Ecology

1.
Fukuda, S. et al. Bifidobacteria can protect from enteropathogenic infection through production of acetate. Nature 469(7331), 543–547 (2011).
ADS  CAS  Article  Google Scholar 
2.
Huda, M. N. et al. Stool microbiota and vaccine responses of infants. Pediatrics 134(2), e362–372 (2014).
Article  Google Scholar 

3.
Chichlowski, M., De Lartigue, G., German, J. B., Raybould, H. E. & Mills, D. A. Bifidobacteria isolated from infants and cultured on human milk oligosaccharides affect intestinal epithelial function. J. Pediatr. Gastroenterol. Nutr. 55(3), 321–332 (2012).
CAS  Article  Google Scholar 

4.
Lewis, Z. T. & Mills, D. A. Differential establishment of bifidobacteria in the breastfed infant Ggut. Nestle Nutr. Inst. Workshop Series. 88, 149–159 (2017).
Article  Google Scholar 

5.
Tannock, G. W., Lee, P. S., Wong, K. H. & Lawley, B. Why don’t all infants have bifidobacteria in their stool?. Front. Microbiol. 7, 834 (2016).
Article  Google Scholar 

6.
Kumar, H. et al. The bifidogenic effect revisited—ecology and health perspectives of bifidobacterial colonization in early life. Microorganisms 8(12), 1855. https://doi.org/10.3390/microorganisms8121855 (2020).

7.
Bryant, K. & McDonald, L. C. Clostridium difficile infections in children. Pediatr. Infect. Dis. J. 28(2), 145–146 (2019).
Article  Google Scholar 

8.
Lee, S. H., Gong, Y. N. & Ryoo, E. Clostridium difficile colonization and/or infection during infancy and the risk of childhood allergic diseases. Korean J. Pediatr. 60(5), 145–150 (2017).
Article  Google Scholar 

9.
Shamir, R. The benefits of breast feeding. Nestle Nutr. Inst. Workshop Series. 86, 67–76 (2016).
Article  Google Scholar 

10.
Turck, D. et al. Breastfeeding: Health benefits for child and mother. Arch. Pediatr. Organe Off. Soc. Francaise Pediatr. 20, S29-48 (2013).
Google Scholar 

11.
Martin, R. et al. Human milk is a source of lactic acid bacteria for the infant gut. J. Pediatr. 143(6), 754–758 (2003).
CAS  Article  Google Scholar 

12.
Perez, P. F. et al. Bacterial imprinting of the neonatal immune system: Lessons from maternal cells?. Pediatrics 119(3), e724-732 (2007).
Article  Google Scholar 

13.
Fernandez, L. et al. The microbiota of human milk in healthy women. Cell Mol. Biol. 59(1), 31–42 (2013).
CAS  PubMed  Google Scholar 

14.
Heikkila, M. P. & Saris, P. E. Inhibition of Staphylococcus aureus by the commensal bacteria of human milk. J. Appl. Microbiol. 95(3), 471–478 (2003).
CAS  Article  Google Scholar 

15.
Damaceno, Q. S. et al. Evaluation of potential probiotics isolated from human milk and colostrum. Probiot. Antimicrob. Proteins. 9(4), 371–379 (2017).
Article  Google Scholar 

16.
Boix-Amoros, A., Collado, M. C. & Mira, A. Relationship between milk microbiota, bacterial load, macronutrients, and human cells during lactation. Front. Microbiol. 7, 492 (2016).
Article  Google Scholar 

17.
Collado, M. C., Delgado, S., Maldonado, A. & Rodriguez, J. M. Assessment of the bacterial diversity of breast milk of healthy women by quantitative real-time PCR. Lett. Appl. Microbiol. 48(5), 523–528 (2009).
CAS  Article  Google Scholar 

18.
Martin, R. et al. Isolation of bifidobacteria from breast milk and assessment of the bifidobacterial population by PCR-denaturing gradient gel electrophoresis and quantitative real-time PCR. Appl. Environ. Microbiol. 75(4), 965–969 (2009).
CAS  Article  Google Scholar 

19.
Qian, L., Song, H. & Cai, W. Determination of Bifidobacterium and Lactobacillus in breast milk of healthy women by digital PCR. Beneficial Microb. 7(4), 559–569 (2016).
CAS  Article  Google Scholar 

20.
Soto, A. et al. Lactobacilli and bifidobacteria in human breast milk: Influence of antibiotherapy and other host and clinical factors. J. Pediatr. Gastroenterol. Nutr. 59(1), 78–88 (2014).
Article  Google Scholar 

21.
Sugahara, H., Odamaki, T., Hashikura, N., Abe, F. & Xiao, J. Z. Differences in folate production by bifidobacteria of different origins. Biosci. Microb. Food Health. 34(4), 87–93 (2015).
CAS  Article  Google Scholar 

22.
Odamaki, T. et al. Comparative genomics revealed genetic diversity and species/strain-level differences in carbohydrate metabolism of three probiotic bifidobacterial species. Int. J. Genom. 2015, 567809 (2015).
Google Scholar 

23.
Kolida, S. & Gibson, G. R. Synbiotics in health and disease. Ann. Rev. Food Sci. Technol. 2, 373–393 (2011).
Article  Google Scholar 

24.
Gurry, T. Synbiotic approaches to human health and well-being. Microb. Biotechnol. 10(5), 1070–1073 (2017).
Article  Google Scholar 

25.
Chua, M. C. et al. Effect of synbiotic on the gut microbiota of cesarean delivered infants: A randomized, double-blind, multicenter study. J. Pediatr. Gastroenterol. Nutr. 65(1), 102–106 (2017).
Article  Google Scholar 

26.
van Aa, L. B. et al. Effect of a new synbiotic mixture on atopic dermatitis in infants: A randomized-controlled trial. Clin. Exp. Allergy J. Br. Soc. Allergy Clin. Immunol. 40(5), 795–804 (2010).
Google Scholar 

27.
Ouwehand, A. C. A review of dose–responses of probiotics in human studies. Beneficial Microb. 8(2), 143–151 (2017).
CAS  Article  Google Scholar 

28.
Bakker-Zierikzee, A. M. et al. Effects of infant formula containing a mixture of galacto- and fructo-oligosaccharides or viable Bifidobacterium animalis on the intestinal microflora during the first 4 months of life. Br. J. Nutr. 94(5), 783–790 (2005).
CAS  Article  Google Scholar 

29.
Haarman, M. & Knol, J. Quantitative real-time PCR assays to identify and quantify fecal Bifidobacterium species in infants receiving a prebiotic infant formula. Appl. Environ. Microbiol. 71(5), 2318–2324 (2005).
CAS  Article  Google Scholar 

30.
Legendre, P., Oksanen, J. & ter Braak, C. J. F. Testing the significance of canonical axes in redundancy analysis. Methods Ecol. Evol. 2(3), 269–277. https://doi.org/10.1111/j.2041-210X.2010.00078.x (2011).
Article  Google Scholar 

31.
O’Callaghan, A. & van Sinderen, D. Bifidobacteria and their role as members of the human gut microbiota. Front. Microbiol. 7, 925 (2016).
Article  Google Scholar 

32.
Turroni, F., Ribbera, A., Foroni, E., van Sinderen, D. & Ventura, M. Human gut microbiota and bifidobacteria: From composition to functionality. Antonie Van Leeuwenhoek 94(1), 35–50 (2008).
Article  Google Scholar 

33.
Hidalgo-Cantabrana, C. et al. Bifidobacteria and their health-promoting effects. Microbiol. Spectrum. https://doi.org/10.1128/microbiolspec.BAD-0010-2016 (2017).
Article  Google Scholar 

34.
Underwood, M. A. et al. A comparison of two probiotic strains of bifidobacteria in premature infants. J. Pediatr. 163(6), 1585–1591.e1589 (2013).
CAS  Article  Google Scholar 

35.
Bridgman, S. L. et al. Fecal short-chain fatty acid variations by breastfeeding status in infants at 4 months: Differences in relative versus absolute concentrations. Front. Nutr. 4, 11. https://doi.org/10.3389/fnut.2017.00011 (2017).
CAS  Article  PubMed  PubMed Central  Google Scholar 

36.
Wopereis, H. et al. Intestinal microbiota in infants at high risk for allergy: Effects of prebiotics and role in eczema development. J. Allergy Clin. Immunol. 141(4), 1334–1342.e5 (2017).
Article  Google Scholar 

37.
Tunc, V. T., Camurdan, A. D., Ilhan, M. N., Sahin, F. & Beyazova, U. Factors associated with defecation patterns in 0–24-month-old children. Eur. J. Pediatr. 167(12), 1357–1362 (2008).
Article  Google Scholar 

38.
Infante, D. D., Segarra, O. O., Redecillas, S. S., Alvarez, M. M. & Miserachs, M. M. Modification of stool’s water content in constipated infants: management with an adapted infant formula. Nutr. J. 10, 55. https://doi.org/10.1186/1475-2891-10-55 (2011).
Article  PubMed  PubMed Central  Google Scholar 

39.
Valdes-Varela, L., Hernandez-Barranco, A. M., Ruas-Madiedo, P. & Gueimonde, M. Effect of Bifidobacterium upon Clostridium difficile growth and toxicity when co-cultured in different prebiotic substrates. Front. Microbiol. 7, 738 (2016).
CAS  PubMed  PubMed Central  Google Scholar 

40.
Sommer, F., Anderson, J. M., Bharti, R., Raes, J. & Rosenstiel, P. The resilience of the intestinal microbiota influences health and disease. Nat. Rev. Microbiol. 15(10), 630–638 (2017).
CAS  Article  Google Scholar 

41.
Baglatzi, L. et al. Effect of infant formula containing a low dose of the probiotic Bifidobacterium lactis CNCM I-3446 on immune and gut functions in c-section delivered babies: A pilot study. Clin. Med. Insights. Pediatr. 10, 11–19 (2016).
CAS  Article  Google Scholar  More

1.
IRENA. Global Energy Transformation: A Roadmap to 2050 (International Renewable Energy Agency, Abu Dhabi, 2018).
Google Scholar 
2.
Onakpoya, I. J., O’Sullivan, J., Thompson, M. J. & Heneghan, C. J. The effect of wind turbine noise on sleep and quality of life: A systematic review and meta-analysis of observational studies. Environ. Int. 82, 1–9 (2015).
Article  Google Scholar 

3.
Minderman, J., Pendlebury, C. J., Pearce-Higgins, J. W. & Park, K. J. Experimental evidence for the effect of small wind turbine proximity and operation on bird and bat activity. PLoS ONE 7, e41177 (2012).
ADS  CAS  Article  Google Scholar 

4.
Thaxter, C. B. et al. Bird and bat species’ global vulnerability to collision mortality at wind farms revealed through a trait-based assessment. IProc. R. Soc. B 284, 20170829 (2017).
Article  Google Scholar 

5.
Marques, A. T. et al. Understanding bird collisions at wind farms: An updated review on the causes and possible mitigation strategies. Biol. Conserv. 179, 40–52 (2014).
Article  Google Scholar 

