship between terpenes and flammability of leaf litter. For. Ecol. Manag. 257, 471–482 (2009).Article 

Google Scholar 
Mirov, N. T. The terpenes (in relation to the biology of genus Pinus). Ann. Rev. Biochem. 17, 521–540 (1948).CAS 
PubMed 
Article 

Google Scholar 
Mitić, Z. S. et al. Needle terpenes as chemotaxonomic markers in Pinus: Subsections Pinus and Pinaster. Chem. Biodivers. 14, e1600453 (2017).Article 

Google Scholar 
Baradat, P. & Yazdani, R. Genetic expression for monoterpenes in clones of Pinus sylvestris grown on different sites. Scand. J. For. Res. 3, 25–36 (1987).Article 

Google Scholar 
Hanover, J. W. Applications of terpene analysis in forest genetics. New For. 6, 159–178 (1992).Article 

Google Scholar 
He, T., Pausas, J. G., Belcher, C. M., Schwilk, D. W. & Lamont, B. B. Fire-adapted traits of Pinus arose in the fiery Cretaceous. New Phytol. 194, 751–759 (2012).PubMed 
Article 

Google Scholar 
Saladin, B. et al. Fossils matter: Improved estimates of divergence times in Pinus reveal older diversification. Evol. Biol. 17, 95 (2017).
Google Scholar 
Kreye, J. K. et al. Effects of solar heating on the moisture dynamics of forest floor litter in humid environments: Composition, structure, and position matter. Can. J. For. Res. 48, 1331–1342 (2018).Article 

Google Scholar 
Ganteaume, A., Jappiot, M., Curt, T., Lampin, C. & Borgniet, L. Flammability of litter sampled according to two different methods: Comparison of results in laboratory experiments. Int. J. Wildl. Fire 23, 1061–1075 (2014).Article 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2019). https://www.R-project.org/.Felsenstein, J. Phylogenies and the comparative method. Am. Nat. 125, 1–15 (1985).Article 

Google Scholar 
Orme, D., et al. Caper: Comparative Analyses of Phylogenetics and Evolution in R. Version 1.0.1. https://CRAN.R-project.org/package=caper. (2018).Pagel, M. Inferring the historical patterns of biological evolution. Nature 401, 877–884 (1999).CAS 
PubMed 
Article 

Google Scholar 
Freckleton, R. P., Harvey, P. H. & Pagel, M. Phylogenetic analysis and comparative data: A test and review of evidence. Am. Nat. 160, 712–726 (2002).CAS 
PubMed 
Article 

Google Scholar 
Barton, K. MuMIn: Multi-Model Inference. R Package Version 1.43.6. https://CRAN.R-project.org/package=MuMIn. (2019).Little, E.L. Atlas of United States Trees. Vol. 1. Conifers and Important Hardwoods. 1–320. (Miscellaneous Publication 1146, USDA, Forest Service, 1971).Prasad, A.M. & Iverson, L.R. Little’s Range and FIA Importance Value Database for 135 Eastern US Tree Species. http://www.fs.fed.us/ne/delaware/4153/global/littlefia/index.html. (Northeastern Research Station, USDA Forest Service). More

Odonnell, C. Population dynamics and survivorship in bats. In Ecology and Behavioral Methods for the Study of Bats (eds Kunz, T. H. & Parsons, S.) 158–176 (The Johns University Press, 2009).
Google Scholar 
Lebreton, J.-D., Burnham, K. P., Clobert, J. & Anderson, D. R. Modeling survival and testing biological hypotheses using marked animals: A unified approach with case studies. Ecol. Monogr. 62, 67–118 (1992).Article 

Google Scholar 
Gibbons, J. W. & Andrews, K. M. PIT tagging: Simple technology at its best. Bioscience 54, 447–454 (2004).Article 

Google Scholar 
Ellison, L. E. et al. A comparison of conventional capture versus PIT reader techniques for estimating survival and capture probabilities of big brown bats (Eptesicus fuscus). Acta Chiropterologica 9, 149–160 (2007).Article 

Google Scholar 
van Harten, E. et al. High detectability with low impact: Optimizing large PIT tracking systems for cave-dwelling bats. Ecol. Evol. 9, 10916–10928 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Schorr, R. A., Ellison, L. E. & Lukacs, P. M. Estimating sample size for landscape-scale mark-recapture studies of North American migratory tree bats. Acta Chiropterologica 16, 231–239 (2014).Article 

