Ecology

ColoniesColony setup occurred prior to initiation of the study, between March and May 2017, in Mississippi, USA. Using established methods, queenless colony divisions, obtained from a large commercial beekeeping operation, were equalised to an average calculated population size of ~ 7000 workers112, and housed in 10-frame Langstroth hives (Table S1). After acclimatisation for 24–48 h, they each received an imminently emerging queen cell, containing a queen from one of two stocks, added to the same worker baseline. The stocks used consisted of an Italian ‘Commercial’ stock, propagated from collaborator established breeder queens, and thus representative of the industry standard, and the Varroa-resistant ‘Pol-line’ stock54. To ensure consistency, all queens were reared in the same ‘cell builder’ colonies, based at the USDA Honey Bee Breeding, Genetics and Physiology Laboratory, in Baton Rouge, Louisiana, USA. Colonies from each stock were held in independent apiaries, 80 km apart to maintain physical isolation; and to control genetic fidelity, virgin queens were open mated to drones of the same stock via drone saturation. Fourteen days after queen emergence, colonies were inspected, and mated queens were marked with paint on the thorax, to assist with identification, with white corresponding to Commercial, and blue to Pol-line. Colonies were allowed to acclimatise for six weeks before sampling began, and those that failed to achieve mating success, or had unacceptably high [≥ 3.0 ‘mites per hundred bees’ (MPHB)] Varroa levels, were removed, normalising the average between-stock Varroa difference to  More

IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).Sindelar, A. J. et al. Winter oilseed production for biofuel in the US Corn Belt: opportunities and limitations. GCB Bioenergy 9, 508–524 (2017).CAS 

Google Scholar 
Stöckle, C. O. et al. Evaluating opportunities for an increased role of winter crops as adaptation to climate change in dryland cropping systems of the U.S. Inland Pacific Northwest. Clim. Change 146, 247–261 (2018).
Google Scholar 
Williams, C. M., Henry, H. A. L. & Sinclair, B. J. Cold truths: how winter drives responses of terrestrial organisms to climate change. Biol. Rev. 90, 214–235 (2015).
Google Scholar 
Seifert, C. A., Azzari, G. & Lobell, D. B. Satellite detection of cover crops and their effects on crop yield in the Midwestern United States. Environ. Res. Lett. 13, 064033 (2018).
Google Scholar 
Marcillo, G. S. & Miguez, F. E. Corn yield response to winter cover crops: an updated meta-analysis. J. Soil Water Conserv. 72, 226–239 (2017).
Google Scholar 
Zhu, L., Ives, A. R., Zhang, C., Guo, Y. & Radeloff, V. C. Climate change causes functionally colder winters for snow cover-dependent organisms. Nat. Clim. Change 9, 886–893 (2019).
Google Scholar 
Mankin, J. S. & Diffenbaugh, N. S. Influence of temperature and precipitation variability on near-term snow trends. Clim. Dynam. 45, 1099–1116 (2015).
Google Scholar 
Zhu, L., Radeloff, V. C. & Ives, A. R. Characterizing global patterns of frozen ground with and without snow cover using microwave and MODIS satellite data products. Remote Sens. Environ. 191, 168–178 (2017).
Google Scholar 
Huning, L. S. & AghaKouchak, A. Global snow drought hot spots and characteristics. Proc. Natl Acad. Sci. USA 117, 19753–19759 (2020).CAS 

Google Scholar 
Qin, Y. et al. Agricultural risks from changing snowmelt. Nat. Clim. Change 10, 459–465 (2020).
Google Scholar 
Trnka, M. et al. Adverse weather conditions for European wheat production will become more frequent with climate change. Nat. Clim. Change 4, 637–643 (2014).
Google Scholar 
Li, D., Wrzesien, M. L., Durand, M., Adam, J. & Lettenmaier, D. P. How much runoff originates as snow in the western United States, and how will that change in the future? Geophys. Res. Lett. 44, 6163–6172 (2017).
Google Scholar 
Biemans, H. et al. Importance of snow and glacier meltwater for agriculture on the Indo-Gangetic Plain. Nat. Sustain. 2, 594–601 (2019).
Google Scholar 
Acevedo, E., Silva, P. & Silva, H. in Bread Wheat: Improvement and Production (eds Curtis, B. C. et al.) 39–70 (FAO Plant Production and Protection, 2002).Baker, J. T., Pinter, P. J., Reginato, R. J. & Kanemasu, E. T. Effects of temperature on leaf appearance in spring and winter wheat cultivars. Agron. J. 78, 605–613 (1986).
Google Scholar 
Tack, J., Barkley, A. & Nalley, L. L. Effect of warming temperatures on US wheat yields. Proc. Natl Acad. Sci. USA 112, 6931–6936 (2015).CAS 

Google Scholar 
Müller, C. et al. Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications. Geosci. Model Dev. 10, 1403–1422 (2017).
Google Scholar 
Talukder, A. S. M. H. M., McDonald, G. K. & Gill, G. S. Effect of short-term heat stress prior to flowering and early grain set on the grain yield of wheat. Field Crops Res. 160, 54–63 (2014).
Google Scholar 
Farooq, M., Bramley, H., Palta, J. A. & Siddique, K. H. M. Heat stress in wheat during reproductive and grain-filling phases. Crit. Rev. Plant Sci. 30, 491–507 (2011).Cuadra, S. V., Kimball, B. A., Boote, K. J., Suyker, A. E. & Pickering, N. Energy balance in the DSSAT-CSM-CROPGRO model. Agric. For. Meteorol. 297, 108241 (2021).
Google Scholar 
Harder, P., Helgason, W. D. & Pomeroy, J. W. Modeling the snowpack energy balance during melt under exposed crop stubble. J. Hydrometeorol. 19, 1191–1214 (2018).
Google Scholar 
Barlow, K. M., Christy, B. P., O’Leary, G. J., Riffkin, P. A. & Nuttall, J. G. Simulating the impact of extreme heat and frost events on wheat crop production: a review. Field Crops Res. 171, 109–119 (2015).
Google Scholar 
Wang, W. et al. Evaluation of air–soil temperature relationships simulated by land surface models during winter across the permafrost region. Cryosphere 10, 1721–1737 (2016).
Google Scholar 
Seifert, C. A. & Lobell, D. B. Response of double cropping suitability to climate change in the United States. Environ. Res. Lett. 10, 024002 (2015).
Google Scholar 
Pullens, J. W. M. et al. Risk factors for European winter oilseed rape production under climate change. Agric. For. Meteorol. 272–273, 30–39 (2019).
Google Scholar 
Chopra, R. et al. Identification and stacking of crucial traits required for the domestication of pennycress. Nat. Food 1, 84–91 (2020).
Google Scholar 
Crews, T. E., Carton, W. & Olsson, L. Is the future of agriculture perennial? Imperatives and opportunities to reinvent agriculture by shifting from annual monocultures to perennial polycultures. Glob. Sustain. 1, e11 (2018).Harkness, C. et al. Adverse weather conditions for UK wheat production under climate change. Agric. Meteorol. 282–283, 107862 (2020).
Google Scholar 
Schierhorn, F., Hofmann, M., Gagalyuk, T., Ostapchuk, I. & Müller, D. Machine learning reveals complex effects of climatic means and weather extremes on wheat yields during different plant developmental stages. Clim. Change 169, 39 (2021).Michel, S. et al. Improving and maintaining winter hardiness and frost tolerance in bread wheat by genomic selection. Front. Plant Sci. 10, 1195 (2019).
Google Scholar 
Mahfoozi, S., Limin, A. E. & Fowler, D. B. Influence of vernalization and photoperiod responses on cold hardiness in winter cereals. Crop Sci. 41, 1006–1011 (2001).
Google Scholar 
Dutra, E. et al. An improved snow scheme for the ECMWF land surface model: description and offline validation. J. Hydrometeorol. 11, 899–916 (2010).
Google Scholar 
Ge, Y. & Gong, G. Land surface insulation response to snow depth variability. J. Geophys. Res. Atmos. 115, 8107 (2010).
Google Scholar 
Hunt, J. R. et al. Early sowing systems can boost Australian wheat yields despite recent climate change. Nat. Clim. Change 9, 244–247 (2019).
Google Scholar 
Sloat, L. L. et al. Climate adaptation by crop migration. Nat. Commun. 11, 1243 (2020) .Ainsworth, E. A. & Long, S. P. 30 years of free-air carbon dioxide enrichment (FACE): what have we learned about future crop productivity and its potential for adaptation? Glob. Change Biol. 27, 27–49 (2021).
Google Scholar 
Shimoda, S. et al. Effects of snow compaction ‘yuki-fumi’ on soil frost depth and volunteer potato control in potato–wheat rotation system in Hokkaido. Plant Prod. Sci. 24, 186–197 (2021).CAS 

Google Scholar 
Luojus, K. et al. GlobSnow v3.0 Northern Hemisphere snow water equivalent dataset. Sci. Data 8, 163 (2021)..IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions Version 1 (NSIDC, 2008).Jing, Q. et al. Assessing the options to improve regional wheat yield in Eastern Canada using the CSM–CERES–wheat model. Agron. J. 109, 510–523 (2017).
Google Scholar 
Vogel, F. A. & Bange, G. A. Understanding USDA Crop Forecasts (USDA, 1999).Daly, C. et al. Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int. J. Climatol. 28, 2031–2064 (2008).
Google Scholar 
Brown, R. D. & Brasnett, B. Daily Snow Depth Analysis Data Version 1 (Canadian Meteorological Centre, 2010).Brasnett, B. A global analysis of snow depth for numerical weather prediction. J. Appl. Meteorol. Climatol. 38, 726–740 (1999).
Google Scholar 
Toure, A. M., Reichle, R. H., Forman, B. A., Getirana, A. & De Lannoy, G. J. M. Assimilation of MODIS snow cover fraction observations into the NASA catchment land surface model. Remote Sens. 10, 316 (2018).
Google Scholar 
Snauffer, A. M., Hsieh, W. W. & Cannon, A. J. Comparison of gridded snow water equivalent products with in situ measurements in British Columbia, Canada. J. Hydrol. 541, 714–726 (2016).
Google Scholar 
Census of Agriculture (USDA National Agricultural Statistics Service, 2017).Skinner, D. Z. & Mackey, B. Freezing tolerance of winter wheat plants frozen in saturated soil. Field Crops Res. 113, 335–341 (2009).
Google Scholar 
Lollato, R. P. et al. Climate-risk assessment for winter wheat using long-term weather data. Agron. J. 112, 2132–2151 (2020).
Google Scholar 
Siebers, M. H. et al. Heat waves imposed during early pod development in soybean (Glycine max) cause significant yield loss despite a rapid recovery from oxidative stress. Glob. Change Biol. 21, 3114–3125 (2015).
Google Scholar 
Çakir, R. Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops Res. 89, 1–16 (2004).
Google Scholar 
Lobell, D. B. et al. The critical role of extreme heat for maize production in the United States. Nat. Clim. Change 3, 497–501 (2013).
Google Scholar 
Chen, M., Griffis, T. J., Baker, J., Wood, J. D. & Xiao, K. Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes. J. Geophys. Res. Biogeosci. 120, 310–325 (2015).CAS 

Google Scholar 
Larson, K. M. & Small, E. E. Daily Snow Depth and SWE from GPS Signal-to-Noise Ratios Version 1 (NSIDC, 2017).Sturm, M. et al. Estimating snow water equivalent using snow depth data and climate classes. J. Hydrometeorol. 11, 1380–1394 (2010).
Google Scholar 
McCabe, G. J. & Wolock, D. M. Recent declines in western U.S. snowpack in the context of twentieth-century climate variability. Earth Interact. 13, 1–15 (2009).
Google Scholar 
Wu, X. et al. Uneven winter snow influence on tree growth across temperate China. Glob. Change Biol. 25, 144–154 (2019).
Google Scholar 
Qiao, S. et al. Robust negative impacts of climate change on African agriculture. Environ. Res. Lett. 5, 014010 (2010).
Google Scholar 
Lobell, D. B., Schlenker, W. & Costa-Roberts, J. Climate trends and global crop production since 1980. Science 333, 616–620 (2011).CAS 

Google Scholar 
Xie, Y., Gibbs, H. K. & Lark, T. J. Landsat-based Irrigation Dataset (LANID): 30 m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017. Earth Syst. Sci. Data 13, 5689–5710 (2021).
Google Scholar 
Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 490, 254–257 (2012).CAS 