6.
Frick, W. F. et al. Fatalities at wind turbines may threaten population viability of a migratory bat. Biol. Conserv. 209, 172–177 (2017).
Article  Google Scholar 

7.
Horn, J. W., Arnett, E. B. & Kunz, T. H. Behavioral responses of bats to operating wind turbines. J. Wildl. Manag. 72, 123–132 (2008).
Article  Google Scholar 

8.
Roeleke, M., Blohm, T., Kramer-Schadt, S., Yovel, Y. & Voigt, C. C. Habitat use of bats in relation to wind turbines revealed by GPS tracking. Sci. Rep. 6, 28961 (2016).
ADS  CAS  Article  Google Scholar 

9.
Cryan, P. M. et al. Behavior of bats at wind turbines. Proc. Natl. Acad. Sci. 111, 15126–15131 (2014).
ADS  CAS  Article  Google Scholar 

10.
Rydell, J. et al. Mortality of bats at wind turbines links to nocturnal insect migration?. Eur. J. Wildl. Res. 56, 823–827 (2010).
Article  Google Scholar 

11.
Millon, L., Colin, C., Brescia, F. & Kerbiriou, C. Wind turbines impact bat activity, leading to high losses of habitat use in a biodiversity hotspot. Ecol. Eng. 112, 51–54 (2018).
Article  Google Scholar 

12.
Minderman, J., Gillis, M. H., Daly, H. F. & Park, K. J. Landscape-scale effects of single-and multiple small wind turbines on bat activity. Anim. Conserv. 20(5), 455–462 (2017).
Article  Google Scholar 

13.
Lintott, P. R., Richardson, S. M., Hosken, D. J., Fensome, S. A. & Mathews, F. Ecological impact assessments fail to reduce risk of bat casualties at wind farms. Curr. Biol. 26, R1135–R1136 (2016).
CAS  Article  Google Scholar 

14.
Lintott, P. R. et al. Ecobat: An online resource to facilitate transparent, evidence-based interpretation of bat activity data. Ecol. Evol. 8, 935–941 (2018).
Article  Google Scholar 

15.
Rydell, J. et al. Bat mortality at wind turbines in northwestern Europe. Acta Chiropterologica 12, 261–274 (2010).
Article  Google Scholar 

16.
Barré, K., Le Viol, I., Bas, Y., Julliard, R. & Kerbiriou, C. Estimating habitat loss due to wind turbine avoidance by bats: Implications for European siting guidance. Biol. Conserv. 226, 205–214 (2018).
Article  Google Scholar 

17.
Verboom, B. & Huitema, H. The importance of linear landscape elements for the pipistrelle Pipistrellus pipistrellus and the serotine bat Eptesicus serotinus. Landscape Ecol. 12, 117–125 (1997).
Article  Google Scholar 

18.
Roemer, C., Disca, T., Coulon, A. & Bas, Y. Bat flight height monitored from wind masts predicts mortality risk at wind farms. Biol. Conserv. 215, 116–122 (2017).
Article  Google Scholar 

19.
Behr, O. et al. Mitigating bat mortality with turbine-specific curtailment algorithms: A model-based approach. In Wind Energy and Wildlife Interactions 135–160 (Springer, Cham, 2017).
Google Scholar 

20.
Natural England and the Department for Environment, Food & Rural Affairs. Bats: Survey and mitigation for development projects (accessed 12 May 2017, 2015) https://www.gov.uk/guidance/bats-surveys-and-mitigation-for-development-projects.

21.
Akerboom, S. et al. A comparison into the application of the EU species protection regulation with respect to renewable energy projects in the Netherlands, United Kingdom, Belgium, Denmark, and Germany. Eur. Energy Environ. Law Rev. 28(4), 144–158 (2019).
Google Scholar 

22.
Mathews, F., Richardson, S. M., Lintott, P. R. & Hosken, D. Understanding the risk to European protected species (bats) at onshore wind turbine sites to inform risk management. Department for Environment Food and Rural Affairs Science and Research Projects. WC00753 Final Report (Phase 2) (2016).

23.
Fenton, M., Jacobson, S. & Stone, R. An automatic ultrasonic sensing system for monitoring the activity of some bats. Can. J. Zool. 51, 291–299 (1973).
Article  Google Scholar 

24.
Russ, J. British Bat Calls: A Guide to Species Identification (Pelagic Publishing, Exeter, 2012).
Google Scholar 

25.
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2017). https://www.R-project.org/.

26.
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 

27.
Wickham, H. Ggplot2: Elegant Graphics for Data Analysis (Springer, New York, 2009).
Google Scholar 

28.
EUROBATS. Report of the Intersessional Working Group on Wind Turbines and Bat Populations. Doc.EUROBATS.StC9-AC19.12. Heraklion, Greece, 7–10th April 2014.

29.
Harrison, X. A. Using observation-level random effects to model overdispersion in count data in ecology and evolution. PeerJ 2, e616 (2014).
Article  Google Scholar 

30.
Morton, D., Rowland, C., Wood, C., Meek, L., Marston, C., Smith, G., Wadsworth, R. & Simpson, I. Final Report for LCM2007—The new UK land cover map. Countryside Survey Technical Report No 11/07 (2011).

31.
EDINA Digimap Ordnance Survey Service. OS MasterMap Topography Layer (accessed February 2015, 2015). http://edina.ac.uk/digimap. More

1.
Chapin, F. S., Folke, C. & Kofinas, G. P. A framework for understanding change. In Principles of Ecosystem Stewardship (eds Folke, C. et al.) (Springer, Berlin, 2009).
Google Scholar 
2.
Ellis, E. C. & Ramankutty, N. Putting people in the map: Anthropogenic biomes of the world. Front. Ecol. Environ. 6, 439–447 (2008).
Article  Google Scholar 

3.
Conover, M. R. Resolving Human–Wildlife Conflicts: The Science of Wildlife Damage Management (Lewis Publishers CRC Press, Boca Raton, 2002).
Google Scholar 

4.
Madhusudan, M. D. Living amidst large wildlife: Livestock and crop depredation by large mammals in the interior villages of Bhadra Tiger Reserve, South India. Environ. Manag. 31, 0466–0475 (2003).
CAS  Article  Google Scholar 

5.
Aryal, A., Brunton, D. H., Ji, W., Barraclough, R. K. & Raubenheimer, D. Human–carnivore conflict: Ecological and economical sustainability of predation on livestock by snow leopard and other carnivores in the Himalaya. Sustain. Sci. 9, 321–329 (2014).
Article  Google Scholar 

6.
Bhatnagar, Y. V., Wangchuk, R., Prins, H. H., Van Wieren, S. E. & Mishra, C. Perceived conflicts between pastoralism and conservation of the kiang Equus kiang in the Ladakh trans-Himalaya, India. Environ. Manag. 38, 934–941 (2006).
Article  Google Scholar 

7.
Hernández, F., Corcoran, D., Graells, G., Roos, C. & Downey, M. C. Rancher perspectives of a livestock-wildlife conflict in Southern Chile. Rangelands 39, 56–63 (2017).
Article  Google Scholar 

8.
Michalk, D. L. et al. Sustainability and future food security—A global perspective for livestock production. Land Degrad. Dev. 30, 561–573 (2019).
Article  Google Scholar 

9.
Hilker, T., Natsagdorj, E., Waring, R. H., Lyapustin, A. & Wang, Y. Satellite observed widespread decline in Mongolian grasslands largely due to overgrazing. Glob. Change Biol. 20, 418–428 (2014).
ADS  Article  Google Scholar 

10.
Zheng, Z., Feng, C., Ye, S., Diao, Z. & Lü, S. Ecological pressures on grassland ecosystems and their conservation strategies in Northern China. Chin. J. Popul. Resourc. Environ. 13, 87–91 (2015).
Article  Google Scholar 

11.
Wen, L. et al. Effect of degradation intensity on grassland ecosystem services in the alpine region of Qinghai-Tibetan Plateau, China. PLoS ONE 8, e58432 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

12.
Krausman, P. R. et al. Livestock grazing, wildlife habitat, and rangeland values. Rangelands 31, 15–19 (2009).
Article  Google Scholar 

13.
Bestelmeyer, B. T., Estell, R. E. & Havstad, K. M. Big questions emerging from a century of rangeland science and management. Rangel. Ecol. Manag. 65, 543–544 (2012).
Article  Google Scholar 

14.
Galt, D., Molinar, F., Navarro, J., Joseph, J. & Holechek, J. L. Grazing capacity and stocking rate. Rangel. Arch. 22, 7–11 (2000).
Google Scholar 

15.
Hobbs, N. T. & Swift, D. M. Estimates of habitat carrying capacity incorporating explicit nutritional constraints. J. Wildl. Manag. 49, 814–822 (1985).
Article  Google Scholar 

16.
Vallentine, J. F. Grazing Management 2nd edn. (Academic Press, New York, 2001).
Google Scholar 

17.
Mckeon, G. M. et al. Climate change impacts on northern Australian rangeland livestock carrying capacity: A review of issues. Rangel. J. 31, 1–29 (2009).
Article  Google Scholar 

18.
Yu, L., Zhou, L., Liu, W. & Zhou, H. Using remote sensing and GIS technologies to estimate grass yield and livestock carrying capacity of alpine grasslands in Golog Prefecture, China. Pedosphere 20, 342–351 (2010).
Article  Google Scholar 

19.
Chen, J. Review of canceling herds and returning to grassland policy in Sanjiangyuan Region in Qinghai Province: Based on survey of Maduo County. Natl. Res. Qinghai 19, 110–115 (2008).
Google Scholar 

20.
Qin, D. Ecological Protection and Sustainable Development of Three-River-Source Area (Science Press, London, 2014).
Google Scholar 

21.
Zhao, L., Li, Q. & Zhao, X. Multi-functionality and management of grassland in the Sanjiangyuan region. Resour. Sci. 42, 78–86 (2020).
Google Scholar 

22.
Olson, D. M. & Dinerstein, E. The Global 200: A representation approach to conserving the Earth’s most biologically valuable ecoregions. Conserv. Biol. 12, 502–515 (1998).
Article  Google Scholar 

23.
Li, J. et al. Global priority conservation areas in the face of 21st century climate change. PLoS ONE 8, 54839 (2013).
ADS  Article  CAS  Google Scholar 

24.
Zhou, H., Zhou, L., Liu, W., Zhao, X. & Lai, D. Causes of grassland degradation and sustainable development of animal husbandry in Maduo County, Qinghai Province. Grassl. China 25, 63–67 (2003).
Google Scholar 

25.
Xu, J., Chen, J., Hu, Y. & Zhao, Z. Research on the status and the dynamic of grassland degradation in Maduo County Qinghai Province. Pratacult. Sci. 28, 359–364 (2011).
Google Scholar 

26.
NDRCC. Three-River-Source National Park Master Plan. https://www.ndrc.gov.cn/xxgk/zcfb/ghwb/201801/t20180117_962245.html. (National Development and Reform Commission of China, 2018).

