Philippa Kaur

Garfinkel, Y., Ben-Shlomo, D. & Kuperman, T. Large-scale storage of grain surplus in the sixth millennium BC: The silos of Tel Tsaf. Antiquity 83, 309–325 (2009).Article 

Google Scholar 
Rosenberg, D., Garfinkel, Y. & Klimscha, F. Large-scale storage and storage symbolism in the Ancient Near East—a unique clay model of a silo from Tel Tsaf, Israel. Antiquity 91, 885–900 (2017).Article 

Google Scholar 
Ben-Shlomo, D., Hill, A. C. & Garfinkel, Y. Feasting between the revolutions: Evidence from chalcolithic Tel Tsaf, Israel. J. Mediterr. Archaeol. 22, 129–150 (2009).
Google Scholar 
Garfinkel, Y., Ben-Shlomo, D., Freikman, M. & Vered, A. Tel Tsaf: The 2004–2006 excavation seasons. Isr. Explor. J. 57, 1–33 (2007).
Google Scholar 
Freikman, M. & Garfinkel, Y. Sealings before cities: New evidence on the beginnings of administration in the Ancient Near East. Levant 49, 1–22 (2017).Article 

Google Scholar 
Freikman, M., Ben-Shlomo, D. & Garfinkel, Y. A. Stamped sealing from Middle Chalcolithic Tel Tsaf: Implications for the rise of administrative practices in the Levant. Levant 53, 1–12 (2021).Article 

Google Scholar 
Garfinkel, Y., Klimscha, F., Shalev, S. & Rosenberg, D. The beginning of metallurgy in the Southern Levant: A late 6th millennium calBC copper awl from Tel Tsaf, Israel. PLoS One 9, 1–6 (2014).
Google Scholar 
Graham, P. Archaeobotanical remains from late 6th/early 5th millennium BC Tel Tsaf, Israel. J. Archaeol. Sci. 43, 105–110 (2014).Article 

Google Scholar 
Kuijt, I. & Finlayson, B. Evidence for food storage and predomestication granaries 11,000 years ago in the Jordan Valley. PNAS 106, 10966–10970 (2009).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Colledge, S., Conolly, J., Finlayson, B. & Kuijt, I. New insights on plant domestication, production intensification, and food storage: The archaeobotanical evidence from PPNA Dhra. Levant 50, 14–31 (2018).Article 

Google Scholar 
Willcox, G., Fornite, S. & Herveux, L. Early Holocene cultivation before domestication in northern Syria. Veg. Hist. Archaeobot. 17, 313–325 (2008).Article 

Google Scholar 
Palmisano, A. et al. Holocene landscape dynamics and long-term population trends in the Levant. Holocene 29, 708–727 (2019).ADS 
Article 

Google Scholar 
Gophna, R. & Kislev, M. Finds at Tel-Saf (1977–1978). Rev. Bib. 86, 112–114 (1979).
Google Scholar 
Rosenberg, D. et al. Back to Tel Tsaf: A preliminary report on the 2013 season of the renewed project. J. Isr. Prehist. Soc. 44, 148–179 (2014).
Google Scholar 
Lipshchitz, N. Analysis of the botanical remains from Tel Tsaf. Tel Aviv 15, 52–54 (1988).Article 

Google Scholar 
Vita-Finzi, C. et al. Prehistoric economy in the Mount Carmel area of Palestine: Site catchment analysis. In Proceedings of the Prehistoric Society, Vol. 36 (Cambridge University Press, 1970) pp. 1–37.Prior, J. & Price-Williams, D. An investigation of climate change in the Holocene Epoch using archaeological charcoal from Swaziland, South Africa. J. Archaeol. Sci. 12, 457–475 (1985).Article 

Google Scholar 
Shackleton, C. M. & Prins, F. Charcoal analysis and the “Principle of Least Effort”—a conceptual model. J. Archaeol. Sci. 19, 631–637 (1992).Article 

Google Scholar 
Asouti, E. & Austin, P. Reconstructing woodland vegetation and its exploitation by past societies, based on the analysis and interpretation of archaeological wood charcoal macro-remains. Environ. Archaeol. 10, 11–18 (2005).Article 

Google Scholar 
Deckers, K. et al. Characteristics and changes in archaeology-related environmental data during the Third Millennium BC in Upper Mesopotamia. Collective comments to the data discussed during the Symposium. Publ. Inst. Français Études Anatoliennes 19, 573–580 (2007).
Google Scholar 
Marston, J. M. Modeling wood acquisition strategies from archaeological charcoal remains. J. Archaeol. Sci. 36, 2192–2200 (2009).Article 

Google Scholar 
Lev-Yadun, S. Wood remains from archaeological excavations: A review with a Near Eastern perspective. Isr. J. Earth Sci. 56, 139–162 (2007).CAS 
Article 

Google Scholar 
Liphschitz, N. Timber in Ancient Israel Dendroarchaeology and Dendrochronology. Monograph Series of the Institute of Archaeology of Tel Aviv University 26 (Tel Aviv, 2007).Sitry, I. & Langgut, D. Wooden objects from the colt collection—Shivta. Michmanim 28, 31–46 (2019).
Google Scholar 
Srebro, H. & Soffer, T. The New Atlas of Israel: The National Atlas (Survey of Israel; The Hebrew University of Jerusalem, 2011).
Google Scholar 
Gophna, R. & Sadeh, S. Excavations at Tel Tsaf: An early Chalcolithic site in the Jordan Valley. Tel Aviv. 15–16, 3–36 (1988–89).Garfinkel, Y., Ben-Shlomo, D. & Freikman, M. Excavations at Tel Tsaf 2004–2007: Final Report, Volume 1 (Ariel University Press, 2020).
Google Scholar 
Rosenberg, D., Pinsky, S. & Klimscha, F. “The renewed research project at Tel Tsaf, Jordan Valley—2013–2019” in Hadashot Arkeologiyot—Excavations and Surveys in Israel, p. 133 (2021).Gopher, A. The Pottery Neolithic in the southern Levant—a second Neolithic revolution. In Village Communities of the Pottery Neolithic Period in the Menashe Hills, Israel (ed. Gopher, A.) 1525–1611 (Tel Aviv University, 2012).
Google Scholar 
Streit, K. & Garfinkel, Y. Tel Tsaf and the impact of the Ubaid Culture on the Southern Levant: Interpreting the radiocarbon evidence. Radiocarbon 57, 865–880 (2015).Article 

Google Scholar 
Streit, K. & Garfinkel, Y. A specialized ceramic assemblage for water pulling: The Middle Chalcolithic well of Tel Tsaf, Israel. BASOR 374, 61–73 (2015).
Google Scholar 
Garfinkel, Y. Proto-historic courtyard buildings in the southern Levant. In Neolithic and Chalcolithic Archaeology in Eurasia: Building Techniques and Spatial Organization (ed. Gheorghiu, D.) 35–41 (BAR International Series, 2010).
Google Scholar 
Zohary, M. Geobotanical Foundations of the Middle East (Gustav Gischer Verlag, 1973).
Google Scholar 
Bar-Matthews, M. & Ayalon, A. Mid-Holocene climate variations revealed by high-resolution speleothem records from Soreq Cave, Israel and their correlation with cultural changes. Holocene 21, 163–171 (2011).ADS 
Article 

Google Scholar 
Fahn, A., Werker, E. & Baas, P. Wood Anatomy and Identification of Trees and Shrubs from Israel and Adjacent Regions (The Israel Academy of Sciences and Humanities, 1986).
Google Scholar 
Schweingruber, F. H. Anatomy of European Woods (Verlag Paul Haupt, 1990).
Google Scholar 
Bronk Ramsey, C. Bayesian analysis of radiocarbon dates. Radiocarbon 51, 337–360 (2009).Article 

Google Scholar 
Reimer, P. et al. The IntCal20 northern hemisphere radiocarbon age calibration curve (0–55 cal kBP). Radiocarbon 62, 725–757 (2020).CAS 
Article 

Google Scholar 
Zohary, M. Plant Life of Palestine: Israel and Jordan (Ronald Press Co, 1962).
Google Scholar 
Asouti, E. & Hather, J. Charcoal analysis and the reconstruction of ancient woodland vegetation in the Konya Basin, south-central Anatolia, Turkey: Results from the Neolithic site of Çatalhöyük East. Veg. Hist. Archaeobot. 10, 23–32 (2001).Article 

Google Scholar 
Thery-Parisot, I., Chabal, L. & Chrzavzez, J. Anthracology and taphonomy, from wood gathering to charcoal analysis: A review of the taphonomic processes modifying charcoal assemblages, in archaeological contexts. Palaeogeogr. Palaeoclim. Palaeoecol. 291, 142–153 (2010).ADS 
Article 

Google Scholar 
Langgut, D. et al. The earliest near-eastern wooden spinning implements. Antiquity 90, 973–990 (2016).Article 

Google Scholar 
Langgut, D., Tepper, Y., Benzaquen, M., Erickson-Gini, T. & Bar-Oz, G. Environment and horticulture in the Byzantine Negev Desert, Israel: Sustainability, prosperity and enigmatic decline. Quat. Int. 593, 160–177 (2021).Article 