Google Scholar 
Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010).
Google Scholar 
Elliott, J. et al. The global gridded crop model intercomparison: data and modeling protocols for phase 1 (v1.0). Geosci. Model Dev. 8, 261–277 (2015).
Google Scholar 
Li, X., Shen, Z., Harri, A. & Coble, K. H. Comparing survey-based and programme-based yield data: implications for the U.S. Agricultural Risk Coverage-County programme. Geneva Pap. Risk Insur. Issues Pract. 45, 184–202 (2020).
Google Scholar 
Hawkins, E., Osborne, T. M., Ho, C. K. & Challinor, A. J. Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe. Agric. Meteorol. 170, 19–31 (2013).
Google Scholar 
Ho, C. K., Stephenson, D. B., Collins, M., Ferro, C. A. T. & Brown, S. J. Calibration strategies: a source of additional uncertainty in climate change projections. Bull. Am. Meteorol. Soc. 93, 21–26 (2012).
Google Scholar  More

Zhang, N. et al. Members of the Fusarium solani species complex that cause infections in both humans and plants are common in the environment. J. Clin. Microbiol. 44, 2186–2190 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
O’Donnell, K. et al. Molecular Phylogenetic Diversity, Multilocus Haplotype Nomenclature, and In Vitro antifungal resistance within the Fusarium solani species complex. J. Clin. Microbiol. 46, 2477–2490 (2008).PubMed 
PubMed Central 

Google Scholar 
Schroers, H. J. et al. Epitypification of Fusisporium (Fusarium) solani and its assignment to a common phylogenetic species in the Fusarium solani species complex. Mycologia 108, 806–819 (2016).CAS 
PubMed 

Google Scholar 
O’Donnell, K. Molecular phylogeny of the Nectria haematococca-Fusarium solani species complex. Mycologia 92, 919–938 (2000).
Google Scholar 
Gleason, F., Allerstorfer, M. & Lilje, O. Newly emerging diseases of marine turtles, especially sea turtle egg fusariosis (SEFT), caused by species in the Fusarium solani complex (FSSC). Mycology 11, 184–194 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Fernando, N. et al. Fatal Fusarium solani species complex infections in elasmobranchs: the first case report for black spotted stingray (Taeniura melanopsila) and a literature review. Mycoses 58, 422–431 (2015).PubMed 

Google Scholar 
Sarmiento-Ramírez, J. M. et al. Global distribution of two fungal pathogens threatening endangered Sea Turtles. PLoS ONE 9, e85853 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Mayayo, E., Pujol, I. & Guarro, J. Experimental pathogenicity of four opportunist Fusarium species in a murine model. J. Med. Microbiol. 48, 363–366 (1999).CAS 
PubMed 

Google Scholar 
Muhvich, A. G., Reimschuessel, R., Lipsky, M. M. & Bennett, R. O. Fusarium solani isolated from newborn bonnethead sharks, Sphyrna tiburo (L.). J. Fish Dis. 12, 57–62 (1989).
Google Scholar 
Crow, G. L., Brock, J. A. & Kaiser, S. Fusarium solani fungal infection of the lateral line canal system in captive scalloped hammerhead sharks (Sphyrna lewini) in Hawaii. J. Wildl. Dis. 31, 562–565 (1995).CAS 
PubMed 

Google Scholar 
Cabañes, F. J. et al. Cutaneous hyalohyphomycosis caused by Fusarium solani in a loggerhead sea turtle (Caretta caretta L.). J. Clin. Microbiol. 35, 3343–3345 (1997).PubMed 
PubMed Central 

Google Scholar 
Cafarchia, C. et al. Fusarium spp. in Loggerhead Sea Turtles (Caretta caretta): From Colonization to Infection. Vet. Pathol. 57, 139–146 (2019).PubMed 

Google Scholar 
Garcia-Hartmann, M., Hennequin, C., Catteau, S., Béatini, C. & Blanc, V. Cas groupés d’infection à Fusarium solani chez de jeunes tortues marines Caretta caretta nées en captivité. J. Mycol. Med. 28, 113–118 (2017).
Google Scholar 
Orós, J., Delgado, C., Fernández, L. & Jensen, H. E. Pulmonary hyalohyphomycosis caused by Fusarium spp in a Kemp’s ridley sea turtle (Lepidochelys kempi): An immunohistochemical study. N. Z. Vet. J. 52, 150–152 (2004).PubMed 

Google Scholar 
Candan, A. Y., Katılmış, Y. & Ergin, Ç. First report of Fusarium species occurrence in loggerhead sea turtle (Caretta caretta) nests and hatchling success in Iztuzu Beach, Turkey. Biologia (Bratisl). https://doi.org/10.2478/s11756-020-00553-4 (2020).Article 

Google Scholar 
Sarmiento-Ramirez, J. M., van der Voort, M., Raaijmakers, J. M. & Diéguez-Uribeondo, J. Unravelling the Microbiome of eggs of the endangered Sea Turtle Eretmochelys imbricata identifies bacteria with activity against the emerging pathogen Fusarium falciforme. PLoS ONE 9, e95206 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Sarmiento-Ramírez, J. M. et al. Fusarium solani is responsible for mass mortalities in nests of loggerhead sea turtle, Caretta caretta, in Boavista, Cape Verde. FEMS Microbiol. Lett. 312, 192–200 (2010).PubMed 

Google Scholar 
Sarmiento-Ramirez, J. M., Sim, J., Van West, P. & Dieguez-Uribeondo, J. Isolation of fungal pathogens from eggs of the endangered sea turtle species Chelonia mydas in Ascension Island. J. Mar. Biol. Assoc. United Kingdom 97, 661–667 (2017).CAS 

Google Scholar 
Hoh, D., Lin, Y., Liu, W., Sidique, S. & Tsai, I. Nest microbiota and pathogen abundance in sea turtle hatcheries. Fungal Ecol. 47, 100964 (2020).
Google Scholar 
Güçlü, Ö., Bıyık, H. & Şahiner, A. Mycoflora identified from loggerhead turtle (Caretta caretta) egg shells and nest sand at Fethiye beach, Turkey. Afr. J. Microbiol. Res. 4, 408–413 (2010).
Google Scholar 
Gambino, D. et al. First data on microflora of loggerhead sea turtle (Caretta caretta) nests from the coastlines of Sicily. Biol. Open 9, bio045252 (2020).PubMed 
PubMed Central 

Google Scholar 
Bailey, J. B., Lamb, M., Walker, M., Weed, C. & Craven, K. S. Detection of potential fungal pathogens Fusarium falciforme and F. keratoplasticum in unhatched loggerhead turtle eggs using a molecular approach. Endanger. Species Res. 36, 111–119 (2018).
Google Scholar 
Summerbell, R. C. & Schroers, H.-J. Analysis of Phylogenetic Relationship of Cylindrocarpon lichenicola and Acremonium falciforme to the Fusarium solani Species Complex and a Review of similarities in the spectrum of opportunistic infections caused by these fungi. J. Clin. Microbiol. 40, 2866–2875 (2002).CAS 
PubMed 
PubMed Central 

Google Scholar 
Nel, R., Punt, A. E. & Hughes, G. R. Are coastal protected areas always effective in achieving population recovery for nesting sea turtles?. PLoS ONE 8, e63525 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Branch, G. & Branch, M. Living Shores. (Pippa Parker, 2018).Fuller, M. S., Fowles, B. E. & Mclaughlin, D. J. Isolation and pure culture study of marine phycomycetes. Mycologia 56, 745–756 (1964).
Google Scholar 
Greeff, M. R., Christison, K. W. & Macey, B. M. Development and preliminary evaluation of a real-time PCR assay for Halioticida noduliformans in abalone tissues. Dis. Aquat. Organ. 99, 103–117 (2012).CAS 
PubMed 

Google Scholar 
Sandoval-Denis, M., Lombard, L. & Crous, P. W. Back to the roots: a reappraisal of Neocosmospora. Persoonia Mol. Phylogeny Evol. Fungi 43, 90–185 (2019).CAS 

Google Scholar 
O’Donnell, K., Cigelnik, E. & Nirenberg, H. I. Molecular systematics and phylogeography of the Gibberella fujikuroi species complex. Mycologia 90, 465–493 (1998).
Google Scholar 
Geiser, D. M. et al. FUSARIUM-ID v. 1. 0: A DNA sequence database for identifying Fusarium. Eur. J. Plant Pathol. 110, 473–479 (2004).ADS 
CAS 

Google Scholar 
O’Donnell, K. et al. Phylogenetic diversity of insecticolous fusaria inferred from multilocus DNA sequence data and their molecular identification via FUSARIUM-ID and FUSARIUM MLST. Mycologia 104, 427–445 (2012).PubMed 

Google Scholar 
Chehri, K., Salleh, B. & Zakaria, L. Morphological and phylogenetic analysis of Fusarium solani species complex in Malaysia. Microb. Ecol. 69, 457–471 (2015).PubMed 

Google Scholar 
Lanfear, R., Frandsen, P., Wright, A., Senfeld, T. & Calcott, B. PartionFinder 2: new methods for selecting partioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. https://doi.org/10.1093/molbev/msw260 (2016).Article 

Google Scholar 
Ronquist, F. et al. Efficient Bayesian phylogenetic inference and model selection across a large model space. Syst. Biol. 61, 539–542 (2012).PubMed 
PubMed Central 

Google Scholar 
Leslie, J. F. & Summerell, B. A. The Fusarium Laboratory manual (Blackwell Publishing, Hoboken, 2006).
Google Scholar 
Fisher, N. L., Burgess, L. W., Toussoun, T. A. & Nelson, P. E. Carnation leaves as a substrate and for preserving cultures of Fusarium species. Phytopathology 72, 151 (1982).
Google Scholar 
Smyth, C. W. et al. Unraveling the ecology and epidemiology of an emerging fungal disease, sea turtle egg fusariosis (STEF). PLOS Pathog. 15, e1007682 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rachowicz, L. J. et al. The novel and endemic pathogen hypotheses: Competing explanations for the origin of emerging infectious diseases of wildlife. Conserv. Biol. 19, 1441–1448 (2005).
Google Scholar 
Lombard, L., Sandoval-Denis, M., Cai, L. & Crous, P. W. Changing the game: resolving systematic issues in key Fusarium species complexes. Persoonia Mol. Phylogeny Evol. Fungi 43, i–ii (2019).CAS 

Google Scholar 
Short, D. P. G., Donnell, K. O., Zhang, N., Juba, J. H. & Geiser, D. M. Widespread occurrence of diverse human pathogenic types of the fungus Fusarium detected in plumbing drains. J. Clin. Microbiol. 49, 4264–4272 (2011).PubMed 
PubMed Central 

Google Scholar 
White, T. J., Burns, T., Lee, S. & Taylor, J. Amplification and direct identification of fungal ribosomal RNA genes for phylogenetics. In PCR Protocols: a guide to methods and applications (eds Innis, M. A. et al.) 315–322 (Academic Press, San Diego, 1990).
Google Scholar 
Sekimoto, S., Hatai, K. & Honda, D. Molecular phylogeny of an unidentified Haliphthoros-like marine oomycete and Haliphthoros milfordensis inferred from nuclear-encoded small- and large-subunit rRNA genes and mitochondrial-encoded cox2 gene. Mycoscience 48, 212–221 (2007).CAS 

Google Scholar 
Petersen, A. B. & Rosendahl, S. Ø. Phylogeny of the Peronosporomycetes (Oomycota) based on partial sequences of the large ribosomal subunit (LSU rDNA). Mycol. Res. 104, 1295–1303 (2000).CAS 

Google Scholar 
O’Donnell, K. et al. Phylogenetic diversity and microsphere array-based genotyping of human pathogenic fusaria, including isolates from the multistate contact lens-associated U.S. keratitis outbreaks of 2005 and 2006. J. Clin. Microbiol. 45, 2235–2248 (2007).PubMed 
PubMed Central 

Google Scholar 
Migheli, Q. et al. Molecular Phylogenetic diversity of dermatologic and other human pathogenic fusarial isolates from hospitals in Northern and Central Italy. J. Clin. Microbiol. 48, 1076–1084 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar  More

Canadell JG, Monteiro PMS, Costa, MH, Cotrim da Cunha L, Cox PM, Eliseev AV, et al. Global carbon and other biogeochemical cycles and feedbacks. In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, et al. editors. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press; 2021, in press.Rosentreter JA, Borges AV, Deemer BR, Holgerson MA, Liu S, Song C, et al. Half of global methane emissions come from highly variable aquatic ecosystem sources. Nat Geosci. 2021;14:225–30.CAS 