27.
Fu, M. et al. Functional zoning and space management of three-river-source national park. J. Geog. Sci. 29, 2069–2084 (2019).
Article  Google Scholar 

28.
Sun, J. et al. Reconsidering the efficiency of grazing exclusion using fences on the Tibetan Plateau. Sci. Bull. 65, 1405–1414 (2020).
Article  Google Scholar 

29.
Tuanmu, M. et al. Effects of payments for ecosystem services on wildlife habitat recovery. Conserv. Biol. 30, 827–835 (2016).
PubMed  Article  PubMed Central  Google Scholar 

30.
Watzold, F. & Drechsler, M. Spatially uniform versus spatially heterogeneous compensation payments for biodiversity-enhancing land-use measures. Environ. Resour. Econ. 31, 73–93 (2005).
Article  Google Scholar 

31.
Hu, Z., Kong, D. & Jin, L. Grassland eco-compensation: Rate differentiations of “reward for balanced grazing” and its reasons. China Popul. Resour. Environ. 25, 152–159 (2015).
Google Scholar 

32.
Lu, C., Xie, G. & Xiao, Y. Ecological Compensation and the cost of wildlife conservation: Chang Tang Grasslands, Tibet. J. Resour. Ecol. 3, 20–25 (2012).
Article  Google Scholar 

33.
Sitters, J. et al. Herded cattle and wild grazers partition water but share forage resources during dry years in East African savannas. Biol. Cons. 142, 738–750 (2009).
Article  Google Scholar 

34.
Stokely, T. D. & Betts, M. G. Deer-mediated ecosystem service versus disservice depends on forest management intensity. J. Appl. Ecol. 57, 31–42 (2019).
Article  Google Scholar 

35.
Östman, Ö. et al. Estimating competition between wildlife and humans—a case of cormorants and coastal fisheries in the Baltic Sea. PLoS ONE 8, e83763 (2013).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

36.
Guerra, A. S. Wolves of the Sea: Managing human-wildlife conflict in an increasingly tense ocean. Marine Policy 99, 369–373 (2018).
Article  Google Scholar 

37.
Xin, Y. et al. The evaluation of carrying capacity of grassland in Qinghai. Qinghai Pratacult. 20, 13–22 (2011).
Google Scholar 

38.
Du, J., Wang, G. & Li, Y. Rate and causes of degradation of alpine grassland in the source regions of the Yangtze and Yellow River during the last 45 years. Acta Pratacult. Sin. 24, 5–15 (2015).
Google Scholar 

39.
Yu, L. et al. Using remote sensing and GIS technologies to estimate grass yield and livestock carrying capacity of alpine grasslands in Golog Prefecture, China. Pedosphere 20, 342–351 (2010).
Article  Google Scholar 

40.
Lü, X. et al. Spatio-temporal changes of grassland production based on MODIS NPP in the Three-River Source Region from 2006 to 2015. J. Nat. Resour. 32, 1857–1868 (2017).
Google Scholar 

41.
Knapp, A. K. et al. Resolving the Dust Bowl paradox of grassland responses to extreme drought. Proc. Natl. Acad. Sci. 117, 22249–22255 (2020).
CAS  PubMed  Article  PubMed Central  Google Scholar 

42.
Wu, X. et al. Predicting the shift of threatened ungulates’ habitats with climate change in Altun Mountain National Nature Reserve of the Northwestern Qinghai-Tibetan Plateau. Clim. Change 142, 331–344 (2017).
Article  Google Scholar 

43.
Maduo County Local Records Compilation Committee. Maduo County Local Record (Qinghai Ethnic Publishing House, Qinghai, 2011).
Google Scholar 

44.
Kondoh, H., Koizumi, T. & Ikeda, K. A geostatistical approach to spatial density distributions of sika deer (Cervus nippon). J. For. Res. 18, 93–100 (2013).
Article  Google Scholar 

45.
Norris, D. et al. How to not inflate population estimates? Spatial density distribution of white-lipped peccaries in a continuous Atlantic forest. Anim. Conserv. 14, 492–501 (2011).
Article  Google Scholar 

46.
Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259 (2006).
Article  Google Scholar 

47.
Field, C. B., Randerson, J. T. & Malmström, C. M. Global net primary production: Combining ecology and remote sensing. Remote Sens. Environ. 51, 74–88 (1995).
ADS  Article  Google Scholar 

48.
Ali, I., Cawkwell, F., Dwyer, E., Barrett, B. & Green, S. Satellite remote sensing of grasslands: From observation to management. J. Plant Ecol. 9, 649–671 (2016).
Article  Google Scholar 

49.
Chen, A. et al. Moisture availability mediates the relationship between terrestrial gross primary production and solar-induced chlorophyll fluorescence: Insights from global-scale variations. Glob. Change Biol. 2, 15373 (2020).
Article  Google Scholar 

50.
Department of Animal Husbandry. Calculation of reasonable rangeland carrying capacity of natural grassland (NY/T635–2015). (Ministry of Agriculture and Rural Affairs of the People’s Republic of China, 2015).

51.
Zhao, F., Lin, G. & Zhao, Z. The analysis of relationship between grassland and livestock based on MODIS vegetation index in Madoi in Qinghai. Heilongjiang Anim. Sci. Vet. Med. 1, 75–77 (2012).
Google Scholar 

52.
Yang, L. et al. Tick-defense grooming patterns of two sympatric Tibetan ungulates. J. Zool. 307, 242–248 (2019).
Article  Google Scholar  More

1.
Giller, K. E. et al. N2 Africa: Putting nitrogen fixation to work for smallholder farmers in Africa. In Agrological Intensification of Agricultural Systems in the African Highlands (eds Vanlauwe, B. et al.) 156–174 (Routledge, London, 2013).
Google Scholar 
2.
Goss, M. J., de Varennes, A., Smith, P. S. & Ferguson, J. A. Nitrogen fixation by soybean grown with different levels of mineral nitrogen and fertilizer replacement value for a following crop. Can. J. So. Sci. 82, 139–145 (2002).
Article  Google Scholar 

3.
Abdul-Aziz, A.L. Contribution of rhizobium and phosphorus fertilizer to biological nitrogen fixation and grain yield of soybean in the Tolon District. A Thesis Submitted to the Department of Crop and Soil Sciences, Faculty of Agriculture, Kwame Nkrumah University of Science and Technology, Kumasi, in partial fulfillment of the requirement of the degree of Master of Science in soil science (2013).

4.
Argaw, S. Evaluation of co-inoculation of Bradyrhizobium japonicum and phosphate solubilizing Pseudomonas spp. effect on soybean (Glycine max L. (Merri)) in Assossa area. J. Agric. Sci. Tech. 14, 213–224 (2012).
CAS  Google Scholar 

5.
Keneni, G. et al. Phenotypic diversity for symbio-agronomic characters in Ethiopia chickpea (Cicer arietinum L.) germplasm accessions. Afr. J. Biotechnol. 11(63), 12634–12651 (2012).
Google Scholar 

6.
Ouma, E. W., Asango, A. M., Maingi, J. & Njeru, M. Elucidating the potential of native rhizobial isolates to improve biological nitrogen fixation and growth of common bean and soybean in smallholder farming systems of Kenya. Int. J. Agron. 2016, 1–7 (2016).
Article  CAS  Google Scholar 

7.
Stajković, O. et al. Improvement of common bean growth by co-inoculation with Rhizobium and plant growth-promoting bacteria. Rom. Biotech. Lett. 16, 5919–5926 (2011).
Google Scholar 

8.
Chen, Y. X. et al. Faba bean (Vicia faba L.) nodulating rhizobia in Panxi, China, are diverse at species, plant growth promoting ability, and symbiosis related gene levels. Front. Microbiol. 9, 1–10 (2018).
Article  Google Scholar 

9.
Saἲdi, S., Chebil, S., Gtari, M. & Mhamdi, R. Characterization of root-nodule bacteria isolated from vicia faba and selection of plant growth promoting isolates. World J. Microbiol. Biotechnol. 29, 1099–1106 (2013).
Article  CAS  Google Scholar 

10.
Workalemahu, W. The effect of indigenous toot nodulating bacteria on nodulation and growth of faba bean (Vicia faba L.) in the low-input agricultural systems of Tigray highlands, northern Ethiopia. Momona Ethiop. J. Sci. 1(2), 30–43 (2009).
Article  Google Scholar 

11.
Sánchez-Cañizares, C. et al. Genomic diversity in the endosymbiotic bacterium Rhizobium leguminosarum. Genes. 9(60), 1–26 (2018).
Google Scholar 

12.
Laguerre, G., Louvrier, P., Allard, M. R. & Amarger, N. Compatibility of rhizobial genotypes within natural populations of Rhizobium leguminosarum biovar viciae for nodulation of host-legumes. Appl. Environ. Microbiol. 69(4), 2276–2283 (2003).
CAS  PubMed  PubMed Central  Article  Google Scholar 

13.
Sachs, J. L., Kembel, S. W., Lau, A. M. & Simms, E. L. In situphylogenetic structure and diversity of wild Bradyrhizobium communities. Appl. Environ. Microbiol. 75, 4727–4735 (2009).
CAS  PubMed  PubMed Central  Article  Google Scholar 

14.
Laguerre, G., Depret, G., Bourion, V. & Duc, G. Rhizobium leguminosarumbv. viciae genotypes interact with pea plants in developmental responses of nodules, roots and shoots. New Phytol. 176, 680–690 (2007).
PubMed  Article  Google Scholar 

15.
McKenzie, R. H. et al. Response of peat or rhizobia inoculation and start nitrogen in Alberta. Can. J. Plant Sci. 81, 637–643 (2001).
Article  Google Scholar 

16.
Siczek, A. & Lipiec, J. Impact of faba bean-seed rhizobial inoculation on microbial activity in the rhizosphere soil during growing season. Int. J. Mol. Sci. 17(784), 1–9 (2016).
Google Scholar 

17.
Downie, J. A. The roles of extracellular proteins, polysaccharides and signals in the interactions of rhizobia with legume roots. FEMS Microbiol. Rev. 34, 150–170 (2010).
CAS  PubMed  Article  Google Scholar 

18.
Fujita, H., Aoki, S. & Kawaguchi, M. Evolutionary dynamics of nitrogen fixation in the legume-rhizobia symbiosis. PLoS ONE 9, e93670 (2014).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

19.
Beltayef, H. et al. Statement of biological nitrogen fixation in snap bean under Mediterranean semi-arid conditions. Bulgarian J. of Agri. Sci. 24(2), 244–251 (2018).
Google Scholar 

20.
Pitkäjärvi, J. et al. Persistence, population dynamics and competitiveness for nodulation of marker gene tagged Rhizobium galegaestrains in field lysimeters in the Boreal climatic zone. FEMS Microbiol. Ecol. 2, 2 (2003).
Google Scholar 

21.
Bouyoucos, G. J. Hydrometer method improvement for making particle size analysis of soils. Agron. J. 54, 179–186 (1962).
Google Scholar 