Google Scholar 
Baker, G. B. et al. The effect of forearm bands on insectivorous bats (Microchiroptera) in Australia. Wildl. Res. 28, 229–237 (2001).Article 

Google Scholar 
O’Shea, T. J., Ellison, L. E. & Stanley, T. R. Survival estimation in bats: Historical overview, critical appraisal, and suggestions for new approaches. In Sampling Rare or Elusive Species: Concepts, Designs, and Techniques for Estimating Population Parameters (ed. Thompson, W. L.) 297–336 (Island Press, 2004).
Google Scholar 
O’Shea, T. J. et al. Recruitment in a Colorado population of big brown bats: Breeding probabilities, litter size, and first-year survival. J. Mammal. 91, 418–428 (2010).Article 

Google Scholar 
O’Shea, T. J., Ellison, L. E. & Stanley, T. R. Adult survival and population growth rate in Colorado big brown bats (Eptesicus fuscus). J. Mammal. 92, 433–443 (2011).Article 

Google Scholar 
Schorr, R. A. & Siemers, J. L. Population dynamics of little brown bats (Myotis lucifugus) at summer roosts: Apparent survival, fidelity, abundance, and the influence of winter conditions. Ecol. Evol. 11, 7427–7438 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
O’Donnell, C. F. J., Edmonds, H. & Hoare, J. M. Survival of PIT-tagged lesser short-tailed bats (Mystacina tuberculata) through a pest control operation using the toxin pindone in bait stations. N. Z. J. Ecol. 35, 291–295 (2011).
Google Scholar 
Edmonds, H., Pryde, M. & O’Donnell, C. Survival of PIT-tagged lesser short-tailed bats (Mystacina tuberculata) through an aerial 1080 pest control operation. N. Z. J. Ecol. 41, 186–192 (2017).
Google Scholar 
Reusch, C. et al. Differences in seasonal survival suggest species-specific reactions to climate change in two sympatric bat species. Ecol. Evol. 9, 7957–7965 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
IUCN. The IUCN red list of threatened species. Version 2020-2. http://www.iucnredlist.org (2020).Lentini, P. E., Bird, T. J., Griffiths, S. R., Godinho, L. N. & Wintle, B. A. A global synthesis of survival estimates for microbats. Biol. Lett. 11, 20150371 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Culina, A., Linton, D. M. & Macdonald, D. W. Age, sex, and climate factors show different effects on survival of three different bat species in a woodland bat community. Glob. Ecol. Conserv. 12, 263–271 (2017).Article 

Google Scholar 
Frick, W. F., Reynolds, D. S. & Kunz, T. H. Influence of climate and reproductive timing on demography of little brown myotis Myotis lucifugus. J. Anim. Ecol. 79, 128–136 (2010).PubMed 
Article 

Google Scholar 
Schorcht, W., Bontadina, F. & Schaub, M. Variation of adult survival drives population dynamics in a migrating forest bat. J. Anim. Ecol. 78, 1182–1190 (2009).PubMed 
Article 

Google Scholar 
Sendor, T. & Simon, M. Population dynamics of the pipistrelle bat: Effects of sex, age and winter weather on seasonal survival. J. Anim. Ecol. 72, 308–320 (2003).Article 

Google Scholar 
Sripathi, K., Raghuram, H., Rajasekar, R., Karuppudurai, T. & Abraham, S. G. Population size and survival in the indian false vampire bat Megaderma lyra. Acta Chiropterologica 6, 145–154 (2004).Article 

Google Scholar 
Papadatou, E., Butlin, R. K., Pradel, R. & Altringham, J. D. Sex-specific roost movements and population dynamics of the vulnerable long-fingered bat, Myotis capaccinii. Biol. Conserv. 142, 280–289 (2009).Article 

Google Scholar 
López-Roig, M. & Serra-Cobo, J. Impact of human disturbance, density, and environmental conditions on the survival probabilities of pipistrelle bat (Pipistrellus pipistrellus). Popul. Ecol. 56, 471–480 (2014).Article 