Google Scholar 
Saunois M, Stavert AR, Poulter B, Bousquet P, Canadell JG, Jackson RB, et al. The global methane budget 2000 – 2017. Earth Syst. Sci Data. 2020;12:1561–623.
Google Scholar 
Lamentowicz M, Gałka M, Pawlyta J, Lamentowicz Ł, Goslar T, Miotk-Szpiganowicz G. Climate change and human impact in the southern Baltic during the last millennium reconstructed from an ombrotrophic bog archive. Stud Quat. 2011;28:3–16.
Google Scholar 
Davidson NC. How much wetland has the world lost? Long-term and recent trends in global wetland area. Mar Freshw Res. 2014;65:934–41.
Google Scholar 
Oertel C, Matschullat J, Zurba K, Zimmermann F, Erasmi S. Greenhouse gas emissions from soils – a review. Geochemistry. 2016;76:327–52.CAS 

Google Scholar 
Liesack W, Schnell S, Revsbech NP. Microbiology of flooded rice paddies. FEMS Microbiol Rev. 2000;24:625–45.CAS 
PubMed 

Google Scholar 
Conrad R. The global methane cycle: recent advances in understanding the microbial processes involved. Environ Microbiol Rep. 2009;1:285–92.CAS 
PubMed 

Google Scholar 
Lyu Z, Shao N, Akinyemi T, Whitman WB. Methanogenesis. Curr Biol. 2018;28:R727–R732.CAS 
PubMed 

Google Scholar 
Kurth JM, Nobu MK, Tamaki H, de Jonge N, Berger S, Jetten MSM, et al. Methanogenic archaea use a bacteria-like methyltransferase system to demethoxylate aromatic compounds. ISME J. 2021;15:3549–65.CAS 
PubMed 
PubMed Central 

Google Scholar 
Mayumi D, Mochimaru H, Tamaki H, Yamamoto K, Yoshioka H, Suzuki Y, et al. Methane production from coal by a single methanogen. Science. 2016;354:222–6.CAS 
PubMed 

Google Scholar 
Bridgham SD, Cadillo-Quiroz H, Keller JK, Zhuang Q. Methane emissions from wetlands: Biogeochemical, microbial, and modeling perspectives from local to global scales. Glob Chang Biol. 2013;19:1325–46.PubMed 

Google Scholar 
Narrowe AB, Borton MA, Hoyt DW, Smith GJ, Daly RA, Angle JC, et al. Uncovering the diversity and activity of methylotrophic methanogens in freshwater wetland soils. mSystems. 2019;4:e00320–19.PubMed 
PubMed Central 

Google Scholar 
Zalman CA, Meade N, Chanton J, Kostka JE, Bridgham SD, Keller JK. Methylotrophic methanogenesis in Sphagnum-dominated peatland soils. Soil Biol Biochem. 2018;118:156–60.CAS 

Google Scholar 
Knief C. Diversity and habitat preferences of cultivated and uncultivated aerobic methanotrophic bacteria evaluated based on pmoA as molecular marker. Front Microbiol. 2015;6:1346.PubMed 
PubMed Central 

Google Scholar 
Le Mer J, Roger P. Production, oxidation, emission and consumption of methane by soils: a review. Eur J Soil Biol. 2001;37:25–50.
Google Scholar 
Wieczorek AS, Drake HL, Kolb S. Organic acids and ethanol inhibit the oxidation of methane by mire methanotrophs. FEMS Microbiol Ecol. 2011;77:28–39.CAS 
PubMed 

Google Scholar 
Welte CU, Rasigraf O, Vaksmaa A, Versantvoort W, Arshad A, Op den Camp HJM, et al. Nitrate- and nitrite-dependent anaerobic oxidation of methane. Environ Microbiol Rep. 2016;8:941–55.CAS 
PubMed 

Google Scholar 
Cui M, Ma A, Qi H, Zhuang X, Zhuang G. Anaerobic oxidation of methane: An ‘active’ microbial process. Microbiol Open. 2015;4:1–11.
Google Scholar 
Ettwig KF, Zhu B, Speth D, Keltjens JT, Jetten MSM, Kartal B. Archaea catalyze iron-dependent anaerobic oxidation of methane. Proc Natl Acad Sci USA. 2016;113:12792–6.CAS 
PubMed 
PubMed Central 

Google Scholar 
Stiehl-Braun PA, Hartmann AA, Kandeler E, Buchmann N, Niklaus PA. Interactive effects of drought and N fertilization on the spatial distribution of methane assimilation in grassland soils. Glob Chang Biol 2011;17:2629–39.
Google Scholar 
Bodelier PLE, Meima-Franke M, Hordijk CA, Steenbergh AK, Hefting MM, Bodrossy L, et al. Microbial minorities modulate methane consumption through niche partitioning. ISME J. 2013;7:2214–28.CAS 
PubMed 
PubMed Central 

Google Scholar 
Karbin S, Hagedorn F, Dawes MA, Niklaus PA. Treeline soil warming does not affect soil methane fluxes and the spatial micro-distribution of methanotrophic bacteria. Soil Biol Biochem. 2015;86:164–71.CAS 

Google Scholar 
Stiehl-Braun PA, Powlson DS, Poulton PR, Niklaus PA. Effects of N fertilizers and liming on the micro-scale distribution of soil methane assimilation in the long-term Park Grass experiment at Rothamsted. Soil Biol Biochem. 2011;43:1034–41.CAS 

Google Scholar 
Menyailo OV, Hungate BA, Abraham WR, Conrad R. Changing land use reduces soil CH4 uptake by altering biomass and activity but not composition of high-affinity methanotrophs. Glob Chang Biol. 2008;14:2405–19.
Google Scholar 
Ciais P, Sabine C, Bala G, Bopp L, Brovkin V, Canadell J, et al. Carbon and Other Biogeochemical Cycles. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, et al. editors. Climate Change 2013 the Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. New York, NY: Cambridge University Press; 2013, 465–570.Täumer J, Kolb S, Boeddinghaus RS, Wang H, Schöning I, Schrumpf M, et al. Divergent drivers of the microbial methane sink in temperate forest and grassland soils. Glob Chang Biol. 2021;27:929–40.PubMed 

Google Scholar 
Kolb S. The quest for atmospheric methane oxidizers in forest soils. Environ Microbiol Rep. 2009;1:336–46.CAS 
PubMed 

Google Scholar 
Kolb S, Horn MA. Microbial CH4 and N2O consumption in acidic wetlands. Front Microbiol. 2012;3:78.CAS 
PubMed 
PubMed Central 

Google Scholar 
Cai Y, Zheng Y, Bodelier PLE, Conrad R, Jia Z. Conventional methanotrophs are responsible for atmospheric methane oxidation in paddy soils. Nat Commun. 2016;7:11728.CAS 
PubMed 
PubMed Central 

Google Scholar 
Dean JF, Middelburg JJ, Röckmann T, Aerts R, Blauw LG, Egger M, et al. Methane feedbacks to the global climate system in a warmer world. Rev Geophys. 2018;56:207–50.
Google Scholar 
Levy-Booth DJ, Giesbrecht IJW, Kellogg CTE, Heger TJ, D’Amore DV, Keeling PJ, et al. Seasonal and ecohydrological regulation of active microbial populations involved in DOC, CO2, and CH4 fluxes in temperate rainforest soil. ISME J. 2019;13:950–63.CAS 
PubMed 

Google Scholar 
Lombard N, Prestat E, van Elsas JD, Simonet P. Soil-specific limitations for access and analysis of soil microbial communities by metagenomics. FEMS Microbiol Ecol. 2011;78:31–49.CAS 
PubMed 

Google Scholar 
Carini P, Marsden PJ, Leff JW, Morgan EE, Strickland MS, Fierer N. Relic DNA is abundant in soil and obscures estimates of soil microbial diversity. Nat Microbiol. 2016;2:16242.PubMed 

Google Scholar 
Blazewicz SJ, Barnard RL, Daly RA, Firestone MK. Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. ISME J. 2013;7:2061–8.CAS 
PubMed 
PubMed Central 

Google Scholar 
Sukenik A, Kaplan-Levy RN, Welch JM, Post AF. Massive multiplication of genome and ribosomes in dormant cells (akinetes) of Aphanizomenon ovalisporum (Cyanobacteria). ISME J. 2012;6:670–9.CAS 
PubMed 

Google Scholar 
Schwartz E, Hayer M, Hungate BA, Koch BJ, McHugh TA, Mercurio W, et al. Stable isotope probing with 18O-water to investigate microbial growth and death in environmental samples. Curr Opin Biotechnol. 2016;41:14–18.CAS 
PubMed 

Google Scholar 
Angel R, Conrad R. Elucidating the microbial resuscitation cascade in biological soil crusts following a simulated rain event. Environ Microbiol. 2013;15:2799–815.CAS 
PubMed 

Google Scholar 
Papp K, Mau RL, Hayer M, Koch BJ, Hungate BA, Schwartz E. Quantitative stable isotope probing with H218O reveals that most bacterial taxa in soil synthesize new ribosomal RNA. ISME J. 2018;12:3043–5.CAS 
PubMed 
PubMed Central 

Google Scholar 
Urich T, Lanzén A, Qi J, Huson DH, Schleper C, Schuster SC. Simultaneous assessment of soil microbial community structure and function through analysis of the meta-transcriptome. PLoS One. 2008;3:e2527.PubMed 
PubMed Central 

Google Scholar 
Peng J, Wegner CE, Liesack W. Short-term exposure of paddy soil microbial communities to salt stress triggers different transcriptional responses of key taxonomic groups. Front Microbiol. 2017;8:400.PubMed 
PubMed Central 

Google Scholar 
Peng J, Wegner CE, Bei Q, Liu P, Liesack W. Metatranscriptomics reveals a differential temperature effect on the structural and functional organization of the anaerobic food web in rice field soil. Microbiome. 2018;6:169.PubMed 
PubMed Central 

Google Scholar 
Abdallah RZ, Wegner CE, Liesack W. Community transcriptomics reveals drainage effects on paddy soil microbiome across all three domains of life. Soil Biol Biochem. 2019;132:131–42.CAS 

Google Scholar 
Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ. Microbiome datasets are compositional: and this is not optional. Front Microbiol. 2017;8:2224.PubMed 
PubMed Central 

Google Scholar 
Moran MA, Satinsky B, Gifford SM, Luo H, Rivers A, Chan LK, et al. Sizing up metatranscriptomics. ISME J. 2013;7:237–43.CAS 
PubMed 

Google Scholar 
Gifford SM, Sharma S, Rinta-Kanto JM, Moran MA. Quantitative analysis of a deeply sequenced marine microbial metatranscriptome. ISME J. 2011;5:461–72.PubMed 

Google Scholar 
Söllinger A, Tveit AT, Poulsen M, Noel SJ, Bengtsson M, Bernhardt J, et al. Holistic assessment of rumen microbiome dynamics through quantitative metatranscriptomics reveals multifunctional redundancy during key steps of anaerobic feed degradation. mSystems 2018;3:e00038–18.PubMed 
PubMed Central 

Google Scholar 
Fischer M, Bossdorf O, Gockel S, Hänsel F, Hemp A, Hessenmöller D, et al. Implementing large-scale and long-term functional biodiversity research: the biodiversity exploratories. Basic Appl Ecol. 2010;11:473–85.
Google Scholar 
IUSS Working Group WRB. World reference base for soil resources 2014, update 2015 international soil classification system for naming soils and creating legends for soil maps. World Soil Resour Reports No 106. Rome: FAO; 2015.Vance ED, Brookes PC, Jenkinson DS. An extraction method for measuring soil microbial biomass C. Soil Biol Biochem. 1987;19:703–7.CAS 

Google Scholar 
Joergensen RG, Mueller T. The fumigation-extraction method to estimate soil microbial biomass: calibaration of the kEN value. Soil Biol Biochem. 1996;28:33–37.CAS 

Google Scholar 
Brookes PC, Landman A, Pruden G, Jenkinson DS. Chloroform fumigation and the release of soil nitrogen: a rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol Biochem. 1985;17:837–42.CAS 

Google Scholar 
Bamminger C, Zaiser N, Zinsser P, Lamers M, Kammann C, Marhan S. Effects of biochar, earthworms, and litter addition on soil microbial activity and abundance in a temperate agricultural soil. Biol Fertil Soils. 2014;50:1189–1200.CAS 

