Philippa Kaur

Clark, C. T. et al. Heavy with child? Pregnancy status and stable isotope ratios as determined from biopsies of humpback whales. Conserv. Physiol. 4, 1–13 (2016).PubMed 
Article 
CAS 

Google Scholar 
Wasser, S. K. et al. Population growth is limited by nutritional impacts on pregnancy success in endangered Southern Resident killer whales (Orcinus orca). PLoS One 12, e0179824. https://doi.org/10.1371/journal.pone.0179824 (2017).Boeuf, B. J., Perez-Cortes, H., Urbán, J., Mate, B. R. & Ollervides, F. High gray whale mortality and low recruitment in 1999: Potential causes and implications. J. Cetacean Res. Manag. 2, 85–99 (1999).
Google Scholar 
Perryman, W. L. & Lynn, M. S. Evaluation of nutritive condition and reproductive status of migrating gray whales (Eschrichtius robustus) based on analysis of photogrammetric data. J. Cetacean Res. Manag. 4, 155–164 (2002).
Google Scholar 
Moore, S. E., Grebmeier, J. M. & Davies, J. R. Gray whale distribution relative to forage habitat in the northern Bering Sea: Current conditions and retrospective summary. Can. J. Zool. 81, 734–742 (2003).Article 

Google Scholar 
Christiansen, F. et al. Poor body condition associated with an unusual mortality event in gray whales. Mar. Ecol. Prog. Ser. 658, 237–252 (2021).ADS 
Article 

Google Scholar 
Martìnez-Aguilar, S. et al. Gray Whale (Eschrichtius robustus) stranding records in Mexico during the winter breeding season in 2019. In IWC (2019).Villegas-Amtmann, S., Schwarz, L. K., Sumich, J. L. & Costa, D. P. A bioenergetics model to evaluate demographic consequences of disturbance in marine mammals applied to gray whales. Ecosphere 6, art183 (2015).Article 

Google Scholar 
Urbán, R. J., Jiménez-López, E., Guzmán, H. M. & Viloria-Gómora, L. Migratory Behavior of an Eastern North Pacific Gray Whale From Baja California Sur to Chirikov Basin, Alaska. Front. Mar. Sci. 8, 1–7 (2021).Article 

Google Scholar 
Kim, L. & Oliver, J. S. Swarming benthic crustaceans in the Bering and Chukchi seas and their relation to geographic patterns in gray whale feeding. Can. J. Zool. 67, 1531–1542 (1989).Article 

Google Scholar 
Perryman, W. L., Joyce, T., Weller, D. W. & Durban, J. W. Environmental factors influencing eastern North Pacific gray whale calf production 1994–2016. Mar. Mammal Sci. 37, 448–462 (2020).Article 

Google Scholar 
Caraveo-Patiño, J. & Soto, L. A. Stable carbon isotope ratios for the gray whale (Eschrichtius robustus) in the breeding grounds of Baja California Sur, Mexico. Hydrobiologia 539, 99–107 (2005).Article 

Google Scholar 
Pyenson, N. D. & Lindberg, D. R. What happened to gray whales during the pleistocene? The ecological impact of sea-level change on benthic feeding areas in the north pacific ocean. PLoS One 6, e21295. https://doi.org/10.1371/journal.pone.0021295 (2011).Alter, S. E., Newsome, S. D. & Palumbi, S. R. Pre-whaling genetic diversity and population ecology in eastern pacific gray whales: Insights from ancient DNA and stable isotopes. PLoS One 7, e35039 (2012).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Dunham, J. S. & Duffus, D. A. Foraging patterns of gray whales in central Clayoquot Sound, British Columbia, Canada. Mar. Ecol. Prog. Ser. 223, 299–310 (2001).ADS 
Article 

Google Scholar 
Nerini, M. A Review of Gray Whale Feeding Ecology (Academic Press, Cambridge, 1984).Book 

Google Scholar 
Jones, M. Lou & Swartz, S. L. Gray whale. In Encyclopedia of Marine Mammals, Vol. 36 1352 (Academic Press, 2009).Moore, S. E., Wynne, K. M., Kinney, J. C. & Grebmeier, J. M. Gray whale occurrence and forage southeast of Kodiak, Island, Alaska. Mar. Mammal Sci. 23, 419–428 (2007).Article 

Google Scholar 
Lagerquist, B. A. et al. Feeding home ranges of pacific coast feeding group gray whales. J. Wildl. Manag. 83, 925–937 (2019).Article 

Google Scholar 
Calambokidis, J., Laake, J. L. & Klimek, A. Updated analysis of abundance and population structure of seasonal gray whales in the Pacific, 2010 (2012).Frasier, T. R., Koroscil, S. M., White, B. N. & Darling, J. D. Assessment of population substructure in relation to summer feeding ground use in the eastern North Pacific gray whale. Endanger. Species Res. 14, 39–48 (2011).Article 

Google Scholar 
Lang, A. R. et al. Assessment of genetic structure among eastern North Pacific gray whales on their feeding grounds. Mar. Mammal Sci. 30, 1473–1493 (2014).CAS 
Article 

Google Scholar 
Burnham, R. & Duffus, D. Patterns of predator-prey dynamics between gray whales (Eschrichtius robustus) and mysid species in Clayoquot Sound. J. Cetacean Res. Manag. 19, 95–103 (2018).
Google Scholar 
Walker, T. J. Primer: With Special Attention to the California Gray Whale (Cabrillo Historical Association Pub QL737, San Diego, 1975).Walker, T. J. The California gray whale comes back (Eschrichtius robustus). Natl. Geogr. Mag. 139(3), 394–415 (1971).
Google Scholar 
Caraveo-Patiño, J. et al. Eco-physiological repercussions of dietary arachidonic acid in cell membranes of active tissues of the Gray whale. Mar. Ecol. 30, 437–447. https://doi.org/10.1111/j.1439-0485.2009.00289.x (2009).ADS 
Article 
CAS 

Google Scholar 
Pirotta, E. et al. A dynamic state model of migratory behavior and physiology to assess the consequences of environmental variation and anthropogenic disturbance on marine vertebrates. Am. Nat. 191, E40–E56. https://doi.org/10.1086/695135 (2018).Busquets-Vass, G. et al. Estimating blue whale skin isotopic incorporation rates and baleen growth rates: Implications for assessing diet and movement patterns in mysticetes. PLoS ONE 12, 1–25 (2017).Article 
CAS 

Google Scholar 
Busquets-Vass, G. et al. Isotope-based inferences of the seasonal foraging and migratory strategies of blue whales in the eastern Pacific Ocean. Mar. Environ. Res. 163, 105201. https://doi.org/10.1016/j.marenvres.2020.105201 (2021).Wild, L. A., Chenoweth, E. M., Mueter, F. J. & Straley, J. M. Evidence for dietary time series in layers of cetacean skin using stable carbon and nitrogen isotope ratios. Rapid Commun. Mass Spectrom. 32, 1425–1438 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gelippi, M., Popp, B., Gauger, M. F. W. & Caraveo-Patiño, J. Tracing gestation and lactation in free ranging gray whales using the stable isotopic composition of epidermis layers. PLoS ONE 15, 1–23. https://doi.org/10.1371/journal.pone.0240171 (2020).Article 
CAS 

Google Scholar 
Graham, B. S., Koch, P. L., Newsome, S. D., McMahon, K. W. & Aurioles, D. Using Isoscapes to Trace the Movements and Foraging Behavior of Top Predators in Oceanic Ecosystems. Isoscapes: Understanding Movement, Pattern, and Process on Earth Through Isotope Mapping. https://doi.org/10.1007/978-90-481-3354-3 (2010).Hobson, K. A. International association for ecology tracing origins and migration of wildlife using stable isotopes: A review. Source Oecol. 120, 314–326 (1999).ADS 

Google Scholar 
Ryan, C. et al. Accounting for the effects of lipids in stable isotope (δ13C and δ15N values) analysis of skin and blubber of balaenopterid whales. Rapid Commun. Mass Spectrom. 26, 2745–2754 (2012).CAS 
PubMed 
Article 

Google Scholar 
Vander Zanden, M. J. & Rasmussen, J. B. Variation in δ15N and δ13C trophic fractionation: Implications for aquatic food web studies. Limnol. Oceanogr. 46, 2061–2066 (2001).ADS 
CAS 
Article 

Google Scholar 
Newsome, S. D., Clementz, M. T. & Koch, P. L. Using stable isotope biogeochemistry to study marine mammal ecology. Mar. Mammal Sci. 26, 509–572 (2010).CAS 

Google Scholar 
Giménez, J., Ramírez, F., Almunia, J., Forero, G. M. & de Stephanis, R. From the pool to the sea: Applicable isotope turnover rates and diet to skin discrimination factors for bottlenose dolphins (Tursiops truncatus). J. Exp. Mar. Bio. Ecol. 475, 54–61 (2016).Article 
CAS 

Google Scholar 
Browning, N. E., Dold, C., I-Fan, J. & Worthy, A. J. Isotope turnover rates and diet–tissue discrimination in skin of ex situ bottlenose dolphins (Tursiops truncatus). J. Exp. Biol. 217, 214–221 (2014).CAS 
PubMed 

Google Scholar 
Borrell, A., Abad-Oliva, N., Gõmez-Campos, E., Giménez, J. & Aguilar, A. Discrimination of stable isotopes in fin whale tissues and application to diet assessment in cetaceans. Rapid Commun. Mass Spectrom. 26, 1596–1602 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Reeb, D., Best, P. B. & Kidson, S. H. Structure of the integument of southern right whales, Eubalaena australis. Anat. Rec. 290, 596–613 (2007).Article 

Google Scholar 
Morales-Guerrero, B. et al. Melanin granules melanophages and a fully-melanized epidermis are common traits of odontocete and mysticete cetaceans. Vet. Dermatol. 28, 213–e50. https://doi.org/10.1111/vde.12392 (2017).PubMed 
Article 

Google Scholar 
Ayliffe, L. K. et al. Turnover of carbon isotopes in tail hair and breath CO2 of horses fed an isotopically varied diet. Oecologia 139, 11–22 (2004).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Hicks, B. D., St. Aubin, D. J., Geraci, J. R. & Brown, W. R. Epidermal growth in the bottlenose dolphin, Tursiops truncatus. J. Invest. Dermatol. 85, 60–63 (1985).CAS 
PubMed 
Article 

Google Scholar 
Aubin, D. J., St. Smith, T. G. & Geraci, J. R. Seasonal epidermal molt in beluga whales, Delphinapterus leucas. Can. J. Zool. 68, 359–367 (1990).Article 

Google Scholar 
Perryman, W. L., Donahue, M. A., Perkins, P. C. & Reilly, S. B. Gray Whale calf production 1994–2000: Are observed fluctuations related to changes in seasonal ice cover?. Mar. Mammal Sci. 18, 121–144 (2002).Article 

Google Scholar 
Urbán, R. J. et al. A review of gray whales (Eschrichtius robustus) on their wintering grounds in Mexican waters. J. Cetacean Res. Manag. 5, 281–295 (2003).
Google Scholar 
Mann, J. Behavioral sampling methods for cetaceans: A review and critique. Mar. Mammal Sci. 15, 102–122 (1999).Article 

Google Scholar 
Tyurneva, O. Y. et al. Photographic identification of the Korean-Okhotsk gray whale (Eschrichtius robustus) offshore northeast Sakhalin island and southeast Kamchatka peninsula (Russia), 2009. In SC/62/BRG9 (2014).Yakovlev, Y. M., Tyurneva, O. M., Vertyankin, V. V. & Van der Wolf, P. Photo-identification of gray whales (Eschrichtius robustus) off the northeast coast of Sakhalin Island in 2018 photo. West. Gray Whale Advis. Panel 20th meeti (2019).Reeb, D. & Best, P. B. A biopsy system for deep core sampling of the blubber of southern right whales, Eubalaena australis. Mar. Mammal Sci. 22, 206–213 (2006).Article 

Google Scholar 
Noren, D. P. & Mocklin, J. A. Review of cetacean biopsy techniques: Factors contributing to successful sample collection and physiological and behavioral impacts. Mar. Mammal Sci. 28, 154–199 (2012).Article 

Google Scholar 
Caraveo-Patiño, J. Ecología alimenticia de la ballena gris (Eschrichtius robustus, Lilljeborg, 1861): Una ventana a la dinámica interna de los ecosistemas. PhD Thesis. Centro de Investigaciones Biológicas del noroeste S.C. http://dspace.cibnor.mx:8080/handle/123456789/90 (2004).Folch, J., Lees, M. & Stanley, G. H. S. A simple method for the isolation and purification of total lipids from animal tissues. J. Biol. Chem. 226, 497–509 (1957).CAS 
PubMed 
Article 

Google Scholar 
DeNiro, M. J. & Epstein, S. Influence of diet on the distribution of nitrogen isotopes in animals. Geochim. Cosmochim. Acta 45, 341–351 (1981).ADS 
CAS 
Article 

Google Scholar 
Iverson, S. J., Arnould, J. P. Y. & Boyd, I. L. Milk fatty acid signatures indicate both major and minor shifts in the diet of lactating Antarctic fur seals. Can. J. Zool. 75, 188–197 (1997).Article 

Google Scholar 
Newsome, S. D., Koch, P. L., Etnier, M. A. & Aurioles-Gamboa, D. Using carbon and nitrogen isotope values to investigate maternal strategies in Northeast Pacific otariids. Mar. Mammal Sci. 22, 556–572 (2006).Article 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).Moore, J. W. & Semmens, B. X. Incorporating uncertainty and prior information into stable isotope mixing models. Ecol. Lett. 11, 470–480 (2008).PubMed 
Article 

Google Scholar 
Parnell, A. C. et al. Bayesian stable isotope mixing models. Environmetrics 24, 387–399 (2013).MathSciNet 

Google Scholar 
Phillips, D. L. & Gregg, J. W. Source partitioning using stable isotopes: Coping with too many sources. Oecologia 136, 261–269 (2003).ADS 
PubMed 
Article 

Google Scholar 
Phillips, D. L. Converting isotope values to diet composition: The use of mixing models. J. Mammal. 93, 342–352 (2012).Article 

Google Scholar 
Parnell, A. C., Inger, R., Bearhop, S. & Jackson, A. L. Source partitioning using stable isotopes: Coping with too much variation. PLoS ONE 5, 1–5 (2010).
Google Scholar 
Baker, H. ASM Handbook: Alloy Phase Diagrams ASM Handbook Alloy Phase Diagrams Vol. 3 (ASM International, Materials Park, 1992).
Google Scholar 
Pereira, G. H. A. On quantile residuals in beta regression. Commun. Stat. Simul. Comput. 48, 302–316 (2019).MathSciNet 
Article 

