Philippa Kaur

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

Meng, L. et al. Proc. Natl Acad. Sci. USA 117, 4228 (2020).CAS 
Article 

Google Scholar 
Wohlfahrt, G., Tomelleri, E. & Hammerle, A. Nat. Ecol. Evol. 3, 1668–1674 (2019).Article 

Google Scholar 
Wortman, S. E. & Lovell, S. T. J. Environ. Qual. 42, 1283–1294 (2013).CAS 
Article 

Google Scholar 
Su, Y. et al. Agri. For. Meterol. 280, 107765 (2020).Article 

Google Scholar 
Smith, I. A., Dearborn, V. K. & Hutyra, L. R. PLoS ONE 14, e0215846 (2019).Article 

Google Scholar 
Richardson, A. D. et al. Nature 560, 368–371 (2018).CAS 
Article 

Google Scholar 
Meineke, E. K., Dunn, R. R. & Frank, S. D. Biol. Lett. 10, 20140586 (2014).Article 

Google Scholar 
Liu, J. et al. Tour. Manag. 70, 262–272 (2019).Article 

Google Scholar 
Li, X. et al. Remote Sens. Environ. 222, 267–274 (2019).CAS 
Article 

Google Scholar 
Wang, S. et al. Nat. Ecol. Evol. 3, 1076–1085 (2019).Article 

Google Scholar 
Feeley, K. J. et al. Nat. Clim. Change 10, 965–970 (2020).CAS 
Article 

Google Scholar 
Li, D. et al. Nat. Ecol. Evol. 3, 1661–1667 (2019).Article 

Google Scholar 
Li, X. et al. Earth Syst. Sci. Data 11, 881–894 (2019).Article 

Google Scholar 
Román, M. O. et al. Remote Sens. Environ. 210, 113–143 (2018).Article 

Google Scholar 
Li, X. et al. Remote Sens. Environ. 215, 74–84 (2018).Article 

Google Scholar  More

Jean Combes’s love of nature as a child led her to note the signs of starting spring. Her long-term records are now part of a vital growing citizen science dataset that starkly shows how climate change is shifting the timing of the natural world.For people living in colder parts of the world, watching for the first signs of spring — from the opening of snowdrops and daffodils, to birds building their nests, to the return of bees and butterflies — is a common winter pastime. Jean Combes has not just been watching out for these signs, but also recording them, ever since she was a child. Taking note of the earliest emergence of leaves in springtime — first as a child of 11 years, and then continuously from the age of 20 years — Jean has now collected one of the longest continuous datasets of spring leaf-out time in the UK (see also Correspondence by Vitasse et al.). These almost 75 years of data show a clear shift that corroborates shifts now acknowledged for diverse species around the world: springtime is coming earlier, and the patterns of advance match the global trends in the changing climate. Jean’s naturalist endeavours have already earned her high honours in the form of an OBE (Order of the British Empire), and recognition of her own work is mirrored in a growing recognition of the vital role of citizen scientists in tracking the signs of our rapidly changing world.
This is a preview of subscription content More

Templeton, T. J., Martinsen, E., Kaewthamasorn, M. & Kaneko, O. The rediscovery of malaria parasites of ungulates. Parasitology 143, 1501–1508. https://doi.org/10.1017/S0031182016001141 (2016).Article 
PubMed 

Google Scholar 
Sheather, A. A malaria parasite in the blood of a buffalo. J. Comp. Pathol. Ther. 32, 80026–80027 (1919).Article 

Google Scholar 
Templeton, T. J. et al. Ungulate malaria parasites. Sci. Rep. 6, 23230. https://doi.org/10.1038/srep23230 (2016).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Kandel, R. C. et al. First report of malaria parasites in water buffalo in Nepal. Vet. Parasitol. Reg. Stud. Rep. 18, 100348. https://doi.org/10.1016/j.vprsr.2019.100348 (2019).Article 

Google Scholar 
Garnham, P. & Edeson, J. Two new malaria parasites of the Malayan mousedeer. Riv. Malariol. 41, 1–8 (1962).CAS 
PubMed 

Google Scholar 
Hoo, C. & Sandosham, A. The early forms of Hepatocystis fieldi and Plasmodium traguli in the Malayan mouse-deer Tragulus javanicus. Med. J. Malays. 22, 299–301 (1968).
Google Scholar 
de Mello, F.d., Paes, S. Sur une plasmodiae du sang des chèvres. Cr. Séanc. Soc. Biol. 88, 829–830 (1923).Kaewthamasorn, M. et al. Genetic homogeneity of goat malaria parasites in Asia and Africa suggests their expansion with domestic goat host. Sci. Rep. 8, 5827. https://doi.org/10.1038/s41598-018-24048-0 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Rattanarithikul, R. H., Bruce, A., Harbach, R. E., Panthusiri, P. & Coleman, R. E. Illustrated keys to the mosquitoes of Thailand IV. Anopheles. Southeast Asian J Trop Med Public Health. 37 (2006).Walter Reed Biosystematics Unit. 2021. Systematic catalogue of Culicidae. http://mosquitocatalog.org. Last accessed on 20/09/2021.Sinka, M. E. et al. The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis. Parasit. Vectors. 4, 89. https://doi.org/10.1186/1756-3305-4-89 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Syafruddin, D. et al. Malaria prevalence in Nias District, North Sumatra Province, Indonesia. Malar. J. 6, 116. https://doi.org/10.1186/1475-2875-6-116 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
Vantaux, A. et al. Anopheles ecology, genetics and malaria transmission in northern Cambodia. Sci. Rep. 11, 6458. https://doi.org/10.1038/s41598-021-85628-1 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Manguin, S., Garros, C., Dusfour, I., Harbach, R. & Coosemans, M. Bionomics, taxonomy, and distribution of the major malaria vector taxa of Anopheles subgenus Cellia in Southeast Asia: An updated review. Infect. Genet. Evol. 8, 489–503. https://doi.org/10.1016/j.meegid.2007.11.004 (2008).CAS 
Article 
PubMed 

Google Scholar 
Paredes-Esquivel, C., Donnelly, M. J., Harbach, R. E. & Townson, H. A molecular phylogeny of mosquitoes in the Anopheles barbirostris Subgroup reveals cryptic species: implications for identification of disease vectors. Mol. Phylogenet. Evol. 50, 141–151. https://doi.org/10.1016/j.ympev.2008.10.011 (2009).CAS 
Article 
PubMed 