Google Scholar 
Wilkinson, G. S. & Adams, D. M. Recurrent evolution of extreme longevity in bats. Biol. Lett. 15, 20180860 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
DELWP. National Recovery Plan for the Southern Bent-wing Bat Miniopterus orianae bassanii (2020).Lumsden, L. & Gray, P. Longevity record for a southern bent-wing bat Miniopterus schreibersii bassanii. Australas. Bat Soc. Newsl. 16, 43–44 (2001).
Google Scholar 
Holz, P. H. et al. Virus survey in populations of two subspecies of bent-winged bats (Miniopterus orianae bassanii and oceanensis) in south-eastern Australia reveals a high prevalence of diverse herpesviruses. PLoS ONE 13, e0197625 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Holz, P. H., Lumsden, L. F., Marenda, M. S., Browning, G. F. & Hufschmid, J. Two subspecies of bent-winged bats (Miniopterus orianae bassanii and oceanensis) in southern Australia have diverse fungal skin flora but not Pseudogymnoascus destructans. PLoS ONE 13, e0204282 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Holz, P. H., Lumsden, L. F. & Hufschmid, J. Ectoparasites are unlikely to be a primary cause of population declines of bent-winged bats in south-eastern Australia. Int. J. Parasitol. Parasites Wildl. 7, 423–428 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Holz, P. H., Lumsden, L. F., Legione, A. R. & Hufschmid, J. Polychromophilus melanipherus and haemoplasma infections not associated with clinical signs in southern bent-winged bats (Miniopterus orianae bassanii) and eastern bent-winged bats (Miniopterus orianae oceanensis). Int. J. Parasitol. Parasites Wildl. 8, 10–18 (2019).PubMed 
Article 

Google Scholar 
Holz, P. H., Clark, P., McLelland, D. J., Lumsden, L. F. & Hufschmid, J. Haematology of southern bent-winged bats (Miniopterus orianae bassanii) from the Naracoorte Caves National Park, South Australia. Comp. Clin. Pathol. 29, 231–237 (2020).CAS 
Article 

Google Scholar 
Dwyer, P. D. The population pattern of Miniopterus schreibersii (Chiroptera) in north-eastern New South Wales. Aust. J. Zool. 14, 1073–1137 (1966).Article 

Google Scholar 
Dwyer, P. D. Mortality factors of the bent-winged bat. Vic. Nat. 83, 31–36 (1966).
Google Scholar 
Dwyer, P. D. Seasonal changes in activity and weight of Miniopterus schreibersii blepotis (Chiroptera) in north-eastern NSW. Aust. J. Zool. 12, 52–69 (1964).Article 

Google Scholar 
Bureau of Meteorology. Drought archive. http://www.bom.gov.au/climate/drought/archive.shtml (2019).Dwyer, P. D. Population ranges of Miniopterus schreibersii (Chiroptera) in south-eastern Australia. Aust. J. Zool. 17, 665–686 (1969).Article 

Google Scholar 
Fleischer, T., Gampe, J., Scheuerlein, A. & Kerth, G. Rare catastrophic events drive population dynamics in a bat species with negligible senescence. Sci. Rep. 7, 7370 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Thomas, D. W. Hibernating bats are sensitive to nontactile human disturbance. J. Mammal. 76, 940–946 (1995).Article 

Google Scholar 
Reeder, D. M. et al. Frequent arousal from hibernation linked to severity of infection and mortality in bats with white-nose syndrome. PLoS ONE 7, e38920 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Turbill, C., Bieber, C. & Ruf, T. Hibernation is associated with increased survival and the evolution of slow life histories among mammals. Proc. R. Soc. B Biol. Sci. 278, 3355–3363 (2011).Article 

Google Scholar 
van Harten, E. Population Dynamics of the Critically Endangered, Southern Bent-Winged Bat Miniopterus orianae bassanii (La Trobe University, 2020).
Google Scholar 
PIRSA. History of the south east drainage system – summary. https://www.pir.sa.gov.au/aghistory/natural_resources/water_resources_ag_dev/history_of_the_south_east_drainage_system_-_summary/history_of_the_south_east_drainage_system_-_summary#_ftnref2 (2017).Harding, C., Herpich, D. & Cranswick, R. H. Examining temporal and spatial changes in surface water hydrology of groundwater dependent ecosystems using WOfS (Water Observations from Space): Southern Border Groundwaters Agreement area, South East South Australia. (2018).Holz, P. H., Lumsden, L. F., Reardon, T., Gray, P. & Hufschmid, J. Does size matter? Morphometrics of southern bent-winged bats (Miniopterus orianae bassanii) and eastern bent-winged bats (Miniopterus orianae oceanensis). Aust. Zool. AZ https://doi.org/10.7882/AZ.2019.019 (2020).Article 

Google Scholar 
Rashid, M. M. & Beecham, S. Characterization of meteorological droughts across South Australia. Meteorol. Appl. 26, 556–568 (2019).Article 