Google Scholar 
Zohary, D. & Spiegel-Roy, P. Beginnings of fruit growing in the Old World. Science 187, 319–327 (1975).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Zohary, D., Hopf, M. & Weiss, E. Domestication of Plants in the Old World 4th edn. (Oxford University Press, 2012).Book 

Google Scholar 
Weiss, E. Beginnings of fruit growing in the Old World two generations later. Isr. J. Plant Sci. 62, 75–85 (2015).Article 

Google Scholar 
Benzaquen, M., Finkelstein, I. & Langgut, D. Vegetation history and human Impact on the environs of Tel Megiddo in the Bronze and Iron Ages (ca 3,500–500 BCE): A dendroarchaeological analysis. Tel Aviv. 49, 1–23 (2019).
Google Scholar 
Carrión, Y., Ntinou, M. & Bada, E. Olea europaea L. in the north Mediterranean Basin during the Pleniglacial and the Early-Middle Holocene. Quat. Sci. Rev. 29, 952–968 (2010).ADS 
Article 

Google Scholar 
Lavee, S. & Zohary, D. The potential of genetic diversity and the effect of geographically isolated resources in olive breeding. Isr. J. Plant Sci. 59, 3–13 (2011).Article 

Google Scholar 
Langgut, D. et al. The origin and spread of olive cultivation in the Mediterranean Basin: The fossil pollen evidence. Holocene 29, 602–922 (2019).Article 

Google Scholar 
Neef, R. Introduction, development and environmental implications of olive culture: The evidence from Jordan. In Man’s Role in the Shaping of the Eastern Mediterranean Landscape (eds Bottema, S. et al.) 295–306 (Rotterdam, 1990).
Google Scholar 
Meadows, J. Olive domestication at Teleilat Ghassul. In Archaeology of the Near East: An Australian Perspective (eds Hopkins, L. & Parker, A.) 13–18 (University of Sydney, 2001).
Google Scholar 
Dighton, A., Fairbairn, A., Bourke, S., Faith, J. T. & Habgood, P. Bronze Age olive domestication in the north Jordan valley: New morphological evidence for regional complexity in early arboricultural practice from Pella in Jordan. Veg. Hist. Archaeobot. 26, 403–413 (2017).Article 

Google Scholar 
Galili, E., Stanley, D. J., Sharvit, J. & Weinstein-Evron, M. Evidence for earliest olive-oil production in submerged settlements off the Carmel Coast, Israel. J. Archaeol. Sci. 24, 1141–1150 (1997).Article 

Google Scholar 
Galili, E. et al. Coastal paleoenvironments and prehistory of the Submerged Pottery Neolithic Settlement of Kfar Samir (Israel). Paléorient 44, 113–132 (2018).
Google Scholar 
Namdar, D., Amrani, A., Getzov, N. & Milevski, I. Olive oil storage during the fifth and sixth millennia BC at Ein Zippori, northern Israel. Isr. J. Plant Sci. 62, 65–74 (2015).Article 

Google Scholar 
Galili, E. et al. Early production of Table Olives at a mid-7th millennium BP submerged site off the Carmel Coast (Israel). Sci. Rep. 11, 1–15 (2021).Article 
CAS 

Google Scholar 
Epstein, C. Oil production in the Golan Heights during the Chalcolithic period. Tel Aviv. 20, 133–146 (1993).Article 

Google Scholar 
Eitam, D. Between the [olive] rows, oil will be produced, presses will be trod…. (Job 24, 11). In La Production du Vin et l’Huile en Mediterranée:[Actes du Symposium International, (Aix-en-Provence et Toulon, 20-22 Novembre 1991 (Bulletin de correspondence hellénique, Supplementary 26) (eds Amouretti, M. C. & Brun, J. P.) 65–90 (Ecole Francaise d’Athènes, 1993).
Google Scholar 
Schiebel, V. Vegetation and Climate History of the Southern Levant During the Last 30000 Years Based on Palynological Investigation (University of Bonn, 2013) PhD Dissertation.Litt, T., Ohlwein, C., Neumann, F. H., Hense, A. & Stein, M. Holocene climate variability in the Levant from the Dead Sea pollen record. Quat. Sci. Rev. 49, 95–105 (2012).ADS 
Article 

Google Scholar 
Van Zeist, W., Baruch, U. & Bottema, S. Holocene palaeoecology of the Hula area, Northeastern Israel. In A Timeless Vale, Archaeological and Related Essays on the Jordan Valley (eds Kaptijn, K. & Petit, L. P.) 29–64 (Leiden University Press, 2009).
Google Scholar 
Neumann, F., Schölzel, C., Litt, T., Hense, A. & Stein, M. Holocene vegetation and climate history of the northern Golan heights (Near East). Veg. Hist. Archaeobot. 16, 329–346 (2007).Article 

Google Scholar 
Kaniewski, D. et al. Primary domestication and early uses of the emblematic olive tree: Palaeobotanical, historical and molecular evidence from the Middle East. Biol. Rev. 87, 885–899 (2012).PubMed 
Article 

Google Scholar 
Moriondo, M. et al. Olive trees as bio-indicators of climate evolution in the Mediterranean Basin. Glob. Ecol. Biogeogr. 22, 818–833 (2013).Article 

Google Scholar 
Langgut, D., Cheddadi, R. & Sharon, G. Climate and environmental reconstruction of the Epipaleolithic Mediterranean Levant (22.0-11.9 ka cal. BP). Quat. Sci. Rev. 270, 107170 (2021).Article 

Google Scholar 
Zinger, A. Olive Cultivation 145th edn. (Israel Ministry of Agriculture, 1995) (in Hebrew).
Google Scholar 
Miller, N. F. Sweeter than wine? The use of the grape in early western Asia. Antiquity 82, 937–946 (2008).Article 

Google Scholar 
Fuller, D. Q. & Stevens, C. J. Between domestication and civilization: The role of agriculture and arboriculture in the emergence of the first urban societies. Veg. Hist. Archaeobot. 28, 263–282 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Lev-Yadun, S. The common fig (Ficus carica) remains in the archaeological record and its domestication processes. In The Fig: Advances in Research and Sustainable Production (eds Flaishman, M. A. & Aksoy, U.) 11–25 (CABI, 2022).
Google Scholar 
Flaishman, M., Rodov, V. & Stover, E. The fig: Botany, horticulture and breeding. Hortic. Rev. 34, 113–196 (2008).CAS 
Article 

Google Scholar 
Langgut, D., Lev-Yadun, S. & Finkelstein, I. The Impact of olive orchard abandonment and rehabilitation on pollen signature: An experimental approach to evaluating fossil pollen data. Ethnoarchaeology 6, 121–135 (2014).Article 

Google Scholar 
Hobbs, J. J. Bedouin Life in the Egyptian Wilderness (University of Texas Press, 1989).
Google Scholar 
Andersen, G. L. et al. Traditional nomadic tending of trees in the Red Sea Hills. J. Arid Environ. 106, 36–44 (2014).ADS 
Article 

Google Scholar 
Mor, E. Reconstructing Tel Bet Yerah’s Natural and Anthropogenic Environment During the Early Bronze Age Through Wood Remains (Tel Aviv University, 2022) MA Thesis, in Hebrew with English abstract.Kislev, M. E., Hartman, A. & Bar-Yosef, O. Early domesticated fig in the Jordan Velley. Science 312, 1372–1374 (2006).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Lev-Yadun, S., Neeman, G., Abbo, S. & Flaishman, M. A. Comment on “Early Domesticated Fig in the Jordan Valley”.. Science 314, 1683a (2006).ADS 
Article 
CAS 

Google Scholar 
Denham, T. Early fig domestication, or gathering of wild parthenocarpic figs?. Antiquity 81, 457–461 (2007).Article 

Google Scholar 
Abbo, S., Gopher, A. & Lev-Yadun, S. Fruit domestication in the near east. Plant Breed. Rev. 39, 325–377 (2015).
Google Scholar 
Gopher, A., Lev-Yadun, S. & Abbo, S. Breaking Ground. Plant Domestication in the Neolithic Levant: The “Core-Area—One-Event” Model Emery and Claire Yass Publications in Archaeology (Tel Aviv University, Tel Aviv, The Institute of Archaeology, 2021).
Google Scholar 
Shennan, S. Property and wealth inequality as cultural niche construction. Philos. Trans. R. Soc. B. Biol. Sci. 366, 918–926 (2011).Article 

Google Scholar 
Twiss, K. The archaeology of food and social diversity. J. Archaeol. Res. 20, 357–395 (2012).Article 

Google Scholar 
Bowles, S. & Choi, J. K. Coevolution of farming and private property during the early Holocene. Proc. Natl. Acad. Sci. 110, 8830–8835 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zeder, M. A. Domestication as a model system for niche construction theory. Evol. Ecol. 30, 325–348 (2016).Article 

Google Scholar 
Khalil, E. L. Symbolic products: Prestige, pride and identity goods. Theory Decis. 49, 53–77 (2000).MATH 
Article 