22.
Black, G. R. & Hertge, K. H. Bulk density. In methods of soil analysis (ed. Klute, A.) 377–382 (SSSA, Madison, Wiscosin, 1986).
Google Scholar 

23.
Carter, M. R. & Gregorich, E. G. Soil Sampling and Methods of Analysis 2nd edn. (Canadian Soil Science Society, Boca Raton, 2008).
Google Scholar 

24.
Mclean, E. O. Aluminum. In Methods of Soil Analysis, Part 2 chemical methods (ed. Black, C. A.) 978–998 (America Sci. Agron, Madison, 1965).
Google Scholar 

25.
van Reeuwijk, L. P. Procedures for Soil Analysis 6th edn. (Technical Paper/International Soil Reference and Information Center, Wageningen, 2002).
Google Scholar 

26.
Jońca, Z. & Lewandowski, W. Verification of measurement capabilities of flame atomic spectrometry for the determination of sodium, potassium, magnesium, and calcium in natural fresh water part I. Comparison of recommended methods. Polish J. Environ. Studies 13(3), 275–280 (2004).
Google Scholar 

27.
Walkley, A. & Black, I. A. An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci. 37, 29–38 (1934).
ADS  CAS  Article  Google Scholar 

28.
Bremner, J. M. & Mulvaney, C. S. Nitrogen total in methods of soil analysis. In Chemical and Microbiological Properties (ed. Page, A. L.) (SSSA, Wiscosin, 1982).
Google Scholar 

29.
Olsen, S. R., Cole, C. V., Watanabe, F. S. & Dean, L. A. Estimation of available phosphorous in soils by extraction with sodium bicarbonate. USDA Circ. 939, 1–19 (1954).
Google Scholar 

30.
Vincent, J. M. A manual for the Practical Study of Root-Nodule Bacteria. IBP Handbook No 15 (Blackwell Scientific Publications Ltd, Oxford, 1970).
Google Scholar 

31.
Woomer, P., Bennett, J. & Yost, R. Overcoming inflexibilities in most-probable-number-procedures. Agron. J. 82, 349–353 (1990).
Article  Google Scholar 

32.
Somasegaran, P. & Hoben, H. J. Handbook for Rhizobia: Methods in Legume-Rhizobium Technology (Springer Verlag, New York, 1994).
Google Scholar 

33.
Broughton, W. J. & Diworth, M. J. Control of leghemoglobin synthesis in snake beans. Biochem. J. 125, 1075–1080 (1971).
CAS  PubMed  PubMed Central  Article  Google Scholar 

34.
Guene, N. F. D., Diouf, A. & Gueye, M. Nodulation and nitrogen fixation of field grown common bean (Phaseolus vulgaris) as influenced by fungicide seed treatment. Afr. J. Biotechnol. 2(7), 198–201 (2003).
CAS  Article  Google Scholar 

35.
Ondieki, D. K., Nyaboga, E. N., Wagacha, J. M. & Mwaura, F. B. Morphological and genetic diversity of rhizobia nodulating cowpea (Vigna unguiculata L.) from agricultural soils of Lower Eastern Kenya. Int. J. Microbiol. 2017, 1–9 (2017).
Article  CAS  Google Scholar 

36.
Rice, W. A., Clyton, G. W., Lupwayi, N. Z. & Olsen, P. E. Evaluation of coated seeds as a Rhizobium delivery system for field pea. Can. J. Plant Sci. 81(1), 248–249 (2001).
Google Scholar 

37.
Beets, P. N., Pearce, S. H., Oliver, G. R. & Clinton, P. W. Root to shoot rations for deriving below-ground biomass of Pinus radiate standards. New Zealand J. Forestry Sci. 37(2), 267–288 (2007).
Google Scholar 

38.
SAS. SAS/STAT Software Syntax, Version 9.0. SAS Institute, Cary, NC. USA(2010).

39.
Raposeiras, R. et al. Rhizobium strains competitiveness on bean nodulation in Cerrado soils. Brasilia 41, 439–447 (2006).
Google Scholar 

40.
Ulzen, J. Optimizing legume-rhizobia symbiosis to enhance legume grain yield in smallholder farming system in Ghana. A thesis submitted to the Department of Crop and Soil Sciences, Faculty of Agriculture, Kwame Nkrumah University Science and Technology, Kumasi, in partial fulfillment of the requirements of the degree of doctor of philosophy in soil science(2018).

41.
Zengeni, R., Mpepereki, S. & Giller, K. E. Manure and soil properties affect survival and persistence of soybean nodulation rhizobia in smallholder soils of Zimbabwe. Agric. Ecosyst. Environ. Appl. Soil Eco. 32, 232–242 (2006).
Article  Google Scholar 

42.
Jida, M. & Assefa, F. Phenotypic diversity and plant growth promoting characteristics of Mesorhizobium species isolated from faba bean (Vicia faba L.) growing areas of Ethiopia. Afr. J. Biotechnol. 11, 7483–7493 (2012).
CAS  Google Scholar 

43.
Kawaletz, H., Molder, I., Terwei, P. A. A. & Ammer, S. Z. C. Pot experiments with woody species. A review. Forestry 87, 4 (2014).
Article  Google Scholar 

44.
Farid, M. & Navabi, A. N2 fixation ability of different dry bean genotypes. Can. J. Plant Sci. 95, 1243–1257 (2015).
CAS  Article  Google Scholar 

45.
Nkot, L. N. et al. Abundance of legume nodulating bacteria in soils of diverse land use systems in Cameroon. Univ. J. Plant Sci. 3(5), 97–108 (2015).
Article  Google Scholar 

46.
Solomon, T., Pant, L.M. & Angaw, T. Effects of inoculation by Bradyrhizobium japonicum strains on nodulation, nitrogen fixation, and yield of soybean (Glycine max L. Merill) varieties on Nitosols of Bako, western Ethiopia. International Scholarly Research Network ISRN Agron. 2012, Article ID 261475, Pp. 1–8 (2012).

47.
Adamu, A., Hailemariam, A., Assefa, F. & Bekele, E. Studies of Rhizobium inoculation and fertilizer treatment on growth and production of faba bean (Vicia faba L.) in some yield-depleted and yield-sustained regions of Semen Shoa. Ethiopia J. of Sci. 24, 197–211 (2001).
Google Scholar 

48.
Mohammadi, K., Sohrabi, Y., Heidari, G., Khalesro, S. & Majidi, M. Effective factors on biological nitrogen fixation. Afr. J. Agric. Res. 7, 1782–1788 (2012).
Google Scholar 

49.
Raven, J. A. Protein turnover and plant RNA and phosphorus requirement in relation to nitrogen fixation. Plant Sci. 189, 25–35 (2012).
Article  CAS  Google Scholar 

50.
Bello, S. K., Yusuf, A. A. & Cargele, M. Performance of cowpea as influenced by native strain of rhizobia, lime and phosphorus in Samaru, Nigeria. Symbiosis 75, 167–176 (2018).
CAS  PubMed  Article  Google Scholar 

51.
Talaat, N. B. & Abdallah, A. M. Response of faba bean (Vicia faba L.) to dual inoculation with Rhizobium and VA mycorrhiza under different levels of N and P fertilization. J. Appl. Sci. Res. 4, 1092–1102 (2008).
CAS  Google Scholar 

52.
Yoseph, T. & Worku, W. Effect of NP fertilizer rate and Bradyrhizobium inoculation on nodulation, N-uptake and crude protein content of soybean (Glycine Max (L) Merrill), at Jinka. Southern Ethiopia. J. Biol. Agric. Healthcare 4(6), 49–54 (2014).
Google Scholar 

53.
Hungria, M., Campo, R. J. & Mendes, I. C. Benefits of inoculation of the common bean (Phaseolus vulgaris) crop with efficient and competitive Rhizobium tropici strains. Biol. Fertl. Soils 39, 51–61 (2003).
Article  CAS  Google Scholar 

54.
Kellman, A.W. Rhizobium inoculation, cultivar and management effects on the growth, development and yield of common bean (Phaseolus vulgaris L.). A PhD thesis, Lincoln University, New Zealand(2008).

55.
Voisin, A. S., Salon, C. & Warembourg, F. R. Seasonal patterns of 13C partitioning between shoot and nodulated roots of N2-or nitrate fed- Pisum sativum (L). Ann. Bot. 91, 539–546 (2003).
CAS  PubMed  PubMed Central  Article  Google Scholar 

56.
Graham, P. H., Hungria, M. & Tlusty, B. Breeding for better nitrogen fixation in grain legumes: Where do the rhizobia fit in?. Crop Manag https://doi.org/10.1094/CM-2004-0301-02-RV (2004).
Article  Google Scholar 

57.
Minalku, A., Gebrekidan, H. & Assefa, F. Symbiotic effectiveness and characterization of Rhizobium strains of faba bean (Vicia faba L.) collected from eastern and western Hararghe highlands of Ethiopia. Ethiopian J. Nat. Resour 11(2), 223–244 (2009).
Google Scholar 

58.
Sindhu, S., Dua, S., Verma, M. K. & Khandewal, A. Growth promotion of legumes by inoculation of rhizosphere bacteria. In Microbes for Legume Improvement (eds Khan, M. S. et al.) (Springer-Verlag, Wien, 2010).
Google Scholar 

59.
Hemissi, I. et al. Effects of some Rhizobium strains on chickpea growth and biological control of Rhizoctonia solani. Afr. J. Micro. Res. 5(25), 4080–4090 (2011).
CAS  Google Scholar 

60.
Zahran, H. H. Rhizobia from Wild legumes: Diversity, taxonomy, ecology, nitrogen fixation and biotechnology. J. Biotechnol. 91, 143–153 (2001).
CAS  PubMed  Article  PubMed Central  Google Scholar 

61.
Zahir, Z. A., Arshad, M. & Frankenberger, J. R. Plant growth promoting Rhizobacteria: Applications and perspectives in agriculture. J. Adv. Agron. 81, 97–16 (2004).
CAS  Article  Google Scholar 

62.
Thilakarathna, M. S. et al. Evaluating the effectiveness of Rhizobium inoculants and micronutrients as technologies for Nepalese common bean smallholder farmers in the real-world context of highly variable hillside environments and indigenous farming practices. Agriculture 9(20), 1–17 (2019).
Google Scholar 

63.
Tena, W., Wolde-Meskel, E. & Walley, F. Symbiotic efficiency of native and exotic Rhizobium strains nodulating lentil (Lens culinaris Medik) in soils of southern Ethiopia. Agronomy 6, 1–11 (2016).
Article  CAS  Google Scholar 

64.
Cakmakci, R., Donmez, M. F. & Erdogan, U. The effect of plant growth promoting rhizobacteria on barley seedling growth, nutrient uptake, some soil properties, and bacterial counts. Turk. J. Agr. For. 31, 189–199 (2007).
CAS  Google Scholar 