Google Scholar 
Osterblom, H., Olsson, O., Blenckner, T. & Furness, W. Junk-food in marine ecosystems. Oikos 117, 967–977 (2008).Article 

Google Scholar 
Martínez del Rio, C. & Carleton, S. A. How fast and how faithful: The dynamics of isotopic incorporation into animal tissues. J. Mammal. 93, 353–359. https://doi.org/10.1644/11-MAMM-S-165.1 (2012).Article 

Google Scholar 
Vander Zanden, M. J., Clayton, M. K., Moody, E. K., Solomon, C. T. & Weidel, B. C. Stable isotope turnover and half-life in animal tissues: A literature synthesis. PLoS One 10, https://doi.org/10.1371/journal.pone.0116182 (2015).CAS 
Article 

Google Scholar 
Dalerum, F. & Angerbjörn, A. Resolving temporal variation in vertebrate diets using naturally occurring stable isotopes. Oecologia 144, 647–658 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Horstmann-Dehn, L., Follmann, E. H., Rosa, C., Zelensky, G. & George, C. Stable carbon and nitrogen isotope ratios in muscle and epidermis of arctic whales. Mar. Mammal Sci. 28, E173–E190. https://doi.org/10.1111/j.1748-7692.2011.00503.x (2012).Hertz, E., Trudel, M., Cox, M. K. & Mazumder, A. Effects of fasting and nutritional restriction on the isotopic ratios of nitrogen and carbon: a meta-analysis. Ecol. Evol. 5, 4829–4839 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Lian, M. et al. Assessing δ13C, δ15N and total mercury measures in epidermal biopsies from gray whales. Front. Mar. Sci. 7, 1–9 (2020).ADS 
Article 

Google Scholar 
Gulland, F. et al. Eastern North Pacific gray whale (Eschrichtius robustus) unusual mortality event, 1999–2000. U.S. Dep. Commer. NOAA Tech. Memo. NMFS-AFSC-150. 33 pp (2005).Popp, B. N. et al. Effect of phytoplankton cell geometry on carbon isotopic fractionation. Geochim. Cosmochim. Acta 62, 69–77 (1998).ADS 
CAS 
Article 

Google Scholar 
Schell, D. M. Declining carrying capacity in the Bering Sea: Isotopic evidence from whale baleen. Limnol. Oceanogr. 45, 459–462 (2000).ADS 
CAS 
Article 

Google Scholar 
Kurle, C. M. & McWhorter, J. K. Spatial and temporal variability within marine isoscapes: Implications for interpreting stable isotope data from marine systems. Mar. Ecol. Prog. Ser. 568, 31–45 (2017).ADS 
CAS 
Article 

Google Scholar 
Keeling, C. D. The Suess effect: 13Carbon –14Carbon interrelations. Environ. Int. 2, 229–300 (1979).CAS 
Article 

Google Scholar 
Grecian, W. J. et al. Contrasting migratory responses of two closely related seabirds to long-term climate change. Mar. Ecol. Prog. Ser. 559, 231–242 (2016).ADS 
CAS 
Article 

Google Scholar 
Pomerleau, C., Nelson, R. J., Hunt, B. P. V., Sastri, A. R. & Williams, W. J. Spatial patterns in zooplankton communities and stable isotope ratios (δ13C and δ15N) in relation to oceanographic conditions in the sub-Arctic Pacific and western Arctic regions during the summer of 2008. J. Plankton Res. 36, 757–775 (2014).CAS 
Article 

Google Scholar 
Lee, S. H. Use of the Beaufort Sea as feeding habitat by bowhead whales (Balaena mysticetus) as indicated by stable isotope ratios. M.S. Thesis. University of Alaska Fairbanks. http://hdl.handle.net/11122/4931 (2000).Cullen, J. T., Rosenthal, Y. & Falkowski, P. G. The effect of anthropogenic CO2 on the carbon isotope composition of marine phytoplankton. Limnol. Oceanogr. 46, 996–998 (2001).ADS 
Article 

Google Scholar 
Schell, D. M. Carbon isotope ratio variations in Bering Sea biota: The role of anthropogenic carbon dioxide. Limnol. Oceanogr. 46, 999–1000 (2001).ADS 
Article 

Google Scholar 
Eide, M., Olsen, A., Ninnemann, U. S. & Eldevik, T. A global estimate of the full oceanic 13C Suess effect since the preindustrial. Glob. Biogeochem. Cycles 31, 492–514 (2017).ADS 
CAS 
Article 

Google Scholar 
Kurle, C. M., Sinclair, E. H., Edwards, A. E. & Gudmundson, C. J. Temporal and spatial variation in the δ15N and δ13C values of fish and squid from Alaskan waters. Mar. Biol. 158, 2389–2404 (2011).Article 

Google Scholar 
Ohman, M. D., Rau, G. H. & Hull, P. M. Multi-decadal variations in stable N isotopes of California Current zooplankton. https://doi.org/10.1016/j.dsr.2011.11.003 (2011).Décima, M., Landry, M. R. & Popp, B. N. Environmental perturbation effects on baseline δ15N values and zooplankton trophic flexibility in the southern California current ecosystem. Limnol. Oceanogr. 58, 624–634 (2013).ADS 
Article 
CAS 

Google Scholar 
Caraveo-Patiño, J., Hobson, K. A. & Soto, L. A. Feeding ecology of gray whales inferred from stable-carbon and nitrogen isotopic analysis of baleen plates. Hydrobiologia 586, 17–25 (2007).Article 

Google Scholar 
Hernández-Aguierre, D. Análisis de la composición de ácidos grasos en los estratos de la capa de grasa (blubber) de la ballena gris Eschrichtius robustus (LILLJEBORG, 1861). M.S. Thesis. Centro de Investigaciones Biológicas del noroeste S.C. http://cibnor.repositorioinstitucional.mx/jspui/handle/1001/182 (2012).Ackman, R. G. Nutritional composition of fats in seafoods. Prog. Food Nutr. Sci. 13, 161–289 (1989).CAS 
PubMed 

Google Scholar 
Lahdes, E., Balogh, G., Fodor, E. & Farkas, T. Adaptation of composition and biophysical properties of phospholipids to temperature by the crustacean, Gammarus spp. Lipids 35, 1093–1098 (2000).CAS 
PubMed 
Article 

Google Scholar 
Sarur-Zanatta, J. C., Millán-Nuñez, R., Gutiérrez-Sigala, C. A. & Small Mattox-Sheahen, C. A. Variation and similarity in three zones with-different type of substrate In Laguna Ojo De Liebre, B.C.S., Mexico. Ciencias Mar. 10, 169–179 (1984).Article 

Google Scholar 
Pirotta, V., Owen, K., Donnelly, D., Brasier, M. J. & Harcourt, R. First evidence of bubble-net feeding and the formation of ‘super-groups’ by the east Australian population of humpback whales during their southward migration. Aquat. Conserv. Mar. Freshw. Ecosyst. https://doi.org/10.1002/aqc.3621 (2021).Article 

Google Scholar 
Carone, E. et al. Sex steroid hormones and behavior reveal seasonal reproduction in a resident fin whale population. Conserv. Physiol. 7, 1–13 (2019).Article 
CAS 

Google Scholar 
Prieto, R., Tobeña, M. & Silva, M. A. Habitat preferences of baleen whales in a mid-latitude habitat. Deep Res. Part II Top. Stud. Oceanogr. 141, 155–167. https://doi.org/10.1016/j.dsr2.2016.07.015 (2017).ADS 
Article 

Google Scholar 
Piatt, J. F. et al. Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014–2016. PLoS One 15 (2020).Savage, K. Alaska and British Columbia large whale unusual mortality event summary report. NOAA Fish Report, Juneau August, 1–42 (2017).Stewart, J. D. & Weller, D. W. NOAA Technical Memorandum NMFS abundance of eastern north pacific gray whales 2019/2020 (2021).Cooke, J. G. Population assessment update for Sakhalin gray whales. West. Gray Whale Advis. Panel 13 (2020). More

Emberts, Z., Escalante, I. & Bateman, P. W. The ecology and evolution of autotomy. Biol. Rev. 94, 1881–1896. https://doi.org/10.1111/brv.12539 (2019).Article 
PubMed 

Google Scholar 
Dunoyer, L. A., Seifert, A. W. & Van Cleve, J. Evolutionary bedfellows: Reconstructing the ancestral state of autotomy and regeneration. J. Exp. Zool. Part B Mol. Dev. Evol. 336, 94–115. https://doi.org/10.1002/jez.b.22974 (2021).Article 

Google Scholar 
Dial, B. E. & Fitzpatrick, L. C. Lizard tail autotomy: function and energetics of postautotomy tail movement in Scincella lateralis. Science https://doi.org/10.1126/science.219.4583.391 (1983).Article 
PubMed 

Google Scholar 
Arnold, E. Caudal autotomy as a defense. Biol. Reptil. 16, 235–273 (1988).
Google Scholar 
Bateman, P. W. & Fleming, P. A. To cut a long tail short: A review of lizard caudal autotomy studies carried out over the last 20 years. J. Zool. (Lond.) 277, 1–14 (2009).Article 

Google Scholar 
Woodland, W. Memoirs: Some observations on caudal autotomy and regeneration in the gecko (Hemidactylus flaviviridis, Rüppel), with notes on the tails of Sphenodon and Pygopus. J. Cell Sci. 2, 63–100 (1920).Article 

Google Scholar 
Alibardi, L. Morphological and Cellular Aspects of Tail and Limb Regeneration in Lizards: A Model System with Implications for Tissue Regeneration in Mammals (Springer, 2010).Book 

Google Scholar 
Maginnis, T. L. The costs of autotomy and regeneration in animals: A review and framework for future research. Behav. Ecol. 17, 857–872. https://doi.org/10.1093/beheco/arl010 (2006).Article 

Google Scholar 
Dial, B. E. & Fitzpatrick, L. C. The energetic costs of tail autotomy to reproduction in the lizard Coleonyx brevis (Sauria: Gekkonidae). Oecologia 51, 310–317. https://doi.org/10.1007/bf00540899 (1981).ADS 
Article 
PubMed 

Google Scholar 
Vitt, L. J., Congdon, J. D. & Dickson, N. A. Adaptive strategies and energetics of tail autotomy in Lizards. Ecology 58, 326–337. https://doi.org/10.2307/1935607 (1977).Article 

Google Scholar 
Clause, A. R. & Capaldi, E. A. Caudal autotomy and regeneration in lizards. J. Exp. Zool. 305, 965–973 (2006).Article 

Google Scholar 
Barr, J. I., Boisvert, C. A. & Bateman, P. W. At what cost? Trade-offs and influences on energetic investment in tail regeneration in lizards following autotomy. J. Dev. Biol. 9, 53 (2021).Article 

Google Scholar 
Etheridge, R. Lizard caudal vertebrae. Copeia, 699–721 (1967).Arnold, E. Evolutionary aspects of tail shedding in lizards and their relatives. J. Nat. Hist. 18, 127–169 (1984).Article 

Google Scholar 
Zani, P. A. Patterns of caudal-autotomy evolution in lizards. J. Zool. (Lond.) 240, 201–220 (1996).Article 

Google Scholar 
Russell, A. & Bauer, A. The m. caudifemoralis longus and its relationship to caudal autotomy and locomotion in lizards (Reptilia: Sauria). J. Zool. (Lond.) 227, 127–143. https://doi.org/10.1111/j.1469-7998.1992.tb04349.x (1992).Article 

Google Scholar 
Arnold, E. Investigating the evolutionary effects of one feature on another: Does muscle spread suppress caudal autotomy in lizards?. J. Zool. (Lond.) 232, 505–523. https://doi.org/10.1111/j.1469-7998.1994.tb01591.x (1994).Article 

Google Scholar 
Bellairs, A. & Bryant, S. Autotomy and regeneration in reptiles. Biol. Reptil. 15, 301–410 (1985).
Google Scholar 
Hoffstetter, R. & Gasc, J. P. Vertebrae and ribs of modern reptiles. Biol. Reptil. 1, 201–310 (1969).
Google Scholar 
Cooper, W. E. Jr. & Frederick, W. G. Predator lethality, optimal escape behavior, and autotomy. Behav. Ecol. 21, 91–96. https://doi.org/10.1093/beheco/arp151 (2009).Article 

Google Scholar 
Fleming, P. A., Valentine, L. E. & Bateman, P. W. Telling tails: Selective pressures acting on investment in lizard tails. Physiol. Biochem. Zool. 86, 645–658 (2013).Article 

Google Scholar 
Bateman, P. W., Fleming, P. A. & Rolek, B. Bite me: Blue tails as a ‘risky-decoy’defense tactic for lizards. Curr. Zool. 60, 333–337 (2014).Article 

Google Scholar 
Hawlena, D., Boochnik, R., Abramsky, Z. & Bouskila, A. Blue tail and striped body: Why do lizards change their infant costume when growing up?. Behav. Ecol. 17, 889–896. https://doi.org/10.1093/beheco/arl023 (2006).Article 

Google Scholar 
Barr, J. I., Somaweera, R., Godfrey, S. S. & Bateman, P. W. Increased tail length in the King’s skink, Egernia kingii (Reptilia: Scincidae): An anti-predation tactic for juveniles?. Biol. J. Linn. Soc. 126, 268–275 (2019).Article 

Google Scholar 
Pafilis, P. & Valakos, E. D. Loss of caudal autotomy during ontogeny of Balkan Green Lizard, Lacerta trilineata. J. Nat. Hist. 42, 409–419 (2008).Article 

Google Scholar 
Masters, C. & Shine, R. Sociality in lizards: family structure in free-living King’s Skinks Egernia kingii from southwestern Australia. Aust. Zool. 32, 377–380 (2003).Article 

Google Scholar 
Cury de Barros, F., Eduardo de Carvalho, J., Abe, A. S. & Kohlsdorf, T. Fight versus flight: The interaction of temperature and body size determines antipredator behaviour in tegu lizards. Anim. Behav. 79, 83–88. https://doi.org/10.1016/j.anbehav.2009.10.006 (2010).Article 