Google Scholar 
Nelissen, R. M. & Meijers, M. H. Social benefits of luxury brands as costly signals of wealth and status. Evol. Hum. Behav. 32, 343–355 (2011).Article 

Google Scholar 
Plourde, A. M. The origins of prestige goods as honest signals of skill and knowledge. Hum. Nat. 19, 374–388 (2008).PubMed 
Article 

Google Scholar 
Hayden, B. The proof is in the pudding: Feasting and the origins of domestication. Curr. Anthropolac. 50, 597–601 (2009).Article 

Google Scholar 
Yahalom-Mack, N. et al. The earliest lead object in the levant. PLoS One 10, e0142948 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Mayshar, J., Moav, M., Neeman, Z. & Pascali, L. The origin of the state: Land productivity or appropriability. J. Polit. Econ. 130, 1091–1144 (2022).Article 

Google Scholar 
Langgut, D. & Sasi, A. The emergence of fruit tree horticulture in Chalcolithic southern Levant. In (Ben-Yosef, E., Jones, I. Eds) And in Length of Days Understanding” (Job 12:12)—Essays on Archaeology in the 21st Century in Honor of Thomas E. Levy (In Press). More

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

A common but controversial sunscreen ingredient that is thought to harm corals might do so because of a chemical reaction that causes it to damage cells in the presence of ultraviolet light. Researchers have discovered that sea anemones, which are similar to corals, make the molecule oxybenzone water-soluble by tacking a sugar onto it. This inadvertently turns oxybenzone into a molecule that — instead of blocking UV light — is activated by sunlight to produce free radicals that can bleach and kill corals. “This metabolic pathway that is meant to detoxify is actually making a toxin,” says Djordje Vuckovic, an environmental engineer at Stanford University in California, who was part of the research team. The animals “convert a sunscreen into something that’s essentially the opposite of a sunscreen”.Oxybenzone is the sun-blocking agent in many suncreams. Its chemical structure causes it to absorb UV rays, preventing damage to skin cells. But it has attracted controversy in recent years after studies reported that it can damage coral DNA, interfere with their endocrine systems and cause deformities in their larvae2. These concerns have led to some beaches in Hawaii, Palau and the US Virgin Islands, banning oxybenzone-containing sunscreens. Last year, the US National Academies of Sciences, Engineering, and Medicine convened a committee to review the science on sunscreen chemicals in aquatic ecosystems; its report is expected in the next few months.The latest study, published on 5 May in Science1, highlights that there has been little research into the potentially toxic effects of the by-products of some substances in sunscreens, says Brett Sallach, an environmental scientist at the University of York, UK. “It’s important to track not just the parent compound, but these transformed compounds that can be toxic,” he says. “From a regulatory standpoint, we have very little understanding of what transformed products are out there and their effects on the environment.”But other factors also threaten the health of coral reefs; these include climate change, ocean acidification, coastal pollution and overfishing that depletes key members of reef ecosystems. The study does not show where oxybenzone ranks in the list.Simulated seaTo understand oxybenzone’s effects, Vuckovic, environmental engineer William Mitch at Stanford and their colleagues turned to sea anemones, which are closely related to corals, and similarly harbour symbiotic algae that give them colour.The researchers exposed anemones with and without the algae to oxybenzone in artificial seawater, and illuminated them with light — including the UV spectrum — that mimicked the 24-hour sunlight cycle. All the animals exposed to both the chemical and sunlight died within 17 days. But those exposed to sunlight without oxybenzone or to oxybenzone without UV light lived.Oxybenzone alone did not produce dangerous reactive molecules when exposed to sunlight, as had been expected, so the researchers thought that the molecule might be metabolized in some way. When they analysed anemone tissues, they found that the chemical bound to sugars accumulated in them, where it triggered the formation of oxygen-based free radicals that are lethal to corals. “Understanding this mechanism could help identify sunscreen molecules without this effect,” Mitch says.The sugar-bound form of oxybenzone amassed at higher levels in the symbiotic algae than in the anemones’ own cells. Sea anemones lacking algae died around a week after exposure to oxybenzone and sunlight, compared with 17 days for those with algae. That suggests the algae protected the animals from oxybenzone’s harmful effects.Corals that have been subject to environmental stressors such as changing temperatures often become bleached, losing their symbiotic algae. “If they’re weaker in this state, rising sea water temperature or ocean acidification might make them more susceptible to these local, anthropogenic contaminants,” Mitch says.Greater dangerIt’s not clear how closely these laboratory-based studies mimic the reality of reef ecosystems. The concentration of oxybenzone at a coral reef can vary widely, depending on factors such as tourist activity and water conditions. Sallach points out that the concentrations used in the study are more like “worst-case exposure” than normal environmental conditions.The study lacks “ecological realism”, agrees Terry Hughes, a marine biologist at James Cook University in Townsville, Australia. Coral-bleaching events on Australia’s Great Barrier Reef, for example, have been linked more closely to trends in water temperature than to shifts in tourist activity. “Mass bleaching happens regardless of where the tourists are,” Hughes says. “Even the most remote, most pristine reefs are bleaching because water temperatures are killing them.”Hughes emphasizes that the greatest threats to reefs remain rising temperatures, coastal pollution and overfishing. Changing sunscreens might not do much to protect coral reefs, Hughes says. “It’s ironic that people will change their sunscreens and fly from New York to Miami to go to the beach,” he says. “Most tourists are happy to use a different brand of sunscreen, but not to fly less and reduce carbon emissions.” More

RBD severity in different rice ecosystems of KarnatakaBased on the observations made during the exploratory surveys of 2018 and 2019 (Table 1 and Fig. 1), it was found that RBD severity significantly varied across studied areas and districts (Fig. 2). The disease severity was highest in Chikmagalur, followed by Kodagu, Shivamogga, Mysore, and Mandya districts which belong to Hilly and Kaveri ecosystems. At the same time, the lowest severity was documented in Udupi, Gulbarga, Gadag, Dakshin Kannad, Raichur, and Bellary districts of coastal, UKP, and TBP ecosystems (Fig. 3A).Table 1 Details of diverse rice-growing ecosystems selected for the study.Full size tableFigure 1Featured map of South-East Asia (A), India (B), and Karnataka (C). A total of 18 administrative districts of Karnataka were considered to gather data on rice blast disease. The area of different districts under study is shown (D). The maps were created using R software (version R-4.0.3).Full size imageFigure 2Distribution map indicating the sampling sites and the severity of rice blast disease in different rice ecosystems of Karnataka during 2018 and 2019. The maps were created using R software (version R-4.0.3).Full size imageFigure 3(A) Bar graph repressing the severity of rice blast disease (RBD) in different districts of Karnataka during 2018 and 2019. (B) Clustering of districts based on the severity of RBD in different districts of Karnataka by hclust method.Full size imageHierarchical cluster analysis using the average linkage method for RBD severity among the 18 administrative districts of diverse rice ecosystems of Karnataka identified two main clusters, namely, cluster I and cluster II (Fig. 3B). Cluster I consist of two subclusters, cluster IA and IB. Subcluster IA consists of Mandya, Dharwad, Mysore, Hassan, Shivamogga, Haveri, and Belgaum; While, Kodagu, and Chikmagalur districts were clustered in IB. Similarly, Cluster II was divided into cluster IIA and cluster IIB. Subcluster IIA comprises Udupi, Gulbarga, Gadag, Raichur, Dakshin Kannad, Uttar Kannad, Koppal and Bellary, and Davanagere district was grouped under cluster IIB.Spatial point pattern analysis of RBDThe cluster and outlier analysis was done using Local Moran’s I and p-values. The analyses have identified RBD cluster patterns at the district level during 2018 and 2019, representing dispersed and aggregated clusters of severity (Fig. 4). Based on positive I value, most of the districts were clustered together (at I  > 0), except the coastal districts such as Uttar Kannad, Udupi, Dakshin Kannad, and interior districts such as Dharwad, Davanagere, and Chikmagalur, which exhibited negative I value (at I  More