Google Scholar 
Sungvornyothin, S., Garros, C., Chareonviriyaphap, T. & Manguin, S. How reliable is the humeral pale spot for identification of cryptic species of the Minimus Complex?. J. Am. Mosq. Control. Assoc. 22, 185–191. https://doi.org/10.2987/8756-971X(2006)22[185:HRITHP]2.0.CO;2 (2006).Article 
PubMed 

Google Scholar 
Brosseau, L. et al. A multiplex PCR assay for the identification of five species of the Anopheles barbirostris complex in Thailand. Parasite. Vectors. 12, 223. https://doi.org/10.1186/s13071-019-3494-8 (2019).Article 

Google Scholar 
Taai, K. & Harbach, R. E. Systematics of the Anopheles barbirostris species complex (Diptera: Culicidae: Anophelinae) in Thailand. Zool. J. Linn. Soc. 174, 244–264. https://doi.org/10.1111/zoj.12236 (2015).Article 

Google Scholar 
Dahan-Moss, Y. et al. Member species of the Anopheles gambiae complex can be misidentified as Anopheles leesoni. Malar. J. 19, 1–9. https://doi.org/10.1186/s12936-020-03168-x (2020).CAS 
Article 

Google Scholar 
De Ang, J. X., Yaman, K., Kadir, K. A., Matusop, A. & Singh, B. New vectors that are early feeders for Plasmodium knowlesi and other simian malaria parasites in Sarawak, Malaysian Borneo. Sci. Rep. https://doi.org/10.1038/s41598-021-86107-3 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Van Bortel, W. et al. Confirmation of Anopheles varuna in Vietnam, previously misidentified and mistargeted as the malaria vector Anopheles minimus. Am. J. Trop. Med. Hyg. 65, 729–732. https://doi.org/10.4269/ajtmh.2001.65.729 (2001).Article 
PubMed 

Google Scholar 
Wharton, R., Eyles, D. E., Warren, M., Moorhouse, D. & Sandosham, A. Investigations leading to the identification of members of the Anopheles umbrosus group as the probable vectors of mouse deer malaria. Bull. World. Health. Organ. 29, 357 (1963).CAS 
PubMed 
PubMed Central 

Google Scholar 
Boundenga, L. et al. Haemosporidian parasites of antelopes and other vertebrates from Gabon, Central Africa. PLoS ONE 11, e0148958. https://doi.org/10.1371/journal.pone.0148958 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Martinsen, E. S. et al. Hidden in plain sight: Cryptic and endemic malaria parasites in North American white-tailed deer (Odocoileus virginianus). Sci. Adv. 2, e1501486. https://doi.org/10.1126/sciadv.1501486 (2016).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Garnham, P. C. C. Malaria Parasites and Other Haemosporidia (Blackwell Sci. Pub, 1966).
Google Scholar 
Nguyen, A. H. L., Tiawsirisup, S. & Kaewthamasorn, M. Low level of genetic diversity and high occurrence of vector-borne protozoa in water buffaloes in Thailand based on 18S ribosomal RNA and mitochondrial cytochrome b genes. Infect. Genet. Evol. 82, 104304. https://doi.org/10.1016/j.meegid.2020.104304 (2020).CAS 
Article 
PubMed 

Google Scholar 
Hebert, P. D., Cywinska, A. & Ball, S. L. Biological identifications through DNA barcodes. Proc. R. Soc. Lond. B Biol. Sci. 270, 313–321. https://doi.org/10.1098/rspb.2002.2218 (2003).CAS 
Article 

Google Scholar 
Cywinska, A., Hunter, F. & Hebert, P. D. Identifying Canadian mosquito species through DNA barcodes. Med. Vet. Entomol. 20, 413–424. https://doi.org/10.1111/j.1365-2915.2006.00653.x (2006).CAS 
Article 
PubMed 

Google Scholar 
Ogola, E. O., Chepkorir, E., Sang, R. & Tchouassi, D. P. A previously unreported potential malaria vector in a dry ecology of Kenya. Parasites Vectors 12, 80. https://doi.org/10.1186/s13071-019-3332-z (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Maquart, P.-O., Fontenille, D., Rahola, N., Yean, S. & Boyer, S. Checklist of the mosquito fauna (Diptera, Culicidae) of Cambodia. Parasite 28, 60. https://doi.org/10.1051/parasite/2021056 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Saeung, A. et al. Geographic distribution and genetic compatibility among six karyotypic forms of Anopheles peditaeniatus (Diptera: Culicidae) in Thailand. Trop. Biomed. 29, 613–625 (2012).CAS 
PubMed 

Google Scholar 
Tainchum, K., Kongmee, M., Manguin, S., Bangs, M. J. & Chareonviriyaphap, T. Anopheles species diversity and distribution of the malaria vectors of Thailand. Trends Parasitol. 31, 109–119. https://doi.org/10.1016/j.pt.2015.01.004 (2015).Article 
PubMed 

Google Scholar 
Chookaew, S. et al. Anopheles species composition in malaria high-risk areas in Ranong Province. Dis. Cont. J. 46, 483–493. https://doi.org/10.14456/dcj.2020.45 (2020).Article 

Google Scholar 
Reid, J. A. The Anopheles barbirostris group (Diptera, Culicidae). Bull. Entomol. Res. 53, 1–57 (1962).Article 

Google Scholar 
Harrison, B. A. & Scanlon, J. E. Medical entomology studies–II. The subgenus Anopheles in Thailand (Diptera: Culicidae). Contributions of the American Entomological Institute (Ann Arbor) 12 (1): iv + 1–iv 307 (1975).Wang, Y., Xu, J. & Ma, Y. Molecular characterization of cryptic species of Anopheles barbirostris van der Wulp in China. Parasite Vectors 7, 592. https://doi.org/10.1186/s13071-014-0592-5 (2014).CAS 
Article 

Google Scholar 
Wang, G. et al. An evaluation of the suitability of COI and COII gene variation for reconstructing the phylogeny of, and identifying cryptic species in, anopheline mosquitoes (Diptera Culicidae). Mitochondrial DNA Part A. 28, 769–777. https://doi.org/10.1080/24701394.2016.1186665 (2017).CAS 
Article 

Google Scholar 
Davidson, J. R. et al. Molecular analysis reveals a high diversity of Anopheles species in Karama, West Sulawesi, Indonesia. Parasite Vectors https://doi.org/10.1186/s13071-020-04252-6 (2020).Article 