Google Scholar 
Storr, G. The genus Egernia (Lacertilia, Scincidae) in Western Australia. Rec. West. Aust. Mus. 6, 147–187 (1978).
Google Scholar 
Cogger, H. G. Reptiles and Amphibians of Australia. 7th edn, (CSIRO Publishing, 2014).Arena, P. C. & Wooller, R. D. The reproduction and diet of Egernia kingii (Reptilia : Scincidae) on Penguin Island, Western Australia. Aust. J. Zool. 51, 495–504. https://doi.org/10.1071/ZO02040 (2003).Article 

Google Scholar 
Dilly, M. L. Factors Affecting the Distribution and Variation in Abundance of the King’s Skink (Egernia kingii) (Gray) in Western Australia, Murdoch University (2000).Pearson, D., Shine, R. & How, R. Sex-specific niche partitioning and sexual size dimorphism in Australian pythons (Morelia spilota imbricata). Biol. J. Linn. Soc. 77, 113–125 (2002).Article 

Google Scholar 
Chapple, D. G. Ecology, life-history, and behaviour in the Australian scincid genus Egernia, with comments on the evolution of complex sociality in lizards. Herpetol. Monogr. 17, 145–180. https://doi.org/10.1655/0733-1347(2003)017[0145:ELABIT]2.0.CO;2 (2003).Article 

Google Scholar 
Itescu, Y., Schwarz, R., Meiri, S., Pafilis, P. & Clegg, S. Intraspecific competition, not predation, drives lizard tail loss on islands. J. Anim. Ecol. 86, 66–74. https://doi.org/10.1111/1365-2656.12591 (2017).Article 
PubMed 

Google Scholar 
Siliceo-Cantero, H., Zúñiga-Vega, J., Renton, K. & Garcia, A. Assessing the relative importance of intraspecific and interspecific interactions on the ecology of Anolis nebulosus lizards from an island vs. a mainland population. Herpetol. Conserv. Biol. 12, 673–682 (2017).
Google Scholar 
Langkilde, T. & Shine, R. Interspecific conflict in lizards: Social dominance depends upon an individual’s species not its body size. Austral Ecol. 32, 869–877 (2007).Article 

Google Scholar 
Pafilis, P., Pérez-Mellado, V. & Valakos, E. Postautotomy tail activity in the Balearic lizard, Podarcis lilfordi. Naturwissenschaften 95, 217–221 (2008).ADS 
CAS 
Article 

Google Scholar 
Browne, C. King’s Skinks (Egernia kingii) Abundance and Juvenile Survival Unaffected by Temporal Change or Presence of Invasive BLACK Rats (Rattus rattus) on Penguin Island, Western Australia, The University of Western Australia (2014).Langton, J. Population Biology of the King’s Skink (Egernia kingii) (Gray) on Penguin Island, Western Australia, Murdoch University (2000).Arena, P. Aspects of the Biology of the King’s Skink Egernia kingii (Gray), Murdoch University (1986).Pafilis, P., Meiri, S., Foufopoulos, J. & Valakos, E. Intraspecific competition and high food availability are associated with insular gigantism in a lizard. Naturwissenschaften 96, 1107–1113. https://doi.org/10.1007/s00114-009-0564-3 (2009).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Martín, J. & Salvador, A. Tail loss reduces mating success in the Iberian rock-lizard, Lacerta monticola. Behav. Ecol. Sociobiol. 32, 185–189 (1993).Article 

Google Scholar 
Salvador, A., Martin, J. & López, P. Tail loss reduces home range size and access to females in male lizards, Psammodromus algirus. Behav. Ecol. 6, 382–387. https://doi.org/10.1093/beheco/6.4.382 (1995).Article 

Google Scholar 
Smyth, M. Changes in the fat scores of the skinks Morethia boulengeri and Hemiergis peronii (Lacertilia). Aust. J. Zool. 22, 135–145. https://doi.org/10.1071/ZO9740135 (1974).Article 

Google Scholar 
Wilson, R. S. & Booth, D. Effect of tail loss on reproductive output and its ecological significance in the skink Eulamprus quoyii. J. Herpetol. 32, 128–131 (1998).Article 

Google Scholar 
Fox, S. F. & McCoy, J. K. The effects of tail loss on survival, growth, reproduction, and sex ratio of offspring in the lizard Uta stansburiana in the field. Oecologia 122, 327–334. https://doi.org/10.1007/s004420050038 (2000).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Dial, B. E. & Fitzpatrick, L. C. Predator escape success in tailed versus tailless Scinella lateralis (Sauria: Scincidae). Anim. Behav. 32, 301–302 (1984).Article 

Google Scholar 
Downes, S. & Shine, R. Why does tail loss increase a lizard’s later vulnerability to snake predators?. Ecology 82, 1293–1303 (2001).Article 

Google Scholar 
Bernardo, J. & Agosta, S. J. Evolutionary implications of hierarchical impacts of nonlethal injury on reproduction, including maternal effects. Biol. J. Linn. Soc. 86, 309–331 (2005).Article 

Google Scholar 
Stankowich, T. & Blumstein, D. T. Fear in animals: A meta-analysis and review of risk assessment. Proc. R. Soc. Biol. Sci. Ser. B 272, 2627–2634. https://doi.org/10.1098/rspb.2005.3251 (2005).Article 

Google Scholar 
Steindler, L. A., Blumstein, D. T., West, R., Moseby, K. E. & Letnic, M. Exposure to a novel predator induces visual predator recognition by naïve prey. Behav. Ecol. Sociobiol. 74, 102. https://doi.org/10.1007/s00265-020-02884-3 (2020).Article 

Google Scholar 
Blumstein, D. T. Moving to suburbia: Ontogenetic and evolutionary consequences of life on predator-free islands. J. Biogeogr. 29, 685–692. https://doi.org/10.1046/j.1365-2699.2002.00717.x (2002).Article 

Google Scholar 
Sih, A. et al. Predator–prey naïveté, antipredator behavior, and the ecology of predator invasions. Oikos 119, 610–621 (2010).Article 

Google Scholar 
Cooper, J. W. E.; Blumstein, D. T. Escaping From Predators: An Integrative View of Escape Decisions. (Cambridge University Press, 2015).Cox, J. G. & Lima, S. L. Naiveté and an aquatic–terrestrial dichotomy in the effects of introduced predators. Trends Ecol. Evol. 21, 674–680 (2006).Article 

Google Scholar 
Blumstein, D. T. & Daniel, J. C. The loss of anti-predator behaviour following isolation on islands. Proc. R. Soc. Biol. Sci. Ser. B 272, 1663–1668 (2005).Article 

Google Scholar 
Blumstein, D. T., Daniel, J. C. & Springett, B. P. A test of the multi-predator hypothesis: Rapid loss of antipredator behavior after 130 years of isolation. Ethology 110, 919–934 (2004).Article 

Google Scholar 
Jolly, C. J., Webb, J. K. & Phillips, B. L. The perils of paradise: An endangered species conserved on an island loses antipredator behaviours within 13 generations. Biol. Lett. 14, 20180222 (2018).Article 

Google Scholar 
Cooper, W. E., Pérez-Mellado, V. & Vitt, L. J. Ease and effectiveness of costly autotomy vary with predation intensity among lizard populations. J. Zool. 262, 243–255 (2004).Article 

Google Scholar 
Elwood, C., Pelsinski, J. & Bateman, B. Anolis sagrei (Brown Anole). Voluntary autotomy. Herpetol. Rev. 43, 642–642 (2012).
Google Scholar 
Slotopolsky, B. Beiträge zur Kenntnis der Verstümmelungs-und Regenerationsvorgänge am Lacertilierschwanze. Zool. Jahrb. Abt. Anat. Ontog. Tiere 43, 39–48 (1922).
Google Scholar  More

D’Amen, M., Zimmermann, N. E. & Pearman, P. B. Conservation of phylogeographic lineages under climate change. Glob. Ecol. Biogeogr. 22, 93–104. https://doi.org/10.1111/j.1466-8238.2012.00774.x (2013).Article 

Google Scholar 
Espíndola, A. et al. Predicting present and future intra-specific genetic structure through niche hindcasting across 24 millennia. Ecol. Lett. 15, 649–657. https://doi.org/10.1111/j.1461-0248.2012.01779.x (2012).Article 
PubMed 

Google Scholar 
Manel, S., Schwartz, M. K., Luikart, G. & Taberlet, P. Landscape genetics: combining landscape ecology and population genetics. Tr. Ecol. Evolut. 18, 189–197. https://doi.org/10.1016/S0169-5347(03)00008-9 (2003).Article 

Google Scholar 
Fontaine, C., Lovett, P., Sanou, H., Maley, J. & Bouvet, J. M. Genetic diversity of the shea tree (Vitellaria paradoxa CF Gaertn), detected by RAPD and chloroplast microsatellite markers. Heredity 93, 639 (2004).CAS 
Article 

Google Scholar 
Hampe, A., El Masri, L. & Petit, R. J. Origin of spatial genetic structure in an expanding oak population. Mol. Ecol. 19, 459–471. https://doi.org/10.1111/j.1365-294X.2009.04492.x (2010).Article 
PubMed 

Google Scholar 
Omondi, S. F., Odee, D. W., Ongamo, G. O., Kanya, J. I. & Khasa, D. P. Genetic consequences of anthropogenic disturbances and population fragmentation in Acacia senegal. Conserv. Genet. 17, 1235–1244. https://doi.org/10.1007/s10592-016-0854-1 (2016).Article 

Google Scholar 
Hewitt, G. Postglacial recolonization of European biota. Biol. J. Lin. Soc. 68, 87–112 (1999).Article 

Google Scholar 
Donkpegan, A. S. L. et al. Population genomics of the widespread African savannah trees Afzelia africana and Afzelia quanzensis reveals no significant past fragmentation of their distribution ranges. Am. J. Bot. 107, 498–509. https://doi.org/10.1002/ajb2.1449 (2020).Article 
PubMed 

Google Scholar 
Etterson, J. R. & Shaw, R. G. Constraint to adaptive evolution in response to global warming. Science 294, 151–154. https://doi.org/10.1126/science.1063656 (2001).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Holderegger, R. & Wagner, H. Landscape genetics. Bioscience 58, 199–207. https://doi.org/10.1641/B580306 (2008).Article 

Google Scholar 
Hampe, A. & Petit, R. J. Conserving biodiversity under climate change: the rear edge matters. Ecol. Lett. 8, 461–467. https://doi.org/10.1111/j.1461-0248.2005.00739.x (2005).Article 
PubMed 

Google Scholar 
Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42. https://doi.org/10.1038/nature01286 (2003).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Pauls, S. U., Nowak, C., Bálint, M. & Pfenninger, M. The impact of global climate change on genetic diversity within populations and species. Mol. Ecol. 22, 925–946. https://doi.org/10.1111/mec.12152 (2013).Article 
PubMed 

Google Scholar 
Arnell, N. W. & Lloyd-Hughes, B. The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios. Climatic Ch. 122, 127–140. https://doi.org/10.1007/s10584-013-0948-4 (2014).ADS 
Article 

Google Scholar 
Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747 (2010).ADS 
CAS 
Article 

Google Scholar 
van Vuuren, D. P. et al. The representative concentration pathways: an overview. Climatic Ch. 109, 5–31. https://doi.org/10.1007/s10584-011-0148-z (2011).ADS 
Article 

Google Scholar 
Prather, M. et al. Annex II: climate system scenario tables. Climate Ch. 1395–1445 (2013).Pachauri, R. K. et al. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Synthesis report (Intergovernmental Panel on Climate Change, Geneva, Switzerland, 2014).Müller, C. Climate change impact on Sub-Saharan Africa. An overview and analysis of scenarios and models (Dt. Inst. für Entwicklungspolitik, Bonn, 2009).Serdeczny, O. et al. Climate change impacts in Sub-Saharan Africa: From physical changes to their social repercussions. Reg. Environ. Ch. 17, 1585–1600. https://doi.org/10.1007/s10113-015-0910-2 (2016).Article 

Google Scholar 
Linder, H. P. et al. The partitioning of Africa: Statistically defined biogeographical regions in sub-Saharan Africa. J. Biogeogr. 39, 1189–1205. https://doi.org/10.1111/j.1365-2699.2012.02728.x (2012).Article 

Google Scholar 
Sexton, G. J. et al. Influence of putative forest refugia and biogeographic barriers on the level and distribution of genetic variation in an African savannah tree, Khaya senegalensis (Desr.) A. Juss. Tree Genet. Genomes https://doi.org/10.1007/s11295-015-0933-3 (2015).Article 

Google Scholar 
Linder, H. P. et al. Numerical re-evaluation of the sub-Saharan phytopchoria of mainland Africa. Biologiske Skrifter 55, 229–252 (2005).ADS 

Google Scholar 
Ruiz Guajardo, J. C. et al. Landscape genetics of the key African acacia species Senegalia mellifera (Vahl)- the importance of the Kenyan Rift Valley. Mol. Ecol. 19, 5126–5139. https://doi.org/10.1111/j.1365-294X.2010.04833.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Kebede, M., Enrich, D., Taberlet, P., Nemomissa, S. & Brochmann, C. Phylogeography and conservation genetics of a giant lobelia (Lobelia giberroa) in Ethiopian and Tropical East African mountains. Mol. Ecol. 16, 1233–1243. https://doi.org/10.1111/j.1365-294x.2007.03232.x (2007).CAS 
Article 
PubMed 

Google Scholar 
Kadu, C. et al. Phylogeography of the Afromontane Prunus africana reveals a former migration corridor between East and West African highlands. Mol. Ecol. 20, 165–178. https://doi.org/10.1111/j.1365-294X.2010.04931.x (2011).CAS 
Article 
PubMed 

Google Scholar 
Lyam, P. T., Duque-Lazo, J., Schnitzler, J., Hauenschild, F. & Müllner-Riehl, A. N. Testing the forest refuge hypothesis in sub-Saharan Africa using species distribution modeling for a key savannah tree species, Senegalia senegal (L.) Britton. Front. Biogeogr. https://doi.org/10.21425/F5FBG48689 (2020).Article 

Google Scholar 
Logossa, Z. A. et al. Molecular data reveal isolation by distance and past population expansion for the shea tree (Vitellaria paradoxa C.F. Gaertn) in West Africa. Mol. Ecol. 20, 4009–4027. https://doi.org/10.1111/j.1365-294X.2011.05249.x (2011).Article 
PubMed 

Google Scholar 
Lompo, D., Vinceti, B., Konrad, H., Gaisberger, H. & Geburek, T. Phylogeography of African locust bean (Parkia biglobosa) reveals genetic divergence and spatially structured populations in west and central Africa. J. Heredity 109, 811–824. https://doi.org/10.1093/jhered/esy047 (2018).Article 