Effects of the application of different improved materials on properties of reclaimed soilSoil organic matter (SOM) and total nitrogen (TN)After the application of different improved materials, the SOM and TN contents in both 0–0.15 m and 0.15–0.30 m layers of the hollow village reclaimed soil showed an overall increasing trend (Fig. 1). In the 0–0.15 m layer, the organic matter content increased by 9.6%, 79.0%, 90.0%, 61.4%, 120.1%, and 131.7% respectively under TM, TF, TO, TMF, TMO and TFO treatments compared with CK treatment, indicating that different improved materials all played important roles in improving the organic matter content of reclaimed soil (Fig. 1a). The improvement of organic matter content in the 0–0.15 m layer of reclaimed soil by the treatments of different improved materials showed as follows: TFO  > TMO  > TO  > TF  > TMF  > TM  > CK, and TO, TMO and TFO treatments with organic fertilizer addition could significantly improve the organic matter content of the reclaimed soil (P  2 mm water-stable aggregates was increased by 88.1%, 194.5%, 203.7%, 376.2%, and 781.7% respectively under TF, TO, TMF, TMO and TFO compared with CK. The proportion of water-stable macroaggregates under different treatments showed as follows: TFO (35.8%)  > TMO (20.7%)  > TO (16.9%)  > TMF (16.3%)  > TF (12.3%)  > TM (10.1%)  > CK (9.0%), and the water-stable macroaggregates were increased by 328.2%, 130.0%, 87.8%, 81.1%, 36.7%, and 12.2% respectively compared with CK, with the maximum increase of 328.2%. In general, all six different amendment material treatments increased the proportion of water-stable macroaggregates in reclaimed soil and promoted the aggregation and cementation of water-stable microaggregates ( 0.25 mm). And the TFO showed the best effect on the increase of water-stable macroaggregates, followed by TMO, TO, and TMF, while TF and TM treatments showed little effect.Figure 2Percentage (%) of soil water-stable aggregates under the application of different improved materials at 0.15–0.30 m Depth. CK: no improved material; TM: maturing agent (ferrous sulfate); TF: fly ash; TO: organic fertilize; TMF: maturing agent + fly ash, TMO: maturing agent + organic fertilizer; TFO: fly ash + organic fertilizer. Different lowercase letters represent significant differences among different improved material treatments in the same particle-size aggregates.Full size imageFigure 3Percentage (%) of soil water-stable aggregates under the application of different improved materials at 0.15–0.30 m Layer. CK: no improved material; TM: maturing agent (ferrous sulfate); TF: fly ash; TO: organic fertilize; TMF: maturing agent + fly ash, TMO: maturing agent + organic fertilizer; TFO: fly ash + organic fertilizer. Different lowercase letters represent significant differences among different improved material treatments in the same particle-size aggregates.Full size imageIn the 0.15–0.30 m layer, the change of water-stable aggregates showed a similar trend to that in the 0–0.15 m layer compared with CK treatment. TF, TO, TMF, TMO and TFO treatments all significantly increased the proportion of  > 2 mm and 1–2 mm water-stable aggregates, and decreased the proportion of water-stable microaggregates (P  2 mm water-stable aggregates by 130.3%, 94.5%, 133.9%, 151.4%, and 309.2% respectively compared with CK, of which TFO treatment showed the most significant effect on the increase of the proportion of water-stable macroaggregates. Compared with the 0–0.15 m layer, the proportion of water-stable macroaggregates in the 0.15–0.30 m layer showed a gradual decrease with the increase of soil depth.Water-stable aggregates structure stabilityThe mean weight diameter (MWD), geometric mean diameter (GMD), unstable aggregate index (ELT), and fractal dimension (D) are important indicators reflecting the structural geometry and stability of soil aggregates, and it has been indicated in this research that the higher the MWD and GMD and the smaller the ELT and D, the better the structural stability of the aggregates and the soil structure27,28. Compared with CK treatment, the MWD and GMD showed a trend of significant increase while the D and ELT showed a trend of significant decrease (P  TF  > TMF  > TM  > CK. The combination of organic–inorganic improved materials can effectively reduce the BD of reclaimed soil, and the BD under TFO treatment was the smallest, 1.19 g cm−3. In the 0.15–0.30 m layer, through variance analysis, the effect of different improved materials on the BD showed a similar decreasing trend to that in the 0–0.15 m layer.Figure 4Effects of the application of different improved materials on BD and SMC. CK: no improved material; TM: maturing agent (ferrous sulfate); TF: fly ash; TO: organic fertilize; TMF: maturing agent + fly ash, TMO: maturing agent + organic fertilizer; TFO: fly ash + organic fertilizer; BD, soil bulk density; SMC, soil moisture content. Different lowercase letters represent significant differences among different improved material treatments in the same soil layer.Full size imageThe soil moisture content (SMC) of the reclaimed soil in the 0–0.15 m and 0.15–0.30 m layers increased significantly after the application of different improved materials (P  TMO  > TMF  > TO  > TF≈TM  > CK (Fig. 4b). In the 0–0.15 m soil layer, the SMC under TM, TF, TO, TMF, TMO and TFO treatments was increased by13.5%, 13.8%, 21.4%, 21.9%, 32.4% and 38.3% respectively compared with CK. The TMO and TFO showed the most significant positive effect on the SMC of reclaimed soil, and the mass water content was 17.4% and 18.2% respectively. In conclusion, compared with CK, these improved materials increased the SOM content and porosity, promoted the formation and stability of aggregates, and increased the retention and transmission of water, which was helpful to maintain more water. Among them, the coupling treatment of organic and inorganic improved materials can hold more soil moisture, and the most significant increase was observed under TFO and TMO.Correlation analysis between soil organic matter and water-stable aggregates parametersTo further explore the correlation between the parameters of the reclaimed soil after the application of six different improved materials, a regression analysis was conducted in this paper on the correlation between the parameters of organic matter and water-stable aggregates with different particle sizes. From Table 2, it could be seen that the organic matter content had a highly significant positive correlation with MWD, GMD and  > 2 mm water-stable aggregates content and a highly significant negative correlation with ELT, D and water-stable microaggregates content ( 2 mm, 1–2 mm, and 0.5–1 mm) content had a significant positive correlation with MWD and GMD values and a highly significant negative correlation with ELT and D values; water-stable microaggregates ( TMO  > TO  > TMF  > TF  > TM  > CK, and different improved materials all significantly increased maize yield compared with CK (P  More