Google Scholar 
Koch O, Tscherko D, Kandeler E. Seasonal and diurnal net methane emissions from organic soils of the Eastern Alps, Austria: Effects of soil temperature, water balance, and plant biomass. Arct Antarct Alp Res. 2007;39:438–48.
Google Scholar 
Tveit AT, Urich T, Svenning MM. Metatranscriptomic analysis of arctic peat soil microbiota. Appl Environ Microbiol. 2014;80:5761–72.CAS 
PubMed 
PubMed Central 

Google Scholar 
Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27:2957–63.PubMed 
PubMed Central 

Google Scholar 
Schmieder R, Edwards R. Quality control and preprocessing of metagenomic datasets. Bioinformatics. 2011;27:863–4.CAS 
PubMed 
PubMed Central 

Google Scholar 
Kopylova E, Noé L, Touzet H. SortMeRNA: Fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics. 2012;28:3211–7.CAS 
PubMed 

Google Scholar 
Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26:2460–1.CAS 
PubMed 

Google Scholar 
Lanzén A, Jørgensen SL, Huson DH, Gorfer M, Grindhaug SH, Jonassen I, et al. CREST – Classification resources for environmental sequence tags. PLoS One. 2012;7:e49334.Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.CAS 
PubMed 

Google Scholar 
Huson DH, Beier S, Flade I, Górska A, El-Hadidi M, Mitra S, et al. MEGAN community edition – interactive exploration and analysis of large-scale microbiome sequencing data. PLoS Comput Biol. 2016;12:e1004957.PubMed 
PubMed Central 

Google Scholar 
Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2014;12:59–60.PubMed 

Google Scholar 
Dumont MG, Lüke C, Deng Y, Frenzel P. Classification of pmoA amplicon pyrosequences using BLAST and the lowest common ancestor method in MEGAN. Front Microbiol. 2014;5:34.PubMed Central 

Google Scholar 
R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018.Oksanen J, Blanchet f. G, Friendly M, Kindt R, Legendre P, McGlinn D, et al. vegan: Community ecology package. 2020. R package version 2.5-7. https://CRAN.R-project.org/package=vegan.Graves S, Piepho H-P, Selzer L. multcompView: Visualizations of paired comparisons. 2019. R package version 0.1-8. https://CRAN.R-project.org/package=multcompView.Günther A, Barthelmes A, Huth V, Joosten H, Jurasinski G, Koebsch F, et al. Prompt rewetting of drained peatlands reduces climate warming despite methane emissions. Nat Commun. 2020;11:1644.PubMed 
PubMed Central 

Google Scholar 
IPCC Task Force on National Greenhouse Gas Inventories. Methodological guidance on lands with wet and drained soilds, and constructed wetlands for wastewater treatment. 2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands. 2014.Tiemeyer B, Albiac Borraz E, Augustin J, Bechtold M, Beetz S, Beyer C, et al. High emissions of greenhouse gases from grasslands on peat and other organic soils. Glob Chang Biol. 2016;22:4134–49.PubMed 

Google Scholar 
Kirschbaum MUF. The temperature dependence of soil organic matter decomposition, and the effect of global warming on soil organic C storage. Soil Biol Biochem. 1995;27:753–60.CAS 

Google Scholar 
Knorr W, Prentice IC, House JI, Holland EA. Long-term sensitivity of soil carbon turnover to warming. Nature 2005;433:298–301.CAS 
PubMed 

Google Scholar 
Dutaur L, Verchot LV. A global inventory of the soil CH4 sink. Glob Biogeochem Cycles. 2007;21:GB4013.
Google Scholar 
McDaniel MD, Saha D, Dumont MG, Hernández M, Adams MA. The effect of land-use change on soil CH4 and N2O fluxes: A global meta-analysis. Ecosystems. 2019;22:1424–43.CAS 

Google Scholar 
Gulledge J, Schimel JP. Moisture control over atmospheric CH4 consumption and CO2 production in diverse Alaskan soils. Soil Biol Biochem. 1998;30:1127–32.CAS 

Google Scholar 
Tveit AT, Urich T, Frenzel P, Svenning MM. Metabolic and trophic interactions modulate methane production by Arctic peat microbiota in response to warming. Proc Natl Acad Sci USA. 2015;112:E2507–E2516.CAS 
PubMed 
PubMed Central 

Google Scholar 
Conrad R. Methane production in soil environments – anaerobic biogeochemistry and microbial life between flooding and desiccation. Microorganisms 2020;8:881.CAS 
PubMed Central 

Google Scholar 
Lyu Z, Lu Y. Metabolic shift at the class level sheds light on adaptation of methanogens to oxidative environments. ISME J. 2018;12:411–23.PubMed 

Google Scholar 
Smith KS, Ingram-Smith C. Methanosaeta, the forgotten methanogen? Trends Microbiol. 2007;15:150–5.CAS 
PubMed 

Google Scholar 
Whitman WB, Bowen TL, Boone DR. The methanogenic bacteria. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F editors. The prokaryotes: other major lineages of bacteria and the archaea. Berlin, Heidelberg: Springer; 2014, pp 123–63.Conrad R. Importance of hydrogenotrophic, aceticlastic and methylotrophic methanogenesis for methane production in terrestrial, aquatic and other anoxic environments: a mini review. Pedosphere. 2020;30:25–39.
Google Scholar 
Söllinger A, Urich T. Methylotrophic methanogens everywhere – physiology and ecology of novel players in global methane cycling. Biochem Soc Trans. 2019;47:1895–907.PubMed 

Google Scholar 
Yang S, Liebner S, Winkel M, Alawi M, Horn F, Dörfer C, et al. In-depth analysis of core methanogenic communities from high elevation permafrost-affected wetlands. Soil Biol Biochem. 2017;111:66–77.CAS 

Google Scholar 
Weil M, Wang H, Bengtsson M, Köhn D, Günther A, Jurasinski G, et al. Long-term rewetting of three formerly drained peatlands drives congruent compositional changes in pro- and eukaryotic soil microbiomes through environmental filtering. Microorganisms. 2020;8:550.CAS 
PubMed Central 

Google Scholar 
Söllinger A, Seneca J, Dahl MB, Motleleng LL, Prommer J, Verbruggen E, et al. Down-regulation of the microbial protein biosynthesis machinery in response to weeks, years, and decades of soil warming. Sci Adv. 2022;8:eabm3230.PubMed 
PubMed Central 

Google Scholar 
Luesken FA, Wu ML, Op den Camp HJM, Keltjens JT, Stunnenberg H, Francoijs KJ, et al. Effect of oxygen on the anaerobic methanotroph ‘Candidatus Methylomirabilis oxyfera’: Kinetic and transcriptional analysis. Environ Microbiol. 2012;14:1024–34.CAS 
PubMed 
PubMed Central 

Google Scholar 
Baani M, Liesack W. Two isozymes of particulate methane monooxygenase with different methane oxidation kinetics are found in Methylocystis sp. strain SC2. Proc Natl Acad Sci. 2008;105:10203–8.CAS 
PubMed 
PubMed Central 

Google Scholar 
Yimga MT, Dunfield PF, Ricke P, Heyer J, Liesack W. Wide distribution of a novel pmoA-like gene copy among type II methanotrophs, and its expression in Methylocystis strain SC2. Appl Environ Microbiol. 2003;69:5593–602.CAS 

Google Scholar 
Tveit AT, Hestnes AG, Robinson SL, Schintlmeister A, Dedysh SN, Jehmlich N, et al. Widespread soil bacterium that oxidizes atmospheric methane. Proc Natl Acad Sci USA. 2019;116:8515–24.CAS 
PubMed 
PubMed Central 

Google Scholar 
Freitag TE, Toet S, Ineson P, Prosser JI. Links between methane flux and transcriptional activities of methanogens and methane oxidizers in a blanket peat bog. FEMS Microbiol Ecol. 2010;73:157–65.CAS 
PubMed 

Google Scholar 
Qin H, Tang Y, Shen J, Wang C, Chen C, Yang J, et al. Abundance of transcripts of functional gene reflects the inverse relationship between CH4 and N2O emissions during mid-season drainage in acidic paddy soil. Biol Fertil Soils. 2018;54:885–95.
Google Scholar  More

Boere, G. C., Galbraith, C. A., Stroud, D. & Thompson, D. B. A. The conservation of waterbirds around the world in Waterbirds Around the World (ed. Boere, G. C., Galbraith, C. A. & Stroud, D. A.) 32–45 (The Stationery Office, Edinburgh, UK, 2007).Butchart, S. H. M. et al. Global biodiversity: Indicators of recent declines. Science 328, 1164–1168. https://doi.org/10.1126/science.1187512,Pubmed:20430971 (2010).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Nebel, S., Porter, J. L. & Kingsford, R. T. Long-term trends of shorebird populations in eastern Australia and impacts of freshwater extraction. Biol. Conserv. 141, 971–980. https://doi.org/10.1016/j.biocon.2008.01.017 (2008).Article 

Google Scholar 
MacKinnon, J., Verkuil, Y. I. & Murray, N. IUCN situation analysis on east and Southeast Asian intertidal habitats, with particular reference to the Yellow Sea (including the Bohai Sea). Occas. Pap. IUCN Species Surviv. Comm. 047, 70.Li, X. et al. Assessing changes of habitat quality for shorebirds in stopover sites: A case study in Yellow River Delta, China. Wetlands 39, 67–77. https://doi.org/10.1007/s13157-018-1075-9 (2019).Article 

Google Scholar 
Murray, N. J., Clemens, R. S., Phinn, S. R., Possingham, H. P. & Fuller, R. A. Tracking the rapid loss of tidal wetlands in the Yellow Sea. Front. Ecol. Environ. 12, 267–272. https://doi.org/10.1890/130260 (2014).Article 

Google Scholar 
Green, J. M. H., Sripanomyom, S., Giam, X. & Wilcove, D. S. The ecology and economics of shorebird conservation in a tropical human-modified landscape. J. Appl. Ecol. 52, 1483–1491. https://doi.org/10.1111/1365-2664.12508 (2015).Article 

Google Scholar 
Toral, G. M. & Figuerola, J. Unraveling the importance of rice fields for waterbird populations in Europe. Biodivers. Conserv. 19, 3459–3469. https://doi.org/10.1007/s10531-010-9907-9 (2010).Article 

Google Scholar 
Masero, J. A. Assessing alternative anthropogenic habitats for conserving waterbirds: salinas as buffer areas against the impact of natural habitat loss for shorebirds. Biodivers. Conserv. 12, 1157–1173. https://doi.org/10.1023/A:1023021320448 (2003).Article 

Google Scholar 
Athearn, N. D. et al. Variability in habitat value of commercial salt production ponds: implications for waterbird management and tidal marsh restoration planning. Hydrobiologia 697, 139–155. https://doi.org/10.1007/s10750-012-1177-y (2012).CAS 
Article 

Google Scholar 
Navedo, J. G. et al. Agroecosystems and conservation of migratory waterbirds: Importance of coastal pastures and factors influencing their use by wintering shorebirds. Biodivers. Conserv. 22, 1895–1907. https://doi.org/10.1007/s10531-013-0516-2 (2013).Article 

Google Scholar 
Navedo, J. G., Fernández, G., Valdivia, N., Drever, M. C. & Masero, J. A. Identifying management actions to increase foraging opportunities for shorebirds at semi-intensive shrimp farms. J. Appl. Ecol. 54, 567–576. https://doi.org/10.1111/1365-2664.12735 (2017).Article 

Google Scholar 
Lawler, S. P. Rice fields as temporary wetlands: A review. Isr. J. Zool. 47, 513–528. https://doi.org/10.1560/X7K3-9JG8-MH2J-XGX1 (2001).Article 

Google Scholar 
Fasola, M. & Ruiz, X. The value of rice fields as substitutes for natural wetlands for waterbirds in the Mediterranean region. Waterbirds 19, 122–128. https://doi.org/10.2307/1521955 (1996).Article 

Google Scholar 
Elphick, C. S. Why study birds in rice fields?. Waterbirds 33, 1–7. https://doi.org/10.1675/063.033.s101 (2010).Article 

Google Scholar 
Lourenço, P. M. & Piersma, T. Stopover ecology of Black-tailed Godwits Limosa limosa limosa in Portuguese rice fields: A guide on where to feed in winter. Bird Study 55, 194–202. https://doi.org/10.1080/00063650809461522 (2008).Article 