Google Scholar 
Leong Pock Tsy, J.-M. et al. Chloroplast DNA phylogeography suggests a West African centre of origin for the baobab, Adansonia digitata L. (Bombacoideae, Malvaceae). Mol. Ecol. 18, 1707–1715. https://doi.org/10.1111/j.1365-294X.2009.04144.x (2009).CAS 
Article 
PubMed 

Google Scholar 
Allal, F. et al. Past climate changes explain the phylogeography of Vitellaria paradoxa over Africa. Heredity 107, 174–186. https://doi.org/10.1038/hdy.2011.5 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Fagg, C. W. & Allison, G. E. Acacia Senegal and the gum arabic trade: monograph and annotated bibliography (University of Oxford, United Kingdom, 2004).
Google Scholar 
Lézine, A. M. Late Quaternary vegetation and climate of the Sahel. Quatern. Res. 32, 317–334 (1989).ADS 
Article 

Google Scholar 
Steele, T. Vertebrate records: Late Pleistocene of Africa. In Encyclopedia of Quaternary Science, edited by S. Elias. (Elsevier, Oxford, 2007), 3139–3150.Raddad, E., Salih, A., Fadl, M., Kaarakka, V. & Luukkanen, O. Symbiotic nitrogen fixation in eight Acacia senegal provenances in dryland clays of the Blue Nile Sudan estimated by the 15N natural abundance method. Plant Soil 275, 261–269. https://doi.org/10.1007/s11104-005-2152-4 (2005).CAS 
Article 

Google Scholar 
Gray, A. et al. Does geographic origin dictate ecological strategies in Acacia senegal (L.) Willd? Evidence from carbon and nitrogen stable isotopes. Plant Soil 369, 479–496. https://doi.org/10.1007/s11104-013-1593-4 (2013).CAS 
Article 

Google Scholar 
Ross, J. H. A conspectus of African acacia species (1979).Odee, D. W., Telford, A., Wilson, J., Gaye, A. & Cavers, S. Plio-Pleistocene history and phylogeography of Acacia senegal in dry woodlands and savannahs of sub-Saharan tropical Africa: evidence of early colonisation and recent range expansion. Heredity 109, 372–382. https://doi.org/10.1038/hdy.2012.52 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Lyam, P. et al. Genetic diversity and distribution of Senegalia senegal (L.) Britton under climate change scenarios in West Africa. PLoS ONE 13, e0194726 (2018).Article 

Google Scholar 
Nicotra, A. B. et al. Plant phenotypic plasticity in a changing climate. Trends in Plant Science 15, 684–692; https://doi.org/10.1016/j.tplants.2010.09.008 (2010).Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978. https://doi.org/10.1002/joc.1276 (2005).Article 

Google Scholar 
ESRI. ArcGIS Desktop: Release 10.5. Redlands, CA: Environmental Systems Research Institute (2020).Kopelman, N. M., Mayzel, J., Jakobsson, M., Rosenberg, N. A. & Mayrose, I. Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Res. 15, 1179–1191. https://doi.org/10.1111/1755-0998.12387 (2015).CAS 
Article 

Google Scholar 
Elhadji, S. D. et al. Exploring genetic diversity and structure of Acacia senegal (L.) Willd to improve its conservation in Niger. African J. Biotechnol. 16, 1650–1659 (2017).Article 

Google Scholar 
Muriira, N. G., Muchugi, A., Yu, A., Xu, J. & Liu, A. Genetic Diversity Analysis Reveals Genetic Differentiation and Strong Population Structure in Calotropis Plants. Sci. Rep. 8, 7832 (2018).ADS 
Article 

Google Scholar 
Conord, C., Gurevitch, J. & Fady, B. Large-scale longitudinal gradients of genetic diversity: a meta-analysis across six phyla in the Mediterranean basin. Ecol. Evol. 2, 2600–2614. https://doi.org/10.1002/ece3.350 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Omondi, S. F. et al. Genetic diversity and population structure of Acacia senegal (L) Willd Kenya. Trop. Plant Biol. 3, 59–70 (2010).Article 

Google Scholar 
Marko, P. B. & Hart, M. W. The complex analytical landscape of gene flow inference. Trends Ecol. Evol. 26, 448–456. https://doi.org/10.1016/j.tree.2011.05.007 (2011).Article 
PubMed 

Google Scholar 
Goncalves, A. L., García, M. V., Heuertz, M. & González-Martínez, S. C. Demographic history and spatial genetic structure in a remnant population of the subtropical tree Anadenanthera colubrina var cebil (Griseb.) Altschul (Fabaceae). Ann. Forest Sci. https://doi.org/10.1007/s13595-019-0797-z (2019).Article 

Google Scholar 
Rosenzweig, M. L. Species diversity in space and time (Cambridge university press, 1995).Vellend, M. & Geber, M. A. Connections between species diversity and genetic diversity. Ecol. Lett. 8, 767–781. https://doi.org/10.1111/j.1461-0248.2005.00775.x (2005).Article 

Google Scholar 
Ackerly, D. D. et al. The geography of climate change: implications for conservation biogeography. Divers. Distrib. 16, 476–487. https://doi.org/10.1111/j.1472-4642.2010.00654.x (2010).Article 

Google Scholar 
Waldvogel, A.-M. et al. Evolutionary genomics can improve prediction of species’ responses to climate change. Evol. Lett. 4, 4–18. https://doi.org/10.1002/evl3.154 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Hutchison, D. W. & Templeton, A. R. Correlation of pairwise genetic and geographic distance measures: inferring the relative influences of gene flow and drift on the distribution of genetic variability. Evol.; Int. J. Org. Evol. 53, 1898–1914 (1999).Article 

Google Scholar 
Shi, M. M., Michalski, S. G., Welk, E., Chen, X. Y. & Durka, W. Phylogeography of a widespread Asian subtropical tree: genetic east-west differentiation and climate envelope modelling suggest multiple glacial refugia. J. Biogeogr. 41, 1710–1720. https://doi.org/10.1111/jbi.12322 (2014).Article 

Google Scholar 
Voss, N., Eckstein, R. L. & Durka, W. Range expansion of a selfing polyploid plant despite widespread genetic uniformity. Ann. Botany 110, 585–593. https://doi.org/10.1093/aob/mcs117 (2012).Article 

Google Scholar 
Fiorini, C. F. et al. Phylogeography of the specialist plant Mandirola hirsuta (Gesneriaceae) suggests ancient habitat fragmentation due to savanna expansion. Flora 262, 151522 (2020).Article 

Google Scholar 
Sexton, J. P., Hangartner, S. B. & Hoffmann, A. A. Genetic isolation by environment or distance: which pattern of gene flow is most common?. Evolution 68, 1–15. https://doi.org/10.1111/evo.12258 (2014).CAS 
Article 
PubMed 

Google Scholar 
Wang, I. J. & Bradburd, G. S. Isolation by environment. Mol. Ecol. 23, 5649–5662. https://doi.org/10.1111/mec.12938 (2014).Article 
PubMed 

Google Scholar 
Nosil, P., Vines, T. H. & Funk, D. J. Reproductive isolation caused by natural selection against immigrants from divergent habitats. Evol.; Int. J. Org. Evol. 59, 705–719 (2005).
Google Scholar 
Wang, I. J. & Summers, K. Genetic structure is correlated with phenotypic divergence rather than geographic isolation in the highly polymorphic strawberry poison-dart frog. Mol. Ecol. 19, 447–458. https://doi.org/10.1111/j.1365-294X.2009.04465.x (2010).Article 
PubMed 

Google Scholar 
Xu, B. et al. Population genetic structure is shaped by historical, geographic, and environmental factors in the leguminous shrub Caragana microphylla on the Inner Mongolia Plateau of China. BMC Plant Biol. 17, 200 (2017).Article 

Google Scholar 
Hendry, A. P. & Day, T. Population structure attributable to reproductive time: isolation by time and adaptation by time. Mol. Ecol. 14, 901–916. https://doi.org/10.1111/j.1365-294X.2005.02480.x (2005).CAS 
Article 
PubMed 

Google Scholar 
Solomon, S., Manning, M., Marquis, M. & Qin, D. Climate change 2007-the physical science basis: Working group I contribution to the fourth assessment report of the IPCC (Cambridge university press, 2007).Thuiller, W. Climate change and the ecologist. Nature 448, 550–552 (2007).ADS 
CAS 
Article 

Google Scholar 
Osland, M. J. et al. Tropicalization of temperate ecosystems in North America: The northward range expansion of tropical organisms in response to warming winter temperatures. Global Ch. Biol. 27, 3009–3034 (2021).Article 

Google Scholar 
Higgins, S. I., Lavorel, S. & Revilla, E. Estimating plant migration rates under habitat loss and fragmentation. Oikos 101, 354–366 (2003).Article 

Google Scholar 
Jump, A. S. & Penuelas, J. Running to stand still: adaptation and the response of plants to rapid climate change. Ecol. Lett. 8, 1010–1020. https://doi.org/10.1111/j.1461-0248.2005.00796.x (2005).Article 
PubMed 

Google Scholar 
Jump, A. S., Marchant, R. & Peñuelas, J. Environmental change and the option value of genetic diversity. Trends Plant Sci. 14, 51–58. https://doi.org/10.1016/j.tplants.2008.10.002 (2009).CAS 
Article 
PubMed 

Google Scholar 
Kirk, H. & Freeland, J. R. Applications and implications of neutral versus non-neutral markers in molecular ecology. Int. J. Mol. Sci. 12, 3966–3988. https://doi.org/10.3390/ijms12063966 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Bucharova, A. et al. Mix and match: regional admixture provenancing strikes a balance among different seed-sourcing strategies for ecological restoration. Conserv. Genet. 20, 7–17. https://doi.org/10.1007/s10592-018-1067-6 (2019).Article 

Google Scholar 
Tong, Y. et al. Ex situ conservation of Pinus koraiensis can preserve genetic diversity but homogenizes population structure. Forest Ecol. Manag. 465, 117820 (2020).Article 

Google Scholar 
Vessella, F., Simeone, M. C. & Schirone, B. Quercus suber range dynamics by ecological niche modelling: from the Last Interglacial to present time. Quat. Sci. Rev. 119, 85–93. https://doi.org/10.1016/j.quascirev.2015.04.018 (2015).ADS 
Article 

Google Scholar 
Lovejoy, T. E. Climate change and biodiversity (TERI Press, India, 2006).
Google Scholar 
Poczai, P., Varga, I., Bell N.E. & Hyvonen, J. The molecular basis of plant genetic diversity. In Genomics meets biodiversity: advances in molecular marker development and their applications in plant genetic diversity assessment. The molecular basis of plant genetic diversity, edited by M. Caliskan (InTech Open Access Publisher2012), 3–31.Botermans, M., Sosef, M. S. M., Chatrou, L. W. & Couvreur, T. L. P. Revision of the African Genus Hexalobus (Annonaceae). Syst. Bot. 36, 33–48. https://doi.org/10.1600/036364411X553108 (2011).Article 

Google Scholar 
Sosef, M. et al. Exploring the floristic diversity of tropical Africa. BMC Biol. 15, 15 (2017).Article 

Google Scholar 
Chapuis, M.-P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631. https://doi.org/10.1093/molbev/msl191 (2007).CAS 
Article 
PubMed 

Google Scholar 
Escoffier, L. & Lische, H. ARLEQUIN suite ver. 3.5. A new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Res. 10, 564–567 (2010).Article 

Google Scholar 
Lewis, P. O. & Zaykin, D. Genetic data analysis: computer program for the analysis of allelic data. Mol. Ecol. 11, 1157–1164 (2002).Article 

Google Scholar 
AComputer Program to Calculate F-Statistics. Goudet, J. FSTAT (Version 1.2). J. Hered. 6, 245–246 (1995).
Google Scholar 
El Mousadik, A. & Petit, R. J. High level of genetic differentiation for allelic richness among populations of the argan tree [Argania spinosa (L.) Skeels] endemic to Morocco. Theor. Appl. Genet. 92, 832–839 (1996).Article 

Google Scholar 
Raymond, M. & Rousset, F. GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J. Heredity 86, 248–249 (1995).Article 

Google Scholar 
Pritchard, J., Stephens, M. & Donelly, P. Inference of Population Structure Using Multilocus Genotype Data, 945–959 (2000).Falush, D., Stephens, M. & Pritchard, J. K. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164, 1567–1587 (2003).CAS 
Article 

Google Scholar 
Earl, D. A. & von Holdt, B. M. STRUCTURE HARVESTER A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361. https://doi.org/10.1007/s12686-011-9548-7 (2012).Article 

Google Scholar 
Pritchard, J. K., Wen, W. & Falush, D. Documentation for STRUCTURE software: Version 2.3. University of Chicago, Chicago, IL, 1–37 (2010).Eliades, N. G. & Eliades, D. G. HAPLOTYPE ANALYSIS: software for analysis of haplotype data. Forest Goettingen (Germany): Genetics and Forest Tree Breeding, Georg-August University Goettingen (2009).Leigh, J. W. & Bryant, D. POPART: full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).Article 

Google Scholar 
Peakall, R. & Smouse, P. E. Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.x (2006).Article 

Google Scholar 
Title, P. O. & Bemmels, J. B. ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography 41, 291–307. https://doi.org/10.1111/ecog.02880 (2018).Article 

Google Scholar 
Hengl, T. et al. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).Article 

Google Scholar 
Wang, I. J. Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological isolation. Evolution 67, 3403–3411. https://doi.org/10.1111/evo.12134 (2013).Article 
PubMed 

Google Scholar  More

Fu, C. H. et al. Relationships among fisheries exploitation, environmental conditions, and ecological indicators across a series of marine ecosystems. J. Mar. Syst. 148, 101–111 (2015).Article 

Google Scholar 
Too, C. C., Ong, K. S., Yule, C. M. & Keller, A. Putative roles of bacteria in the carbon and nitrogen cycles in a tropical peat swamp fores. Basic Appl. Ecol. 52, 109–123 (2020).Article 

Google Scholar 
Hou, R. J. et al. Effects of biochar and straw on greenhouse gas emission and its response mechanism in seasonally frozen farmland ecosystems. Catena 194, 104735 (2020).CAS 
Article 

Google Scholar 
Wang, X., Lu, P., Yang, P. L. & Ren, S. M. Effects of fertilizer and biochar applications on the relationship among soil moisture, temperature, and N2O emissions in farmland. PeerJ 9, e11674–e11674 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Tang, Z. M., Liu, X. R., Zhang, Q. W. & Li, G. C. Effects of biochar and straw on soil N2O emission from a wheat maize rotation system. Huan Jing Ke Xue 42(3), 1569–1580 (2021).PubMed 