Google Scholar 
Beebe, N. W. DNA barcoding mosquitoes: advice for potential prospectors. Parasitology 145(5), 622–633. https://doi.org/10.1017/S0031182018000343 (2018).CAS 
Article 
PubMed 

Google Scholar 
Gunathilaka, N. Illustrated key to the adult female Anopheles (Diptera: Culicidae) mosquitoes of Sri Lanka. Appl. Entomol. Zool. 52, 69–77. https://doi.org/10.1007/s13355-016-0455-y (2017).Article 
PubMed 

Google Scholar 
WHO. Pictorial identification key of important disease vectors in the WHO South-East Asia Region. https://apps.who.int/iris/handle/10665/332202 (accessed 20 August 2021).Rigg, C. A., Hurtado, L. A., Calzada, J. E. & Chaves, L. F. Malaria infection rates in Anopheles albimanus (Diptera: Culicidae) at Ipetí-Guna, a village within a region targeted for malaria elimination in Panamá. Infect. Genet. Evol. 69, 216–223. https://doi.org/10.1016/j.meegid.2019.02.003 (2019).Article 
PubMed 

Google Scholar 
Torres-Cosme, R. et al. Natural malaria infection in anophelines vectors and their incrimination in local malaria transmission in Darién, Panama. PLoS ONE 16, e0250059. https://doi.org/10.1371/journal.pone.0250059 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Beebe, N. W. & Saul, A. Discrimination of all Members of the Anopheles punctulatus complex by polymerase chain reaction-restriction fragment length polymorphism analysis. Am. J. Trop. Med. Hyg. 53, 478–481. https://doi.org/10.4269/ajtmh.1995.53.478 (1995).CAS 
Article 
PubMed 

Google Scholar 
Perkins, S. L. & Schall, J. J. A molecular phylogeny of malaria parasites recovered from cytochrome b gene sequences. J. Parasitol. 88, 972–978. https://doi.org/10.1645/0022-3395(2002)088[0972:AMPOMP]2.0.CO;2 (2002).CAS 
Article 
PubMed 

Google Scholar 
Snounou, G. et al. High sensitivity of detection of human malaria parasites by the use of nested polymerase chain reaction. Mol. Biochem. Parasitol. 61, 315–320. https://doi.org/10.1016/0166-6851(93)90077-b (1993).CAS 
Article 
PubMed 

Google Scholar 
Hall, T. A. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic. Acids. Symp. Ser. 41, 95–98 (1999).CAS 

Google Scholar 
Schoener, E. et al. Avian Plasmodium in Eastern Austrian mosquitoes. Malar. J. 16, 389. https://doi.org/10.1186/s12936-017-2035-1 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Ventim, R. et al. Avian malaria infections in western European mosquitoes. Parasitol. Res. 111, 637–645. https://doi.org/10.1007/s00436-012-2880-3 (2012).Article 
PubMed 

Google Scholar 
Huelsenbeck, J. P. & Ronquist, F. MRBAYES: Bayesian inference of phylogeny. Bioinformatics 17, 754–755 (2001).CAS 
Article 

Google Scholar 
Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior summarization in Bayesian phylogenetics using tracer 1.7. Syst. Biol. 67, 901–904 (2018).CAS 
Article 

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

CORRESPONDENCE
05 April 2022

Regreening: green is not always gold

Michael C. Orr

0
&

Alice C. Hughes

1

Michael C. Orr

Institute of Zoology, Chinese Academy of Sciences, Beijing, China.

View author publications

You can also search for this author in PubMed
 Google Scholar

Alice C. Hughes

University of Hong Kong, Hong Kong, China.

View author publications

You can also search for this author in PubMed
 Google Scholar

Twitter

Facebook

Email

As the upcoming United Nations Biodiversity Conference in Kunming, China, ushers in the UN decade of ecosystem restoration, regreening efforts are sprouting worldwide. Adding vegetation — expedited by new technologies such as EcoFit, which predicts what trees will thrive in a given environment — can salvage highly disturbed habitats, benefiting native species and offsetting climate change. But when aimed at halting desertification, regreening can have a devastating cost for native ecosystems.