Google Scholar 
Elphick, C. S. & Oring, L. W. Conservation implications of flooding rice fields on winter waterbird communities. Agric. Ecosyst. Environ. 94, 17–29. https://doi.org/10.1016/S0167-8809(02)00022-1 (2003).Article 

Google Scholar 
Maeda, T. Patterns of bird abundance and habitat use in rice fields of the Kanto Plain, central Japan. Ecol. Res. 16, 569–585. https://doi.org/10.1046/j.1440-1703.2001.00418.x (2001).Article 

Google Scholar 
Choi, S. H., Nam, H. K. & Yoo, J. C. Characteristics of population dynamics and habitat use of shorebirds in rice fields during spring migration. Korean J. Environ. Agric. 33, 334–343. https://doi.org/10.5338/KJEA.2014.33.4.334 (2014).Article 

Google Scholar 
Shuford, W. D., Humphrey, J. M. & Nur, N. Breeding status of the Black tern in California. West. Birds 32, 189–217 (2001).
Google Scholar 
Sánchez-Guzmán, J. M. et al. Identifying new buffer areas for conserving waterbirds in the Mediterranean basin: The importance of the rice fields in Extremadura, Spain. Biodivers. Conserv. 16, 3333–3344. https://doi.org/10.1007/s10531-006-9018-9 (2007).Article 

Google Scholar 
Rendón, M. A., Green, A. J., Aguilera, E. & Almaraz, P. Status, distribution and long-term changes in the waterbird community wintering in Doñana, south–west Spain. Biol. Conserv. 141, 1371–1388. https://doi.org/10.1016/j.biocon.2008.03.006 (2008).Article 

Google Scholar 
Ibáñez, C., Curcó, A., Riera, X., Ripoll, I. & Sánchez, C. Influence on birds of rice field management practices during the growing season: A review and an experiment. Waterbirds 33, 167–180. https://doi.org/10.1675/063.033.s113 (2010).Article 

Google Scholar 
Pierluissi, S. Breeding waterbirds in rice fields: A global review. Waterbirds 33, 123–132. https://doi.org/10.1675/063.033.0117 (2010).Article 

Google Scholar 
Day, J. H. & Colwell, M. A. Waterbird communities in rice fields subjected to different post-harvest treatments. Waterbirds 21, 185–197. https://doi.org/10.2307/1521905 (1998).Article 

Google Scholar 
Elphick, C. S. & Oring, L. W. Winter management of Californian rice fields for waterbirds. J. Appl. Ecol. 35, 95–108. https://doi.org/10.1046/j.1365-2664.1998.00274.x (1998).Article 

Google Scholar 
Manley, S. W., Kaminski, R. M., Reinecke, K. J. & Gerard, P. D. Waterbird foods in winter-managed ricefields in Mississippi. J. Wildl. Manag. 68, 74–83. https://doi.org/10.2193/0022-541X(2004)068[0074:WFIWRI]2.0.CO;2 (2004).Article 

Google Scholar 
Pernollet, C. A., Cavallo, F., Simpson, D., Gauthier-Clerc, M. & Guillemain, M. Seed density and waterfowl use of rice fields in Camargue, France. Jour. Wild. Mgmt 81, 96–111. https://doi.org/10.1002/jwmg.21167 (2017).Article 

Google Scholar 
Nam, H. K., Choi, S. H. & Yoo, J. C. Influence of foraging behaviors of shorebirds on habitat use in rice fields during spring migration. Korean J. Environ. Agric. 34, 178–185. https://doi.org/10.5338/KJEA.2015.34.3.35 (2015).Article 

Google Scholar 
Nam, H. K., Choi, S. H., Choi, Y. S. & Yoo, J. C. Patterns of waterbirds abundance and habitat use in rice fields. Korean J. Environ. Agr. 31, 359–367. https://doi.org/10.5338/KJEA.2012.31.4.359 (2012).Article 

Google Scholar 
Nam, H. K., Choi, Y. S., Choi, S. H. & Yoo, J. C. Distribution of waterbirds in rice fields and their use of foraging habitats. Waterbirds 38, 173–183. https://doi.org/10.1675/063.038.0206 (2015).Article 

Google Scholar 
Hua, N., Tan, K., Chen, Y. & Ma, Z. Key research issues concerning the conservation of migratory shorebirds in the Yellow Sea region. Bird Conserv. Int. 25, 38–52. https://doi.org/10.1017/S0959270914000380 (2015).Article 

Google Scholar 
Stroud, D. A. et al. The conservation and population status of the world’s waders at the turn of the millennium in. Waterbirds Around the World Conference 643–648 (The Stationery Office, Edinburgh, UK, 2006).Taft, O. W. & Haig, S. M. The value of agricultural wetlands as invertebrate resources for wintering shorebirds. Agric. Ecosyst. Environ. 110, 249–256. https://doi.org/10.1016/j.agee.2005.04.012 (2005).Article 

Google Scholar 
Strum, K. M. et al. Winter management of California’s rice fields to maximize waterbird habitat and minimize water use. Agric. Ecosyst. Environ. 179, 116–124. https://doi.org/10.1016/j.agee.2013.08.003 (2013).Article 

Google Scholar 
Dias, R. A., Blanco, D. E., Goijman, A. P. & Zaccagnini, M. E. Density, habitat use, and opportunities for conservation of shorebirds in rice fields in southeastern South America. Condor Ornithol. Appl. 116, 384–393. https://doi.org/10.1650/CONDOR-13-160.1 (2014).Article 

Google Scholar 
Golet, G. H. et al. Using ricelands to provide temporary shorebird habitat during migration. Ecol. Appl. 28, 409–426. https://doi.org/10.1002/eap.1658,Pubmed:29205645 (2018).Article 
PubMed 

Google Scholar 
Choi, G., Nam, H. K., Son, S. J., Do, M. S. & Yoo, J. C. The impact of agricultural activities on habitat use by the Wood sandpiper and Common greenshank in rice fields. Ornithol. Sci. 20, 27–37. https://doi.org/10.2326/osj.20.27 (2021).Article 

Google Scholar 
Choi, S. H. & Nam, H. K. Flexible behavior of the Black-tailed godwit Limosa limosa is key to successful refueling during staging at rice paddy fields in Midwestern Korea. Zool. Sci. 37, 255–262. https://doi.org/10.2108/zs190120,Pubmed:32549539 (2020).Article 

Google Scholar 
Cole, M. L., Leslie, D. M. Jr. & Fisher, W. L. Habitat use by shorebirds at a stopover site in the southern Great Plains. Southwest. Nat. 47, 372–378. https://doi.org/10.2307/3672495 (2002).Article 

Google Scholar 
Rundle, W. D. & Fredrickson, L. H. Managing seasonally flooded impoundments for migrant rails and shorebirds. Wildl. Soc. Bull., 80–87 (1981).Taylor, D. M. & Trost, C. H. Use of lakes and reservoirs by migrating shorebirds in Idaho. Gr Basin Nat. 52, 179–184 (1992).
Google Scholar 
Hands, H. M., Ryan, M. R. & Smith, J. W. Migrant shorebird use of marsh, Moist-Soil, and flooded agricultural habitats. Wildl. Soc. Bull. 1973–2006(19), 457–464 (1991).
Google Scholar 
Skagen, S. K. & Knopf, F. L. Migrating shorebirds and habitat dynamics at a prairie wetland complex. Wilson Bull., 91–105 (1994).Weber, L. M. & Haig, S. M. Shorebird use of South Carolina managed and natural coastal wetlands. J. Wildl. Manag. 60, 73–82. https://doi.org/10.2307/3802042 (1996).Article 

Google Scholar 
Collazo, J. A., O’Harra, D. A. & Kelly, C. A. Accessible habitat for shorebirds: factors influencing its availability and conservation implications. Waterbirds, 13–24 (2002).Helmers, D.L. Shorebird Management Manual. Western Hemisphere Shorebird Reserve Network (Manomet Cntr for Conservation Sciences, Manomet, MA, 1992).Verkuil, Y., Koolhaas, A. & Van Der Winden, J. Wind effects on prey availability: how northward migrating waders use brackish and hypersaline lagoons in the Sivash, Ukraine. Neth. J. Sea Res. 31, 359–374. https://doi.org/10.1016/0077-7579(93)90053-U (1993).Article 

Google Scholar 
Davis, C. A. & Smith, L. M. Ecology and management of migrant shorebirds in the Playa Lakes Region of Texas. Wildl. Monogr., 3–45 (1998).Barter, M. Shorebirds of the Yellow Sea: Importance, threats and conservation status in Wetlands Int. Global Ser. Oceania 9, 5–13.Katayama, N., Baba, Y. G., Kusumoto, Y. & Tanaka, K. A review of post-war changes in rice farming and biodiversity in Japan. Agric. Syst. 132, 73–84. https://doi.org/10.1016/j.agsy.2014.09.001 (2015).Article 

Google Scholar 
Mukherjee, A. Adaptiveness of cattle egret’s (Bubulcus ibis) foraging. Zoos Print J. 15, 331–333 (2000). https://doi.org/10.11609/JoTT.ZPJ.15.10.331-3.Choi, Y. S., Kim, S. S. & Yoo, J. C. Feeding activity of cattle egrets and intermediate egrets at different stages of rice culture in Korea. J. Ecol. Environ. 33, 149–155. https://doi.org/10.5141/JEFB.2010.33.2.149 (2010).Article 

Google Scholar 
Katayama, N., Amano, T., Fujita, G. & Higuchi, H. Spatial overlap between the intermediate egret Egretta intermedia and its aquatic prey at two spatiotemporal scales in a rice paddy landscape. Zool. Stud. 51, 1105–1112 (2013).
Google Scholar 
Sebastián-González, E. & Green, A. J. Reduction of avian diversity in created versus natural and restored wetlands. Ecography 39, 1176–1184. https://doi.org/10.1111/ecog.01736 (2016).Article 

Google Scholar 
Walton, M. E. M. et al. A model for the future: ecosystem services provided by the aquaculture activities of Veta La Palma, Southern Spain. Aquaculture 448, 382–390. https://doi.org/10.1016/j.aquaculture.2015.06.017 (2015).Article 

Google Scholar 
R Development Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2014).Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

Google Scholar 
Lüdecke, D. sjPlot: data visualization for statistics in social science. R package version 1.6.9. org/Package=sjPlot > (2016). http://CRAN.Rproject. More

Hall, M. J., Burns, A. L., Martin, J. M. & Hochuli, D. F. Flight initiation distance changes across landscapes and habitats in a successful urban coloniser. Urban Ecosyst. https://doi.org/10.1007/s11252-020-00969-5 (2020).Article 

Google Scholar 
Møller, A. P., Samia, D. S. M., Weston, M. A., Guay, P. J. & Blumstein, D. T. Flight initiation distances in relation to sexual dichromatism and body size in birds from three continents. Biol. J. Linn. Soc. 117, 823–831 (2016).
Google Scholar 
Morelli, F. et al. Contagious fear: Escape behavior increases with flock size in European gregarious birds. Ecol. Evol. 9, 6096–6104 (2019).PubMed 
PubMed Central 

Google Scholar 
Samia, D. S. M. et al. Rural-urban differences in escape behavior of European birds across a latitudinal gradient. Front. Ecol. Evol. 5, 66 (2017).ADS 

Google Scholar 
Blumstein, D. T. Developing an evolutionary ecology of fear: How life history and natural history traits affect disturbance tolerance in birds. Anim. Behav. 71, 389–399 (2006).
Google Scholar 
McFarland, D. Oxford companion to animal behavior. (Oxford University Press, 1987).Stankowich, T. & Blumstein, D. T. Fear in animals: A meta-analysis and review of risk assessment. Proc. R. Soc. B Biol. Sci. 272, 2627–2634 (2005).
Google Scholar 
Lima, S. L. Maximizing feeding efficiency and minimizing time exposed to predators: a trade-off in the black-capped chickadee. Oecologia 66, 60–67 (1985).ADS 
PubMed 