Google Scholar 
Kong, Q., Wang, Z. B., Niu, P. F. & Miao, M. S. Greenhouse gas emission and microbial community dynamics during simultaneous nitrification and denitrification process. Biores. Technol. 210, 94–100 (2016).CAS 
Article 

Google Scholar 
Han, Z. M. et al. Spatial-temporal dynamics of agricultural drought in the Loess Plateau under a changing environment: Characteristics and potential influencing factors. Agric. Water Manag. 244, 106540 (2021).Article 

Google Scholar 
Clemens, S. et al. Nitrification inhibitors can increase post-harvest nitrous oxide emissions in an intensive vegetable production system. Sci. Rep. 7(1), 1–9 (2017).Article 
CAS 

Google Scholar 
Zhang, D. J. et al. Effects of tillage and fertility on soil nitrogen balance and greenhouse gas emissions of wheat-maize rotation system in Central Henan Province, China. J. Appl. Ecol. 32(5), 1753–1760 (2021).
Google Scholar 
Liu, X. C. et al. Response of soil N2O emissions to precipitation pulses under different nitrogen availabilities in a semiarid temperate steppe of Inner Mongolia, China. J. Arid Land 6(04), 410–422 (2014).Article 

Google Scholar 
Hu, Q. Y. et al. Combined effects of straw returning and chemical n fertilization on greenhouse gas emissions and yield from paddy fields in northwest Hubei Province, China. J. Soil Sci. Plant Nutr. 20(2), 392–406 (2019).Article 
CAS 

Google Scholar 
Sun, Z. C. et al. Effects of straw returning and feeding on greenhouse gas emissions from integrated rice-crayfish farming in Jianghan Plain, China. Environ. Sci. Pollut. Res. 26(12), 11710–11718 (2019).CAS 
Article 

Google Scholar 
Mei, K. et al. Stimulation of N2O emission by conservation tillage management in agricultural lands: A meta-analysis. Soil Tillage Res. 182, 86–93 (2018).Article 

Google Scholar 
Wang, H. Y., Wu, J. Q., Li, G. & Yan, L. J. Changes in soil carbon fractions and enzyme activities under different vegetation types of the northern Loess Plateau. Ecol. Evol. 10(21), 12211–12223 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Sadiq, M., Li, G., Rahim, N. & Tahir, M. M. Sustainable conservation tillage technique for improving soil health by enhancing soil physicochemical quality indicators under wheat mono-cropping system conditions. Sustainability 13(15), 8177–8177 (2021).CAS 
Article 

Google Scholar 
Nie, Z. G. et al. Evaluating the effects of different sowing dates and tillage methods on dry-land wheat grain dry matter accumulation based on the APSIM model. J. Appl. Ecol. 32(3), 913–920 (2021).
Google Scholar 
Alhassan, A. M., Yang, C. J., Ma, W. W. & Li, G. Influence of conservation tillage on Greenhouse gas fluxes and crop productivity in spring-wheat agroecosystems on the Loess Plateau of China. PeerJ 9, e11064–e11064 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Mou, L. M. et al. Breeding report of a new dryland spring wheat variety Dingxi 42. Gansu Agric. Sci. Technol. 01, 1–3 (2015).ADS 

Google Scholar 
Ma, W. W., Li, G., Wu, J. H., Xu, G. R. & Wu, J. Q. Respiration and CH4 fluxes in Tibetan peatlands are influenced by vegetation degradation. CATENA 195, 104789 (2020).CAS 
Article 

Google Scholar 
Wu, J. Q. et al. Vegetation degradation impacts soil nutrients and enzyme activities in wet meadow on the Qinghai-Tibet Plateau. Sci. Rep. 10(1), 21271–21271 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Défossez, P. et al. Impact of soil water content on the overturning resistance of young Pinus Pinaster in sandy soil. For. Ecol. Manag. 480, 118614 (2021).Article 

Google Scholar 
Mao, J., Nierop, K. G., Rietkerk, M., Damsté, J. S. S. & Te Dekker, S. C. infuence of vegetation on soil water repellency-markers and soil hydrophobicity. Sci. Total Environ. 566, 608–620 (2016).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Lu, Y., Si, B., Li, H. & Biswas, A. Elucidating controls of the variability of deep soil bulk density. Geoderma 348, 146–157 (2019).ADS 
Article 

Google Scholar 
Huang, T. T., Yang, N., Lu, C., Qin, X. L. & Siddique, K. Soil organic carbon, total nitrogen, available nutrients, and yield under different straw returning methods. Soil Tillage Res. 214, 105171 (2021).Article 

Google Scholar 
Yang, J. M., Zhang, Z. Q. & Cao, G. J. Soil nitrate and nitrite content determined by Skalar SAN++. Soil Fertil. Sci. China 02, 101–105 (2014).
Google Scholar 
Chen, N. et al. Effect of biodegradable film mulching on crop yield, soil microbial and enzymatic activities, and optimal levels of irrigation and nitrogen fertilizer for the Zea mays crops in arid region. Sci. Total Environ. 776, 145970–145970 (2021).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Akhtar, K. et al. Straw mulching with inorganic nitrogen fertilizer reduces soil CO2 and N2O emissions and improves wheat yield. Sci. Tot. Environ. 741, 140488 (2020).CAS 
Article 

Google Scholar 
Ma, E. et al. Effects of rice straw returning methods on N2O emission during wheat-growing season. Nutr. Cycl. Agroecosyst. 88(3), 463–469 (2009).Article 
CAS 

Google Scholar 
Yeboah, S. et al. Greenhouse gas emissions in a spring wheat–field pea sequence under different tillage practices in semi-arid Northwest China. Nutr. Cycl. Agroecosyst. 106(1), 77–91 (2016).CAS 
Article 

Google Scholar 
Zahid, A., Ali, S., Ahmed, M. & Iqbal, N. Improvement of soil health through residue management and conservation tillage in rice-wheat cropping system of Punjab, Pakistan. Agronomy 10(12), 1844–1844 (2020).CAS 
Article 

Google Scholar 
Dharmendra, S. et al. Effect of reversal of conservation tillage on soil nutrient availability and crop nutrient uptake in soybean in the vertisols of central India. Sustainability. 12(16), 6608 (2020).Article 
CAS 

Google Scholar 
Orzech, K., Wanic, M. & Załuski, D. The effects of soil compaction and different tillage systems on the bulk density and moisture content of soil and the yields of winter oilseed rape and cereals. Agriculture 11(7), 666–666 (2021).CAS 
Article 

Google Scholar 
Fan, B. Q. & Liu, Q. L. Effect of conservation tillage and straw application on the soil microorganism and P-dissolving characteristics. Chin. J. Eco-Agric. 03, 130–132 (2005).
Google Scholar 
Liu, X. et al. Dynamic contribution of microbial residues to soil organic matter accumulation influenced by maize straw mulching. Geoderma 333, 35–42 (2019).ADS 
CAS 
Article 

Google Scholar 
Wang, W. Y. et al. Conservation tillage enhances crop productivity and decreases soil nitrogen losses in a rainfed agroecosystem of the Loess Plateau, China. J. Clean. Prod. 274, 122854 (2020).CAS 
Article 

Google Scholar 
Zhang, Y., Xie, D. T., Ni, J. P. & Zeng, X. B. Conservation tillage practices reduce nitrogen losses in the sloping upland of the Three Gorges Reservoir area: No-till is better than mulch-till. Agric. Ecosyst. Environ. 300, 107003 (2020).CAS 
Article 

Google Scholar 
Andrea, F. et al. May conservation tillage enhance soil C and N accumulation without decreasing yield in intensive irrigated croplands? Results from an eight-year maize monoculture. Agric. Ecosyst. Environ. 296, 106926 (2020).Article 
CAS 

Google Scholar 
Wu, J. et al. Effects of different tillage and straw retention practices on soil aggregates and carbon and nitrogen sequestration in soils of the northwestern China. J. Arid. Land 11(04), 567–578 (2019).Article 

Google Scholar 
Niu, Y. N., Shen, Y. Y., Nan, Z. B., Yang, J. & Yang, Z. W. College of Pastoral Agriculture Science & Technology, Lanzhou University, China. Influence of different cultivation managements on organic carbon and nitrate nitrogen of top soil in the Loess Plateau, northwestern China. Proceedings of the XXI International Grassland Congress and the VIII International Rangeland Congress (volume II) (2008).Wang, Q., Li, F. R., Zhang, E. H., Li, G. & Vance, M. The effects of irrigation and nitrogen application rates on yield of spring wheat (longfu-920), and water use efficiency and nitrate nitrogen accumulation in soil. Aust. J. Crop Sci. 6(4), 662–672 (2012).
Google Scholar 
Pisani, O. et al. Soil nitrogen dynamics and leaching under conservation tillage in the Atlantic Coastal Plain, Georgia, United States. J. Soil Water Conserv. 72(5), 519–529 (2017).Article 

Google Scholar 
Cao, W. C. et al. Key production processes and influencing factors of nitrous oxide emissions from agricultural soils. J. Nutr. Fertil. 25(10), 1781–1798 (2019).
Google Scholar 
Liu, B., Huang, G. B., Gao, Y. Q., Li, Q. P. & Huang, T. Effects of no-tillage on daily dynamics of CO2 and N2O emission from spring wheat field during mature stage. J. Gansu Agric. Univ. 45(01), 82–87 (2010).
Google Scholar 
Akhtar, K. et al. Straw mulching with inorganic nitrogen fertilizer reduces soil CO2 and N2O emissions and improves wheat yield. Sci. Total Environ. 741, 140488 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Sina, B., Youngsun, K., Janine, K. & Gerhard, G. Plastic mulching in agriculture: Friend or foe of N2O emissions. Agric. Ecosyst. Environ. 167, 43–51 (2013).Article 
CAS 

Google Scholar 
Seiichi, N., Michio, K., Masako, T., Seiichiro, Y. & Naoto, K. Nitrous oxide evolved from soil covered with plastic mulch film in horticultural field. Biol. Fertil. Soils 48(7), 787–795 (2012).Article 
CAS 

Google Scholar 
Wang, J., Cai, L. Q., Zhang, R. Z., Wang, Y. L. & Dong, W. J. Effects of Tillage Measures on soil greenhouse gas (CO2, CH4, N2O) flux in temperate semi-arid area. Chin. J. Eco-Agric. 19(06), 1295–1300 (2011).CAS 
Article 

Google Scholar 
Chen, G. H. et al. Can conservation tillage reduce N2O emissions on cropland transitioning to organic vegetable production?. Sci. Total Environ. 618, 927–940 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Narendra, K. L. & Rattan, L. Soil aggregation and greenhouse gas flux after 15 years of wheat straw and fertilizer management in a no-till system. Soil Tillage Res. 126, 78–89 (2013).Article 

Google Scholar 
Liang, W., Shi, Y., Zhang, H., Yue, J. & Huang, G. H. Greenhouse gas emissions from Northeast china rice fields in fallow season. Pedosphere 17(5), 630–638 (2007).CAS 
Article 

Google Scholar 
Bremner, J. M., Robbins, S. G. & Blackmer, A. M. Seasonal variability in emission of nitrous oxide from soil. Geophys. Res. Lett. 7(9), 641–644 (1980).ADS 
CAS 
Article 

Google Scholar 
Maag, M. & Vinther, F. P. Nitrous oxide emission by nitrification and denitrification in the different soil types and at different soil moisture contents and temperature. Appl. Soil. Ecol. 4(1), 5–14 (1996).Article 

Google Scholar 
Castaldi, S. Responses of nitrous oxide, dinitrogen and carbon dioxide production and oxygen consumption to temperature in forest and agricultural light-textured soils determined by model experiment. Biol. Fertil. Soils 32(1), 67–72 (2000).MathSciNet 
CAS 
Article 

Google Scholar 
Braker, G., Schwarz, J. & Conrad, R. Influence of temperature on the composition and activity of denitrifying soil communities. FEMS Microbiol. Ecol. 73(1), 134–148 (2010).CAS 
PubMed 

Google Scholar 
Hu, H. W., Chen, D. & He, J. Z. Microbial regulation of terrestrial nitrous oxide formation: Understanding the biological pathways for prediction of emission rates. Narnia 39(5), 729–749 (2015).CAS 

Google Scholar 
Pokharel, P. & Chang, S. X. Biochar decreases the efficacy of the nitrification inhibitor nitrapyrin in mitigating nitrous oxide emissions at different soil moisture levels. J. Environ. Manage. 295, 113080–113080 (2021).CAS 
PubMed 
Article 

Google Scholar 
Shu, X. X. et al. Response of soil N2O emission and nitrogen utilization to organic matter in the wheat and maize rotation system. Sci. Rep. 11(1), 4396–4396 (2021).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bergaust, L., Mao, Y. J., Bakken, L. R. & Frostegård, A. Denitrification response patterns during the transition to anoxic respiration and posttranscriptional effects of suboptimal pH on nitrous [corrected] oxide reductase in Paracoccus denitrificans. Appl. Environ. Microbiol. 76(19), 6387–6396 (2010).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

May, R. M. Nature 238, 413–414 (1972).CAS 
Article 
PubMed 

Google Scholar 
Yonatan, Y., Amit, G., Friedman, J. & Bashan, A. Nat. Eco. Evo., https://doi.org/10.1038/s41559-022-01745-8 (2022).Yodzis, P. Nature 289, 674–676 (1981).Article 

Google Scholar 
Winemiller, K. O. Am. Nat. 134, 960–968 (1989).Article 

Google Scholar 
James, A. et al. Am. Nat. 185, 680–692 (2015).Article 
PubMed 

Google Scholar 
Schmid-Araya, J. M. et al. J. Anim. Ecol. 71, 1056–1062 (2002).Article 

Google Scholar 
Bashan, A. et al. Nature 534, 259–262 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Human Microbiome Project Consortium. Nature 486, 207–214 (2012).Article 

Google Scholar 
Moitinho-Silva, L. et al. Gigascience 6, 1–7 (2017).CAS 
Article 
PubMed 

Google Scholar 
Dunne, J. A., Williams, R. J. & Martinez, N. D. Proc. Natl Acad. Sci. USA 99, 12917–12922 (2002).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Grilli, J., Barabás, G., Michalska-Smith, M. J. & Allesina, S. Nature 548, 210–213 (2017).CAS 
Article 
PubMed 