Study area and speciesWe selected three sites across an elevation gradient in the western Swiss Alps (Bex, Canton de Vaud), situated at 890, 1400 and 1900 m above sea level (hereafter, the low, middle, and high sites; Supplementary Fig. 1). The three sites span a temperature gradient ranging from 2.5 to 9.6 °C (mean annual temperature from 1981 to 201544; Supplementary Table 1). With increasing elevation, soil moisture increased, and the growing season length was shortened by a longer snow-covered period, as measured from July 2019 to June 2020 (Supplementary Fig. 2). All sites were established on south-facing and shallow slopes in pasture and fenced to exclude livestock.We included 14 herbaceous focal species that frequently occur in this region, half of which originated from low elevation (hereafter lowland species) and half from high elevation (highland species, Supplementary Table 2). Lowland species had upper range limits (defined as the 90th percentile of their elevation distribution) below 1500 m (with the exception of Plantago lanceolata, with a 90th percentile of 1657 m), while highland species had lower range limits (defined as the 10th percentile of their elevation distribution) above 1500 m, based on a dataset of 550 vegetation plots from the study area45. These species consisted of 12 perennial and two biennial species, which are the dominant life histories in this region. Species were selected to include a range of functional types (7 forbs, 4 grasses, 3 legumes) and functional traits (based on plant height, specific leaf area and seed mass). Seeds were obtained from regional suppliers given the large quantities that were needed to establish the experiment (Supplementary Table 2).Field competition experimentWe designed a field experiment to study the effects of elevation on population growth rates and competitive outcomes by growing focal plants either without competition or competing with a background monoculture of the same or another species (Supplementary Fig. 1). In spring 2017, we established 18 plots (1.6 × 1 m, 0.2 m deep) at each of the three field sites, lined with wire mesh to exclude rodents (except at the high site) and with weed-suppressing fabric on the sides to prevent roots growing in from outside. To control for soil effects, the beds were then filled with a silt loam soil that originated from a nutrient-poor meadow at 1000 m a.s.l. within the study area. Four plots were maintained as bare soil plots (non-competition plots). The other 14 plots received 9 g m−2 of viable seeds of each species, which allowed the establishment of a monoculture of relatively high density (competition plots). We then periodically weeded the plots to maintain monocultures over the course of the experiment. All species except for two (Arnica montana and Daucus carota) successfully established monocultures, of which 11 species (including six lowland species and five highland species) were fully established by autumn 2017. We then resowed the other plots that failed to establish, which subsequently established either in spring 2018 (Poa trivialis and Poa alpina in the low site and Bromus erectus in the middle site) or autumn 2018 (Aster alpinus, P. trivialis and P. alpina in the middle site and Sesleria caerulea in the low and high sites). Species that failed to establish were included only as focal species for the calculation of invasion population growth rates (i.e. the density was low for A. montana and D. carota in all sites, Trifolium badium in the low site and S. caerulea in the middle site, probably due to high mortality rates caused by drought).We first raised focal seedlings of each species in a greenhouse for six weeks on standard compost and then transplanted them into the field (Supplementary Fig. 1). To test for responses to elevation in the absence of competition, focal plants were transplanted into non-competition plots at 25 cm apart in autumn 2017 (n = 9 per species and site). To test for effects of competition, we transplanted focal individuals into established plots with 14 cm spacing (n = 9 per focal species, competitor and site). Focal plants that died within two weeks of transplanting were replaced (ca. 5%), assuming mortality was caused by transplant shock. Note that we transplanted focal plants into plots only when the background monocultures were fully established. In 2018 and 2019, we replaced dead focal individuals in spring and autumn (ca. 10% each time). The full design included 56 unique interspecific pairs in each site accounting for 61% of all 14 × 13 = 91 possible pairwise combinations. These pairs were selected to evenly sample differences in functional trait space based on a pilot analysis using plant height, specific leaf area and seed mass obtained from the LEDA dataset46. Each focal species competed against four lowland and four highland species, yielding 14 lowland–lowland and highland–highland pairs and 28 lowland–highland pairs. Across all three sites, this design resulted in N = 3780 individuals in total ([56 interspecific pairs × 2 + 14 intraspecific pairs + 14 non-competition] × 9 individuals × 3 sites).Demographic dataWe followed each focal individual between 2017 and 2020 to monitor individual-based demographic performance (i.e. vital rates; Supplementary Fig. 4). Survival was monitored twice a year at the beginning and the end of the growing season. Towards the end of the growing season each year (August–September), we measured all individuals to record plant size, whether they flowered, and to estimate seed production on flowering individuals. To estimate focal plant size, we measured size-related morphological traits on all focal individuals at each census (i.e. the number and/or length of flowering stalks, leaves or ramets, depending on the species) and estimated dry aboveground biomass using regression models fitted using collected plant samples (mean R2 = 0.871; Supplementary Data 1; Supplementary Methods). To estimate seed production, we counted the number and measured the size of fruits on reproductive individuals; we then estimated the number of seeds produced by each individual using regression models fitted using intact fruits of each species collected at the early fruiting stage on background plants (mean R2 = 0.806; Supplementary Data 2; Supplementary Methods). We conducted a separate experiment to estimate the germination and recruitment of each species in each site (Supplementary Methods).Population modellingTo estimate population growth rates (λ), we built integral projection models to incorporate multiple vital rates across the life cycle47 (see Supplementary Table 3 for model structure and parameters). Separate IPMs were built to estimate intrinsic growth rates using plants growing in the absence of competition (in non-competition plots) and invasion growth rates using plants growing within the background monocultures (in competition plots), under the assumption that monocultures were at equilibrium (see Supplementary Fig. 5 for a test of this assumption) and that focal individuals did not interact with each other but only with the background species. We used plant size (i.e. estimated dry aboveground biomass, log scale) as a continuous state variable and fitted linear models to estimate vital rate parameters by combining multiple-year demographic data over three censuses (i.e. 2017–2018, 2018–2019, and 2019–2020; see Supplementary Methods for consideration of more complex models). We modelled the probability of survival, flowering, and seedling establishment using generalized linear models with a binomial error distribution, modelled growth and seed production using general linear models and described the offspring size distribution using Gaussian probability density functions. We modelled seed germination, seedling establishment and the seedling size distribution as size-independent functions, assuming they are unaffected by maternal size (Supplementary Fig. 4; Supplementary Table 3). For each vital rate of each species, we selected the best-fitted vital rate model by comparing all nested models of the full models using the Akaike information criterion corrected for small samples (AICc), which allowed us to avoid overfitting models and to borrow strength across competitor species and sites in cases where full models were outperformed by reduced models (Supplementary Methods; Supplementary Data 3 and 4).We calculated population growth rates (λ) as the dominant eigenvalue of the IPMs, which represents the discrete per-capita growth rate (i.e. ({N}_{t+1}=lambda {N}_{t}))47. To evaluate the uncertainty around λ, we performed parametric bootstraps for size-dependent vital rates (i.e. survival, growth, flowering, and fecundity). Specifically, we resampled the parameters of each vital rate model using multivariate normal distributions based on their means and covariance matrices48. We then fitted all IPMs and estimated λ for each of the 500 bootstrap replicates (Supplementary Data 5).Estimation of niche differences, relative fitness differences, and coexistence outcomesWe quantified niche and relative fitness differences and predicted coexistence outcomes following the method of Carroll et al.49. This method is based on species’ sensitivity to competition defined as the proportional reduction of the population growth rate of a focal species i when invading a population of a competitor species j that is at its single-species equilibrium, and is mathematically equivalent to one minus the response ratio:$${S}_{ij}=1-frac{{{{{{{rm{ln}}}}}}}(lambda_{{ij}})}{{{{{{rm{ln}}}}}}({lambda}_{i})}$$
(1)
where λij denotes the invasion growth rate of focal species i and λi is its intrinsic growth rate. The natural logarithm of discrete population growth rates λ estimated from IPMs are equivalent to per-capita growth rate in continuous population growth models50, and this transformation makes sensitivities compatible with the coexistence analysis described below. Sensitivity is greater than 0 for antagonistic interactions, with higher values equating to stronger competition, while facilitative interactions lead to negative sensitivities.For a pair of species, modern coexistence theory predicts that niche differences (ND) promote coexistence by reducing the intensity of interspecific competition experienced by both species. Therefore, a pair of species with a large niche difference should display small mean sensitivities to competition from each other. Consequently, niche differences can be calculated as one minus the geometric mean of the two sensitivities (i.e. niche overlap). In contrast, relative fitness differences (RFD) quantify the degree of asymmetry in species’ competitive abilities. Therefore, a pair of species with a large fitness difference should display large differences in their sensitivities to competition from each other, as quantified as the geometric standard deviation of sensitivities49:$${{{{{rm{ND}}}}}}=1-sqrt{{S}_{{ij}}{S}_{{ji}}}$$
(2)
$${{{{{rm{RFD}}}}}}=sqrt{{S}_{{ji}}/{S}_{{ij}}}$$
(3)
There are three possible outcomes of competition between a given pair of species: stable coexistence, a priority effect, and competitive exclusion. These can be quantified based on either invasion criteria or the relative magnitude of niche differences versus relative fitness differences15,51. Stable coexistence is only possible when both species are able to invade each other’s equilibrium populations; this condition is met when ND  > 0 and ({{{{{rm{RFD}}}}}} , < , frac{1}{1-{{{{{rm{ND}}}}}}})49, which is equivalent to (frac{1}{{{{{{rm{RFD}}}}}}(1-{{{{{rm{ND}}}}}})} > 1), with greater values indicating more stable coexistence and providing a metric for the strength of coexistence (i.e., coexistence metric26). When neither species can invade when rare, then priority effects occur, meaning that whichever species is initially established within a community has an advantage and excludes the other. This could happen when a species pair has a small niche difference and a small relative fitness difference, that is ND  , frac{1}{1-{{{{{rm{ND}}}}}}}). We quantified competitive outcomes and coexistence metrics for each of the 500 bootstrap replicates of the dataset (Supplementary Data 6).Note that we excluded facilitative interactions that were present in 13% of all pairs because the equations for niche differences and relative fitness differences are not compatible with negative values of sensitivity (Eq. 2 and 3); we did not exclude facilitative interactions for other analyses. We quantified the coexistence determinants of species pairs in cases where either one or both of the species were predicted to be unable to persist in the absence of neighbours (i.e. ln(λintrinsic)  More

Mackintosh NA. The southern stocks of whalebone whales 1942.Perrin, W. F. & Wursig, B. Thewissen JGM “Hans” (Academic Press, 2009).
Google Scholar 
Rizzo, L. Y. & Schulte, D. A review of humpback whales’ migration patterns worldwide and their consequences to gene flow. J. Mar. Biol. Assoc. U.K. 89, 995–1002. https://doi.org/10.1017/S0025315409000332 (2009).Article 

Google Scholar 
Baker, C. S. et al. Strong maternal fidelity and natal philopatry shape genetic structure in North Pacific humpback whales. Mar. Ecol. Prog. Ser. 494, 291–306. https://doi.org/10.3354/meps10508 (2013).ADS 
Article 

Google Scholar 
Clapham, P. J. et al. Seasonal occurrence and annual return of humpback whales, Megaptera novaeangliae, in the southern Gulf of Maine. Can J Zool 71, 440–443. https://doi.org/10.1139/z93-063 (1993).Article 

Google Scholar 
Dawbin, W. H. The seasonal migratory cycle of humpback whales. Whales Dolphins Porpoises 4, 145–70 (1966).Article 

Google Scholar 
Horton, T. W., Zerbini, A. N., Andriolo, A., Danilewicz, D. & Sucunza, F. Multi-decadal humpback whale migratory route fidelity despite oceanographic and geomagnetic change. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.00414 (2020).Article 

Google Scholar 
Larsen, A. H., Sigurjónsson, J., Oien, N., Vikingsson, G. & Palsbøll, P. Populations genetic analysis of nuclear and mitochondrial loci in skin biopsies collected from central and northeastern North Atlantic humpback whales (Megaptera novaeangliae): Population identity and migratory destinations. Proc. Biol. Sci. 263, 1611–1618. https://doi.org/10.1098/rspb.1996.0236 (1996).CAS 
Article 
PubMed 

Google Scholar 
Palsbøll, P. J. et al. Genetic tagging of humpback whales. Nature 388, 767–9. https://doi.org/10.1038/42005 (1997).ADS 
Article 
PubMed 

Google Scholar 
Barendse, J. et al. Migration redefined? Seasonality, movements and group composition of humpback whales Megaptera novaeangliae off the west coast of South Africa. Afr. J. Mar. Sci. 32, 1–22. https://doi.org/10.2989/18142321003714203 (2010).Article 