65.
Kyei-Boahen, S., Giroux, C. & Walley, F. L. Fall vs Springrhizobial inoculation of chickpea. Can. J. Plant Sci. 85, 893–896 (2005).
Article  Google Scholar 

66.
Oğutcu, H., Algur, O. F., Elkoca, E. & Kantar, F. The determination of symbiotic effectiveness of Rhizobium strains isolated from wild chickpeas collected from high altitudes in Erzurum. Turkey J. Agric. Forestry 32, 241–248 (2008).
Google Scholar 

67.
Korir, H., Mungai, N. W., Thuita, M., Hamba, Y. & Masso, G. Co-inoculation effect of rhizobia and plant growth promoting rhizobacteria on common bean growth in a low phosphorus soil. Front. Plant Sci. 8, 141 (2017).
PubMed  PubMed Central  Article  Google Scholar 

68.
van de Werf, A. & Negal, O. S. Carbon allocation to shoots and roots in relation to nitrogen supply is mediated by cytokinins and sucrose: Opinion. Plant Soil 185, 21–32 (1996).
Article  Google Scholar 

69.
Koevoets, I. T., Venema, J. H., Elzegna, J. T. M. & Testerink, C. Roots withstanding their environment: Exploiting root system architecture responses to abiotic stress to improve crop tolerance. Front. Plant Sci. 7, 1335 (2016).
PubMed  PubMed Central  Article  Google Scholar 

70.
Ferreira, P. A. A., Bomfeti, C. A., Soares, B. L. & Moreira, F. M. S. Efficient nitrogen-fixing Rhizobium strains isolated from Amazonian soils are highly tolerant to acidity and aluminum. World J. Microbiol. Biotechnol. 28(5), 1947–1959 (2012).
Article  CAS  Google Scholar 

71.
Kawaka, F., Dida, M.M., Peter, A., Opala, P.A., Ombori, O., Maingi, J., Osoro, N., Muthini, M., Amoding, A., Mukaminega, D. & Muoma, J. Symbiotic efficiency of native rhizobia nodulating common bean (Phaseolus vulgaris L.) in soils of western Kenya. International Scholarly Research Notices (2014).

72.
Guo, Y. J., Ni, Y. & Huang, J. G. Effects of Rhizobium, arbuscular mycorrhiza and lime on nodulation, growth and nutrient uptake of lucerne in acid purplish soil in China. Trop. Grassl. 44, 109–114 (2010).
Google Scholar 

73.
Gicharu, G. K., Gitonga, N. M., Boga, H., Cheruiyot, R. C. & Maingi, J. M. Effect of inoculating selected climbing bean cultivars with different rhizobia strains on nitrogen fixation. Int. J. Microbiol. Res. 1(2), 25–31 (2013).
Google Scholar 

74.
Mothapo, N. V. et al. Cropping history affects nodulation and symbiotic efficiency of distinct hairy vetch (Vicia villosa Roth) genotypes with resident soil rhizobia. Biol. Fertil. Soils. 49(7), 871–879 (2013).
Article  Google Scholar 

75.
Oono, R. & Denison, R. F. Comparing symbiotic efficiency between swollen versus non-swollen RhizobialBacteriods. Plant Physiol. 154, 1541–1548 (2010).
CAS  PubMed  PubMed Central  Article  Google Scholar 

76.
Sharma, S., Upadhyay, R. G. & Sharma, C. R. Effect of Rhizobium inoculation and nitrogen on growth, dry matter accumulation and yield of black gram (Vigna mungo). Legume Res. 23(1), 64–66 (2000).
Google Scholar 

77.
Kantar, F., Elkoca, E., Ögütcü, H. & Algur, Ö. F. Chickpea yields in relation to Rhizobium inoculation from wild chickpea at high altitudes. J. Agron. Crop Sci. 189, 291–297 (2003).
Article  Google Scholar  More

1.
Anker, J. C. H. et al. Distance to pig farms as risk factor for community-onset livestock-associated MRSA CC398 infection in persons without known contact to pig farms: a nationwide study. Zoonoses Public Health 65, 352–360 (2018).
CAS  PubMed  PubMed Central  Article  Google Scholar 
2.
Broens, E. M., Graat, E. A. M., Van Der Wolf, P. J., Van De Giessen, A. W. & De Jong, M. C. M. Prevalence and risk factor analysis of livestock associated MRSA-positive pig herds in The Netherlands. Prev. Vet. Med. 102, 41–49 (2011).
CAS  PubMed  Article  PubMed Central  Google Scholar 

3.
Sørensen, A. I. V. Spread and control of livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) in Danish pig herds. PhD Thesis, March 2018 Anna Irene Vedel Sørensen. (2018).

4.
Danish Veterinary and Food Administration. Results of screening for livestock-associated MRSA in pigs in 2016. Fødevarestyrelsen. www.foedevarestyrelsen.dk/Nyheder/Aktuelt/Documents/MRSA%20ekspertgruppe%20-%20resultatene%20forekomst%20af%20husdyr-MRSA%20i%20svin%202016.pdf (2017).

5.
Schulz, J., Boklund, A., Toft, N. & Halasa, T. Drivers for livestock-associated methicillin-resistant staphylococcus aureus spread among Danish pig herds: a simulation study. Sci. Rep. 8, 1–11 (2018).
Article  CAS  Google Scholar 

6.
Borck Høg, B. et al. DANMAP 2016: use of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from food animals, food and humans in Denmark. Statens Serum Institut, National Veterinary Institute, Technical University of Denmark National Food Institute, Technical University of Denmark (2017).

7.
Borck Høg, B. et al. DANMAP 2017: use of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from food animals, food and humans in Denmark. Statens Serum Institut, National Veterinary Institute, Technical University of Denmark National Food Institute, Technical University of Denmark (2018).

8.
Larsen, J. et al. Emergence of livestock-associated methicillin-resistant staphylococcus aureus bloodstream infections in Denmark. Clin. Infect. Dis. 65, 1072–1076 (2017).
PubMed  PubMed Central  Article  Google Scholar 

9.
Gibbs, S. G., Green, C. F., Tarwater, P. M. & Scarpino, P. V. Airborne antibiotic resistant and nonresistant bacteria and fungi recovered from two swine herd confined animal feeding operations. J. Occup. Environ. Hyg. 1, 699–706 (2004).
PubMed  Article  PubMed Central  Google Scholar 

10.
Scarpino, P. V. & Quinn, H. Bioaerosol distribution patterns adjacent to two swine-growing-finishing housed confinement units in the American Midwest. J. Aerosol Sci. 29, 553–554 (1998).
ADS  Article  Google Scholar 

11.
Baldacchino, F., Muenworn, V., Desquesnes, M., Desoli, F. & Charoenviriyaphap, T. Transmission of pathogens by Stomoxys flies (Diptera, Muscidae): a review. Parasite 20, 26 (2013).
PubMed  PubMed Central  Article  Google Scholar 

12.
Nayduch, D. & Burrus, R. G. Flourishing in filth: house fly-microbe interactions across life history. Ann. Entomol. Soc. Am. 110, 6–18 (2017).
CAS  Article  Google Scholar 

13.
Bahrndorff, S., De Jonge, N., Skovgård, H. & Nielsen, J. L. Bacterial communities associated with houseflies (Musca domestica L.) sampled within and between farms. PLoS ONE 12, 1–15 (2017).
Article  CAS  Google Scholar 

14.
Park, R. et al. Microbial communities of the house fly Musca domestica vary with geographical location and habitat. Microbiome 7, 1–12 (2019).
CAS  Article  Google Scholar 

15.
Forsey, T. & Darougar, S. Transmission of chlamydiae by the housefly. Br. J. Ophthalmol. 65, 147–150 (1981).
CAS  PubMed  PubMed Central  Article  Google Scholar 

16.
Skovgård, H., Kristensen, K. & Hald, B. Retention of Campylobacter (Campylobacterales: Campylobacteraceae) in the house fly (Diptera: Muscidae). J. Med. Entomol. 48, 1202–1209 (2011).
PubMed  Article  Google Scholar 

17.
Mellor, P. S., Kitching, R. P. & Wilkinson, P. J. Mechanical transmission of capripox virus and African swine fever virus by Stomoxys calcitrans. Res. Vet. Sci. 43, 109–112 (1987).
CAS  PubMed  Article  PubMed Central  Google Scholar 

18.
Nayduch, D., Cho, H. & Joyner, C. Staphylococcus aureus in the house fly: temporospatial fate of bacteria and expression of the antimicrobial peptide defensin. J. Med. Entomol. 50, 171–178 (2013).
PubMed  PubMed Central  Article  Google Scholar 

19.
Espinosa-Gongora, C., Dahl, J., Elvstrøm, A., van Wamel, W. J. & Guardabassi, L. Individual predisposition to Staphylococcus aureus colonization in pigs on the basis of quantification, carriage dynamics, and serological profiles. Appl. Environ. Microbiol. 81, 1251–1256 (2015).
CAS  PubMed  PubMed Central  Article  Google Scholar 

20.
Friesen, K., Berkebile, D. R., Zhu, J. J. & Taylor, D. B. Laboratory rearing of stable flies and other Muscoid Diptera. J. Vis. Exp. 138, 1–7 (2018)
Google Scholar 

21.
Liu, C. M. et al. Staphylococcus aureus and the ecology of the nasal microbiome. Sci. Adv. 1, 5 (2015).
Google Scholar 

22.
Beresford, D. V. & Sutcliffe, J. F. Local infestation or long-distance migration? The seasonal recolonization of dairy farms by Stomoxys calcitrans (Diptera: Muscidae) in South Central Ontario, Canada. J. Econ. Entomol. 102, 788–798 (2009).
CAS  PubMed  Article  Google Scholar 

23.
Bailey, D. L., Whitfield, T. L. & Smittle, B. J. Flight and dispersal of the stable fly. J. Econ. Entomol. 66, 410–411 (1973).
Article  Google Scholar 

24.
Hogsette, J. A. & Ruff, J. P. Stable fly (Diptera: Muscidae) migration in northwest Florida. Environ. Entomol. 14, 170–175 (1985).
Article  Google Scholar 

25.
SPF-system. Landbrug and Fødevarer: Sundhedsstyringen. http://spfsus.dk/en (2020).

26.
Hansen, J. E. et al. LA-MRSA CC398 in dairy cattle and veal calf farms indicates spillover from pig production. Front. Microbiol. 10, 2733 (2019).
PubMed  PubMed Central  Article  Google Scholar 

27.
Singhal, N., Kumar, M., Kanaujia, P. K. & Virdi, J. S. MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Front. Microbiol. 6, 1–16 (2015).
Article  Google Scholar 

28.
IBM Corp. IBM SPSS Statistics for Windows v 25.0. Armonk, NY: IBM Corp. (2017).

29.
Clopper, C. J. & Pearson, E. S. The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 26, 404 (1934).
MATH  Article  Google Scholar 

30.
Therneau, T. A Package for Survival Analysis in R. R package version 3. 1–11. https://cran.r-project.org/package=survival. (2020).