Google Scholar  More

He, Z. et al. Speciation with gene flow via cycles of isolation and migration: insights from multiple mangrove taxa. Natl Sci. Rev. 6, 275–288 (2019).CAS 
Article 
PubMed 

Google Scholar 
Zhou, R. et al. Population genetics of speciation in nonmodel organisms: I. Ancestral polymorphism in mangroves. Mol. Biol. Evol. 24, 2746–2754 (2007).CAS 
Article 
PubMed 

Google Scholar 
Xu, S. et al. Genome-wide convergence during evolution of mangroves from woody plants. Mol. Biol. Evol. 34, 1008–1015 (2017).CAS 
PubMed 

Google Scholar 
He, Z. et al. Convergent adaptation of the genomes of woody plants at the land–sea interface. Natl Sci. Rev. 7, 978–993 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Lyu, H., He, Z., Wu, C.-I. & Shi, S. Convergent adaptive evolution in marginal environments: unloading transposable elements as a common strategy among mangrove genomes. New Phytol. 217, 428–438 (2018).CAS 
Article 
PubMed 

Google Scholar 
Xu, S. et al. The origin, diversification and adaptation of a major mangrove clade (Rhizophoreae) revealed by whole-genome sequencing. Natl Sci. Rev. 4, 721–734 (2017).CAS 
Article 
PubMed 

Google Scholar 
Feng, X. et al. Molecular adaptation to salinity fluctuation in tropical intertidal environments of a mangrove tree Sonneratia alba. BMC Plant Biol. 20, 178 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Feng, X. et al. Genomic insights into molecular adaptation to intertidal environments in the mangrove Aegiceras corniculatum. New Phytol. 231, 2346–2358 (2021).CAS 
Article 
PubMed 

Google Scholar 
Angelini, C. et al. A keystone mutualism underpins resilience of a coastal ecosystem to drought. Nat. Commun. 7, 12473 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Atwood, T. B. et al. Global patterns in mangrove soil carbon stocks and losses. Nat. Clim. Change 7, 523–528 (2017).CAS 
Article 

Google Scholar 
Barbier, E. B. et al. Coastal ecosystem-based management with nonlinear ecological functions and values. Science 319, 321–323 (2008).CAS 
Article 
PubMed 

Google Scholar 
Barbier, E. B. et al. The value of estuarine and coastal ecosystem services. Ecol. Monogr. 81, 169–193 (2011).Article 

Google Scholar 
Hensel, M. J. S. & Silliman, B. R. Consumer diversity across kingdoms supports multiple functions in a coastal ecosystem. Proc. Natl Acad. Sci. USA 110, 20621–20626 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Tomlinson, P. B. The Botany of Mangroves 2nd edn (Cambridge Univ. Press, 2016).Rovai, A. S. et al. Global controls on carbon storage in mangrove soils. Nat. Clim. Change 8, 534–538 (2018).CAS 
Article 

Google Scholar 
Alongi, D. M. Carbon sequestration in mangrove forests. Carbon Manag. 3, 313–322 (2012).CAS 
Article 

Google Scholar 
Grant, K. M. et al. Sea-level variability over five glacial cycles. Nat. Commun. 5, 5076 (2014).CAS 
Article 
PubMed 

Google Scholar 
Guo, Z. et al. Extremely low genetic diversity across mangrove taxa reflects past sea level changes and hints at poor future responses. Glob. Change Biol. 24, 1741–1748 (2018).Article 

Google Scholar 
Li, H. & Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 475, 493–496 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Sollars, E. S. A. et al. Genome sequence and genetic diversity of European ash trees. Nature 541, 212–216 (2017).CAS 
Article 
PubMed 

Google Scholar 
Zhao, S. et al. Whole-genome sequencing of giant pandas provides insights into demographic history and local adaptation. Nat. Genet. 45, 67–71 (2013).CAS 
Article 
PubMed 

Google Scholar 
Duke, N. C. in Mangrove Ecosystems: A Global Biogeographic Perspective (eds Rivera-Monroy, V. H. et al.) 17–53 (Springer, 2017).Ellison, A. M., Farnsworth, E. J. & Merkt, R. E. Origins of mangrove ecosystems and the mangrove biodiversity anomaly. Glob. Ecol. Biogeogr. 8, 95–115 (1999).
Google Scholar 
Gee, C. T. The mangrove palm Nypa in the geologic past of the new world. Wetl. Ecol. Manag. 9, 181–203 (2001).Article 

Google Scholar 
Germeraad, J. H., Hopping, C. A. & Muller, J. Palynology of tertiary sediments from tropical areas. Rev. Palaeobot. Palynol. 6, 189–348 (1968).Article 

Google Scholar 
Graham, A. Paleobotanical evidence and molecular data in reconstructing the historical phytogeography of Rhizophoraceae. Ann. Missouri Bot. Gard. 93, 325–334 (2006).Article 

Google Scholar 
Mazer, S. J. & Tiffney, B. H. Fruits of Wetherellia and Palaeowetherellia (?Euphorbiaceae) from Eocene sediments in Virginia and Maryland. Brittonia 34, 300–333 (1982).Muller, J. Fossil pollen records of extant angiosperms. Bot. Rev. 47, 1–142 (1981).Article 

Google Scholar 
Srivastava, J. & Prasad, V. Evolution and paleobiogeography of mangroves. Mar. Ecol. 40, e12571 (2019).Hu, M.-J. et al. Chromosome-scale assembly of the Kandelia obovata genome. Hortic. Res. 7, 75 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Jin, Y. & Qian, H. V.PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).Article 

Google Scholar 
Zachos, J. C., Dickens, G. R. & Zeebe, R. E. An early Cenozoic perspective on greenhouse warming and carbon-cycle dynamics. Nature 451, 279–283 (2008).CAS 
Article 
PubMed 

Google Scholar 
Handley, L., Crouch, E. M. & Pancost, R. D. A New Zealand record of sea level rise and environmental change during the Paleocene–Eocene Thermal Maximum. Palaeogeogr. Palaeoclimatol. Palaeoecol. 305, 185–200 (2011).Article 

Google Scholar 
Louca, S. & Pennell, M. W. Extant timetrees are consistent with a myriad of diversification histories. Nature 580, 502–505 (2020).CAS 
Article 
PubMed 

Google Scholar 
Saintilan, N. et al. Thresholds of mangrove survival under rapid sea level rise. Science 368, 1118–1121 (2020).CAS 
Article 
PubMed 

Google Scholar 
Lu, J. & Wu, C.-I. Weak selection revealed by the whole-genome comparison of the X chromosome and autosomes of human and chimpanzee. Proc. Natl Acad. Sci. USA 102, 4063–4067 (2005).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Lynch, M. et al. Perspective: spontaneous deleterious mutation. Evolution 53, 645–663 (1999).Article 
PubMed 

Google Scholar 
Ohta, T. Slightly deleterious mutant substitutions in evolution. Nature 246, 96–98 (1973).CAS 
Article 
PubMed 

Google Scholar 
Ohta, T. The nearly neutral theory of molecular evolution. Annu. Rev. Ecol. Syst. 23, 263–286 (1992).Article 

Google Scholar 
Liu, X. & Fu, Y. X. Exploring population size changes using SNP frequency spectra. Nat. Genet. 47, 555–559 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Liu, X. & Fu, Y.-X. Stairway Plot 2: demographic history inference with folded SNP frequency spectra. Genome Biol. 21, 280 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Krauss, K. W. et al. How mangrove forests adjust to rising sea level. New Phytol. 202, 19–34 (2014).Article 
PubMed 

Google Scholar 
Lovelock, C. E. et al. The vulnerability of Indo-Pacific mangrove forests to sea-level rise. Nature 526, 559–563 (2015).CAS 
Article 
PubMed 

Google Scholar 
Frederiksen, N. O. Review of Early Tertiary Sporomorph Paleoecology (American Association of Stratigraphic Palynologists Foundation, 1985).Smith, D. E., Harrison, S., Firth, C. R. & Jordan, J. T. The early Holocene sea level rise. Quat. Sci. Rev. 30, 1846–1860 (2011).Article 

Google Scholar 
Bouillon, S. et al. Mangrove production and carbon sinks: a revision of global budget estimates. Glob. Biogeochem. Cycles 22, GB2013 (2008).Article 
CAS 

Google Scholar 
Donato, D. C. et al. Mangroves among the most carbon-rich forests in the tropics. Nat. Geosci. 4, 293–297 (2011).CAS 
Article 

Google Scholar 
Hamilton, S. E. & Friess, D. A. Global carbon stocks and potential emissions due to mangrove deforestation from 2000 to 2012. Nat. Clim. Change 8, 240–244 (2018).CAS 
Article 

Google Scholar 
Hutchison, J., Manica, A., Swetnam, R., Balmford, A. & Spalding, M. Predicting global patterns in mangrove forest biomass. Conserv. Lett. 7, 233–240 (2014).Article 

Google Scholar 
Ouyang, X. & Lee, S. Y. Improved estimates on global carbon stock and carbon pools in tidal wetlands. Nat. Commun. 11, 317 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bauer, J. E. et al. The changing carbon cycle of the coastal ocean. Nature 504, 61–70 (2013).CAS 
Article 
PubMed 

Google Scholar 
Richards, D. R., Thompson, B. S. & Wijedasa, L. Quantifying net loss of global mangrove carbon stocks from 20 years of land cover change. Nat. Commun. 11, 4260 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Sanders, C. J. et al. Are global mangrove carbon stocks driven by rainfall? J. Geophys. Res. Biogeosci. 121, 2600–2609 (2016).Article 

Google Scholar 
Alongi, D. M. Carbon cycling and storage in mangrove forests. Ann. Rev. Mar. Sci. 6, 195–219 (2014).Article 
PubMed 

Google Scholar 
Valiela, I., Bowen, J. L. & York, J. K. Mangrove forests: one of the world’s threatened major tropical environments. Bioscience 51, 807–815 (2001).Article 

Google Scholar 
Doyle, J. J. & Doyle, J. L. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 19, 11–15 (1987).
Google Scholar 
Yang, G., Zhou, R., Tang, T. & Shi, S. Simple and efficient isolation of high-quality total RNA from Hibiscus tiliaceus, a mangrove associate and its relatives. Prep. Biochem. Biotechnol. 38, 257–264 (2008).CAS 
Article 
PubMed 

Google Scholar 
Wang, O. et al. Efficient and unique cobarcoding of second-generation sequencing reads from long DNA molecules enabling cost-effective and accurate sequencing, haplotyping, and de novo assembly. Genome Res. 29, 798–808 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, B. et al. Estimation of genomic characteristics by analyzing k-mer frequency in de novo genome projects. Preprint at https://arxiv.org/abs/1308.2012v2 (2013).Vurture, G. W. et al. GenomeScope: fast reference-free genome profiling from short reads. Bioinformatics 33, 2202–2204 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Chin, C.-S. et al. Phased diploid genome assembly with single-molecule real-time sequencing. Nat. Methods 13, 1050–1054 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Ruan, J. & Li, H. Fast and accurate long-read assembly with wtdbg2. Nat. Methods 17, 155–158 (2020).CAS 
Article 
PubMed 

Google Scholar 
Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat. Methods 18, 170–175 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Xiao, C.-L. et al. MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads. Nat. Methods 14, 1072–1074 (2017).CAS 
Article 
PubMed 

Google Scholar 
Chin, C.-S. et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat. Methods 10, 563–569 (2013).CAS 
Article 
PubMed 

Google Scholar 
Vaser, R., Sović, I., Nagarajan, N. & Šikić, M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res. 27, 737–746 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Weisenfeld, N. I., Kumar, V., Shah, P., Church, D. M. & Jaffe, D. B. Direct determination of diploid genome sequences. Genome Res. 27, 757–767 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Luo, R. et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 4, 30 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259 (2015).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Durand, N. C. et al. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 3, 95–98 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Durand, N. C. et al. Juicebox provides a visualization system for Hi-C contact maps with unlimited zoom. Cell Syst. 3, 99–101 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Dudchenko, O. et al. De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356, 92–95 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bao, W., Kojima, K. K. & Kohany, O. Repbase Update, a database of repetitive elements in eukaryotic genomes. Mob. DNA 6, 11 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Tarailo‐Graovac, M. & Chen, N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr. Protoc. Bioinformatics 25, 4.10.1–4.10.14 (2009).Article 

Google Scholar 
Flynn, J. M. et al. RepeatModeler2 for automated genomic discovery of transposable element families. Proc. Natl Acad. Sci. USA 117, 9451–9457 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Xu, Z. & Wang, H. LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 35, W265–W268 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Stanke, M. et al. AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Res. 34, W435–W439 (2006).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Burge, C. & Karlin, S. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 268, 78–94 (1997).CAS 
Article 
PubMed 

Google Scholar 
Majoros, W. H., Pertea, M. & Salzberg, S. L. TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics 20, 2878–2879 (2004).CAS 
Article 
PubMed 

Google Scholar 
Birney, E. Genewise and genomewise. Genome Res. 14, 988–995 (2004).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Kent, W. J. BLAT—The BLAST-Like Alignment Tool. Genome Res. 12, 656–664 (2002).CAS 
PubMed 
PubMed Central 

Google Scholar 
Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Cantarel, B. L. et al. MAKER: an easy-to-use annotation pipeline designed for emerging model organism genomes. Genome Res. 18, 188–196 (2007).Article 
CAS 
PubMed 

Google Scholar 
Haas, B. J. et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the program to assemble spliced alignments. Genome Biol. 9, R7 (2008).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Seppey, M., Manni, M. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness. Methods Mol. Biol. 1962, 227–245 (2019).CAS 
Article 
PubMed 

Google Scholar 
Katoh, K. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Suyama, M., Torrents, D. & Bork, P. PAL2NAL: robust conversion of protein sequence alignments into the corresponding codon alignments. Nucleic Acids Res. 34, W609–W612 (2006).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552 (2000).CAS 
Article 
PubMed 

Google Scholar 
Kozlov, A. M., Darriba, D., Flouri, T., Morel, B. & Stamatakis, A. RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics 35, 4453–4455 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Yang, Z. PAML 4: Phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).CAS 
Article 
PubMed 

Google Scholar 
Reis, M. Dos & Yang, Z. Approximate likelihood calculation on a phylogeny for Bayesian estimation of divergence times. Mol. Biol. Evol. 28, 2161–2172 (2011).Article 
CAS 
PubMed 

Google Scholar 
Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T. GGTREE: an package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol. Evol. 8, 28–36 (2017).Article 