Google Scholar 
Sol, D. et al. Risk-taking behavior, urbanization and the pace of life in birds. Behav. Ecol. Sociobiol. 72, 59 (2018).
Google Scholar 
Lockwood, R., Swaddle, J. P. & Rayner, J. M. V. Avian Wingtip Shape Reconsidered: Wingtip Shape Indices and Morphological Adaptations to Migration. J. Avian Biol. 29, 273–292 (1998).
Google Scholar 
Møller, A. P. Birds. in Escaping from predators: An integrative view of escape decisions and refuge use (eds. Cooper, W. E. J. & Blumstein, D. T.) 88–112 (Cambridge University Press, 2015).Møller, A. P. Flight distance of urban birds, predation and selection for urban life. Behav. Ecol. Sociobiol. 63, 63–75 (2008).
Google Scholar 
Fernández-Juricic, E. et al. Relationships of anti-predator escape and post-escape responses with body mass and morphology: a comparative avian study. Evol. Ecol. Res. 8, 731–752 (2006).
Google Scholar 
Weston, M. A., Mcleod, E. M., Blumstein, D. T. & Guay, P. J. A review of flight-initiation distances and their application to managing disturbance to Australian birds. Emu 112, 269–286 (2012).
Google Scholar 
Hemmingsen, A. The relation of shyness (flushing distance) to body size. Spolia Zool Musei Hauniensis 11, 74–76 (1951).
Google Scholar 
Blumstein, D. T. Flight-initiation distance in birds is dependent on intruder starting distance. J. Wildl. Manage. 67, 852–857 (2013).
Google Scholar 
Glover, H. K., Weston, M. A., Maguire, G. S., Miller, K. K. & Christie, B. A. Towards ecologically meaningful and socially acceptable buffers: Response distances of shorebirds in Victoria, Australia, to human disturbance. Landsc. Urban Plan. 103, 326–334 (2011).
Google Scholar 
Geist, C., Liao, J., Libby, S. & Blumstein, D. T. Does intruder group size and orientation affect flight initiation distance in birds?. Anim. Biodivers. Conserv. 28, 69–73 (2001).
Google Scholar 
Mikula, P. Pedestrian density influences flight distances of urban birds. Ardea 102, 53–60 (2014).
Google Scholar 
Piratelli, A. J., Favoretto, G. R. & de Almeida Maximiano, M. F. Factors affecting escape distance in birds. Zoologia 32, 438–444 (2015).Burger, J. & Gochfeld, M. Human activity influence and diurnal and nocturnal foraging of Sanderlings (Calidris alba). Condor 93, 259–265 (1991).
Google Scholar 
Møller, A. P. & Garamszegi, L. Z. Between individual variation in risk-taking behavior and its life history consequences. Behav. Ecol. 23, 843–853 (2012).
Google Scholar 
Ferguson, S. M., Gilson, L. N. & Bateman, P. W. Look at the time: diel variation in the flight initiation distance of a nectarivorous bird. Behav. Ecol. Sociobiol. 73, 147 (2019).
Google Scholar 
Garamszegi, L. Z. & Møller, A. P. Partitioning within-species variance in behaviour to within- and between-population components for understanding evolution. Ecol. Lett. 20, 599–608 (2017).PubMed 

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

Google Scholar 
Dufour, P. et al. Reconstructing the geographic and climatic origins of long-distance bird migrations. J. Biogeogr. 47, 155–166 (2020).
Google Scholar 
Sol, D. et al. Evolutionary divergence in brain size between migratory and resident birds. PLoS ONE 5, e9617 (2010).ADS 
PubMed 
PubMed Central 

Google Scholar 
Bonnet-Lebrun, A. S., Somveille, M., Rodrigues, A. S. L. & Manica, A. Exploring intraspecific variation in migratory destinations to investigate the drivers of migration. Oikos 130, 187–196 (2021).
Google Scholar 
Zurell, D., Gallien, L., Graham, C. H. & Zimmermann, N. E. Do long-distance migratory birds track their niche through seasons?. J. Biogeogr. 45, 1459–1468 (2018).
Google Scholar 
Samia, D. S. M., Nakagawa, S., Nomura, F., Rangel, T. F. & Blumstein, D. T. Increased tolerance to humans among disturbed wildlife. Nat. Commun. 6, 8877 (2015).ADS 
CAS 
PubMed 

Google Scholar 
Ydenberg, R. C. & Dill, L. M. The economics of fleeing from predators. Adv. Study Behav. 16, 229–249 (1986).
Google Scholar 
Cooper, W. E. J. & Blumstein, D. T. Escape behavior: importance, scope, and variables. in Escaping from predators: An integrative view of escape decisions (eds. Cooper, W. E. J. & Blumstein, D. T.) 3–14 (Cambridge University Press, 2015). https://doi.org/10.1017/CBO9781107447189.002.Sayol, F., Sol, D. & Pigot, A. L. Brain size and life history interact to predict urban tolerance in birds. Front. Ecol. Evol. 8, 58 (2020).
Google Scholar 
Sayol, F., Downing, P. A., Iwaniuk, A. N., Maspons, J. & Sol, D. Predictable evolution towards larger brains in birds colonizing oceanic islands. Nat. Commun. 9, 2820 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Tobias, J. A. & Pigot, A. L. Integrating behaviour and ecology into global biodiversity conservation strategies. Philos. Trans. R. Soc. B Biol. Sci. 374, 20190012 (2019).
Google Scholar 
Wilman, H. et al. EltonTraits 1.0: Species-level foraging attributes of the world’s birds and mammals. Ecology 95, 2027 (2014).
Google Scholar 
Kamilar, J. M. & Cooper, N. Phylogenetic signal in primate behaviour, ecology and life history. Philos. Trans. R. Soc. B Biol. Sci. 368, 20120341–22012034 (2013).
Google Scholar 
Machado, J. P., Antunes, A., Borges, R., Gomes, C. & Rocha, A. P. Measuring phylogenetic signal between categorical traits and phylogenies. Bioinformatics https://doi.org/10.1093/bioinformatics/bty800 (2018).Article 

Google Scholar 
Ericson, P. G. P. et al. Diversification of Neoaves: integration of molecular sequence data and fossils. Biol. Lett. 2, 543–547 (2006).PubMed 
PubMed Central 

Google Scholar 
Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).CAS 
PubMed 

Google Scholar 
Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).CAS 

Google Scholar 
Revell, L. J. & Chamberlain, S. A. Rphylip: An R interface for PHYLIP R package. (2014).Blomberg, S. P. & Garland, T. Tempo and mode in evolution: phylogenetic inertia, adaptation and comparative methods. J. Evol. Biol. 15, 899–910 (2003).
Google Scholar 
Keck, F., Rimet, F., Bouchez, A. & Franc, A. Phylosignal: An R package to measure, test, and explore the phylogenetic signal. Ecol. Evol. 6, 2774–2780 (2016).PubMed 
PubMed Central 

Google Scholar 
Münkemüller, T. et al. How to measure and test phylogenetic signal. Methods Ecol. Evol. 3, 743–756 (2012).
Google Scholar 
Kot, M. Adaptation: Statistics and a null model for estimating phylogenetic effects. Syst. Zool. 39, 227–241 (1990).
Google Scholar 
Blomberg, S. P., Garland, T. J. & Ives, A. R. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution (N. Y.) 57, 717–745 (2003).
Google Scholar 
Pagel, M. Inferring the historical patterns of biological evolution. Nature 401, 877–884 (1999).ADS 
CAS 
PubMed 

Google Scholar 
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002).MATH 

Google Scholar 
McCullagh, P. & Nelder, J. A. Generalized Linear Models. (Chapman and Hall, 1989).Pinheiro, J. et al. nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1-140. 1–117 (2019).Nakazawa, M. ‘fmsb’ Functions for Medical Statistics Book with some Demographic Data – R package version 0.6.1. (2017).R Development Core Team. R: A language and environment for statistical computing. (2021).Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S. (Springer, 2002). https://doi.org/10.1007/978-0-387-21706-2. More

Mack, R. N. et al. Biotic invasions: Causes, epidemiology, global consequences, and control. Ecol. Appl. 10(3), 689–710 (2000).
Google Scholar 
Pimentel, D. Biological invasionseconomic and environmental costs of alien plant, animal, and microbe species. No. 577.18 B5/2011. 2011.Jackson, T. Addressing the economic costs of invasive alien species: Some methodological and empirical issues. Int. J. Sustain. Soc. 7(3), 221–240 (2015).
Google Scholar 
Walker, B. H. & Steffen, W. L. Interactive and integrated effects of global change on terrestrial ecosystems. In The Terrestrial Biosphere and Global Change. Implications for Natural and Managed Ecosystems, Synthesis Volume. International Geosphere-Biosphere Program Book Series 4 (eds Walker, B. et al.) 329–375 (Cambridge University Press, 1999).
Google Scholar 
Wilcove, D. S., Rothstein, D., Dubow, J., Phillips, A. & Losos, E. Quantifying threats to imperiled species in the United States. Bioscience 48(8), 607–615 (1998).
Google Scholar 
Robinson, T. W. Introduction, Spread and Areal Extent of Saltcedar [Tamarix] in the Western States (No. 491) (US Government Printing Office, 1965).
Google Scholar 
Marlin, D., Newete, S. W., Mayonde, S. G., Smit, E. R. & Byrne, M. J. Invasive Tamarix (Tamaricaceae) in South Africa: Current research and the potential for biological control. Biol. Invasions 19(10), 2971–2992 (2017).
Google Scholar 
Pearce, C. M. & Smith, D. G. Saltcedar: Distribution, abundance, and dispersal mechanisms, northern Montana, USA. Wetlands 23(2), 215–228 (2003).
Google Scholar 
Newete, S. W., Mayonde, S. & Byrne, M. J. Distribution and abundance of invasive Tamarix genotypes in South Africa. Weed Res. 59(3), 191–200 (2019).CAS 

Google Scholar 
Chew, M. K. The monstering of tamarisk: How scientists made a plant into a problem. J. Hist. Biol. 42(2), 231–266 (2009).PubMed 

Google Scholar 
Richardson, D. M., Macdonald, I. A. W., Hoffmann, J. H. & Henderson, L. Alienplantinvasions. In The Vegetation of Southern Africa (eds Cowling, R. M. et al.) 535–570 (Cambridge University Press, 1997).
Google Scholar 
Ehrenfeld, J. G. Effects of exotic plant invasions on soil nutrient cycling processes. Ecosystems 6(6), 503–523 (2003).CAS 

Google Scholar 
Haubensak, K. A., D’Antonio, C. M. & Alexander, J. Effects of nitrogen-fixing shrubs in Washington and Coastal California1. Weed Technol. 18(sp1), 1475–1479 (2004).
Google Scholar 
Hawkes, C. V., Wren, I. F., Herman, D. J. & Firestone, M. K. Plant invasion alters nitrogen cycling by modifying the soil nitrifying community. Ecol. Lett. 8(9), 976–985 (2005).PubMed 

Google Scholar 
Kourtev, P. S., Ehrenfeld, J. G. & Häggblom, M. Exotic plant species alter the microbial community structure and function in the soil. Ecology 83(11), 3152–3166 (2002).
Google Scholar 
Saggar, S., McIntosh, P. D., Hedley, C. B. & Knicker, H. Changes in soil microbial biomass, metabolic quotient, and organic matter turnover under Hieracium (H. pilosella L.). Biol. Fertility Soils 30(3), 232–238 (1999).CAS 

Google Scholar 
Dudley, T. L., DeLoach, C. J., Levich, J. E. & Carruthers, R. I. Saltcedar invasion of western riparian areas: Impacts and new prospects for control. Trans. N. Am. Wildlife Nat. Resources Conf. 65, 345–381 (2000).
Google Scholar 
Algotsson, E. Biological diversity. In Environmental Management in South Africa 2nd edn (eds Strydom, H. A. & King, N. D.) 97–125 (Juta Cape Town, 2009).
Google Scholar 
Mayonde, S. G., Cron, G. V., Gaskin, J. F. & Byrne, M. J. Tamarix (Tamaricaceae) hybrids: The dominant invasive genotype in Southern Africa. Biol. Invasions 18(12), 3575–3594 (2016).
Google Scholar 
Corbin, J. D. & D’Antonio, C. M. Effects of exotic species on soil nitrogen cycling: Implications for restoration1. Weed Technol. 18(sp1), 1464–1468 (2004).CAS 