Google Scholar 
Culina, A., Linton, D. M., Pradel, R., Bouwhuis, S. & Macdonald, D. W. Live fast, don’t die young: Survival–reproduction trade-offs in long-lived income breeders. J. Anim. Ecol. 88, 746–756 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Kunz, T. H., Whitaker, J. O. & Wadanoli, M. D. Dietary energetics of the insectivorous Mexican free-tailed bat (Tadarida brasiliensis) during pregnancy and lactation. Oecologia 101, 407–415 (1995).CAS 
PubMed 
Article 

Google Scholar 
Adams, R. A. & Hayes, M. A. Water availability and successful lactation by bats as related to climate change in arid regions of western North America. J. Anim. Ecol. 77, 1115–1121 (2008).PubMed 
Article 

Google Scholar 
Henry, M., Thomas, D. W., Vaudry, R. & Carrier, M. Foraging distances and home range of pregnant and lactating little brown bats (Myotis lucifugus). J. Mammal. 83, 767–774 (2002).Article 

Google Scholar 
Lučan, R. & Radil, J. Variability of foraging and roosting activities in adult females of Daubenton’s bat (Myotis daubentonii) in different seasons. Biologia (Bratisl.) 65 (2010).Amorim, F., Jorge, I., Beja, P. & Rebelo, H. Following the water? Landscape-scale temporal changes in bat spatial distribution in relation to Mediterranean summer drought. Ecol. Evol. 8, 5801–5814 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
O’Donnell, C. F. J. Timing of breeding, productivity and survival of long-tailed bats Chalinolobus tuberculatus (Chiroptera: Vespertilionidae) in cold-temperate rainforest in New Zealand. J. Zool. 257, 311–323 (2002).Article 

Google Scholar 
Holz, P. H., Stent, A., Lumsden, L. F. & Hufschmid, J. Trauma found to be a significant cause of death in a pathological investigation of bent-winged bats (Miniopterus orianae). J. Zoo Wildl. Med. 50, 966–971 (2020).PubMed 
Article 

Google Scholar 
Hughes, P. M., Rayner, J. M. V. & Jonesg, G. Ontogeny of ‘true’ flight and other aspects of growth in the bat Pipistrellus pipistrellus. J. Zool. 236, 291–318 (1995).Article 

Google Scholar 
Wund, M. A. Learning and the development of habitat-specific bat echolocation. Anim. Behav. 70, 441–450 (2005).Article 

Google Scholar 
McGuire, L. P. et al. Common condition indices are no more effective than body mass for estimating fat stores in insectivorous bats. J. Mammal. 99, 1065–1071 (2018).Article 

Google Scholar 
Mispagel, C. et al. DDT and metabolites residues in the southern bent-wing bat (Miniopterus schreibersii bassanii) of south-eastern Australia. Chemosphere 55, 997–1003 (2004).CAS 
PubMed 
Article 

Google Scholar 
Allinson, G. et al. Organochlorine and trace metal residues in adult southern bent-wing bat (Miniopterus schreibersii bassanii) in southeastern Australia. Chemosphere 64, 1464–1471 (2006).CAS 
PubMed 
Article 

Google Scholar 
Kolkert, H., Andrew, R., Smith, R., Rader, R. & Reid, N. Insectivorous bats selectively source moths and eat mostly pest insects on dryland and irrigated cotton farms. Ecol. Evol. https://doi.org/10.1002/ece3.5901 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Sherwin, H. A., Montgomery, W. I. & Lundy, M. G. The impact and implications of climate change for bats. Mammal Rev. 43, 171–182 (2013).Article 

Google Scholar 
O’Shea, T. J., Cryan, P. M., Hayman, D. T. S., Plowright, R. K. & Streicker, D. G. Multiple mortality events in bats: A global review. Mammal Rev. 46, 175–190 (2016).Article 

Google Scholar 
Mundinger, C., Scheuerlein, A. & Kerth, G. Long-term study shows that increasing body size in response to warmer summers is associated with a higher mortality risk in a long-lived bat species. Proc. R. Soc. B Biol. Sci. 288, 20210508 (2021).Article 

Google Scholar 
Adams, R. A. & Hayes, M. A. Assemblage-level analysis of sex-ratios in Coloradan bats in relation to climate variables: A model for future expectations. Glob. Ecol. Conserv. 14, e00379 (2018).Article 

Google Scholar 
Crichton, E. G., Seamark, R. F. & Krutzsch, P. H. The status of the corpus luteum during pregnancy in Miniopterus schreibersii (Chiroptera: Vespertilionidae) with emphasis on its role in developmental delay. Cell Tissue Res. 258, 183–201 (1989).CAS 
PubMed 
Article 