31.
Therneau, T. M. & Grambsch, P. M. Modeling Survival Data: Extending the Cox Model (Springer, New York, 2000).
Google Scholar 

32.
R Core Team. R: A language and environment for statistical computing. https://www.r-project.org/ (2020).

33.
Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Article  Google Scholar 

34.
Anonymous Kort and Matrikelstyrelsen. Beregnede adressekoordinater v 1.0 (2001).

35.
Dahlem, G. A. House fly: (musca domestica) in Encyclopedia of insects. In Encyclopedia Insects (eds Resh, V. H. & Cardé, R. T.) 469–470 (Elsevier, Amsterdam, 2009).
Google Scholar 

36.
Skovgård, H. & Nachman, G. Population dynamics of stable flies Stomoxys Calcitrans (Diptera: Muscidae) at an organic dairy farm in Denmark based on mark-recapture with destructive sub-sampling. Environ. Entomol. 41, 20–29 (2012).
PubMed  Article  PubMed Central  Google Scholar 

37.
Taylor, D. B. et al. Dispersal of stable flies (Diptera: Muscidae) from Larval development sites in a Nebraska landscape. Environ. Entomol. 39, 1101–1110 (2010).
CAS  PubMed  Article  Google Scholar 

38.
Quarterman, K., Kilpatrick, J. & Mathis, W. Fly dispersal in a rural area near Savannah, Georgia. J. Econ. Entomol. 47, 413–419 (1954).
Article  Google Scholar 

39.
Schoof, H. F., Siverly, R. E. & Jensen, J. A. House fly dispersion studies in metropolitan areas. J. Econ. Entomol. 45, 675–683 (1952).
CAS  Article  Google Scholar 

40.
Chakrabarti, S., Kambhampati, S. & Zurek, L. Assessment of house fly dispersal between rural and urban habitats in Kansas, USA. J. Kansas Entomol. Soc. 83, 172–188 (2010).
Article  Google Scholar 

41.
Gill, C., Bahrndorff, S. & Lowenberger, C. Campylobacter jejuni in Musca domestica: an examination of survival and transmission potential in light of the innate immune responses of the house flies. Insect Sci. 24, 584–598 (2017).
CAS  PubMed  Article  Google Scholar 

42.
Nayduch, D., Noblet, G. P. & Stutzenberger, F. J. Vector potential of houseflies for the bacterium Aeromonas caviae. Med. Vet. Entomol. 16, 193–198 (2002).
CAS  PubMed  Article  Google Scholar 

43.
Fasanella, A. et al. Evaluation of the house fly Musca domestica as a mechanical vector for an Anthrax. PLoS ONE 5, 4–8 (2010).
Article  CAS  Google Scholar 

44.
Baleba, S. B. S., Torto, B., Masiga, D., Weldon, C. W. & Getahun, M. N. Egg-laying decisions based on olfactory cues enhance offspring fitness in Stomoxys calcitrans L. (Diptera: Muscidae). Sci. Rep. 9, 1–13 (2019).
CAS  Article  Google Scholar 

45.
Zhu, J. J., Zhang, Q. H., Taylor, D. B. & Friesen, K. A. Visual and olfactory enhancement of stable fly trapping. Pest Manag. Sci. 72, 1765–1771 (2016).
CAS  PubMed  Article  Google Scholar 

46.
Rosen, K., Roesler, U., Merle, R. & Friese, A. Persistent and transient airborne MRSA colonization of piglets in a newly established animal model. Front. Microbiol. 9, 1–12 (2018).
Article  Google Scholar 

47.
Angen, Ø., Feld, L., Larsen, J., Rostgaard, K. & Skov, R. Transmission of methicillin-resistant staphylococcus aureus to human volunteers visiting a swine farm. Appl. Environ. Microbiol. 83, 1–10 (2017).
CAS  Article  Google Scholar 

48.
Feld, L., Bay, H., Angen, Ø., Larsen, A. R. & Madsen, A. M. Survival of LA-MRSA in dust from swine farms. Ann. Work Expo. Heal. 62, 147–156 (2018).
CAS  Article  Google Scholar 

49.
Madsen, A. M., Markouch, A., Frederiksen, M. W. & Tendal, K. Measurement of dust-borne MRSA in pig farms using different approaches. J. Appl. Microbiol. 126, 1580–1593 (2019).
CAS  PubMed  Article  Google Scholar 

50.
Hald, B., Sommer, H. M. & Skovgård, H. Use of fly screens to reduce Campylobacter spp. introduction in broiler houses. Emerg. Infect. Dis. 13, 1951–1953 (2007).
PubMed  PubMed Central  Article  Google Scholar  More

1.
Grant, T. & Denny, M. J. S. Distribution of the platypus in Australia with guidelines for management. A report to Australian National Parks and Wildlife Service. Mount King Ecological Surveys, Oberon, New South Wales (1991).
2.
Serena, M., Worley, M., Swinnerton, M. & Williams, G. Effect of food availability and habitat on the distribution of platypus (Ornithorhynchus anatinus) foraging activity. Aust. J. Zool. 49, 263–277 (2001).
Article  Google Scholar 

3.
Serena, M., Thomas, J., Williams, G. & Officer, R. Use of stream and river habitats by the platypus, Ornithorhynchus anatinus, in an urban fringe environment. Aust. J. Zool. 46, 267–282 (1998).
Article  Google Scholar 

4.
Bino, G. et al. The platypus: evolutionary history, biology, and an uncertain future. J. Mammal. 100, 308–327 (2019).
PubMed  PubMed Central  Article  Google Scholar 

5.
Gardner, J. & Serena, M. Spatial-organization and movement patterns of adult male platypus, Ornithorhynchus anatinus (Monotremata, Ornithorhynchidae). Aust. J. Zool. 43, 91–103 (1995).
Article  Google Scholar 

6.
Bino, G., Kingsford, R. T., Grant, T., Taylor, M. D. & Vogelnest, L. Use of implanted acoustic tags to assess platypus movement behaviour across spatial and temporal scales. Sci. Rep. 8, 5117 (2018).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

7.
Grant, T., Grigg, G. C., Beard, L. & Augee, M. Movements and burrow use by platypuses, Ornithorhynchus anatinus, in the Thredbo River, New South Wales. In Platypus and Echidnas (ed. Augee, M. L.) 263–267 (The Royal Zoological Society of NSW, Sydney, 1992).
Google Scholar 

8.
Griffiths, J., Kelly, T. & Weeks, A. Impacts of high flows on platypus movements and habitat use in an urban stream. Report to Melbourne Water. Cesar, VIC, Australia (2014).

9.
Gust, N. & Handasyde, K. Seasonal-variation in the ranging behavior of the platypus (Ornithorhynchus anatinus) on the Goulburn River, Victoria. Aust. J. Zool. 43, 193–208 (1995).
Article  Google Scholar 

10.
Serena, M. Use of time and space by platypus (Ornithorhynchus anatinus: Monotremata) along a Victorian stream. J. Zool. 232, 117–131 (1994).
Article  Google Scholar 

11.
Temple-Smith, P. & Grant, T. Uncertain breeding: a short history of reproduction in monotremes. Reprod. Fertil. Dev. 13, 487–497 (2001).
CAS  PubMed  Article  PubMed Central  Google Scholar 

12.
Temple-Smith, P. D. Seasonal breeding biology of the platypus, Ornithorhynchus anatinus (Shaw, 1799), with special reference to the male (1973).

13.
Bino, G., Grant, T. R. & Kingsford, R. T. Life history and dynamics of a platypus (Ornithorhynchus anatinus) population: four decades of mark-recapture surveys. Sci. Rep. 5, 16073 (2015).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

14.
Serena, M. & Williams, G. A. Movements and cumulative range size of the platypus (Ornithorhynchus anatinus) inferred from mark-recapture studies. Aust. J. Zool. 60, 352–359 (2012).
Article  Google Scholar 

15.
Grant, T. Body temperatures of free-ranging platypuses, Ornithorhynchus anatinus (Monotremata), with observations on their use of burrows. Aust. J. Zool. 31, 117–122 (1983).
Article  Google Scholar 

16.
Bethge, P., Munks, S., Otley, H. & Nicol, S. Activity patterns and sharing of time and space of platypuses, Ornithorhynchus anatinus, in a subalpine Tasmanian lake. J. Mammal. 90, 1350–1356 (2009).
Article  Google Scholar 

17.
Macgregor, J. et al. Novel use of in-stream microchip readers to monitor wild platypuses. Pac. Conserv. Biol. 21, 101–101 (2015).
Article  Google Scholar 

18.
Grant, T. Captures, capture mortality, age and sex ratios of platypuses, Ornithorhynchus anatinus, during studies over 30 years in the upper Shoalhaven River in New South Wales. Proc. Linn. Soc. NSW 125, 217–226 (2004).
Google Scholar 

19.
Grant, T. & Temple-Smith, P. Conservation of the platypus, Ornithorhynchus anatinus: threats and challenges. Aquat. Ecosyst. Health Manag. 6, 5–18 (2003).
Article  Google Scholar 

20.
Griffiths, J., Kelly, T. & Weeks, A. Net-avoidance behaviour in platypuses. Aust. Mammal. 35, 245–247 (2013).
Article  Google Scholar 

21.
Griffiths, J. & Weeks, A. Impact of environmental flows on platypuses in a regulated river. Report to Melbourne Water. Cesar, VIC, Australia (2015).

22.
Hawke, T. et al. Fine-scale movements and interactions of platypuses, and the impact of an environmental flushing flow. Freshw. Biol. 2020(00), 1–12 (2020).
Google Scholar 

23.
Erskine, W. et al. Bedform maintenance and pool destratification by the new environmental flows on the Snowy River downstream of the Jindabyne Dam, New South Wales. J. Proc. R. Soc. N. S. W. 150, 152–171 (2017).
Google Scholar 

24.
Rohlfs, A. M. Rehabilitating the Snowy River: The influence of environmental flow releases on dissolved organic carbon supply and utilisation. PhD thesis, University of Technology, Sydney, Australia (2016).

25.
Pigram, J. J. Options for rehabilitation of Australia’s Snowy River: an economic perspective. Regul. Rivers Res. Manag. 16, 363–373 (2000).
Article  Google Scholar 

26.
Davey, C. Mitta Mitta Biological Monitoring Program 2013–2014 Annual Report. Annual report prepared for the Murray Darling Basin Authority by The Murray–Darling Freshwater Research Centre, MDFRC Publication 45/2014, September, 88pp. Canberra, Australia (2014).

27.
Watts, R. J., Ryder, D. S. & Allan, C. Environmental monitoring of variable flow trials conducted at Dartmouth Dam, 2001/02-07/08-Synthesis of key findings and operational guidelines. Institute for Land, Water and Society Report Number 50, Charles Sturt University, Albury, NSW (2009).