Google Scholar 
Sanderson, M. J. r8s: inferring absolute rates of molecular evolution and divergence times in the absence of a molecular clock. Bioinformatics 19, 301–302 (2003).CAS 
Article 
PubMed 

Google Scholar 
Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).Article 
PubMed 

Google Scholar 
Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89–92 (2014).CAS 
Article 
PubMed 

Google Scholar 
Louca, S. & Doebeli, M. Efficient comparative phylogenetics on large trees. Bioinformatics 34, 1053–1055 (2018).CAS 
Article 
PubMed 

Google Scholar 
Liang, Y. et al. Chromosome level genome assembly of Andrographis paniculata. Front. Genet. 11, 701 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Zhang, L. et al. The water lily genome and the early evolution of flowering plants. Nature 577, 79–84 (2020).CAS 
Article 
PubMed 

Google Scholar 
Huang, X. et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat. Genet. 42, 961–967 (2010).CAS 
Article 
PubMed 

Google Scholar 
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Miller, K. G. et al. The Phanerozoic record of global sea-level change. Science 310, 1293–1298 (2005).CAS 
Article 
PubMed 

Google Scholar 
Marçais, G. et al. MUMmer4: a fast and versatile genome alignment system. PLoS Comput. Biol. 14, e1005944 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Narasimhan, V. et al. BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data. Bioinformatics 32, 1749–1751 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly 6, 80–92 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Hudson, R. R. Generating samples under a Wright–Fisher neutral model of genetic variation. Bioinformatics 18, 337–338 (2002).CAS 
Article 
PubMed 

Google Scholar  More

The Acadian Forest of eastern Canada has shown a pervasive signal of forest degradation since 1985 (Fig. 1). Since 1985, >3 million ha have been clear-cut (Fig. 1d), with most of this area now occupied by either tree plantations and thinnings (Fig. 1c–e), which are dominated by single tree species20, or a mix of early successional tree species (Fig. 1a,d,e). Despite some ingrowth due to succession, old forest has declined by 39% during the period observed (Extended Data Fig. 1a,b; Supplementary Methods). The pattern of extensive harvest of old forest, followed by rapid regeneration of young forest appears to be common across many forest regions of North America (for example, central Canada, southeastern United States, western United States; Fig. 1b) (ref. 10) and can be considered ‘forest degradation’ in that these practices simplify forest structure, reduce tree species diversity and truncate old-forest age classes6. During the same 35-year time period, forest cover remained relatively stable, increasing by a net 6.5% (Fig. 3a, red line)21.Fig. 3: Forest degradation rather than loss drives habitat declines in old forest-associated bird species.a, Habitat trends (1985–2020) for the seven bird species exhibiting the greatest population declines according to SDMs; all of these species are old forest associated. During the same time interval, total forest cover did not decline (red line, right axis), indicating that habitat loss is a function of forest degradation rather than loss. b,c, Predicted habitat loss (pink) and gain (blue) between 1985 and 2020 for two example species: Blackburnian warbler (33% habitat loss; b) and golden-crowned kinglet (38% habitat loss; c). Habitat loss was quantified using SDMs with Landsat data as independent variables strongly predicted population trends for forest bird species.Full size imageOverall, SDMs using Landsat reflectance bands as predictors performed well for most forest bird species when tested on 50% spatially discrete hold-out data (Extended Data Fig. 2; (bar x) area under the curve (AUC) = 0.73 [range: 0.60–0.90]). SDMs therefore provided reliable estimates of habitat suitability and distribution for most of the 54 species. Species with lower model-prediction success tended to be associated with fine-scale forest structure (for example, individual tall trees, standing and fallen dead wood) which are poorly captured by satellite imagery.We back cast SDMs to quantify habitat change for all 54 forest bird species from 1985 to 2020. Habitat declines occurred for 66% of species during 1985–2020; 93% of species exhibited habitat reductions over the past decade (Fig. 3 and Extended Data Fig. 3). Species showing the greatest decreases in habitat were golden-crowned kinglet (Regulus satrapa; −38%) and Blackburnian warbler (Setophaga fusca; −33%; Supplementary Video 1) with seven species showing habitat declines >25% (Fig. 3). Most species with strongly declining habitat are associated with old forests22 (Fig. 4a,b), which is consistent with forest degradation due to harvesting of old forest. Indeed, clear-cut harvest alone was strongly associated with habitat declines for all old forest-associated species (Fig. 4c and Extended Data Figs. 4 and 5). Forest succession into old age classes was apparently insufficient to compensate for this rate of loss. Fifteen species exhibited habitat increases, but most (14 out of 15) of these tend to be associated with young or immature forests (Fig. 4a,b).Fig. 4: Evidence for the effect of forest degradation on mature-forest bird species.a, The relationship between habitat change, estimated from SDMs and independently derived population change estimates from the BBS for the Acadian forest. Bird species of mature (old) forests (M; dark green dots) exhibit the greatest habitat loss; this is generally reflected in strongly negative population trends. Bird species associated with regenerating forest (R; red dots) tend to have stable or increasing habitat but still show BBS population declines. b, The relationship between quantitatively derived estimates of mature-forest association and habitat change from 1985 to 2020. Mature forest-associated species tend to be losing the most habitat in relation to immature- (I; light-green dots) and regeneration-associated species. Successional stage categorizations (R, I, M) are from Birds of the World (BOW). The regression line was fit using a hierarchical Bayesian model (Supplementary Methods) and grey shading in b shows 95% credible intervals. Only a subset of species is shown in b (those with quantitative data for mature-forest associations; Supplementary Methods). c, The relationship between area clear-cut occurring from 1985 to 2020 in each species’ habitat within a 200 m-diameter buffer surrounding BBS routes (N = 90) and habitat loss (1985–2020) at the same scale for six mature forest-associated species. Black lines are regression lines and grey bands are 95% confidence intervals (regression estimates in Supplementary Table 3). As expected, clear-cutting is strongly associated with habitat loss, which indicates that ingrowth of new habitat is rarely compensated for by habitat loss (a signature of forest degradation via old age–class truncation).Full size imageSeveral lines of evidence support forest management as the primary driver of forest degradation rather than alternative mechanisms (for example, climate-mediated forest decline, natural disturbance, permanent deforestation). First, our SDMs did not include climate data so the reflectance changes from satellite imagery used in our SDMs were predominantly due to forest compositional changes. Although climate (for example, inter-annual differences in precipitation) can cause subtle differences in reflectance (leaf colour) over time, most changes in the magnitude of reflectance are due to changes in forest composition or cover rather than effects of climate23 (Supplementary Figs. 1 and 2). Indeed, if the observed habitat declines were due to climate effects or natural disturbance, we would expect to see parallel habitat declines in protected areas, which we did not (Extended Data Figs. 6 and 7). Second, species exhibiting the greatest declines in habitat are those most strongly associated with old forest (Fig. 4a,b), which is the primary target of timber harvest. Indeed, the amount of area clear-cut was strongly associated with habitat loss for old forest-associated bird species (Fig. 4c and Extended Data Figs. 4 and 5). Third, deforestation (defined as permanent conversion to another land-cover type)24 was not a primary driver of habitat loss in our region; deforestation contributed 0.95, and 20 species had posterior probabilities >0.8. Importantly, most of the species showing an effect of habitat loss along routes on changes in population decline have lost substantial habitat over the time period and are associated with old forest (for example, Blackburnian warbler, northern parula [Setophaga americana], red-breasted nuthatch [Sitta canadensis], boreal chickadee [Poecile hudsonicus], dark-eyed junco [Junco hyemalis]; Extended Data Fig. 8), which would be expected with the harvest of old forest—a component of forest degradation. It is important to note that this test is highly challenging because many factors can drive annual fluctuations in bird abundance (for example, weather, phenology, conditions during migration or on the wintering grounds). Also, in any given year, habitat change along BBS routes can be quite small for some species; this low inter-annual variation in a predictor variable can preclude high statistical power to detect effects.We estimated the net number of breeding individuals that have probably disappeared due to habitat loss from 1985 to 2020 using published accounts of territory sizes for each species22 (Supplementary Table 5). This calculation assumes that available habitat is consistently occupied, which is supported by strong associations between habitat amount along BBS routes and bird abundance over the long term. Across all species, back-cast SDMs indicate that a net 28,215,247 ha (282,153 km2) of habitat has been lost, equating to a loss of between 16,779,704 and 52,243,938 breeding pairs (33,559,408–104,487,876 individuals; Supplementary Methods and Supplementary Table 5). One might expect that forest degradation, rather than resulting in broad-scale declines across species, is simply causing species turnover from old forest-associated bird species to young-forest associates. However, it is important to note that we quantified net bird decline from an unbiased list of the 54 most common forest bird species in eastern Canada. This list included both early and late successional species. Such net bird declines could be due to the fact that (1) even some early seral species are losing habitat (probably due to conversion from diverse early successional forest to species-poor plantations and thinnings)26 and (2) in this region, more species occupy older forests than regenerating forests27.We also quantified overall population trends for 54 species of forest birds using data from the BBS (Fig. 6). These estimates give the total magnitude of population changes which include, but are not limited to, habitat loss or gain effects. Thirty-nine of the 54 species examined (72%) are in population decline (defined as having 95% credible intervals that do not bound zero). The magnitude of the declines for 15 forest bird species is severe ( >5% per year). It is notable that most species exhibiting both habitat loss and population declines are old-forest associates (Fig. 4a; bottom left quadrant, dark green dots), with old-forest species exhibiting the greatest habitat losses (Fig. 4b and Supplementary Methods; hierarchical regression, (hat beta) = −16.66 [6.32 SE]).Fig. 6: Population trends for forest-associated birds in eastern Canada.a, Population trend parameter estimates and posterior distributions for 54 species of forest birds derived from Bayesian models. Seventy-two percent of species that are sufficiently common to model experienced population declines from 1985 to 2019. Colour key is provided in Fig. 5. The vertical green line indicates a population trend of zero. Dashed vertical lines coincide with trends of −15% (−0.15), −10% (−0.10) and −5% (−0.05) annual population trends. b, Predicted linear population trends for 1985–2019 (regression lines are mean trends derived from Bayesian Poisson models, Supplementary Methods) including annual variation estimated from BBS data. Shaded purple areas reflect 95% credible intervals and reflect the magnitude of species population declines shown in a. Populations of these eight old forest-associated species have declined 60–90% over the period observed.Full size imageBBS declines are not restricted to old-forest species; several species in rapid population decline are early seral species (for example, Lincoln’s sparrow [Melospiza lincolnii], mourning warbler [Geothlypis philadelphia]; Fig. 4a, bottom right quadrant). Despite the fact that these species have gained habitat over 35 years, their populations continue to decline. Only three species (black-capped chickadee [Poecile atricapillus], hairy woodpecker [Leuconotopicus villosus] and ruby-throated hummingbird [Archilochus colubris]) are increasing in abundance. Populations of these species increased despite evidence of habitat decline (Fig. 4a, top left quadrant)—perhaps because each benefit from anthropogenic habitats and supplemental food. Importantly, habitat changes from 1985 to 2019 along BBS routes were representative of changes at the scale of the entire region for most species (Extended Data Fig. 9), so BBS population trends are highly likely to reflect population trends at the regional scale. This contrasts to the 1965–1985 period when mature-forest loss along routes was slower than in the broader region28.We also modelled BBS population trends over the past ten years, as this is the period of importance for informing listing decisions under the Committee on the Status of Endangered Wildlife in Canada (COSEWIC). Nine species have exhibited population declines >30% over ten years (Supplementary Fig. 3), which meets the criterion for consideration as ‘threatened’ under COSEWIC Criterion A (ref. 29). More

Sharma, S. & Chatterjee, S. Microplastic pollution, a threat to marine ecosystem and human health: A short review. Environ. Sci. Pollut. Res. 24(27), 21530–21547 (2017).Article 

Google Scholar 
Gray, A. D., Wertz, H., Leads, R. R. & Weinstein, J. E. Microplastic in two South Carolina Estuaries: Occurrence, distribution, and composition. Mar. Pollut. Bull. 128, 223–233 (2018).CAS 
PubMed 
Article 

Google Scholar 
Weinstein, J. E., Dekle, J. L., Leads, R. R. & Hunter, R. A. Degradation of bio-based and biodegradable plastics in a salt marsh habitat: Another potential source of microplastics in coastal waters. Mar. Pollut. Bull. 160, 111518 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Robin, R. S. et al. Holistic assessment of microplastics in various coastal environmental matrices, southwest coast of India. Sci. Total Environ. 703, 134947 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Kwon, O. Y., Kang, J. H., Hong, S. H. & Shim, W. J. Spatial distribution of microplastic in the surface waters along the coast of Korea. Mar. Pollut. Bull. 155, 110729 (2020).CAS 
PubMed 
Article 

Google Scholar 
Fendall, L. S. & Sewell, M. A. Contributing to marine pollution by washing your face: Microplastics in facial cleansers. Mar. Pollut. Bull. 58(8), 1225–1228 (2009).CAS 
PubMed 
Article 

Google Scholar 
Hantoro, I., Löhr, A. J., Van Belleghem, F. G., Widianarko, B. & Ragas, A. M. Microplastics in coastal areas and seafood: Implications for food safety. Food Addit. Contam. Part A 36(5), 674–711 (2019).CAS 
Article 

Google Scholar 
Retama, I. et al. Microplastics in tourist beaches of Huatulco Bay, Pacific coast of southern Mexico. Mar. Pollut. Bull. 113(1–2), 530–535 (2016).CAS 
PubMed 
Article 

Google Scholar 
Frias, J. P. G. L., Otero, V. & Sobral, P. Evidence of microplastics in samples of zooplankton from Portuguese coastal waters. Mar. Environ. Res. 95, 89–95 (2014).CAS 
PubMed 
Article 

Google Scholar 
Hosseini, R., Sayadi, M. H., Aazami, J. & Savabieasfehani, M. Accumulation and distribution of microplastics in the sediment and coastal water samples of Chabahar Bay in the Oman Sea, Iran. Mar. Pollut. Bull. 160, 111682 (2020).CAS 
PubMed 
Article 

Google Scholar 
Andrady, A. L. Persistence of Plastic Litter in the Oceans. Marine Anthropogenic Litter 57–72 (Springer, 2015).Leads, R. R. & Weinstein, J. E. Occurrence of tire wear particles and other microplastics within the tributaries of the Charleston Harbor Estuary, South Carolina, USA. Mar. Pollut. Bull. 145, 569–582 (2019).CAS 
PubMed 
Article 