Google Scholar 
Olsen, I. C. The analysis of continuous mark-recapture data (Norwegian University of Science and Technology, 2006).
Google Scholar 
Barbour, A. B., Ponciano, J. M. & Lorenzen, K. Apparent survival estimation from continuous mark-recapture/resighting data. Methods Ecol. Evol. 4, 846–853 (2013).Article 

Google Scholar 
van Harten, E. et al. Recovery of southern bent-winged bats (Miniopterus orianae bassanii) after PIT-tagging and the use of surgical adhesive. Aust. Mammal. 42, 216–219 (2020).Article 

Google Scholar 
McDonald, T. L., Amstrup, S. C. & Manly, B. F. Tag loss can bias Jolly-Seber capture-recapture estimates. Wildl. Soc. Bull. 31, 814–822 (2003).
Google Scholar 
van Harten, E. et al. Low rates of PIT-tag loss in an insectivorous bat species. J. Wildl. Manag. 85, 1739–1743 (2021).Article 

Google Scholar 
Lebl, K. & Ruf, T. An easy way to reduce PIT-tag loss in rodents. Ecol. Res. 25, 251–253 (2010).Article 

Google Scholar 
Rigby, E. L., Aegerter, J., Brash, M. & Altringham, J. D. Impact of PIT tagging on recapture rates, body condition and reproductive success of wild Daubenton’s bats (Myotis daubentonii). Vet. Rec. 170, 101 (2012).CAS 
PubMed 
Article 

Google Scholar 
Locatelli, A. G., Ciuti, S., Presetnik, P., Toffoli, R. & Teeling, E. Long-term monitoring of the effects of weather and marking techniques on body condition in the Kuhl’s pipistrelle bat, Pipistrellus kuhlii. Acta Chiropterologica 21, 87–102 (2019).Article 

Google Scholar 
Paniw, M. et al. The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: A global analysis. J. Anim. Ecol. 90, 1398–1407 (2021).PubMed 
Article 

Google Scholar 
Frick, W. F., Kingston, T. & Flanders, J. A review of the major threats and challenges to global bat conservation. Ann. N. Y. Acad. Sci. 1469, 5–25 (2020).PubMed 
Article 

Google Scholar 
Brunet-Rossinni, A. K. & Wilkinson, G. S. Methods for age estimation and the study of senescence in bats. In Ecological and Behavioral Methods for the Study of Bats (eds Kunz, T. H. & Parsons, S.) 315–325 (Johns Hopkins University Press, 2009).
Google Scholar 
Churchill, S. Australian Bats (Allen and Unwin, 2008).
Google Scholar 
Laake, J. L. RMark: An R interface for analysis of capture-recapture data with MARK. 25 (2013).Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference (Springer, 2002). https://doi.org/10.1007/b97636.Book 
MATH 

Google Scholar 
Caswell, H. Matrix population models. In Encyclopedia of Environmetrics (eds El-Shaarawi, A. H. & Piegorsch, W. W.) (Wiley, Berlin, 2006). https://doi.org/10.1002/9780470057339.vam006m.Chapter 

Google Scholar 
Dwyer, P. D. The breeding biology of Miniopterus schreibersii blepotis (Termminck) (Chiroptera) in north-eastern NSW. Aust. J. Zool. 11, 219–240 (1963).Article 

Google Scholar 
Richardson, E. G. The biology and evolution of the reproductive cycle of Miniopterus schreibersii and M. australis (Chiroptera: Vespertilionidae). J. Zool. 183, 353–375 (1977).Article 

Google Scholar  More

Kollas, C., Körner, C. & Randin, C. F. Spring frost and growing season length co-control the cold range limits of broad-leaved trees. J. Biogeogr. 41, 773–783 (2014).Article 

Google Scholar 
Lenz, A., Hoch, G., Körner, C. & Vitasse, Y. Convergence of leaf-out towards minimum risk of freezing damage in temperate trees. Funct. Ecol. 30, 1480–1490 (2016).Article 

Google Scholar 
Körner, C. et al. Where, why and how? Explaining the low-temperature range limits of temperate tree species. J. Ecol. 104, 1076–1088 (2016).Article 
CAS 

Google Scholar 
Körner, C. Plant adaptation to cold climates. F1000Research 5, 2769 (2016).Article 

Google Scholar 
Vitra, A., Lenz, A. & Vitasse, Y. Frost hardening and dehardening potential intemperate trees from winter to budburst. New Phytol. 216, 113–123 (2017).PubMed 
Article 