28.
Vogelnest, L. & Woods, R. Medicine of Australian Mammals (CSIRO Publishing, Clayton, 2008).
Google Scholar 

29.
McCullagh, P. & Nelder, J. A. Generalized Linear Models 2nd edn. (Chapman and Hall, London, 1989).
Google Scholar 

30.
Bates, D. et al. Package “lme4”. Convergence 12, 2 (2015).
Google Scholar 

31.
R Development Core Team. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2020).

32.
Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.3.0. https://CRAN.R-project.org/package=emmean.

33.
Wood, S. N. & Augustin, N. H. GAMs with integrated model selection using penalized regression splines and applications to environmental modelling “Manuscript”. Ecol. Model. 157, 157–177 (2002).
Article  Google Scholar 

34.
Wood, S. N. Generalized Additive Models: An Introduction with R (Chapman and Hall/CRC, Boca Raton, 2017).
Google Scholar 

35.
Wood, S., Scheipl, F. & Wood, M. S. Package ‘gamm4’. Am. Stat. 45, 339 (2017).
Google Scholar 

36.
Hazen, E. L. et al. Ontogeny in marine tagging and tracking science: technologies and data gaps. Mar. Ecol. Prog. Ser. 457, 221–240 (2012).
ADS  Article  Google Scholar 

37.
McClellan, C. M. & Read, A. J. Complexity and variation in loggerhead sea turtle life history. Biol. Lett. 3, 592–594 (2007).
PubMed  PubMed Central  Article  Google Scholar 

38.
Taylor, M. D., Babcock, R. C., Simpfendorfer, C. A. & Crook, D. A. Where technology meets ecology: acoustic telemetry in contemporary Australian aquatic research and management. Mar. Freshw. Res. 68, 1397–1402 (2017).
Article  Google Scholar 

39.
Pillans, R., Fry, G., Steven, A. & Patterson, T. Environmental influences on long-term movement patterns of a euryhaline Elasmobranch (Carcharhinus leucas) within a subtropical estuary. Estuar. Coasts 43, 2152–2169 (2020).
CAS  Article  Google Scholar 

40.
Otley, H. M., Munks, S. A. & Hindell, M. A. Activity patterns, movements and burrows of platypuses (Ornithorhynchus anatinus) in a sub-alpine Tasmanian lake. Aust. J. Zool. 48, 701–713 (2000).
Article  Google Scholar 

41.
Hendry, A. P. et al. Evolution Illuminated: Salmon and Their Relatives (Oxford University Press, Oxford, 2003).
Google Scholar 

42.
Stevick, P. et al. Population spatial structuring on the feeding grounds in North Atlantic humpback whales (Megaptera novaeangliae). J. Zool. 270, 244–255 (2006).
Article  Google Scholar 

43.
Cutts, C., Brembs, B., Metcalfe, N. & Taylor, A. Prior residence, territory quality and life-history strategies in juvenile Atlantic salmon (Salmo salar L.). J. Fish Biol. 55, 784–794 (1999).
Article  Google Scholar 

44.
Haley, M. P. Resource-holding power asymmetries, the prior residence effect, and reproductive payoffs in male northern elephant seal fights. Behav. Ecol. Sociobiol. 34, 427–434 (1994).
Article  Google Scholar 

45.
Lindstedt, S. L., Miller, B. J. & Buskirk, S. W. Home range, time, and body size in mammals. Ecology 67, 413–418 (1986).
Article  Google Scholar 

46.
Turner, F. B., Jennrich, R. I. & Weintraub, J. D. Home ranges and body size of lizards. Ecology 50, 1076–1081 (1969).
Article  Google Scholar 

47.
Slavenko, A., Itescu, Y., Ihlow, F. & Meiri, S. Home is where the shell is: predicting turtle home range sizes. J. Anim. Ecol. 85, 106–114 (2016).
PubMed  Article  Google Scholar 

48.
McNab, B. K. Bioenergetics and the determination of home range size. Am. Nat. 97, 133–140 (1963).
Article  Google Scholar 

49.
Greenwood, P. J. Mating systems, philopatry and dispersal in birds and mammals. Anim. Behav. 28, 1140–1162 (1980).
Article  Google Scholar 

50.
Soderquist, T. R. & Serena, M. Juvenile behaviour and dispersal of chuditch (Dasyurus geoffroii) (Marsupialia: Dasyuridae). Aust. J. Zool. 48, 551–560 (2000).
Article  Google Scholar 

51.
Cockburn, A., Scott, M. P. & Scotts, D. J. Inbreeding avoidance and male-biased natal dispersal in Antechinus spp. (Marsupialia: Dasyuridae). Anim. Behav. 33, 908–915 (1985).
Article  Google Scholar 

52.
Furlan, E. et al. Dispersal patterns and population structuring among platypuses, Ornithorhynchus anatinus, throughout south-eastern Australia. Conserv. Genet. 14, 837–853 (2013).
CAS  Article  Google Scholar 

53.
Kolomyjec, S. H. Relationships of northern platypus (Ornithorhynchus anatinus) populations: a molecular approach (2010).

54.
Faragher, R., Grant, T. & Carrick, F. Food of the platypus (Ornithorhynchus anatinus) with notes on the food of brown trout (Salmo trutta) in the Shoalhaven River, NSW. Aust. J. Ecol. 4, 171–179 (1979).
Article  Google Scholar 

55.
Todd, C. R., Ryan, T., Nicol, S. J. & Bearlin, A. R. The impact of cold water releases on the critical period of post-spawning survival and its implications for Murray cod (Maccullochella peelii peelii): a case study of the Mitta Mitta River, southeastern Australia. River Res. Appl. 21, 1035–1052 (2005).
Article  Google Scholar 

56.
Koehn, J., Doeg, T., Harrington, D. & Milledge, G. The effects of Dartmouth Dam on the aquatic fauna of the Mitta Mitta River. Report to the Murray-Darling Basin Commission. Arthur Rylah Institute for Environmental Research, Melbourne (1995).

57.
Hawke, T., Bino, G., & Kingsford, R. T. Damming insights: impacts and implications of river regulation on platypus populations. Aquat Conserv Mar Freshw Ecosystems. in press. (2021).

58.
Hawke, T., Bino, G. & Kingsford, R. T. Platypus: paucities and peril. A response to: limitations on the use of historical and database sources to identify changes in distribution and abundance of the platypus. Glob. Ecol. Conserv. 21, e00857 (2019).
Article  Google Scholar 

59.
Hawke, T., Bino, G. & Kingsford, R. T. A silent demise: historical insights into population changes of the iconic platypus (Ornithorhynchus anatinus). Glob. Ecol. Conserv. 20, e00720 (2019).
Article  Google Scholar 

60.
Bino, G., Kingsford, R. T. & Wintle, B. A. A stitch in time—synergistic impacts to platypus metapopulation extinction risk. Biol. Conserv. 242, 108399 (2020).
Article  Google Scholar  More

Different sampling strategies yield different microbial communities
The sampling strategies compared in this study (homogenizing tissue before subsampling and homogenizing tissue after subsampling) are common methods found in the literature for characterizing plant-associated microbial communities14,23,26,29. Procrustes analyses and community overlap between sampling strategies demonstrated that different strategies can capture disparate microbial communities within plants, with the extent of these differences depending on the community targeted and plant tissue type sampled. In FFE as well as bacterial and non-AM fungal communities in roots, subsamples from the same plant resulted in completely different sets of species recovered, illustrating the severe undersampling that is inherent to each of these strategies. With these sampling strategies, we are undoubtedly sacrificing power and accuracy to characterize the subtler aspects of plant microbiome interactions, despite often seeing community differences across landscapes, treatments or seasons.
Richness was higher when homogenizing before subsampling for bacteria only, despite differences observed in composition for all groups. It is perhaps surprising that homogenizing plant tissues before subsampling did not recover more species than homogenizing after subsampling for fungi as well, because with the former approach, more plant tissue is initially represented. Indeed, a previous study showed that sample pooling or homogenizing before subsampling resulted in a higher richness of soil fungi compared to equally sized individual samples50. In Song et al. (2015)50 they also found that multiple individual subsamples, rather than the single homogenized subsample, resulted in higher richness. This may suggest that the scale at which we are physically able to break down the particle size of plant tissues, as opposed to soil, is not always fine enough to sufficiently homogenize the fungi within. Because of this, plant-associated microbial communities may require a greater sampling effort than soil microbes. Additionally, the removal of low-abundant SVs did not result in differences in richness between the two sampling strategies for any microbial group, suggesting that neither strategy is better at capturing rare species. Although this study was performed only on milkweed plants, we believe that these results are applicable to other plant species as well. The richness reported here is similar to other studies of plant-associated microbes (e.g.51,52), indicating that differences in subsamples were not due to extreme richness of milkweed-associated microbes.
Microbial diversity should inform sampling effort
The higher congruency that we saw between sampling strategies for AMF compared to other microbial communities may be due to the differences in their local and global estimated richness. While the global number of AMF species has been estimated in the hundreds to low thousands42,53, global estimates of fungal species in general range in the millions54,55. A recent global estimate of bacterial richness suggests similar scales56. In this study specifically, AMF had the lowest total SV richness and the greatest similarity between sampling strategies, while foliar fungal endophytes had the highest SV richness, and the lowest overlap of SVs between strategies. Since the amount of tissue sampled was equal for all microbial communities, the sampling effort was likely much higher for AMF (relative to the whole AMF community), than it was for bacteria and non-AM fungi. Consequently, with each sample we are likely sampling a much larger proportion of true AMF species richness.
Even though the estimated total community richness was highest for foliar fungi, the average estimated richness per individual plant was highest for AMF. This suggests that similar AMF SVs re-occurred across all plants with low species turnover. On the other hand, fungi in leaves had lower average richness per plant (Fig. 4, Supplementary Fig. S3), but the highest total richness, meaning that there was higher turnover of FFE species among plants sampled. These results may be a direct reflection of the overall community richness of the different microbial groups as well as their ability to spread and co-occur within plants. Based on these patterns, more individual plants and a greater sampling effort within individuals are likely needed to characterize FFE communities compared to AMF communities.
Rare SVs contribute to variation among subsamples
Our results show that low abundant, rare SVs largely contributed to the differences seen between sampling strategies. Even AMF communities, which were already similar, increased in overlap by 50% between strategies after low abundant SVs (represented by  More

1.
Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 
2.
Sánchez-Bayo, F. & Wyckhuys, K. A. G. Worldwide decline of the entomofauna: a review of its drivers. Biol. Conserv. 232, 8–27 (2019).
Article  Google Scholar 

3.
van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420 (2020).
ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

4.
Losey, E. J. & Vaughan, M. The economic value of ecological services provided by insects. Bioscience 56, 311 (2006).
Article  Google Scholar 

5.
Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl. Acad. Sci. USA 115, 6506–6511 (2018).
CAS  PubMed  Article  PubMed Central  Google Scholar 

6.
Yang, L. H. & Gratton, C. Insects as drivers of ecosystem processes. Curr. Opin. Insect Sci. 2, 26–32 (2014).
PubMed  Article  PubMed Central  Google Scholar 