Access options

Access through your institution

Change institution

Buy or subscribe

/* style specs start */
style{display:none!important}.LiveAreaSection-193358632 *{align-content:stretch;align-items:stretch;align-self:auto;animation-delay:0s;animation-direction:normal;animation-duration:0s;animation-fill-mode:none;animation-iteration-count:1;animation-name:none;animation-play-state:running;animation-timing-function:ease;azimuth:center;backface-visibility:visible;background-attachment:scroll;background-blend-mode:normal;background-clip:borderBox;background-color:transparent;background-image:none;background-origin:paddingBox;background-position:0 0;background-repeat:repeat;background-size:auto auto;block-size:auto;border-block-end-color:currentcolor;border-block-end-style:none;border-block-end-width:medium;border-block-start-color:currentcolor;border-block-start-style:none;border-block-start-width:medium;border-bottom-color:currentcolor;border-bottom-left-radius:0;border-bottom-right-radius:0;border-bottom-style:none;border-bottom-width:medium;border-collapse:separate;border-image-outset:0s;border-image-repeat:stretch;border-image-slice:100%;border-image-source:none;border-image-width:1;border-inline-end-color:currentcolor;border-inline-end-style:none;border-inline-end-width:medium;border-inline-start-color:currentcolor;border-inline-start-style:none;border-inline-start-width:medium;border-left-color:currentcolor;border-left-style:none;border-left-width:medium;border-right-color:currentcolor;border-right-style:none;border-right-width:medium;border-spacing:0;border-top-color:currentcolor;border-top-left-radius:0;border-top-right-radius:0;border-top-style:none;border-top-width:medium;bottom:auto;box-decoration-break:slice;box-shadow:none;box-sizing:border-box;break-after:auto;break-before:auto;break-inside:auto;caption-side:top;caret-color:auto;clear:none;clip:auto;clip-path:none;color:initial;column-count:auto;column-fill:balance;column-gap:normal;column-rule-color:currentcolor;column-rule-style:none;column-rule-width:medium;column-span:none;column-width:auto;content:normal;counter-increment:none;counter-reset:none;cursor:auto;display:inline;empty-cells:show;filter:none;flex-basis:auto;flex-direction:row;flex-grow:0;flex-shrink:1;flex-wrap:nowrap;float:none;font-family:initial;font-feature-settings:normal;font-kerning:auto;font-language-override:normal;font-size:medium;font-size-adjust:none;font-stretch:normal;font-style:normal;font-synthesis:weight style;font-variant:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;grid-auto-columns:auto;grid-auto-flow:row;grid-auto-rows:auto;grid-column-end:auto;grid-column-gap:0;grid-column-start:auto;grid-row-end:auto;grid-row-gap:0;grid-row-start:auto;grid-template-areas:none;grid-template-columns:none;grid-template-rows:none;height:auto;hyphens:manual;image-orientation:0deg;image-rendering:auto;image-resolution:1dppx;ime-mode:auto;inline-size:auto;isolation:auto;justify-content:flexStart;left:auto;letter-spacing:normal;line-break:auto;line-height:normal;list-style-image:none;list-style-position:outside;list-style-type:disc;margin-block-end:0;margin-block-start:0;margin-bottom:0;margin-inline-end:0;margin-inline-start:0;margin-left:0;margin-right:0;margin-top:0;mask-clip:borderBox;mask-composite:add;mask-image:none;mask-mode:matchSource;mask-origin:borderBox;mask-position:0% 0%;mask-repeat:repeat;mask-size:auto;mask-type:luminance;max-height:none;max-width:none;min-block-size:0;min-height:0;min-inline-size:0;min-width:0;mix-blend-mode:normal;object-fit:fill;object-position:50% 50%;offset-block-end:auto;offset-block-start:auto;offset-inline-end:auto;offset-inline-start:auto;opacity:1;order:0;orphans:2;outline-color:initial;outline-offset:0;outline-style:none;outline-width:medium;overflow:visible;overflow-wrap:normal;overflow-x:visible;overflow-y:visible;padding-block-end:0;padding-block-start:0;padding-bottom:0;padding-inline-end:0;padding-inline-start:0;padding-left:0;padding-right:0;padding-top:0;page-break-after:auto;page-break-before:auto;page-break-inside:auto;perspective:none;perspective-origin:50% 50%;pointer-events:auto;position:static;quotes:initial;resize:none;right:auto;ruby-align:spaceAround;ruby-merge:separate;ruby-position:over;scroll-behavior:auto;scroll-snap-coordinate:none;scroll-snap-destination:0 0;scroll-snap-points-x:none;scroll-snap-points-y:none;scroll-snap-type:none;shape-image-threshold:0;shape-margin:0;shape-outside:none;tab-size:8;table-layout:auto;text-align:initial;text-align-last:auto;text-combine-upright:none;text-decoration-color:currentcolor;text-decoration-line:none;text-decoration-style:solid;text-emphasis-color:currentcolor;text-emphasis-position:over right;text-emphasis-style:none;text-indent:0;text-justify:auto;text-orientation:mixed;text-overflow:clip;text-rendering:auto;text-shadow:none;text-transform:none;text-underline-position:auto;top:auto;touch-action:auto;transform:none;transform-box:borderBox;transform-origin:50% 50% 0;transform-style:flat;transition-delay:0s;transition-duration:0s;transition-property:all;transition-timing-function:ease;vertical-align:baseline;visibility:visible;white-space:normal;widows:2;width:auto;will-change:auto;word-break:normal;word-spacing:normal;word-wrap:normal;writing-mode:horizontalTb;z-index:auto;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;margin:0}.LiveAreaSection-193358632{width:100%}.LiveAreaSection-193358632 .login-option-buybox{display:block;width:100%;font-size:17px;line-height:30px;color:#222;padding-top:30px;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-access-options{display:block;font-weight:700;font-size:17px;line-height:30px;color:#222;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-login >li:not(:first-child)::before{transform:translateY(-50%);content:”;height:1rem;position:absolute;top:50%;left:0;border-left:2px solid #999}.LiveAreaSection-193358632 .additional-login >li:not(:first-child){padding-left:10px}.LiveAreaSection-193358632 .additional-login >li{display:inline-block;position:relative;vertical-align:middle;padding-right:10px}.BuyBoxSection-683559780{display:flex;flex-wrap:wrap;flex:1;flex-direction:row-reverse;margin:-30px -15px 0}.BuyBoxSection-683559780 .box-inner{width:100%;height:100%}.BuyBoxSection-683559780 .readcube-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:1;flex-basis:255px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:300px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox-nature-plus{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:100%;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .title-readcube{display:block;margin:0;margin-right:20%;margin-left:20%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-buybox{display:block;margin:0;margin-right:29%;margin-left:29%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .asia-link{color:#069;cursor:pointer;text-decoration:none;font-size:1.05em;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:1.05em6}.BuyBoxSection-683559780 .access-readcube{display:block;margin:0;margin-right:10%;margin-left:10%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .usps-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .price-buybox{display:block;font-size:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;padding-top:30px;text-align:center}.BuyBoxSection-683559780 .price-from{font-size:14px;padding-right:10px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .issue-buybox{display:block;font-size:13px;text-align:center;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:19px}.BuyBoxSection-683559780 .no-price-buybox{display:block;font-size:13px;line-height:18px;text-align:center;padding-right:10%;padding-left:10%;padding-bottom:20px;padding-top:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .vat-buybox{display:block;margin-top:5px;margin-right:20%;margin-left:20%;font-size:11px;color:#222;padding-top:10px;padding-bottom:15px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:17px}.BuyBoxSection-683559780 .button-container{display:flex;padding-right:20px;padding-left:20px;justify-content:center}.BuyBoxSection-683559780 .button-container >*{flex:1px}.BuyBoxSection-683559780 .button-container >a:hover,.Button-505204839:hover,.Button-1078489254:hover,.Button-2808614501:hover{text-decoration:none}.BuyBoxSection-683559780 .readcube-button{background:#fff;margin-top:30px}.BuyBoxSection-683559780 .button-asia{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;margin-top:75px}.BuyBoxSection-683559780 .button-label-asia,.ButtonLabel-3869432492,.ButtonLabel-3296148077,.ButtonLabel-1566022830{display:block;color:#fff;font-size:17px;line-height:20px;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;text-align:center;text-decoration:none;cursor:pointer}.Button-505204839,.Button-1078489254,.Button-2808614501{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;max-width:320px;margin-top:10px}.Button-505204839 .readcube-label,.Button-1078489254 .readcube-label,.Button-2808614501 .readcube-label{color:#069}
/* style specs end */Subscribe to Nature+Get immediate online access to the entire Nature family of 50+ journals$29.99monthlySubscribeSubscribe to JournalGet full journal access for 1 year$199.00only $3.90 per issueSubscribeAll prices are NET prices. VAT will be added later in the checkout.Tax calculation will be finalised during checkout.Buy articleGet time limited or full article access on ReadCube.$32.00BuyAll prices are NET prices.