Google Scholar 
Dy, G. & Payette, S. Frost hollows of the boreal forest as extreme environments for black spruce tree growth. Can. J. For. Res. 37, 492–504 (2007).Article 

Google Scholar 
Marquis, B., Bergeron, Y., Simard, M. & Tremblay, F. Growing-season frost is a better predictor of tree growth than mean annual temperature in boreal mixedwood forest plantations. Glob. Change Biol. 26, 6537–6554 (2020).ADS 
Article 

Google Scholar 
Hufkens, K. et al. Ecological impacts of a widespread frost event following early spring leaf-out. Glob. Change Biol. 18, 2365–2377 (2012).ADS 
Article 

Google Scholar 
Guo, X., Khare, S., Silvestro, R. & Rossi, S. Minimum spring temperatures at the provenance origin drive leaf phenology in sugar maple populations. Tree Physiol. 40, 1639–1647 (2020).CAS 
PubMed 
Article 

Google Scholar 
Marquis, B., Bergeron, Y., Simard, M. & Tremblay, F. Probability of spring frosts, not growing degree-days, drives onset of spruce bud burst in plantations at the boreal-temperate forest ecotone. Front. Plant Sci. 11, 1031 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Mahony, C. R., Cannon, A. J., Wang, T. & Aitken, S. N. A closer look at novel climates: New methods and insights at continental to landscape scales. Glob. Change Biol. 23, 3934–3955 (2017).ADS 
Article 

Google Scholar 
Roman-Palacios, C. & Wiens, J. Recent responses to climate change reveal the drivers of species extinction and survival. Proc. Natl. Acad. Sci. U.S.A. 117, 4211–4217 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Chuine, I. A unified model for budburst of trees. J. Theor. Biol. 207, 337–347 (2000).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Horvath, P. et al. Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models. Biogeosciences 18, 95–112 (2021).ADS 
CAS 
Article 

Google Scholar 
Wullschleger, S. D. et al. Plant functional types in Earth system models: Past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems. Ann. Bot. Lond. 114, 1–16 (2014).CAS 
Article 

Google Scholar 
Deser, C. et al. Insights from earth system model initial-condition large ensembles and future prospects. Nat. Clim. Change 10, 277–286 (2020).ADS 
Article 

Google Scholar 
Machete, R. L. & Smith, L. A. Demonstrating the value of larger ensembles in forecasting physical systems. Tellus A Dyn. Meteorol. Oceanogr. 68, 28393 (2016).Article 

Google Scholar 
Deser, C., Phillips, A., Bourdette, V. & Teng, H. Uncertainty in climate change projections: The role of internal variability. Clim. Dyn. 38, 527–546 (2012).Article 

Google Scholar 
Leduc, M. et al. The ClimEx project: A 50-member ensemble of climate change projections at 12-km resolution over Europe and Northeastern North America with the Canadian regional climate model (CRM5). J. Appl. Meteor. Climatol. 58, 663–693 (2019).ADS 
Article 

Google Scholar 
Innocenti, S., Mailhot, A., Leduc, M., Cannon, A. J. & Frigon, A. Projected changes in the probability distributions, seasonality, and spatiotemporal scaling of daily and subdaily extreme precipitation simulated by a 50-member ensemble over Northeastern North America. J. Geophys. Res. Atmos. 124, 19 (2019).Article 

Google Scholar 
Kay, J. E. et al. The community earth system model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability. Bull. Am. Meteor. Soc. 96, 1333–1349 (2015).ADS 
Article 

Google Scholar 
Thompson, D. W. J., Barnes, E. A., Deser, C., Foust, W. E. & Phillips, A. S. Quantifying the role of internal climate variability in future climate trends. J. Clim. 28, 6443–6456 (2015).ADS 
Article 

Google Scholar 
Kumar, D. & Ganguly, A. R. Intercomparison of model response and internal variability across climate model ensembles. Clim. Dyn. 51, 207–219 (2018).Article 

Google Scholar 
Gu, L. et al. The contribution of internal climate variability to climate change impacts on droughts. Sci. Total Environ. 684, 229–246 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Mittermeier, M., Braun, M., Hofstätter, M., Wang, Y. & Ludwig, R. Detecting climate change effects on Vb cyclones in a 50-member single-model ensemble using machine learning. Geophys. Res. Lett. 46, 14653–14661 (2019).ADS 
Article 

Google Scholar 
Fyfe, J. C. et al. Large near-term projected snowpack loss over the western United States. Nat. Commun. 8, 14996 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).MATH 
Book 