Google Scholar 
Best, B. P., Sekiguchi, K. & Findlay, P. K. A suspended migration of humpback whales Megaptera novaeangliae on the west coast of South Africa. Mar. Ecol. Prog. Ser. 118, 1–12. https://doi.org/10.3354/meps118001 (1995).ADS 
Article 

Google Scholar 
Brown, M. R., Corkeron, P. J., Hale, P. T., Schultz, K. W. & Bryden, M. M. Evidence for a sex-segregated migration in the humpback whale (Megaptera novaeangliae). Proc. R. Soc. Lond. B 259, 229–234. https://doi.org/10.1098/rspb.1995.0034 (1995).ADS 
CAS 
Article 

Google Scholar 
Christensen, I., Haug, T. & Øien, N. Seasonal distribution, exploitation and present abundance of stocks of large baleen whales (Mysticeti) and sperm whales (Physeter macrocephalus) in Norwegian and adjacent waters. ICES J. Mar. Sci. 49, 341–355. https://doi.org/10.1093/icesjms/49.3.341 (1992).Article 

Google Scholar 
Corkeron, P. J. & Connor, R. C. Why do baleen whales migrate?1. Mar. Mamm. Sci. 15, 1228–1245. https://doi.org/10.1111/j.1748-7692.1999.tb00887.x (1999).Article 

Google Scholar 
Pomilla, C. & Rosenbaum, H. C. Against the current: An inter-oceanic whale migration event. Biol. Lett. 1, 476–479. https://doi.org/10.1098/rsbl.2005.0351 (2005).Article 
PubMed 
PubMed Central 

Google Scholar 
Druskat, A., Ghosh, R., Castrillon, J. & Bengtson Nash, S. M. Sex ratios of migrating southern hemisphere humpback whales: A new sentinel parameter of ecosystem health. Mar. Environ. Res. 151, 104749. https://doi.org/10.1016/j.marenvres.2019.104749 (2019).CAS 
Article 
PubMed 

Google Scholar 
Atkinson, A. et al. Krill (Euphausia superba) distribution contracts southward during rapid regional warming. Nat. Clim. Chang. 9, 142–147. https://doi.org/10.1038/s41558-018-0370-z (2019).ADS 
Article 

Google Scholar 
Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature 432, 100–103. https://doi.org/10.1038/nature02996 (2004).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Flores, H. et al. Impact of climate change on Antarctic krill. Mar. Ecol. Prog. Ser. 458, 1–19. https://doi.org/10.3354/meps09831 (2012).ADS 
Article 

Google Scholar 
Andrews-Goff, V. et al. Humpback whale migrations to Antarctic summer foraging grounds through the southwest Pacific Ocean. Sci. Rep. 8, 12333. https://doi.org/10.1038/s41598-018-30748-4 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Garrigue, C., Clapham, P. J., Geyer, Y., Kennedy, A. S. & Zerbini, A. N. Satellite tracking reveals novel migratory patterns and the importance of seamounts for endangered South Pacific humpback whales. R. Soc. Open Sci. 2, 150489. https://doi.org/10.1098/rsos.150489 (2015).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Riekkola, L., Andrews-Goff, V., Friedlaender, A., Constantine, R. & Zerbini, A. N. Environmental drivers of humpback whale foraging behavior in the remote Southern Ocean. J. Exp. Mar. Biol. Ecol. 517, 1–12. https://doi.org/10.1016/j.jembe.2019.05.008 (2019).Article 

Google Scholar 
Fleming, A. H., Clark, C. T., Calambokidis, J. & Barlow, J. Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current. Glob. Change Biol. 22, 1214–1224. https://doi.org/10.1111/gcb.13171 (2016).ADS 
Article 

Google Scholar 
Nash, S. M. B. et al. Signals from the south; humpback whales carry messages of Antarctic sea-ice ecosystem variability. Glob. Change Biol. 24, 1500–1510. https://doi.org/10.1111/gcb.14035 (2018).ADS 
Article 

Google Scholar 
Cartwright, R. et al. Fluctuating reproductive rates in Hawaii’s humpback whales, Megaptera novaeangliae, reflect recent climate anomalies in the North Pacific. R. Soc. Open Sci. 6, 181463. https://doi.org/10.1098/rsos.181463 (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Tulloch, V. J. D., Plagányi, É. E., Matear, R., Brown, C. J. & Richardson, A. J. Ecosystem modelling to quantify the impact of historical whaling on Southern Hemisphere baleen whales. Fish Fish. 19, 117–137. https://doi.org/10.1111/faf.12241 (2018).Article 

Google Scholar 
Jonsen, I. D., Flemming, J. M. & Myers, R. A. Robust state–space modeling of animal movement data. Ecology 86, 2874–2880. https://doi.org/10.1890/04-1852 (2005).Article 

Google Scholar 
Morales, J. M., Haydon, D. T., Frair, J., Holsinger, K. E. & Fryxell, J. M. Extracting more out of relocation data: Building movement models as mixtures of random walks. Ecology 85, 2436–2445. https://doi.org/10.1890/03-0269 (2004).Article 

Google Scholar 
Patterson, T. A., Thomas, L., Wilcox, C., Ovaskainen, O. & Matthiopoulos, J. State–space models of individual animal movement. Trends Ecol. Evol. 23, 87–94. https://doi.org/10.1016/j.tree.2007.10.009 (2008).Article 
PubMed 

Google Scholar 
Jonsen, I. Joint estimation over multiple individuals improves behavioural state inference from animal movement data. Sci. Rep. https://doi.org/10.1038/srep20625 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Mills Flemming, J., Jonsen, I. D., Myers, R. A. & Field, C. A. Hierarchical state-space estimation of leatherback turtle navigation ability. PLoS ONE 5, e14245. https://doi.org/10.1371/journal.pone.0014245 (2010).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Andriolo, A., Kinas, P. G., Engel, M. H., Martins, C. C. A. & Rufino, A. M. Humpback whales within the Brazilian breeding ground: Distribution and population size estimate. Endanger. Species Res. 11, 233–243. https://doi.org/10.3354/esr00282 (2010).Article 

Google Scholar 
Ward, E., Zerbini, A. N., Kinas, P. G., Engel, M. H. & Andriolo, A. Estimates of population growth rates of humpback whales (Megaptera novaeangliae) in the wintering grounds off the coast of Brazil (Breeding Stock A). J Cetacean Res. Manag. 3, 145–149 (2011).
Google Scholar 
Zerbini, A. N. et al. Assessing the recovery of an Antarctic predator from historical exploitation. R. Soc. Open Sci. 6, 190368. https://doi.org/10.1098/rsos.190368 (2019).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bortolotto, G. A., Danilewicz, D., Hammond, P. S., Thomas, L. & Zerbini, A. N. Whale distribution in a breeding area: Spatial models of habitat use and abundance of western South Atlantic humpback whales. Mar. Ecol. Prog. Ser. 585, 213–227. https://doi.org/10.3354/meps12393 (2017).ADS 
Article 

Google Scholar 
Martins, C. C. A., Andriolo, A., Engel, M. H., Kinas, P. G. & Saito, C. H. Identifying priority areas for humpback whale conservation at Eastern Brazilian Coast. Ocean Coast. Manag. 75, 63–71. https://doi.org/10.1016/j.ocecoaman.2013.02.006 (2013).Article 

Google Scholar 
Albertson, G. R. et al. Temporal stability and mixed-stock analyses of humpback whales (Megaptera novaeangliae) in the nearshore waters of the Western Antarctic Peninsula. Polar Biol. 41, 323–340. https://doi.org/10.1007/s00300-017-2193-1 (2018).Article 

Google Scholar 
Engel, M. & Martin, A. Feeding grounds of the western South Atlantic humpback whale population. Mar. Mamm. Sci. 25, 964–969 (2009).Article 

Google Scholar 
Engel, M. H. et al. Mitochondrial DNA diversity of the Southwestern Atlantic humpback whale (Megaptera novaeangliae) breeding area off Brazil, and the potential connections to Antarctic feeding areas. Conserv. Genet. 5, 1253–1262. https://doi.org/10.1007/s10592-007-9453-5 (2008).CAS 
Article 

Google Scholar 
Stevick, P., De Godoy, L. P., McOsker, M., Engel, M. & Allen, J. A note on the movement of a humpback whale from Abrolhos Bank, Brazil to South Georgia. J. Cetac. Res. Manag. 8, 297 (2006).
Google Scholar 
Zerbini, A. N. et al. Migration and summer destinations of humpback whales (Megaptera novaeangliae) in the western South Atlantic Ocean. J. Cetacean Res. Manag. 3, 113–8 (2011).
Google Scholar 
Zerbini, A. N. et al. Satellite-monitored movements of humpback whales Megaptera novaeangliae in the Southwest Atlantic Ocean. Mar. Ecol. Prog. Ser. 313, 295–304. https://doi.org/10.3354/meps313295 (2006).ADS 
Article 