Additional access options:

Log in

Learn about institutional subscriptions

Nature 604, 40 (2022)
doi: https://doi.org/10.1038/d41586-022-00944-4

Competing Interests
The authors declare no competing interests.

Related Articles

See more letters to the editor

Subjects

Biodiversity

Conservation biology

Climate change

Latest on:

Biodiversity

China: protect black soil for biodiversity
Correspondence 05 APR 22

Funding battles stymie ambitious plan to protect global biodiversity
News 31 MAR 22

Are there limits to economic growth? It’s time to call time on a 50-year argument
Editorial 16 MAR 22

Climate change

The microbiologist working to understand how oceans absorb carbon dioxide
Spotlight 05 APR 22

By the numbers: China’s net-zero ambitions
Spotlight 05 APR 22

Turning industrial CO2 into battery fuel
Spotlight 05 APR 22

Jobs

Junior group leader position in Human immunology, Pathophysiology and Immunotherapy at Inserm-Université Paris Cité Unit 976

National Institute for Health and Medical Research (INSERM)
Paris, France

Senior Assistant Editor

Elsevier Inc.
London, Greater London, United Kingdom

Dean, Gordon W. Davis College of Agricultural Sciences and Natural Resources

Texas Tech University (TTU)
Lubbock, TX, United States

Postdoctoral fellow positions in cancer stem cells, single cell genomics, and tumor immunology

Houston Methodist in “ affiliation with Weill- Cornell Medical College
Houston, United States More

Wang, L.C.H. Ecological, physiological, and biochemical aspects of torpor in mammals and birds in Advances in comparative and environmental physiology (ed. Wang, L.C.H.) 361–401 (Springer, 1989).Humphries, M.M., Speakman, J.R., & Thomas, D.W. Temperature, hibernation energetics, and the cave and continental distributions of little brown myotis in Functional and Evolutionary Ecology of Bats (ed. Zubaid, A., McCracken, G.F., & Kunz, T.H.) 23–37 (Oxford Press, 2005).Hudson, J.W. Torpidity in mammals in Comparative physiology of thermoregulation. (ed. Whittow, G.C., Hudson, J.W., & Deavers, D.R.) 97–165 (Academic Press, 1973).Geiser, F. & Ruf, T. Hibernation versus daily torpor in mammals and birds: Physiological variables and classification of torpor patterns. Phys. Zool. 68, 935–966 (1995).Article 

Google Scholar 
Davis, W. H. & Hitchcock, H. B. Biology and migration of the bat, Myotis lucifugus, New England. J. Mamm. 46, 296–313. https://doi.org/10.2307/1377850 (1965).Article 

Google Scholar 
Speakman, J. R. & Rowland, A. Preparing for inactivity: How insectivorous bats deposit a fat store for hibernation. Proc. Nutr. Soc. 58, 123–131. https://doi.org/10.1079/PNS19990017 (1999).CAS 
Article 
PubMed 

Google Scholar 
Boyles, J. G., Johnson, J. S., Blomberg, A. & Lilley, T. M. Optimal hibernation theory. Mammal Rev. 50, 91–100. https://doi.org/10.1111/mam.12181 (2020).Article 

Google Scholar 
Britzke, E. R., Sewell, P., Hohmann, M. G., Smith, R. & Scott, R. Use of temperature-sensitive transmitters to monitor the temperature profiles of hibernating bats affected with white-nose syndrome. Northeast. Nat. 17, 239–246. https://doi.org/10.1656/045.017.0207 (2010).Article 

Google Scholar 
Halsall, A. L., Boyles, J. G. & Whitaker, J. O. Jr. Body temperature patterns of big browns during winter in a building hibernaculum. J. Mamm. 93, 497–503. https://doi.org/10.1644/11-MAMM-A-262.1 (2012).Article 

Google Scholar 
Johnson, J. S., Lacki, M. J., Thomas, S. C. & Grider, J. F. Frequent arousals from winter torpor in Rafinesque’s big-eared bat (Corynorhinus rafinesquii). PLoS ONE 7, e49754. https://doi.org/10.1371/journal.pone.0049754 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Jonasson, K. A. & Willis, C. K. R. Hibernation energetics of free-ranging little brown bats. J. Exp. Bio. 215, 2141–2149. https://doi.org/10.1242/jeb.066514 (2012).Article 

Google Scholar 
Day, K. M. & Tomasi, T. E. Winter energetics of female Indiana bats Myotis sodalis. Physiol. Biochem. Zool. 87, 56–64. https://doi.org/10.1086/671563 (2014).Article 
PubMed 

Google Scholar 
Meierhofer, M. B. et al. Winter habitats of bats in Texas. PLoS ONE 14, e0220839. https://doi.org/10.1371/journal.pone.0220839 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Boyles, J. G. Benefits of knowing the costs of disturbance to hibernating bats. Wildl. Soc. Bull. 41, 388–392. https://doi.org/10.1002/wsb.755 (2017).Article 

Google Scholar 
Frick, W. F. et al. Pathogen dynamics during invasion and establishment of white-nose syndrome explain mechanisms of host persistence. Ecology 98, 624–631. https://doi.org/10.1002/ecy.1706 (2017).Article 
PubMed 

Google Scholar 
Cheng, T. L. et al. The scope and severity of white-nose syndrome on hibernating bats in North America. Conserv. Biol. 35, 1586–1597. https://doi.org/10.1111/cobi.13739 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Cryan, P. M., Meteyer, C. U., Boyles, J. G. & Blehert, D. S. Wing pathology of white-nose syndrome in bats suggests life-threatening disruption of physiology. BMC Biol. 8, 1–8 (2010).Article 

Google Scholar 
Cryan, P. M. et al. Electrolyte depletion in white-nose syndrome bats. J. Wild. Dis. 49, 398–402 (2013).CAS 
Article 

Google Scholar 
Frick, W. F. et al. Disease alters macroecological patterns of North American bats. Glob. Ecol. Biogeogr. 24, 741–749. https://doi.org/10.1111/geb.12290 (2015).Article 

Google Scholar 
Bernard, R.F., Willcox, E.V., Parise, K.L., Foster, J.T., & McCracken, G.F. White-nose syndrome fungus, Pseudogymnoascus destructans, on bats captured emerging from caves during winter in the southeastern United States. BMC Zool. https://doi.org/10.1186/s40850-017-0021-2 (2017).Davy, C. M. et al. The other white-nose syndrome transcriptome: Tolerant and susceptible hosts respond differently to the pathogen Pseudogymnoascus destructans. Ecol. Evol. 7, 7161–7170. https://doi.org/10.1002/ece3.3234 (2015).Article 