Google Scholar 
Marchante, E., Kjøller, A., Struwe, S. & Freitas, H. Soil recovery after removal of the N 2-fixing invasive Acacia longifolia: Consequences for ecosystem restoration. Biol. Invasions 11(4), 813–823 (2009).
Google Scholar 
Magadlela, D. & Mdzeke, N. Social benefits in the Working for Water programme as a public works initiative: Working for water. S. Afr. J. Sci. 100(1–2), 94–96 (2004).
Google Scholar 
Yelenik, S. G., Stock, W. D. & Richardson, D. M. Ecosystem level impacts of invasive Acacia saligna in the South African fynbos. Restor. Ecol. 12(1), 44–51 (2004).
Google Scholar 
Malcolm, G. M., Bush, D. S. & Rice, S. K. Soil nitrogen conditions approach preinvasion levels following restoration of nitrogen-fixing black locust (Robinia pseudoacacia) stands in a Pine-Oak Ecosystem. Restor. Ecol. 16(1), 70–78 (2008).
Google Scholar 
Maron, J. L. & Jefferies, R. L. Bush lupine mortality, altered resource availability, and alternative vegetation states. Ecology 80(2), 443–454 (1999).
Google Scholar 
AgriLASA (Agri Laboratory Association of Southern Africa). 2004. Soil handbook.Okalebo, J.R., Gathua, K.W. & Woomer, P.L. (2002). Laboratory methods of soil and plant analysis: A working manual second edition. Sacred Africa, Nairobi, 21.LECO. 2003. Truspec CN Carbon/Nitrogen Determinator Instructions Manual. LECO Corporation, St Joseph, USA.Suarez, D. L., Wood, J. D. & Lesch, S. M. Effect of SAR on water infiltration under a sequential rain–irrigation management system. Agric. Water Manag. 86(1–2), 150–164 (2006).
Google Scholar 
Dane, J.H., and Hopmans, JW. (2002). Water retention and storage. GC Method of soil analysis. SSSA book series. Madison, Wisconsin, USA. 1692, 671–720.Blakemore, L.C., Searle, P.L. and Daly, B.K. (1987). Methods for chemical analysis of soils. New Zealand Soil Bureau Scientific, Report 80. New Zealand, Lower Hutt: New Zealand Society of Soil Science, 103.Buckham, L.E. (2011). Contrasting growth traits and insect interactions of two Tamarix species and a hybrid (Tamaricaceae) used for mine rehabilitation in South Africa (Doctoral dissertation).Ladenburger, C. G., Hild, A. L., Kazmer, D. J. & Munn, L. C. Soil salinity patterns in Tamarix invasions in the Bighorn Basin, Wyoming, USA. J. Arid Environ. 65(1), 111–128 (2006).ADS 

Google Scholar 
Beukes, P. C. & Ellis, F. Soil and vegetation changes across a Succulent Karoo grazing gradient. Afr. J. Range Forage Sci. 20(1), 11–19 (2003).
Google Scholar 
Liu, M. et al. Monitoring the invasion of Spartina alterniflora using multi-source high-resolution imagery in the Zhangjiang Estuary, China. Remote Sensing 9(6), 539 (2017).ADS 

Google Scholar 
Newete, S. W., Abd Elbasit, M. A. & Araya, T. Soil salinity and moisture content under non-native Tamarix species. Int. J. Phytorem. 22(9), 931–938. https://doi.org/10.1080/15226514.2020.1774503 (2020).CAS 
Article 

Google Scholar 
Whitford, W. G., Anderson, J. & Rice, P. M. Stemflow contribution to the ’fertile island’effect in creosotebush, Larrea tridentata. J. Arid Environ. 35(3), 451–457 (1997).ADS 

Google Scholar 
Li, C., Li, Y. & Ma, J. Spatial heterogeneity of soil chemical properties at fine scales induced by Haloxylon ammodendron (Chenopodiaceae) plants in a sandy desert. Ecol. Res. 26(2), 385–394 (2011).MathSciNet 
CAS 

Google Scholar 
Sookbirsingh, R., Karina, C., Thomas, E.G. & Rusell, RC. (2010). Salt separation processes in the saltcedar Tamarix ramosissima (Lebed.). Commun Soil Sci Plant Anal. 41(10), 1271–1281.Newete, S.W., Allem, S.M., Venter, N. and Byrne, M.J. Tamarix efficiency in salt excretion and physiological tolerance to salt-induced stress in South Africa. Int. J. Phytoremediat. 1–7 (2019).Di Tomaso, J. M. Impact, biology, and ecology of saltcedar (Tamarix spp.) in the southwestern United States. Weed Technol. 12(2), 326–336 (1998).
Google Scholar 
Smith, S. D., Devitt, D. A., Sala, A., Cleverly, J. R. & Busch, D. E. Water relations of riparian plants from warm desert regions. Wetlands 18(4), 687–696 (1998).
Google Scholar 
Lesica, P. & DeLuca, T. H. Is tamarisk allelopathic?. Plant Soil 267(1–2), 357–365 (2004).CAS 

Google Scholar 
Bagstad, K. J., Lite, S. J. & Stromberg, J. C. Vegetation, soils, and hydrogeomorphology of riparian patch types of a dryland river. Western N. Am. Naturalist 66(1), 23–45 (2006).
Google Scholar 
Lehnhoff, E. A., Rew, L. J., Zabinski, C. A. & Menalled, F. D. Reduced impacts or a longer lag phase? Tamarix in the northwestern USA. Wetlands 32(3), 497–508 (2012).
Google Scholar 
Ye, W., Wang, H. X., Gao, J., Liu, H. J. & Yan, L. Simulation of salt ion migration in soil under reclaimed water irrigation. J. Agro-Environ. Sci. 33(5), 1007–1015 (2014).CAS 

Google Scholar 
Yang, S. C. et al. Characterization of soil salinization based on canonical correspondence analysis method in Gansu Yellow River irrigation district of Northwest China. Scientia Agricultura Sinica 47(1), 100–110 (2014).CAS 

Google Scholar 
Zhang, L. H., Chen, P. H., Li, J., Chen, X. B. & Feng, Y. Distribution of soil salt ions around Tamarix chinensis individuals in the Yellow River Delta. Acta Ecol. Sin. 36(18), 5741–5749 (2016).CAS 

Google Scholar 
Zhang, T., Zhan, X., He, J., Feng, H. & Kang, Y. Salt characteristics and soluble cations redistribution in an impermeable calcareous saline-sodic soil reclaimed with an improved drip irrigation. Agric. Water Manag. 197, 91–99 (2018).
Google Scholar 
Yin, C. H., Feng, G. U., Zhang, F., Tian, C. Y. & Tang, C. Enrichment of soil fertility and salinity by tamarisk in saline soils on the northern edge of the Taklamakan Desert. Agric. Water Manag. 97(12), 1978–1986 (2010).
Google Scholar 
Chaudhari, P. R., Ahire, D. V., Ahire, V. D., Chkravarty, M. & Maity, S. Soil bulk density as related to soil texture, organic matter content and available total nutrients of Coimbatore soil. Int. J. Sci. Res. Publ. 3(2), 1–8 (2013).CAS 

Google Scholar 
Tanveera, A., Kanth, T. A., Tali, P. A. & Naikoo, M. Relation of soil bulk density with texture, total organic matter content and porosity in the soils of Kandi Area of Kashmir valley, India. Int. Res. J. Earth Sci. 4(1), 1–6 (2016).
Google Scholar 
Sharma, B. & Bhattacharya, S. Soil bulk density as related to soil texture, moisture content, Ph, electrical conductivity, organic carbon, organic matter content and available macro nutrients of Pandoga sub watershed, Una District of HP (India). Int. J. Eng. Res. Dev. 13(12), 72–76 (2017).
Google Scholar  More

Milner-Gulland, E. J. & Bennett, E. L. Wild meat: The bigger picture. Trends Ecol. Evol. 18, 351–357 (2003).
Google Scholar 
Van Vliet, N. et al. Bushmeat and human health: Assessing the evidence in tropical and sub-tropical forests. Ethnobio. Conserv. 6, 3. https://doi.org/10.15451/ec2017-04-6.3-1-45 (2017).Article 

Google Scholar 
Ingram, D. J. et al. Wild meat is still on the menu: Progress in wild meat research, policy, and practice from 2002 to 2020. Annu. Rev. Environ. Resour. 46, 221–254. https://doi.org/10.1146/annurev-environ-041020-063132 (2021).Article 

Google Scholar 
Golden, C. D., Fernald, L. C. H., Brashares, J. S., Rasolofoniaina, B. J. R. & Kremen, C. Benefits of wildlife consumption to child nutrition in a biodiversity hotspot. P. Natl. Acad. Sci. 108, 19653–19656 (2011).ADS 
CAS 

Google Scholar 
Roe, D. et al. Beyond banning wildlife trade: COVID-19, conservation and development. World Dev. 136, 105121. https://doi.org/10.1016/j.worlddev.2020.105121 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Zhou, W., Orrick, K., Lim, A. & Dove, M. Reframing conservation and development perspectives on bushmeat. Environ. Res. Lett. 17, 011001. https://doi.org/10.1088/1748-9326/ac3db1 (2021).ADS 
Article 

Google Scholar 
Cawthorn, D.-M. & Hoffman, L. C. The bushmeat and food security nexus: A global account of the contributions, conundrums and ethical collisions. Food Res. Int. 76, 906–925 (2015).PubMed Central 

Google Scholar 
Antunes, A. P. et al. A conspiracy of silence: Subsistence hunting rights in the Brazilian Amazon. Land Use Policy 84, 1–11 (2019).
Google Scholar 
Friant, S. et al. Eating bushmeat improves food security in a biodiversity and infectious disease “Hotspot”. EcoHealth 17, 125–138 (2020).PubMed 

Google Scholar 
Fa, J. E., Currie, D. & Meeuwig, J. Bushmeat and food security in the Congo Basin: Linkages between wildlife and people’s future. Environ. Conserv. 30, 71–78 (2003).
Google Scholar 
Borgerson, C., Razafindrapaoly, B., Rajaona, D., Rasolofoniaina, B. J. R. & Golden, C. D. Food insecurity and the unsustainable hunting of wildlife in a UNESCO world heritage site. Front. Sustain. Food Syst. 3, 99. https://doi.org/10.3389/fsufs.2019.00099 (2019).Article 

Google Scholar 
Booth, H. et al. Investigating the risks of removing wild meat from global food systems. Curr. Biol. 31, 1788–1797. https://doi.org/10.1016/j.cub.2021.01.079 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
van Vliet, N., Nebesse, C. & Nasi, R. Bushmeat consumption among rural and urban children from Province Orientale, Democratic Republic of Congo. Oryx 49, 165–174 (2015).
Google Scholar 
Sirén, A. & Machoa, J. Fish, wildlife, and human nutrition in tropical forests: A fat gap?. Interciencia 33, 186–193 (2008).
Google Scholar 
Sarti, F. M. et al. Beyond protein intake: Bushmeat as source of micronutrients in the Amazon. E&S 20, 22 (2015).
Google Scholar 
Hoffman, L. C. What is the role and contribution of meat from wildlife in providing high quality protein for consumption?. Anim. Front. 2, 15 (2012).
Google Scholar 
Fa, J. E. et al. Disentangling the relative effects of bushmeat availability on human nutrition in central Africa. Sci. Rep. 5, 8168. https://doi.org/10.1038/srep08168 (2015).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Castro, T. G., Baraldi, L. G., Muniz, P. T. & Cardoso, M. A. Dietary practices and nutritional status of 0–24-month-old children from Brazilian Amazonia. Public Health Nutr. 12, 2335–2342 (2009).CAS 
PubMed 

Google Scholar 
Mintz, S. W. & Du Bois, C. M. The anthropology of food and eating. Annu. Rev. Anthropol. 31, 99–119 (2002).
Google Scholar 
Lokossou, Y. U. A., Tambe, A. B., Azandjèmè, C. & Mbhenyane, X. Socio-cultural beliefs influence feeding practices of mothers and their children in Grand Popo, Benin. J. Health Popul. Nutr. 40, 33 (2021).PubMed 
PubMed Central 

Google Scholar 
Murphy, S. P. & Allen, L. H. Nutritional importance of animal source foods. J. Nutr. 133, 3932S-3935S (2003).CAS 
PubMed 

Google Scholar 
Neumann, C. G. et al. Animal source foods improve dietary quality, micronutrient status, growth and cognitive function in Kenyan School Children: Background, study design and baseline findings. J. Nutr. 133, 3941S-3949S (2003).CAS 
PubMed 

Google Scholar 
Desalegn, A., Mossie, A. & Gedefaw, L. Nutritional iron deficiency anemia: Magnitude and its predictors among school age children, Southwest Ethiopia: A community based cross-sectional study. PLoS ONE 9, e114059 (2014).ADS 
PubMed Central 

Google Scholar 
Safiri, S. et al. Burden of anemia and its underlying causes in 204 countries and territories, 1990–2019: Results from the Global Burden of Disease Study 2019. J. Hematol. Oncol. 14, 185 (2021).PubMed 
PubMed Central 