Google Scholar 
de Castro, F. R. et al. Are marine protected areas and priority areas for conservation representative of humpback whale breeding habitats in the western South Atlantic?. Biol. Conserv. 179, 106–114. https://doi.org/10.1016/j.biocon.2014.09.013 (2014).Article 

Google Scholar 
Heide-Jørgensen, M. P., Kleivane, L., OIen, N., Laidre, K. L. & Jensen, M. V. A new technique for deploying Sa℡lite transmitters on baleen whales: Tracking a blue whale (balaenoptera Musculus) in the North Atlantic. Mar. Mamm. Sci. 17, 949–54. https://doi.org/10.1111/j.1748-7692.2001.tb01309.x (2011).Article 

Google Scholar 
Heide-Jørgensen, M. P. et al. From greenland to Canada in ten days: Tracks of bowhead whales, Balaena mysticetus, across Baffin Bay. Arctic 56, 21–31 (2003).Article 

Google Scholar 
Heide-Jørgensen, M. P., Laidre, K. L., Jensen, M. V., Dueck, L. & Postma, L. D. Dissolving stock discreteness with Sa℡lite tracking: Bowhead whales in Baffin Bay. Mar. Mamm. Sci. 22, 34–45. https://doi.org/10.1111/j.1748-7692.2006.00004.x (2006).Article 

Google Scholar 
Zerbini, A. N., Fernandez, A. A., Andriolo, A., Clapham, P. J., Crespo, E., Gonzalez, R., et al. Satellite tracking of southern right whales (Eubalaena australis) from Golfo San Matias, Rio Negro Province, Argentina. Scientific Committee of the International Whaling Commission SC67b, Bled, Slovenia (2018).Chittleborough, R. G. Dynamics of two populations of the humpback whale, Megaptera novaeangliae (Borowski). Mar. Freshwater Res. 16, 33–128. https://doi.org/10.1071/mf9650033 (1965).Article 

Google Scholar 
Freitas, C., Lydersen, C., Fedak, M. A. & Kovacs, K. M. A simple new algorithm to filter marine mammal Argos locations. Mar. Mamm. Sci. 24, 315–325. https://doi.org/10.1111/j.1748-7692.2007.00180.x (2008).Article 

Google Scholar 
Lambertsen, R. H. A biopsy system for large whales and its use for cytogenetics. J. Mamm. 68, 443–445. https://doi.org/10.2307/1381495 (1987).Article 

Google Scholar 
Mendelssohn, R. rerddapXtracto: Extracts Environmental Data from “ERDDAP” Web Services. (2020).Chin, T. M., Milliff, R. F. & Large, W. G. Basin-scale, high-wavenumber sea surface wind fields from a multiresolution analysis of scatterometer data. J. Atmos. Oceanic Technol. 15, 741–763. https://doi.org/10.1175/1520-0426(1998)015%3c0741:BSHWSS%3e2.0.CO;2 (1998).ADS 
Article 

Google Scholar 
Orsi, A. H., Whitworth, T. & Nowlin, W. D. On the meridional extent and fronts of the antarctic circumpolar current. Deep Sea Res. Part I 42, 641–673. https://doi.org/10.1016/0967-0637(95)00021-W (1995).Article 

Google Scholar 
Johnson, D. S., London, J. M., Lea, M.-A. & Durban, J. W. Continuous-time correlated random walk model for animal telemetry data. Ecology 89, 1208–1215. https://doi.org/10.1890/07-1032.1 (2008).Article 
PubMed 

Google Scholar 
Bedriñana-Romano, L. et al. Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model. Sci. Rep. 11, 2709. https://doi.org/10.1038/s41598-021-82220-5 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
McClintock, B. T., London, J. M., Cameron, M. F. & Boveng, P. L. Modelling animal movement using the Argos satellite telemetry location error ellipse. Methods Ecol. Evol. 6, 266–277. https://doi.org/10.1111/2041-210X.12311 (2015).Article 

Google Scholar 
Akaike, H. Theory and an Extension of the Maximum Likelihood Principal. International Symposium on Information Theory (Akademiai Kaiado, 1973).MATH 

Google Scholar 
Auger-Méthé, M. et al. Spatiotemporal modelling of marine movement data using Template Model Builder (TMB). Mar. Ecol. Prog. Ser. 565, 237–249. https://doi.org/10.3354/meps12019 (2017).ADS 
Article 

Google Scholar 
Jonsen, I. D. et al. Movement responses to environment: Fast inference of variation among southern elephant seals with a mixed effects model. Ecology 100, e02566. https://doi.org/10.1002/ecy.2566 (2019).CAS 
Article 
PubMed 

Google Scholar 
Kristensen, K., Nielsen, A., Berg, C. W., Skaug, H. & Bell, B. TMB: Automatic differentiation and laplace approximation. J. Stat. Softw. https://doi.org/10.18637/jss.v070.i05 (2016).Article 

Google Scholar 
Marcondes, M. C. C. et al. The Southern Ocean Exchange: Porous boundaries between humpback whale breeding populations in southern polar waters. Sci. Rep. 11, 23618. https://doi.org/10.1038/s41598-021-02612-5 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Derville, S., Torres, L. G., Zerbini, A. N., Oremus, M. & Garrigue, C. Horizontal and vertical movements of humpback whales inform the use of critical pelagic habitats in the western South Pacific. Sci. Rep. 10, 4871. https://doi.org/10.1038/s41598-020-61771-z (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Noad, M. J. & Cato, D. H. Swimming speeds of singing and non-singing humpback whales during migration. Mar. Mamm. Sci. 23, 481–495. https://doi.org/10.1111/j.1748-7692.2007.02414.x (2007).Article 

Google Scholar 
Gabriele, C. M. et al. Estimating the mortality rate of humpback whale calves in the central North Pacific Ocean. Can. J. Zool. 79, 589–600. https://doi.org/10.1139/z01-014 (2001).Article 

Google Scholar 
Korb, R. E., Whitehouse, M. J., Atkinson, A. & Thorpe, S. E. Magnitude and maintenance of the phytoplankton bloom at South Georgia: A naturally iron-replete environment. Mar. Ecol. Progress Ser. 368, 75–91 (2008).ADS 
CAS 
Article 

Google Scholar 
Korb, R. E., Whitehouse, M. J. & Ward, P. SeaWiFS in the southern ocean: Spatial and temporal variability in phytoplankton biomass around South Georgia. Deep Sea Res. Part II 51, 99–116. https://doi.org/10.1016/j.dsr2.2003.04.002 (2004).ADS 
CAS 
Article 

Google Scholar 
Atkinson, A. et al. Oceanic circumpolar habitats of Antarctic krill. Mar. Ecol. Prog. Ser. 362, 1–23. https://doi.org/10.3354/meps07498 (2008).ADS 
CAS 
Article 

Google Scholar 
Murphy, E. J. et al. Southern antarctic circumpolar current front to the northeast of South Georgia: Horizontal advection of krill and its role in the ecosystem. J. Geophys. Res. Oceans https://doi.org/10.1029/2002JC001522 (2004).Article 

Google Scholar 
Schmidt, K., Atkinson, A., Pond, D. W. & Ireland, L. C. Feeding and overwintering of Antarctic krill across its major habitats: The role of sea ice cover, water depth, and phytoplankton abundance. Limnol. Oceanogr. 59, 17–36. https://doi.org/10.4319/lo.2014.59.1.0017 (2014).ADS 
Article 

Google Scholar 
Trathan, P. N. et al. Oceanographic variability and changes in Antarctic krill (Euphausia superba) abundance at South Georgia. Fish. Oceanogr. 12, 569–583. https://doi.org/10.1046/j.1365-2419.2003.00268.x (2003).Article 

Google Scholar 
Venables, H. J. & Meredith, M. P. Theory and observations of Ekman flux in the chlorophyll distribution downstream of South Georgia. Geophys. Res. Lett. https://doi.org/10.1029/2009GL041371 (2009).Article 

Google Scholar 
Krafft, B. A. et al. Distribution and demography of Antarctic krill in the Southeast Atlantic sector of the Southern Ocean during the austral summer 2008. Polar Biol. 33, 957–968. https://doi.org/10.1007/s00300-010-0774-3 (2010).Article 

Google Scholar 
Murphy, E. J. et al. Spatial and temporal operation of the Scotia Sea ecosystem: A review of large-scale links in a krill centred food web. Philos. Trans. R. Soc. B Biol. Sci. 362, 113–48. https://doi.org/10.1098/rstb.2006.1957 (2007).CAS 
Article 

Google Scholar 
Thorpe, S. E., Murphy, E. J. & Watkins, J. L. Circumpolar connections between Antarctic krill (Euphausia superba Dana) populations: Investigating the roles of ocean and sea ice transport. Deep Sea Res. Part I 54, 792–810. https://doi.org/10.1016/j.dsr.2007.01.008 (2007).Article 

Google Scholar 
Mori, M. et al. Modelling dispersal of juvenile krill released from the Antarctic ice edge: Ecosystem implications of ocean movement. J. Mar. Syst. 189, 50–61. https://doi.org/10.1016/j.jmarsys.2018.09.005 (2019).Article 