Google Scholar 
Liu, Q. et al. Extension of the growing season increases vegetation exposure to frost. Nat. Commun. 9, 426 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Zohner, C. M. et al. Late-spring frost risk between 1959 and 2017 decreased in North America but increased in Europe and Asia. Proc. Natl. Acad. Sci. U.S.A. 117, 12192–12200 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ma, Q., Huang, J.-G., Hänninen, H. & Berninger, F. Divergent trends in the risk of spring frost damage to trees in Europe with recent warming. Glob. Change Biol. 25, 351–360 (2018).ADS 
Article 

Google Scholar 
Cannell, M. G. R. & Smith, R. I. Climatic warming, spring budburst and forest damage on trees. J. Appl. Ecol. 23, 177–191 (1986).Article 

Google Scholar 
Morin, X. & Chuine, I. Will tree species experience increased frost damage due to climate change because of changes in leaf phenology? Can. J. For. Res. 44, 1555–1565 (2014).Article 

Google Scholar 
Fu, Y. et al. Progress in plant phenology modeling under global climate change. Sci. China Earth Sci. 63, 1237 (2020).ADS 
Article 

Google Scholar 
Gill, A. L. et al. Changes in autumn senescence in northern hemisphere deciduous trees: A meta-analysis of autumn phenology studies. Ann Bot. 116, 875–888 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Perrin, M., Rossi, S. & Isabel, S. N. Synchronisms between bud and cambium phenology in black spruce: Early-flushing provenances exhibit early xylem formation. Tree Physiol. 37, 593–603 (2017).PubMed 
Article 

Google Scholar 
Guo, X. et al. Common-garden experiment reveals clinical trends of bud phenology in black spruce populations from a latitudinal gradient in the boreal forest. J. Ecol. https://doi.org/10.1111/1365-2745.13582 (2021).Article 

Google Scholar 
Usmani, A. et al. Ecotypic differentiation of black spruce populations: Temperature triggers bud burst but not bud set. Trees 34, 1313–1321 (2020).Article 

Google Scholar 
Buttò, V., Rozenberg, P., Deslauriers, A., Rossi, S. & Morin, H. Environmental and developmental factors driving xylem anatomy and micro-density in black spruce. New Phytol. 230, 957. https://doi.org/10.1111/nph.17223 (2021).CAS 
Article 
PubMed 

Google Scholar 
Keenan, T. F. & Richardson, A. D. The timing of autumn senescence is affected by the timing of spring phenology: Implications for predictive models. Glob. Change Biol. 21, 2634–2641 (2015).ADS 
Article 

Google Scholar 
Zani, D., Crowther, T. W., Mo, L., Renner, S. S. & Zohner, C. M. Increased growing-season productivity drives earlier autumn leaf senescence in temperate trees. Science 370, 1066–1071 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Silvestro, R. et al. From phenology to forest management: Ecotypes selection can avoid early or late frosts, but not both. For. Ecol. Manage. 436, 21–26 (2019).Article 

Google Scholar 
D’Orangeville, L. et al. Beneficial effects of climate warming on boreal tree growth may be transitory. Nat. Commun. 9, 3213 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Menezes-Silva, P. E. et al. Different ways to die in a changing world: Consequences of climate change for tree species performance and survival through an ecophysiological perspective. Ecol. Evol. 9, 11979–11999 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Schwarz, J. A., Saha, S. & Bauhus, J. Potential of forest thinning to mitigate drought stress: A meta-analysis. For. Ecol. Manage. 380, 261–273 (2016).Article 

Google Scholar 
Marquis, B., Bergeron, Y., Simard, M. & Tremblay, F. Disentangling the effect of topography and microtopography on near-ground growing-season frosts at the boreal-temperate forest ecotone (Québec, Canada). New For. https://doi.org/10.1007/s11056-021-09840-7 (2021).Article 

Google Scholar 
Marquis, B. growth stagnation of planted spruce in boreal mixedwoods: Importance of landscape, microsite, and growing-season frosts. For. Ecol. Manage. 479, 118533 (2021).Article 

Google Scholar 
Pedlar, J. et al. The implementation of assisted migration in Canadian forests. For. Chron. 87, 766–777 (2011).Article 

Google Scholar 
Marris, E. Planting the forest for the future. Nature 459, 906–908 (2009).CAS 
PubMed 
Article 