Google Scholar 
Vos, T. et al. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet 388, 1545–1602 (2016).
Google Scholar 
Investing in the future: a united call to action on vitamin and mineral deficiencies: global report, 2009. (Micronutrient Initiative, 2009).Walker, S. P. et al. Child development: Risk factors for adverse outcomes in developing countries. Lancet 369, 145–157 (2007).PubMed 

Google Scholar 
Saloojee, H. & Pettifor, J. M. Iron deficiency and impaired child development: The relation may be causal, but it may not be a priority for intervention. BMJ 323, 1377–1378 (2001).CAS 
PubMed 
PubMed Central 

Google Scholar 
Neumann, C., Harris, D. M. & Rogers, L. M. Contribution of animal source foods in improving diet quality and function in children in the developing world. Nutr. Res. 22, 193–220 (2002).CAS 

Google Scholar 
Haileselassie, M. et al. Why are animal source foods rarely consumed by 6–23 months old children in rural communities of Northern Ethiopia? A qualitative study. PLoS ONE 15, e0225707 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Victor, R., Baines, S. K., Agho, K. E. & Dibley, M. J. Factors associated with inappropriate complementary feeding practices among children aged 6–23 months in Tanzania: Complementary feeding practices in Tanzania. Matern. Child Nutr. 10, 545–561 (2014).PubMed 

Google Scholar 
Morsello, C. et al. Cultural attitudes are stronger predictors of bushmeat consumption and preference than economic factors among urban Amazonians from Brazil and Colombia. E&S 20, 21 (2015).
Google Scholar 
Parry, L., Barlow, J. & Pereira, H. Wildlife Harvest and Consumption in Amazonia’s Urbanized Wilderness: Wildlife consumption in urbanized Amazonia. Conserv. Lett. 7, 565–574 (2014).
Google Scholar 
Chaves, W. A., Wilkie, D. S., Monroe, M. C. & Sieving, K. E. Market access and wild meat consumption in the central Amazon, Brazil. Biol. Conserv. 212, 240–248 (2017).
Google Scholar 
Dufour, D. L., Piperata, B. A., Murrieta, R. S. S., Wilson, W. M. & Williams, D. D. Amazonian foods and implications for human biology. Ann. Hum. Biol. 43, 330–348 (2016).PubMed 

Google Scholar 
Piperata, B. A. Nutritional status of Ribeirinhos in Brazil and the nutrition transition. Am. J. Phys. Anthropol. 133, 868–878 (2007).PubMed 

Google Scholar 
Garcia, M. T., Granado, F. S. & Cardoso, M. A. Alimentação complementar e estado nutricional de crianças menores de dois anos atendidas no Programa Saúde da Família em Acrelândia, Acre, Amazônia Ocidental Brasileira. Cad. Saúde Pública 27, 305–316 (2011).PubMed 

Google Scholar 
Marques, R. C., Bernardi, J. V. E., Dorea, C. C. & Dórea, J. G. Intestinal parasites, anemia and nutritional status in young children from transitioning Western Amazon. IJERPH 17, 577 (2020).PubMed Central 

Google Scholar 
Granado, F. S., Augusto, R. A., Muniz, P. T. & Cardoso, M. A. Team, the A. S. Anaemia and iron deficiency between 2003 and 2007 in Amazonian children under 2 years of age: Trends and associated factors. Public Health Nutr. 16, 1751–1759 (2013).PubMed 

Google Scholar 
Nogueira-de-Almeida, C. A. et al. Prevalence of childhood anaemia in Brazil: Still a serious health problem: A systematic review and meta-analysis. Public Health Nutr. 24, 6450–6465. https://doi.org/10.1017/S136898002100286X (2021).Article 
PubMed 

Google Scholar 
de Souza, A. A., Mingoti, S. A., Paes-Sousa, R. & Heller, L. Combination of conditional cash transfer program and environmental health interventions reduces child mortality: An ecological study of Brazilian municipalities. BMC Public Health 21, 627 (2021).PubMed 
PubMed Central 

Google Scholar 
Ferreira, H. S. et al. Prevalence of anaemia in Brazilian children in different epidemiological scenarios: An updated meta-analysis. Public Health Nutr. 24, 2171–2184 (2021).PubMed 

Google Scholar 
Leite, M. S. et al. Prevalence of anemia and associated factors among indigenous children in Brazil: Results from the First National Survey of Indigenous People’s Health and Nutrition. Nutr. 12, 69 (2013).
Google Scholar 
WHO, W. H. O. Prevalence of anaemia in children aged 6–59 months (%). https://www.who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-anaemia-in-children-under-5-years-(-) (2021).Schreiner, M. A Poverty Probability Index (PPI®) for Brazil (2008). (2010).Walzer, C. COVID-19 and the curse of piecemeal perspectives. Front. Vet. Sci. 7, 582983 (2020).PubMed 
PubMed Central 

Google Scholar 
Carignano, T. P., Morsello, C. & Parry, L. Rural-urban mobility influences wildmeat access and consumption in the Brazilian Amazon. Oryx (In press).Ferreira, M. U. et al. Anemia and iron deficiency in school children, adolescents, and adults: A community-based study in Rural Amazonia. Am. J. Public Health 97, 237–239 (2007).PubMed 
PubMed Central 

Google Scholar 
de Castro, T. G., Silva-Nunes, M., Conde, W. L., Muniz, P. T. & Cardoso, M. A. Anemia e deficiência de ferro em pré-escolares da Amazônia Ocidental brasileira: Prevalência e fatores associados. Cad. Saúde Pública 27, 131–142 (2011).PubMed 

Google Scholar 
Cotta, R. M. M. et al. Social and biological determinants of iron deficiency anemia. Cad. Saúde Pública 27, s309–s320 (2011).PubMed 

Google Scholar 
Chaves, W. A., Valle, D., Tavares, A. S., Morcatty, T. Q. & Wilcove, D. S. Impacts of rural to urban migration, urbanization, and generational change on consumption of wild animals in the Amazon. Conserv. Biol. 35, 1186–1197. https://doi.org/10.1111/cobi.13663 (2020).Article 

Google Scholar 
El Bizri, H. R. et al. Urban wild meat consumption and trade in central Amazonia. Conserv. Biol. 34, 438–448 (2020).PubMed 

Google Scholar 
Chaves, W. A., Valle, D., Tavares, A. S., von Mühlen, E. M. & Wilcove, D. S. Investigating illegal activities that affect biodiversity: The case of wildlife consumption in the Brazilian Amazon. Ecol. Appl. 31, e02402. https://doi.org/10.1002/eap.2402 (2021).Article 
PubMed 

Google Scholar 
Chaves, W. A., Monroe, M. C. & Sieving, K. E. Wild meat trade and consumption in the Central Amazon, Brazil. Hum. Ecol. 47, 733–746 (2019).
Google Scholar 
Ohl-Schacherer, J. et al. The sustainability of subsistence hunting by matsigenka native communities in Manu National Park, Peru. Conserv. Biol. 21, 1174–1185 (2007).PubMed 

Google Scholar 
Shaffer, C. A., Yukuma, C., Marawanaru, E. & Suse, P. Assessing the sustainability of Waiwai subsistence hunting in Guyana by comparison of static indices and spatially explicit, biodemographic models. Anim. Conserv. 21, 148–158 (2018).
Google Scholar 
Pesquisa de orçamentos familiares, 2008–2009. (IBGE, 2010).Aguiar, J. P. L. Tabela de composição de alimentos da Amazônia. Acta Amaz 26, 121–126 (1996).
Google Scholar 
de Bruyn, J. et al. Food composition tables in resource-poor settings: exploring current limitations and opportunities, with a focus on animal-source foods in sub-Saharan Africa. Br. J. Nutr. 116, 1709–1719 (2016).PubMed Central 

Google Scholar 
World Bank. Poverty and Shared Prosperity 2020: Reversals of Fortune. (World Bank, 2020).Coad, L. M. et al. Toward a Sustainable, Participatory and Inclusive Wild Meat Sector. (Center for International Forestry Research (CIFOR) https://doi.org/10.17528/cifor/007046 (2019).Cowlishaw, G., Mendelson, S. & Rowcliffe, J. M. Evidence for post-depletion sustainability in a mature bushmeat market. J. Appl. Ecol. 42, 460–468 (2005).
Google Scholar 
Carignano Torres, P., Morsello, C., Parry, L. & Pardini, R. Forest cover and social relations are more important than economic factors in driving hunting and bushmeat consumption in post-frontier Amazonia. Biol. Conserv. 253, 108823. https://doi.org/10.1016/j.biocon.2020.108823 (2021).Article 

Google Scholar 
Nunes, A. V., Oliveira-Santos, L. G. R., Santos, B. A., Peres, C. A. & Fischer, E. Socioeconomic drivers of hunting efficiency and use of space by traditional Amazonians. Hum. Ecol. 48, 307–315 (2020).
Google Scholar 
Freitas, C. T. et al. Co-management of culturally important species: A tool to promote biodiversity conservation and human well-being. People Nat. 2, 61–81 (2020).
Google Scholar 
Campos-Silva, J. V., Peres, C. A., Antunes, A. P., Valsecchi, J. & Pezzuti, J. Community-based population recovery of overexploited Amazonian wildlife. PECON 15, 266–270 (2017).
Google Scholar 
Nunes, A. V., Peres, C. A., de Constantino, P. A. L., Santos, B. A. & Fischer, E. Irreplaceable socioeconomic value of wild meat extraction to local food security in rural Amazonia. Biol. Conserv. 236, 171–179 (2019).
Google Scholar 
Balarajan, Y., Ramakrishnan, U., Özaltin, E., Shankar, A. H. & Subramanian, S. Anaemia in low-income and middle-income countries. Lancet 378, 2123–2135 (2011).PubMed 

Google Scholar 
Mendes, M. M. et al. Association between iron deficiency anaemia and complementary feeding in children under 2 years assisted by a Conditional Cash Transfer programme. Public Health Nutr. 24, 4080–4090 (2021).PubMed 

Google Scholar 
Brondízio, E. S., de Lima, A. C. B., Schramski, S. & Adams, C. Social and health dimensions of climate change in the Amazon. Ann. Hum. Biol. 43, 405–414 (2016).PubMed 

Google Scholar 
Ingram, D. J. Wild meat in changing times. J. Ethnobiol. 40, 117 (2020).
Google Scholar 
Nunes, A. V., Guariento, R. D., Santos, B. A. & Fischer, E. Wild meat sharing among non-indigenous people in the southwestern Amazon. Behav. Ecol. Sociobiol. 73, 26 (2019).
Google Scholar 
Parry, L. et al. Social vulnerability to climatic shocks is shaped by urban accessibility. Ann. Am. Assoc. Geogr. 108, 125–143 (2018).
Google Scholar 
IBGE, I. B. de G. e E. Censo Demográfico 2010. (2010).IBGE, I. B. de G. e E. Estimativas da população residente para os municípios e para as unidades da federação com data de referência em 1o de julho de 2019. (2019).Cardoso, M. A., Scopel, K. K. G., Muniz, P. T., Villamor, E. & Ferreira, M. U. Underlying factors associated with anemia in amazonian children: A population-based cross-sectional study. PLOS ONE 7, e36341 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Mattiello, V. et al. Diagnosis and management of iron deficiency in children with or without anemia: consensus recommendations of the SPOG Pediatric Hematology Working Group. Eur. J. Pediatr. 179, 527–545 (2020).PubMed 

Google Scholar 
R Core Team. R: The R project for statistical computing. (2015).Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009). https://doi.org/10.1007/978-0-387-87458-6.Book 
MATH 

Google Scholar 
Devereux, S. Social Protection for Rural Poverty Reduction. Rural Transformations Technical Series 1 (2016).Barton, K. Mu-MIn: Multi-model Inference. R Package Version 0.12.2/r18. (2009).Burnham, K. P., Anderson, D. R. & Burnham, K. P. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002).MATH 

Google Scholar 
Berti, P. R. Intrahousehold distribution of food: A review of the literature and discussion of the implications for food fortification programs. Food Nutr. Bull. 33, S163–S169 (2012).PubMed 

Google Scholar 
Piperata, B. A., Schmeer, K. K., Hadley, C. & Ritchie-Ewing, G. Dietary inequalities of mother–child pairs in the rural Amazon: Evidence of maternal-child buffering?. Soc. Sci. Med. 96, 183–191 (2013).PubMed 
PubMed Central 

Google Scholar  More