Google Scholar 
Kohlbach, D. et al. Ice algae-produced carbon is critical for overwintering of antarctic krill Euphausia superba. Front. Mar. Sci. https://doi.org/10.3389/fmars.2017.00310 (2017).Article 

Google Scholar 
Meyer, B. et al. The winter pack-ice zone provides a sheltered but food-poor habitat for larval Antarctic krill. Nat. Ecol. Evol. 1, 1853–1861. https://doi.org/10.1038/s41559-017-0368-3 (2017).Article 
PubMed 

Google Scholar 
Meyer, B. et al. Physiology, growth, and development of larval krill Euphausia superba in autumn and winter in the Lazarev Sea, Antarctica. Limnol. Oceanogr. 54, 1595–1614. https://doi.org/10.4319/lo.2009.54.5.1595 (2009).ADS 
CAS 
Article 

Google Scholar 
Lancelot, C. et al. Spatial distribution of the iron supply to phytoplankton in the Southern Ocean: A model study. Biogeosciences 6, 2861–2878. https://doi.org/10.5194/bg-6-2861-2009 (2009).ADS 
CAS 
Article 

Google Scholar 
Brierley, A. S. et al. Antarctic krill under Sea Ice: Elevated abundance in a narrow band just south of Ice Edge. Science 295, 1890–1892. https://doi.org/10.1126/science.1068574 (2002).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Schmidt, K., Atkinson, A., Venables, H. J. & Pond, D. W. Early spawning of Antarctic krill in the Scotia Sea is fuelled by “superfluous” feeding on non-ice associated phytoplankton blooms. Deep Sea Res. Part II 59–60, 159–172. https://doi.org/10.1016/j.dsr2.2011.05.002 (2012).ADS 
Article 

Google Scholar 
Walsh, J., Reiss, C. S. & Watters, G. M. Flexibility in Antarctic krill Euphausia superba decouples diet and recruitment from overwinter sea-ice conditions in the northern Antarctic Peninsula. Mar. Ecol. Prog. Ser. 642, 1–19. https://doi.org/10.3354/meps13325 (2020).ADS 
CAS 
Article 

Google Scholar 
Saba, G. K. et al. Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula. Nat. Commun. 5, 4318. https://doi.org/10.1038/ncomms5318 (2014).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Friedlaender, A. S. et al. Whale distribution in relation to prey abundance and oceanographic processes in shelf waters of the Western Antarctic Peninsula. Mar. Ecol. Prog. Ser. 317, 297–310. https://doi.org/10.3354/meps317297 (2006).ADS 
Article 

Google Scholar 
Murase, H., Matsuoka, K., Ichii, T. & Nishiwaki, S. Relationship between the distribution of euphausiids and baleen whales in the Antarctic (35° E–145° W). Polar Biol 25, 135–145. https://doi.org/10.1007/s003000100321 (2002).Article 

Google Scholar 
Reisinger, R. R. et al. Combining regional habitat selection models for large-scale prediction: Circumpolar habitat selection of Southern Ocean humpback whales. Remote Sens. 13, 2074. https://doi.org/10.3390/rs13112074 (2021).ADS 
Article 

Google Scholar 
Thiele, D. et al. Seasonal variability in whale encounters in the Western Antarctic Peninsula. Deep Sea Res. Part II 51, 2311–2325. https://doi.org/10.1016/j.dsr2.2004.07.007 (2004).ADS 
Article 

Google Scholar 
Whitehouse, M. J. et al. Rapid warming of the ocean around South Georgia, Southern Ocean, during the 20th century: Forcings, characteristics and implications for lower trophic levels. Deep Sea Res. Part I 55, 1218–1228. https://doi.org/10.1016/j.dsr.2008.06.002 (2008).Article 

Google Scholar 
Dawson, H. R. S., Strutton, P. G. & Gaube, P. The unusual surface chlorophyll signatures of southern Ocean Eddies. J. Geophys. Res. Oceans 123, 6053–6069. https://doi.org/10.1029/2017JC013628 (2018).ADS 
CAS 
Article 

Google Scholar 
Kahru, M., Mitchell, B. G., Gille, S. T., Hewes, C. D. & Holm-Hansen, O. Eddies enhance biological production in the weddell-scotia confluence of the Southern Ocean. Geophys. Res. Lett. https://doi.org/10.1029/2007GL030430 (2007).Article 

Google Scholar 
Fach, B. A., Hofmann, E. E. & Murphy, E. J. Modeling studies of antarctic krill Euphausia superba survival during transport across the Scotia Sea. Mar. Ecol. Prog. Ser. 231, 187–203. https://doi.org/10.3354/meps231187 (2002).ADS 
Article 

Google Scholar 
Ichii, T., Katayama, K., Obitsu, N., Ishii, H. & Naganobu, M. Occurrence of Antarctic krill (Euphausia superba) concentrations in the vicinity of the South Shetland Islands: Relationship to environmental parameters. Deep Sea Res. Part I 45, 1235–1262. https://doi.org/10.1016/S0967-0637(98)00011-9 (1998).Article 

Google Scholar 
Witek, Z., Kalinowski, J. & Grelowski, A. Formation of Antarctic Krill Concentrations in Relation to Hydrodynamic Processes and Social Behaviour. In Antarctic Ocean and Resources Variability (ed. Sahrhage, D.) 237–44 (Springer, 1988). https://doi.org/10.1007/978-3-642-73724-4_21.Chapter 

Google Scholar 
Bost, C. A. et al. The importance of oceanographic fronts to marine birds and mammals of the southern oceans. J. Mar. Syst. 78, 363–376. https://doi.org/10.1016/j.jmarsys.2008.11.022 (2009).Article 

Google Scholar 
Carranza, M. M. & Gille, S. T. Southern Ocean wind-driven entrainment enhances satellite chlorophyll-a through the summer. J. Geophys. Res. Oceans 120, 304–323. https://doi.org/10.1002/2014JC010203 (2015).ADS 
Article 

Google Scholar 
Luis, A. J. & Pandey, P. C. Seasonal variability of QSCAT-derived wind stress over the Southern Ocean. Geophys. Res. Lett. https://doi.org/10.1029/2003GL019355 (2004).Article 

Google Scholar 
Fiechter, J. & Moore, A. M. Interannual spring bloom variability and Ekman pumping in the coastal Gulf of Alaska. J. Geophys. Res. Oceans https://doi.org/10.1029/2008JC005140 (2009).Article 

Google Scholar 
Cimino, M. A. et al. Essential krill species habitat resolved by seasonal upwelling and ocean circulation models within the large marine ecosystem of the California Current System. Ecography 43, 1536–1549. https://doi.org/10.1111/ecog.05204 (2020).Article 

Google Scholar 
Meehl, G. A. et al. Sustained ocean changes contributed to sudden Antarctic sea ice retreat in late 2016. Nat. Commun. 10, 14. https://doi.org/10.1038/s41467-018-07865-9 (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Parkinson, C. L. A 40-y record reveals gradual Antarctic sea ice increases followed by decreases at rates far exceeding the rates seen in the Arctic. PNAS 116, 14414–14423. https://doi.org/10.1073/pnas.1906556116 (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Siegel, V. Krill stocks in high latitudes of the Antarctic Lazarev Sea: seasonal and interannual variation in distribution, abundance and demography. Polar Biol. 35, 1151–1177. https://doi.org/10.1007/s00300-012-1162-y (2012).Article 

Google Scholar 
Francis, D., Eayrs, C., Cuesta, J. & Holland, D. Polar cyclones at the origin of the reoccurrence of the maud rise polynya in austral winter 2017. J. Geophys. Res. Atmos. 124, 5251–5267. https://doi.org/10.1029/2019JD030618 (2019).ADS 
Article 

Google Scholar 
Jena, B., Ravichandran, M. & Turner, J. Recent reoccurrence of large open-ocean polynya on the maud rise seamount. Geophys. Res. Lett. 46, 4320–4329. https://doi.org/10.1029/2018GL081482 (2019).ADS 
Article 

Google Scholar 
Brandt, A. et al. Maud rise–a snapshot through the water column. Deep Sea Res. Part II 58, 1962–1982. https://doi.org/10.1016/j.dsr2.2011.01.008 (2011).ADS 
Article 

Google Scholar 
Plötz, J., Weidel, H. & Bersch, M. Winter aggregations of marine mammals and birds in the north-eastern Weddell Sea pack ice. Polar Biol 11, 305–309. https://doi.org/10.1007/BF00239022 (1991).Article 

Google Scholar 
Hazen, E. L. et al. Predicted habitat shifts of Pacific top predators in a changing climate. Nat. Clim. Change 3, 234–238. https://doi.org/10.1038/nclimate1686 (2013).ADS 
Article 

Google Scholar 
Moore, S. E. & Huntington, H. P. Arctic marine mammals and climate change: Impacts and resilience. Ecol. Appl. 18, S157–S165. https://doi.org/10.1890/06-0571.1 (2008).Article 
PubMed 

Google Scholar  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