Google Scholar 
Klisz, M. et al. Limitations at the limit? Diminishing of genetic effects in Norway spruce provenance trials. Front. Plant Sci. 10, 306 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Pedlar, J. H., McKenney, D. W. & Lu, P. Critical seed transfer distances for selected tree species in eastern North America. J. Ecol. https://doi.org/10.1111/1365-2745.13605 (2021).Article 

Google Scholar 
Prudhomme, G. O. et al. Ecophysiology and growth of white spruce seedlings from various seed sources along a climatic gradient support the need for assisted migration. Front. Plant Sci. 8, 2214 (2017).Article 

Google Scholar 
Girardin, M. P. et al. Annual aboveground carbon uptake enhancements from assisted gene flow in boreal black spruce forests are not long-lasting. Nat. Commun. 12, 1169 (2021).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zohner, C. M., Mo, L., Sebald, V. & Renner, S. S. Leaf-out in northern ecotypes of wide-ranging trees requires less spring warming, enhancing the risk of spring frost damage at cold range limits. Glob. Ecol. Biogeogr. 29, 1065–1072 (2020).Article 

Google Scholar 
Saucier, J.-P., Baldwin, K., Krestov, P. & Jorgenson, T. Boreal forests. In Routledge Handbook of Forest Ecology (eds Peh, K.S.-H. et al.) 7–29 (Routledge, 2015).
Google Scholar 
Hutchinson, M. F. et al. Development and testing of Canada-wide interpolated spatial models of daily minimum-maximum temperature and precipitation for 1961–2003. J. Appl. Meteorol. Climatol. 48, 725–741 (2009).ADS 
Article 

Google Scholar 
Gennaretti, F., Sangelantoni, L. & Grenier, P. Toward daily climate scenarios for Canadian Arctic coastal zones with more realistic temperature-precipitation interdependence. J. Geophys. Res. Atmos. 120, 862–877 (2015).Article 

Google Scholar 
Mpelasoka, F. S. & Chiew, F. H. S. Influence of rainfall scenario construction methods on runoff projections. J. Hydrometeorol. 10, 1168–1183 (2009).ADS 
Article 

Google Scholar 
Giorgi, F. Thirty years of regional climate modeling: Where are we and where are we going next? J. Geophys. Res. 124, 5696–5723 (2019).Article 

Google Scholar 
Laughlin, G. P. & Kalma, J. D. Frost hazard assessment from local weather and terrain data. Agric. For. Meteorol. 40, 1–16 (1987).ADS 
Article 

Google Scholar 
Sørland, S. L., Schar, C., Luthi, D. & Kjellstrom, E. Bias patterns and climate change signals in GCM-RCM model chains. Environ. Res. Lett. 13, 074017 (2018).ADS 
Article 

Google Scholar 
von Trentini, F., Aalbers, E. E., Fischer, E. M. & Ludwig, R. Comparing interannual variability in three regional single-model initial-condition large ensembles (smiles) over Europe. Earth Syst. Dyn. 11, 1013–1031 (2020).ADS 
Article 

Google Scholar 
Hänninen, H. & Pelkonen, H. Effects of temperature on dormancy release in Norway spruce and Scots pine seedlings. Silva Fenn. 22, 5357 (1988).
Google Scholar 
Lechowicz, M. J. Why do temperate deciduous trees leaf out at different times? Adaptation and ecology of forest communities. Am. Nat. 124, 821–842 (1984).Article 

Google Scholar 
Olson, M. S. et al. The adaptive potential of Populus balsamifera L. to phenology requirements in a warmer global climate. Mol. Ecol. 22, 1214–1230 (2013).CAS 
PubMed 
Article 

Google Scholar 
Hawkins, C. D. B. & Dhar, A. Spring bud phenology of 18 Betula papyrifera populations in British Columbia. Scand. J. For. Res. 27, 507–519 (2012).Article 

Google Scholar 
Bronson, D. R., Gower, S. T., Tanner, M. & Van Herk, I. Effect of ecosystem warming on boreal black spruce bud burst and shoot growth. Glob. Change Biol. 15, 1534–1543 (2009).ADS 
Article 

Google Scholar 
Basler, D. Evaluating phenological models for the prediction of leaf-out dates in six temperate tree species across central Europe. Agric. For. Meteorol. 217, 10–21 (2016).ADS 
Article 

Google Scholar 
Man, R., Lu, P. & Dang, Q.-L. Insufficient chilling effects vary among boreal tree species and chilling duration. Front. Plant Sci. https://doi.org/10.3389/fpls.2017.01354 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
R Development Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020). http://www.R-project.org. More