Google Scholar 
Lilley, T. M. et al. Resistance is futile: RNA-sequencing reveals differing responses to bat fungal pathogen in Nearctic Myotis lucifugus and Palearctic Myotis myotis. Oecologia 191, 295–309. https://doi.org/10.1007/s00442-019-04499-6 (2019).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bernard, R. F. & McCracken, G. F. Winter behavior of bats and the progression of white-nose syndrome in the southeastern United States. Ecol. Evol. 7, 1487–1496. https://doi.org/10.1002/ece3.2772 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Moosman, P.R., Warner, D.P., Hendren, R.H., & Hosler, M.J. Potential for monitoring eastern small-footed bats on talus slopes. Northeast. Nat. https://www.jstor.org/stable/26453719 (2015).Bernard, R. F. et al. Identifying research needs to inform white-nose syndrome management decisions. Cons. Sci. Prac. 2(e220), 2020. https://doi.org/10.1111/csp2.220 (2020).Article 

Google Scholar 
Reynolds, D. S., Shoemaker, K., Oettingen, S. V. & Najjar, S. High rates of winter activity and arousals in two New England bat species: implications for a reduced white-nose syndrome impact?. Northeast. Nat. 24, B188–B208. https://doi.org/10.1656/045.024.s720 (2017).Article 

Google Scholar 
Bernard, R. F., Willcox, E. V., Jackson, R. T., Brown, V. A. & McCracken, G. F. Feasting, not fasting: Winter diets of cave hibernating bats in the United States. Front. Zool. 18, 1–13. https://doi.org/10.1186/s12983-021-00434-9 (2021).Article 

Google Scholar 
Prendergast, B. J., Freeman, D. A., Zucker, I. & Nelson, R. J. Periodic arousal from hibernation is necessary for initiation of immune responses in ground squirrels. Am. J. Phys. 282, 1054–1062. https://doi.org/10.1152/ajpregu.00562.2001 (2002).Article 

Google Scholar 
Dobony, C. A. et al. Little brown myotis persist despite exposure to white-nose syndrome. J. Fish Wild. 2, 190–195. https://doi.org/10.3996/022011-JFWM-014 (2011).Article 

Google Scholar 
Rowley, J. J. & Alford, R. A. Hot bodies protect amphibians against chytrid infection in nature. Sci. Rep. 3, 1–4. https://doi.org/10.1038/srep01515 (2013).CAS 
Article 

Google Scholar 
Verant, M. L. et al. White-nose syndrome initiates a cascade of physiologic disturbances in the hibernating bat host. BMC Physiol. 14, 10 (2014).Article 

Google Scholar 
Verant, M. L. et al. Temperature-dependent growth of Geomyces destructans, the fungus that causes bat white-nose syndrome. PLoS ONE 7, e46280. https://doi.org/10.1371/journal.pone.0046280 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Brownlee-Bouboulis, S. A. & Reeder, D. M. White-nose syndrome-affected little brown Myotis (Myotis lucifugus) increase grooming and other active behaviors during arousals from hibernation. J. Wildl. Dis. 49, 850–859. https://doi.org/10.7589/2012-10-242 (2013).Article 
PubMed 

Google Scholar 
Campbell, J. Tennessee winter bat population and white-nose syndrome monitoring report for 2018–2019. TWRA Wildlife Technical Report 16-4. http://www.tnbwg.org/2019%20Annual%20Monitoring%20Report.pdf (2019).Langwig, K. E. et al. Sociality, density-dependence and microclimates determine the persistence of populations suffering from a novel fungal disease, white-nose syndrome. Eco. Let. 15, 1050–1057. https://doi.org/10.1111/j.1461-0248.2012.01829.x (2012).Article 

Google Scholar 
Langwig, K.E., et al. Drivers of variation in species impacts for a multi-host fungal disease of bats. Philos. Trans. R. Soc. B Biol. Sci. 371, 20150456. https://doi.org/10.1098/rstb.2015.0456 (2016).Aldridge, H.D.J.N., & Brigham, R.M. Load carrying and maneuverability in an insectivorous bat: A test of the 5% ‘rule’ of radio-telemetry. J. Mamm. 69, 379–382. https://doi.org/10.2307/1381393 (1988)Sikes, R. S. et al. Guidelines of the American Society of Mammalogists for the use of wild mammals in research and education. J. Mamm. 97, 663–688. https://doi.org/10.1093/jmammal/gyw078 (2016).Article 

Google Scholar 
Barclay, R. M. R. et al. Can external radiotransmitters be used to assess body temperature and torpor in bats?. J. Mammal. 77, 1102–1106. https://doi.org/10.2307/1382791 (1996).Article 

Google Scholar 
Turbill, C., & Geiser, F. Hibernation by tree-roosting bats. J. Comp. Physiol. B. 178, 597–605. https://doi.org/10.1007/s00360-007-0249-1 (2008)Park, K.J., Jones, G., & Ransome, R.D. Torpor, arousal and activity of hibernating greater horseshoe bats (Rhinolophus ferrumequinum). Funct. Ecol. 14, 580–588 (2000).Reeder, D. M. et al. Frequent arousal from hibernation linked to severity of infection and mortality in bats with white-nose syndrome. PLoS ONE 7, e38920. https://doi.org/10.1371/journal.pone.0038920 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Sirajuddin, P. Vulnerability of tri-colored bats (Perimyotis subflavus) to white-nose syndrome in the southeastern United States. M.S thesis at https://www.proquest.com/dissertations-theses/vulnerability-tri-colored-bats-i-perimyotis/docview/2185672601/se-2?accountid=8361 (2018).R Development Core Team 3.6.1. A Language and Environment for Statistical Computing. http://www.r-project.org (2019).Bates, D., Maechler, M., Bolker, B., & Walker, S. lme4: Linear mixed-effects models using ‘Eigen’ and S4. R Packag. version 1.1-13. ftp://cran.r-project.org/pub/R/web/packages/lme4/lme4.pdf. (2017)Czenze, Z. J. & Willis, C. K. R. Warming up and shipping out: Arousal and emergence timing in hibernating little brown bats (Myotis lucifugus). J. Comp. Physiol. B-Biochem. Syst. Environ. Physiol. 185, 575–586. https://doi.org/10.1007/s00360-015-0900-1 (2015).Article 