Google Scholar 
Nor, N. H. M. & Obbard, J. P. Microplastics in Singapore’s coastal mangrove ecosystems. Mar. Pollut. Bull. 79(1–2), 278–283 (2014).PubMed 

Google Scholar 
Plastics Europe. Plastics—The Facts 2017. (Plastics Europe, 2017).Lusher, A. L., Welden, N. A., Sobral, P., & Cole, M. Sampling, isolating and identifying microplastics ingested by fish and invertebrates. In Analysis of Nanoplastics and Microplastics in Food 119–148. (CRC Press, 2020).Murray, F. & Cowie, P. R. Plastic contamination in the decapod crustacean Nephrops norvegicus (Linnaeus, 1758). Mar. Pollut. Bull. 62(6), 1207–1217 (2011).CAS 
PubMed 
Article 

Google Scholar 
Gray, A. D. & Weinstein, J. E. Size-and shape-dependent effects of microplastic particles on adult daggerblade grass shrimp (Palaemonetes pugio). Environ. Toxicol. Chem. 36(11), 3074–3080 (2017).CAS 
PubMed 
Article 

Google Scholar 
Au, S. Y., Bruce, T. F., Bridges, W. C. & Klaine, S. J. Responses of Hyalella azteca to acute and chronic microplastic exposures. Environ. Toxicol. Chem. 34(11), 2564–2572 (2015).CAS 
PubMed 
Article 

Google Scholar 
Cole, M. et al. Microplastic ingestion by zooplankton. Environ. Sci. Technol. 47(12), 6646–6655 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Woods, M. N., Stack, M. E., Fields, D. M., Shaw, S. D. & Matrai, P. A. Microplastic fiber uptake, ingestion, and egestion rates in the blue mussel (Mytilus edulis). Mar. Pollut. Bull. 137, 638–645 (2018).CAS 
PubMed 
Article 

Google Scholar 
Scott, N. et al. Particle characteristics of microplastics contaminating the mussel Mytilus edulis and their surrounding environments. Mar. Pollut. Bull. 146, 125–133 (2019).CAS 
PubMed 
Article 

Google Scholar 
Van Cauwenberghe, L., Claessens, M., Vandegehuchte, M. B. & Janssen, C. R. Microplastics are taken up by mussels (Mytilus edulis) and lugworms (Arenicola marina) living in natural habitats. Environ. Pollut. 199, 10e17 (2015).
Google Scholar 
Waite, H. R., Donnelly, M. J. & Walters, L. J. Quantity and types of microplastics in the organic tissues of the eastern oyster Crassostrea virginica and Atlantic mud crab Panopeus herbstii from a Florida estuary. Mar. Pollut. Bull. 129(1), 179–185 (2018).CAS 
PubMed 
Article 

Google Scholar 
Quanbin, L. et al. Uptake and elimination of microplastics by Tigriopus japonicus and its impact on feeding behavior. Asian J. Ecotoxicol. 4, 184–191. https://doi.org/10.7524/AJE.1673-5897.20191216002 (2020).Article 

Google Scholar 
Galloway, T. S. & Lewis, C. N. Marine microplastics spell big problems for future generations. Proc. Natl. Acad. Sci. U.S.A. 113(9), 2331e2333 (2016).Article 
CAS 

Google Scholar 
Galloway, T. S., Cole, M. & Lewis, C. Interactions of microplastic debris throughout the marine ecosystem. Nat. Ecol. Evol. 1, 0116. https://doi.org/10.1038/s41559-017-0116 (2017).Article 

Google Scholar 
Carlos de Sá, L., Luís, L. G. & Guilhermino, L. Effects of microplastics on juveniles of the common goby (Pomatoschistus microps): Confusion with prey, reduction of the predatory performance and efficiency, and possible influence of developmental conditions. Environ. Pollut. 196, 359–362 (2015).PubMed 
Article 
CAS 

Google Scholar 
Cole, M., Lindeque, P., Halsband, C. & Galloway, T. S. Microplastics as contaminants in the marine environment: A review. Mar. Pollut. Bull. 62(12), 2588–2597 (2011).CAS 
PubMed 
Article 

Google Scholar 
Key, P. B., Chung, K. W., West, J. B., Pennington, P. L. & DeLorenzo, M. E. Developmental and reproductive effects in grass shrimp (Palaemon pugio) following acute larval exposure to a thin oil sheen and ultraviolet light. Aquat. Toxicol. 228, 105651 (2020).CAS 
PubMed 
Article 

Google Scholar 
Allen, D. M., Harding, J. M., Stroud, K. B. & Yozzo, K. L. Movements and site fidelity of grass shrimp (Palaemonetes pugio and P. vulgaris) in salt marsh intertidal creeks. Mar. Biol. 162(6), 1275–1285 (2015).Article 

Google Scholar 
Kunz, A. K., Ford, M. & Pung, O. J. Behavior of the grass shrimp Palaemonetes pugio and its response to the presence of the predatory fish Fundulus heteroclitus. Am. Midl. Nat. 155, 286–294. https://doi.org/10.1674/0003-0031 (2006).Article 

Google Scholar 
Barbier, E. B. et al. The value of estuarine and coastal ecosystem services. Ecol. Monogr. 81, 169–193 (2011).Article 

Google Scholar 
Cozar, A. et al. Plastic debris in the open ocean. PNAS 111, 10239e10244. https://doi.org/10.1073/pnas.1314705111 (2014).CAS 
Article 

Google Scholar 
Leads, R. R., Burnett, K. G. & Weinstein, J. E. The effect of microplastic ingestion on survival of the grass shrimp Palaemonetes pugio (Holthuis, 1949) challenged with Vibrio campbellii. Environ. Toxicol. Chem. 38(10), 2233–2242 (2019).CAS 
PubMed 
Article 

Google Scholar 
Beiras, R., Duran, I., Bellas, J. & Sanchez-Marín, P. Biological effects of contaminants: Paracentrotus lividus sea urchin embryo test with marine sediment elutriates. Int. Counc. Explor. Sea. Technol. Environ. Mar. Sci. 51, 113 (2012).
Google Scholar 
Kögel, T., Bjorøy, Ø., Toto, B., Bienfait, A. M. & Sanden, M. Micro-and nanoplastic toxicity on aquatic life: Determining factors. Sci. Total Environ. 709, 136050 (2020).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Lindeque, P. K. et al. Are we underestimating microplastic abundance in the marine environment? A comparison of microplastic capture with nets of different mesh-size. Environ Pollut. 265(Pt A), 114721. https://doi.org/10.1016/j.envpol.2020.114721 (2020).CAS 
Article 
PubMed 

Google Scholar 
Andrady, A. L. Microplastics in the marine environment. Mar. Pollut. Bull. 62(8), 1596e1605 (2011).Article 
CAS 

Google Scholar 
Leight, A. K., Scott, G. I., Fulton, M. H. & Daugomah, J. W. Long term monitoring of grass shrimp Palaemonetes spp. Population metrics at sites with agricultural runoff influences 1, 2. Integr. Comp. Biol. 45(1), 143–150 (2005).CAS 
PubMed 
Article 

Google Scholar 
Weinstein, J. E. & Garner, T. R. Piperonyl butoxide enhances the bioconcentration and photoinduced toxicity of fluoranthene and benzo [a] pyrene to larvae of the grass shrimp (Palaemonetes pugio). Aquat. Toxicol. 87(1), 28–36 (2008).CAS 
PubMed 
Article 

Google Scholar 
Key, P. B., Chung, K. W., Hoguet, J., Sapozhnikova, Y. & DeLorenzo, M. E. Toxicity of the mosquito control insecticide phenothrin to three life stages of the grass shrimp (Palaemonetes pugio). J. Environ. Sci. Health B 46(5), 426–431 (2011).CAS 
PubMed 
Article 

Google Scholar 
Broad, A. C. Larval development of Palaemonetes pugio Holthuis. Biol. Bull. 112, 144–161 (1957).Article 

Google Scholar 
Broad, A. C. The relationship between diet and larval development of Palaemonetes. Biol. Bull. 112, 162–170 (1957).Article 

Google Scholar 
Sandifer, P. A. Effects of temperature and salinity on larval development of grass shrimp, Palaemonetes vulgaris (Decapoda, Caridea). Fish. Bull. 71(1), 115 (1973).
Google Scholar 
Boston, M. A. & Provenzano, A. J. Attempted hybridization of the grass shrimp Palaemonetes (Caridea, palaemonidae) with an evaluation of taxonomic characters of juveniles. Estuaries 5(3), 165–174 (1982).Article 

Google Scholar 
Anderson, G. S. Species profiles: Life histories and environmental requirements of coastal fishes and invertebrates (Gulf of Mexico): Grass shrimp (No. 4). The Service. (1985).Vikas, P. A. et al. Unraveling the effects of live microalgal enrichment on Artemia nauplii. Indian J. Fish. 59(4), 111–121 (2012).
Google Scholar 
Provenzano, A. J., Schmitz, K. B. & Boston, M. A. Survival, duration of larval stages, and size of postlarvae of grass shrimp, Palaemonetes pugio, reared from Kepone® contaminated and uncontaminated populations in Chesapeake Bay. Estuaries 1(4), 239–244 (1978).Article 

Google Scholar 
Johnson, W. S., & Allen, D. M. Zooplankton of the Atlantic and Gulf Coasts: A Guide to Their Identification and Ecology. (JHU Press, 2012).Hubschman, J. H. The development and function of neurosecretory sites in the eyestalks of larval Palaemonetes (Decapoda: Natantia) (Doctoral dissertation, The Ohio State University, 1962).Wheeler, M. W., Park, R. M. & Bailer, A. J. Comparing median lethal concentration values using confidence interval overlap or ratio tests. Environ. Toxicol. Chem. Int. J. 25(5), 1441–1444 (2006).CAS 
Article 

Google Scholar 
Isobe, A., Kubo, K., Tamura, Y., Nakashima, E. & Fujii, N. Selective transport of microplastics and mesoplastics by drifting in coastal waters. Mar. Pollut. Bull. 89(1–2), 324–330 (2014).CAS 
PubMed 
Article 

Google Scholar 
Syakti, A. D. et al. Beach macro-litter monitoring and floating microplastic in a coastal area of Indonesia. Mar. Pollut. Bull. 122(1–2), 217–225. https://doi.org/10.1016/j.marpolbul.2017.06.046 (2017) (Epub 2017 Jun 20 PMID: 28645761).CAS 
Article 
PubMed 

Google Scholar 
Reisser, J. et al. Marine plastic pollution in waters around Australia: Characteristics, concentrations, and pathways. PLoS One 8(11), e80466 (2013).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Järlskog, I. et al. Occurrence of tire and bitumen wear microplastics on urban streets and in sweepsand and washwater. Sci. Total Environ. 729, 138950. https://doi.org/10.1016/j.scitotenv.2020.138950 (2020) (Epub 2020 Apr 26. PMID: 32371211).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Key, P. B., Fulton, M. H., Scott, G. I., Layman, S. L. & Wirth, E. F. Lethal and sublethal effects of malathion on three life stages of the grass shrimp, Palaemonetes pugio. Aquat. Toxicol. 40(4), 311–322 (1998).CAS 
Article 

Google Scholar 
DeLorenzo, M. E., Serrano, L., Chung, K. W., Hoguet, J. & Key, P. B. Effects of the insecticide permethrin on three life stages of the grass shrimp, Palaemonetes pugio. Ecotoxicol. Environ. Saf. 64(2), 122–127 (2006).CAS 
PubMed 
Article 

Google Scholar 
Key, P. B., Meyer, S. L. & Chung, K. W. Lethal and sub-lethal effects of the fungicide chlorothalonil on three life stages of the grass shrimp, Palaemonetes pugio. J. Environ. Sci. Health B 38(5), 539–549 (2003).PubMed 
Article 
CAS 

Google Scholar 
Key, P. B., Chung, K. W., Hoguet, J., Shaddrix, B. & Fulton, M. H. Toxicity and physiological effects of brominated flame retardant PBDE-47 on two life stages of grass shrimp, Palaemonetes pugio. Sci. Total Environ. 399(1–3), 28–32 (2008).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ziajahromi, S., Kumar, A., Neale, P. A. & Leusch, F. D. Environmentally relevant concentrations of polyethylene microplastics negatively impact the survival, growth and emergence of sediment-dwelling invertebrates. Environ. Pollut. 236, 425–431 (2018).CAS 
PubMed 
Article 

Google Scholar 
Redondo-Hasselerharm, P. E., Falahudin, D., Peeters, E. T. & Koelmans, A. A. Microplastic effect thresholds for freshwater benthic macroinvertebrates. Environ. Sci. Technol. 52(4), 2278–2286 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lehtiniemi, M. et al. Exposure to leachates from post-consumer plastic and recycled rubber causes stress responses and mortality in a copepod Limnocalanus macrurus. Mar. Pollut. Bull. 173, 113103 (2021).CAS 
PubMed 
Article 

Google Scholar 
Martínez-Gómez, C., León, V. M., Calles, S., Gomáriz-Olcina, M. & Vethaak, A. D. The adverse effects of virgin microplastics on the fertilization and larval development of sea urchins. Mar. Environ. Res. 130, 69–76 (2017).PubMed 
Article 
CAS 

Google Scholar 
Khosrovyan, A., Gabrielyan, B. & Kahru, A. Ingestion and effects of virgin polyamide microplastics on Chironomus riparius adult larvae and adult zebrafish Danio rerio. Chemosphere 259, 127456 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Le Bihanic, F. et al. Organic contaminants sorbed to microplastics affect marine medaka fish early life stages development. Mar Pollut Bull. 154, 111059. https://doi.org/10.1016/j.marpolbul.2020.111059 (2020) (Epub 2020 Mar 31 PMID: 32319895).CAS 
Article 
PubMed 

Google Scholar 
LeMoine, C. M. et al. Transcriptional effects of polyethylene microplastics ingestion in developing zebrafish (Danio rerio). Environ. Pollut. 243, 591–600 (2018).CAS 
PubMed 
Article 

Google Scholar 
Freeman, J. A. Regulation of tissue growth in crustacean larvae by feeding regime. Biol. Bull. 178(3), 217–221 (1990).CAS 
PubMed 
Article 

Google Scholar 
Ma, H. et al. Microplastics in aquatic environments: Toxicity to trigger ecological consequences. Environ. Pollut. 261, 114089 (2020).CAS 
PubMed 
Article 

Google Scholar  More