Google Scholar 
Conover, W.J. Practical Nonparametric Statistics. (Wiley, 1999).Crawley, M.J. The R Book: Second Edition. (Wiley, 2013)Lenth, R., Singmann, H., Love, J., Buerkner, P., & Herve, M. Package ‘emmeans’. R Packag. version 1.7.0. https://cran.r-project.org/web/packages/emmeans/emmeans.pdf (2021)Best, T.L. & Jennings, J.B. Myotis leibii. Mammalian Species 547, 1–6. https://doi.org/10.2307/3504255 (1997)Frank, C.L., Herzog, C.,. Laske, J.P., & Cardino V. The role of skin temperature in the resistance of Myotis leibii to white-nose syndrome presented at the 49th Symposium of the North American Society for Bat Research, Kalamazoo, Michigan https://www.nasbr.org/resources/docs/meetings/year/2019/NASBR-2019-Abstracts-Draft-191001.pdf (2019)Johnson, J.S., Scafini, M.R., Sewall, B.J., & Turner, G.G. Hibernating bat species in Pennsylvania use colder winter habitats following the arrival of white-nose syndrome in Conservation and Ecology of Pennsylvania’s Bats (ed. Butchkoski, C.M., Reeder, D.M., Turner, G.G., & Whidden, H.P) 181–199 (The Pennsylvania Academy of Science, 2016)Haase, C.G., et al. Body mass and hibernation microclimate may predict bat susceptibility to white‐nose syndrome. Eco. Evo. 11, 506–515 https://doi.org/10.1002/ece3.7070 (2021)Veilleux, J.P. A Noteworthy Hibernation Record of Myotis leibii (Eastern Small-footed Bat) in Massachusetts. Northeast. Nat. 14, 501–502 https://doi.org/10.1656/1092-6194(2007)14[501:ANHROM]2.0.CO;2 (2007)Boyles, J. G., Dunbar, M. B. & Whitaker, J. O. Activity following arousal in winter in North American vespertilionid bats. Mamm. Rev. 36, 267–280. https://doi.org/10.1111/j.1365-2907.2006.00095.x (2006).Article 

Google Scholar 
Webb, P. I., Speakman, J. R. & Racey, P. A. How hot is a hibernaculum? A review of the temperatures at which bats hibernate. Can. J. Zool. 74, 761–765. https://doi.org/10.1139/z96-087 (1996).Article 

Google Scholar 
Jackson, R.T., Willcox, E.V., Zobel, J.M., & Bernard, R.F. Hibernation behavior of four bat species with differing susceptibility to white-nose syndrome. In review (2021).Fujita, M. S. & Kunz, T. H. Pipstrellus subflavus. Mamm. Spec. 228, 1–6. https://doi.org/10.2307/3504021 (1984).Article 

Google Scholar 
Bohn, S. J. et al. Evidence of ‘sickness behaviour’ in bats with white-nose syndrome. Behaviour 152, 981–1003. https://doi.org/10.1163/1568539X-00003384 (2016).Article 

Google Scholar 
Tuttle, M. D. Status, causes of decline, and management of endangered gray bats. J. Wild. Manag. 43, 1–17. https://doi.org/10.2307/3800631 (1979).Article 

Google Scholar 
Harvey, M.J., Altenbach, J.S., & Best, T.L. Bats of the Eastern United States. (JHU Press, 2011).Klüg-Baerwald, B. J., Lausen, C. L., Willis, C. K. & Brigham, R. M. Home is where you hang your bat: Winter roost selection by prairie-living big brown bats. J. Mamm. 98, 752–760. https://doi.org/10.1093/jmammal/gyx039 (2017).Article 

Google Scholar 
Sandel, J. K. et al. Use and selection of winter hibernacula by the eastern pipistrelle (Pipistrellus subflavus) in Texas. J. Mamm. 82, 173–178. https://doi.org/10.1644/1545-1542(2001)082%3c0173:UASOWH%3e2.0.CO;2 (2001).Article 

Google Scholar 
Hayes, J. P., Ober, H. K., Sherwin, R. E. Survey and monitoring of bats in Ecological and behavioral methods for the study of bats (ed. Kunz, T. H., Parsons, S.). 120–129 (JHU Press, 2009). More

Collection of wolf hair samplesHair samples were collected by researchers from opportunistically found-dead wolves upon standard necropsy (all the Alpine and part of the Iberian samples) or in the field (all the Dinaric-Balkan and most of the Iberian samples), or from legally harvested wolves (only in the Scandinavian population). At the time of sample collection, wolves were legally harvested in Sweden, Slovenia, and Spain, and under total protection in Portugal and Italy. Hair samples were collected from four body regions, when possible: lumbar (n = 133), dorsal cervical (n = 66), tail (n = 33) and ventral thorax (n = 27) (Tables S1 and S2). The hair was cut as close as possible to the skin with scissors to avoid collecting hair follicles, but in some samples, hairs were pulled from the carcass. Samples were stored at room temperature in paper envelopes. Age, sex, date, and cause of death/capture, geographical location, body mass, and total length were obtained for most of the wolves.Age was estimated by the dental eruption and wear or cementum age analysis and classified as ‘juveniles’ ( 2 years)40, or ‘unknown’. Sex was assessed by inspection of genitalia. Causes of death were classified as ‘acute’, likely lasting minutes to hours (vehicle accident and legal or illegal shooting); ‘subacute’, likely lasting hours to days (drowning, poisoning, trapping and intraspecific aggression); ‘chronic’, likely lasting several weeks (infectious diseases—canine distemper, canine parvovirosis, leptospirosis; sarcoptic mange; or neoplastic diseases) or ‘unknown’. Total length was obtained by measuring with metric tape (1 mm precision) the distance from snout to the distal end of the last tail vertebrae. The body mass was measured with 100 g precision with scales.The detailed protocol for the handling of wolves live trapped in the scope of ecological and conservation studies (n = 7, all from the Iberian population) has been previously described5. Traps were monitored twice every day, in the early morning and late afternoon, hence the duration of restraint after capture was unknown for 8 wolves, potentially up to 12 h. Trap-alarms were deployed in the capture of 2 wolves, with 41 and 70 min intervals between activation of the alarm and administration of the drugs. Live trapping was conducted under permits issued by the nature conservation authorities of Portugal (Instituto de Conservação da Natureza e das Florestas: 338/2007/CAPT, 258/2008/CAPT, 286/2008/CAPT, 260/2009/CAPT, 332/2010/MANU, 333/2010/CAPT, 336/2010/MANU, 26/2012/MANU, and 72/2014/CAPT) and Spain (Dirección Xeral de Conservación da Naturaleza, Xunta de Galicia: E-0020/13-PNPE, 095/2013; Consejería de Medio Ambiente, Principado de Asturias: 31/08/2017-BOPA 05/09/17) and according to European Union directives on the protection of animals used for scientific purposes (Directive 2010/63/EU) and international wildlife standards41,42. The study was undertaken in compliance with the ARRIVE guidelines43.Cortisol extractionThe protocol for the extraction of cortisol from the hair was adapted from previously described procedures15,27. Forty mg of guard hairs were separated from the undercoat and placed in 15 ml falcon tubes. Hair follicles were cut whenever found in the sample. For each sample, the length of three intact hairs was recorded. The samples were washed twice with 40 µl of distilled water/mg hair and three times with the same amount of isopropanol. In each washing step, the samples and washing solution were vortexed, the supernatant discarded, and the hair dried using clean paper towels. After the final wash, samples were dried overnight at room temperature and 30 mg of hair cut into a 2 ml polypropylene screw cap plastic tube with five 4 mm steel beads added to each tube.The hair was ground to a fine powder in a FastPrep sample homogenizer (MP Biomedicals, USA) for four times 1 min at 6.0 m/s. 50 µl methanol/mg hair were added to each sample and sonicated for 30 min at 50 Hz at 50 °C. The samples were incubated for 18 h at 50 °C in an orbital shaker at 160 rpm, centrifuged for 15 min at 14,000g at 20 °C, and 1000 µl of supernatant was collected to a screw cap glass chromatography vial and dried at room temperature in a gentle stream of nitrogen gas. Due to restrictions on laboratory use during the SARS-Cov-2 pandemic, some batches of samples were instead evaporated overnight on a suction hood. This unexpected change in the methanol evaporation protocol was recorded and accounted for in the statistical analysis.Cortisol quantificationA commercial competitive ELISA kit (Cortisol free in Saliva ELISA, Demeditec, Germany) was used to quantify the concentration of cortisol, following the manufacturer’s instructions. The kit plate wells are provided coated with polyclonal rabbit antibody against cortisol, and cortisol-horseradish peroxidase was used as conjugate. According to the manufacturer, the cross-reactivity of the test to selected steroids is low (Table S3), the intra-assay variation is 3.8–5.8% and the inter-assay variation is 6.2–6.4%. Samples, standards, and controls were tested in duplicate.The 4-parameter standard curve was calculated from the log-transformed cortisol concentration of the standard solutions and their measured OD45044. Standard curves were estimated using the software GraphPad Prism 6.04 (GraphPad Software, La Jolla, California USA), and yielded an average R2adjusted = 0.991 (range 0.968–0.999). The cortisol concentration of the reconstituted samples was estimated from the standard curve and converted to cortisol concentration as picograms (pg) of cortisol/mg of guard hair.Intra and inter-assay coefficients of variation were estimated for six ELISA assays of 37–40 samples each. The low and high controls included in the kit were used to estimate the inter-assay coefficient of variation and the duplicate runs of each sample were used to estimate the intra-assay coefficient of variation. Linearity was assessed by two-fold dilutions (1:1, 1:2, 1:4 and 1:8) of 4 extracted samples, comparing the expected and observed concentrations. Recovery was assessed by spiking 6 ground hair samples with known concentrations of cortisol (50, 25, 12.5, 6.25 pg/mg, and no spiking), comparing the expected and observed concentrations.The intra-assay coefficient of variation of the ELISA assays ranged from 6.50 to 9.97% (average 7.66%). The inter-assay coefficient of variation was 11.54% for the low concentration controls and 9.08% for the high concentration controls (average 10.31%). Assay linearity was 91% for the 1:2 dilution, 103% for 1:4, and 117% for 1:8 (average 103%). The recovery of cortisol averaged 94%, being 73% for the 50 pg/mg spiked samples, 74% for 25 pg/mg, 95% for 12.5 pg/mg, and 113% for 6.25 pg/mg.Determinants of hair cortisol concentrationThe potential determinants of HCC investigated included wolf intrinsic variables: sex, age, body condition, body structural size, month of death/capture, and wolf population. The scaled mass index was selected as a measure of body condition45 and estimated from the log-transformed body weight (g) and total length (mm). Log-transformed total length was used as an indicator of body structural size46. Samples were assigned to the Iberian, Alpine, Dinaric-Balkan, or Scandinavian wolf populations16 from the geographical location of the death or live-trapping sites (Fig. 1).The relationship between HCC and additional variables related to the sampling procedure or to the work conducted in the laboratory (length of hair used for cortisol extraction, sample storage time, body region, cause of death/capture, and methanol evaporation protocol), herein referred to as methodological variables, was also investigated as potential confounding variables. Sample storage time was the period in months between death/capture and cortisol extraction. In those samples for which only the year of death was available, 30 June was assigned as the date of death, solely to estimate storage time. All continuous variables were standardized to their z-scores.Statistical analysisFirst, the effect of body region was investigated by a linear mixed model with HCC as the dependent variable, and the independent variables body region, as a categorical fixed effect, and individual wolf, as a random effect. The lumbar region was set as the reference class as it was the most represented in our sample (Table S1). Data from 27 wolves for which samples were available from all 4 body regions were used in this analysis. Four outliers in the dataset violated the assumption of normality in the residuals of the model comparing HCC across body regions (Fig. S1A) and were excluded from this model’s dataset (Fig. S1B).Second, the effect of intrinsic and methodological variables on HCC from the lumbar body region was investigated by another linear mixed model with sex, age, body condition, body structural size (standardized log-transformed total length), cause of death/capture, wolf population, hair length, sample storage time, and methanol evaporation protocol as fixed effect independent variables. The month of death/capture was included as a random effect. Reference classes for the categorical variables were set as female, adult, acute death, Iberian population, and methanol evaporation by nitrogen gas stream. Two outliers in the dataset violated the assumption of normality in the residuals of the model (Full model, Table S4) and were excluded from this analysis (Fig. S1C,D).The goal of this analysis was to assess the relationship between HCC and wolf intrinsic variables, controlling for the potential confounding effect of the methodological variables. Starting from the full model (Table S4), models including all possible combinations of variables were ranked by their AICc using the package “MuMIn”47 in R 3.6.148. The most supported model was selected for inference and models with ΔAICc  More