7.
Hunter, M. D. Insect population dynamics meets ecosystem ecology: effects of herbivory on soil nutrient dynamics. Agric. For. Entomol. 3, 77–84 (2001).
Article  Google Scholar 

8.
Nichols, E. et al. Ecological functions and ecosystem services provided by Scarabaeinae dung beetles. Biol. Conserv. 141, 1461–1474 (2008).
Article  Google Scholar 

9.
Lobry de Bruyn, L. A. & Conacher, A. J. The role of termites and ants in soil modification: a review. Aust. J. Soil Res. 28, 55–93 (1990).
Google Scholar 

10.
Shukla, R. K., Singh, H., Rastogi, N. & Agarwal, V. M. Impact of abundant Pheidole ant species on soil nutrients in relation to the food biology of the species. Appl. Soil Ecol. 71, 15–23 (2013).
Article  Google Scholar 

11.
López-Hernández, D. Nutrient dynamics (C, N and P) in termite mounds of Nasutitermes ephratae from savannas of the Orinoco Llanos (Venezuela). Soil Biol. Biochem. 33, 747–753 (2001).
Article  Google Scholar 

12.
Nkem, J. N., Lobry de Bruyn, L. A., Grant, C. D. & Hulugalle, N. R. The impact of ant bioturbation and foraging activities on surrounding soil properties. Pedobiologia 44, 609–621 (2000).
Article  Google Scholar 

13.
Jouquet, P., Traoré, S., Choosai, C., Hartmann, C. & Bignell, D. Influence of termites on ecosystem functioning. Ecosystem services provided by termites. Eur. J. Soil Biol. 47, 215–222 (2011).
Article  Google Scholar 

14.
Frost, C. J. & Hunter, M. D. Insect canopy herbivory and frass deposition affect soil nutrient dynamics and export in oak mesocosms. Ecology 85, 3335–3347 (2004).
Article  Google Scholar 

15.
Calderon-Cortes, N. et al. Ecosystem engineering and manipulation of host plant tissues by the insect borer Oncideres albomarginata chamela. J. Insect Physiol. 84, 128–136 (2016).
CAS  PubMed  Article  Google Scholar 

16.
Barton, P. S., Cunningham, S. A., Lindenmayer, D. B. & Manning, A. D. The role of carrion in maintaining biodiversity and ecological processes in terrestrial ecosystems. Oecologia 171, 761–772 (2013).
ADS  PubMed  Article  Google Scholar 

17.
Danell, K., Aux, D. B. & Bráthen, K. A. Effect of muskox carcasses on nitrogen concentration in tundra vegetation. Artic 55, 389–392 (2002).
Google Scholar 

18.
Melis, C. et al. Soil and vegetation nutrient response to bison carcasses in Bialowieza primeval forest Poland. Ecol. Res. 22, 807–813 (2007).
ADS  CAS  Article  Google Scholar 

19.
Bump, J. K., Peterson, R. O. & Vucetich, J. A. Wolves modulate soil nutrient heterogeneity and foliar nitrogen by configuring the distribution of ungulate carcasses. Ecology 90, 3159–3167 (2009).
PubMed  Article  Google Scholar 

20.
Benninger, L. A., Carter, D. O. & Forbes, S. L. The biochemical alteration of soil beneath a decomposing carcass. Forensic Sci. Int. 180, 70–75 (2008).
CAS  PubMed  Article  Google Scholar 

21.
Anderson, G. S. & VanLaerhoven, S. L. Initial studies on insect succession on carrion in Southwestern British Columbia. J. Forensic Sci. 41, 617–625 (1996).
Article  Google Scholar 

22.
Matuszewski, S., Bajerlein, D., Konwerski, S. & Szpila, K. Insect succession and carrion decomposition in selected forests of Central Europe. Part 3: succession of carrion fauna. Forensic Sci. Int. 207, 150–163 (2011).
PubMed  Article  Google Scholar 

23.
Barton, P. S., Evans, M. J., Pechal, J. L. & Benbow, M. E. Necrophilous insect dynamics at small vertebrate carrion in a temperate eucalypt woodland. J. Med. Entomol. 54, 964–973 (2017).
PubMed  Article  Google Scholar 

24.
Benbow, M. E., Lewis, A. J., Tomberlin, J. K. & Pechal, J. L. Seasonal necrophagous insect community assembly during vertebrate carrion decomposition. J. Med. Entomol. 50, 440–450 (2013).
CAS  PubMed  Article  Google Scholar 

25.
Payne, J. A. A summer carrion study of the baby pig Sus Scrofa Linnaeus. Ecology 46, 592–602 (1965).
Article  Google Scholar 

26.
Kočárek, P. Decomposition and Coleoptera succession on exposed carrion of small mammal in Opava, the Czech Republic. Eur. J. Soil Biol. 39, 31–45 (2003).
Article  Google Scholar 

27.
Bornemissza, G. F. An analysis of arthropod succession in carrion and the effects of its decomposition on the soil fauna. J. Zool. 5, 1–12 (1957).
Google Scholar 

28.
Parmenter, R. R. & MacMahon, J. A. Carrion decomposition and nutrient cycling in a semiarid shrub–steppe ecosystem. Ecol. Monogr. 79, 637–661 (2009).
Article  Google Scholar 

29.
Pechal, J. L., Benbow, M. E., Crippen, T. L., Tarone, A. M. & Tomberlin, J. K. Delayed insect access alters carrion decomposition and necrophagous insect community assembly. Ecosphere 5, 1–21 (2014).
Article  Google Scholar 

30.
Pukowski, E. Ökologische untersuchungen an necrophorus. Z. Morphol. Oekol. 27, 518–586 (1933).
Article  Google Scholar 

31.
Scott, M. P. The ecology and behavior of burying beetles. Annu. Rev. Entomol. 43, 595–618 (1998).
CAS  PubMed  Article  Google Scholar 

32.
Milne, L. J. & Milne, M. The social behavior of burying beetles. Sci. Am. 235, 84–89 (1976).
Article  Google Scholar 

33.
Müller, J. K. & Eggert, A. K. Paternity assurance by ‘helpful’ males: adaptations to sperm competition in burying beetles. Behav. Ecol. Sociobiol. 24, 245–249 (1989).
Article  Google Scholar 

34.
House, C. M. et al. The evolution of repeated mating in the burying beetle Nicorphorus vespilloides. Evolution 62, 2004–2014 (2008).
PubMed  Article  Google Scholar 

35.
Pettinger, A. M., Steiger, S., Müller, J. K., Sakaluk, S. K. & Eggert, A. K. Dominance status and carcass availability affect the outcome of sperm competition in burying beetles. Behav. Ecol. 22, 1079–1087 (2011).
Article  Google Scholar 

36.
Rozen, D. E., Engelmoer, D. J. P. & Smiseth, P. T. Antimicrobial strategies in burying beetles breeding on carrion. Proc. Natl. Acad. Sci. USA 105, 17890–17895 (2008).
ADS  CAS  PubMed  Article  Google Scholar 

37.
Arce, A. N., Johnston, P. R., Smiseth, P. T. & Rozen, D. E. Mechanisms and fitness effects of antibacterial defences in a carrion beetle. J. Evol. Biol. 25, 930–937 (2012).
CAS  PubMed  Article  Google Scholar 

38.
Hall, C. L. et al. Inhibition of microorganisms on a carrion breeding resource: the antimicrobial peptide activity of burying beetle (Coleoptera: Silphidae) oral and anal secretions. Environ. Entomol. 40, 669–678 (2011).
PubMed  Article  Google Scholar 

39.
Duarte, A., Welch, M., Swannack, C., Wagner, J. & Kilner, R. M. Strategies for managing rival bacterial communities: lessons from burying beetles. J. Anim. Ecol. 87, 414–427 (2018).
PubMed  Article  Google Scholar 

40.
Trumbo, S. T. Reproductive benefits and the duration of paternal care in a biparental burying beetle Necrophorus orbicollis. Behaviour 117, 82–105 (1991).
Article  Google Scholar 

41.
Trumbo, S. T. Fate of mouse carcasses in a Northern Woodland. Ecol. Entomol. 41, 737–740 (2016).
Article  Google Scholar 

42.
Hoback, W. W., Freeman, L., Payton, M. & Peterson, B. C. Burying beetle (Coleoptera: Silphidae: Nicrophorus fabricius) brooding improves soil fertility. Coleopt. Bull. 74, 427–433 (2020).
Article  Google Scholar 

43.
Benbow, M. E. et al. Necrobiome framework for bridging decomposition ecology of autotrophically and heterotrophically derived organic matter. Ecol. Monogr. 89, 1–26 (2018).
Google Scholar 

44.
Carter, D. O., Yellowlees, D. & Tibbett, M. Cadaver decomposition in terrestrial ecosystems. Naturwissenschaften 94, 12–24 (2007).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

45.
Carter, D. O., Yellowlees, D. & Tibbett, M. Temperature affects microbial decomposition of cadavers (Rattus rattus) in contrasting soils. Appl. Soil Ecol. 40, 129–137 (2008).
Article  Google Scholar 

46.
Meyer, J., Anderson, B. & Carter, D. O. Seasonal variation of carcass decomposition and gravesoil chemistry in a cold (Dfa) climate. J. Forensic Sci. 58, 1175–1182 (2013).
PubMed  Article  PubMed Central  Google Scholar 

47.
Metcalf, J. L. et al. Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 351, 158–162 (2016).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

48.
Chen, Y. A., Forschler, B. T. & Nielsen, U. Elemental concentrations in the frass of saproxylic insects suggest a role in micronutrient cycling. Ecosphere 7, 1–13 (2016).
Google Scholar 

49.
Couture, J. J. & Lindroth, R. L. Atmospheric change alters frass quality of forest canopy herbivores. Arthropod. Plant. Interact. 8, 33–47 (2014).
Article  Google Scholar 

50.
Metcalf, J. L. et al. A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system. Elife 2013, 1–19 (2013).
Google Scholar 

51.
Xu, S., Liu, L. L. & Sayer, E. J. Variability of above-ground litter inputs alters soil physicochemical and biological processes: a meta-analysis of litterfall-manipulation experiments. Biogeosciences 10, 7423–7433 (2013).
ADS  Article  CAS  Google Scholar 

52.
Wilson, W. A. et al. Regulation of glycogen metabolism in yeast and bacteria. FEMS Microbiol. Rev. 34, 952–985 (2010).
CAS  PubMed  PubMed Central  Article  Google Scholar 

53.
Achbergerová, L. & Nahálka, J. Polyphosphate—an ancient energy source and active metabolic regulator. Microb. Cell Fact. 10, 1–14 (2011).
Article  CAS  Google Scholar 

54.
Kornberg, A. Inorganic polyphosphate: toward making a forgotten polymer unforgettable. J. Bacteriol. 177, 491–496 (1995).
CAS  PubMed  PubMed Central  Article  Google Scholar 

55.
Wilkinson, J. F. Carbon and energy storage in bacteria. J. Gen. Microbiol. 32, 171–176 (1963).
CAS  PubMed  Article  Google Scholar 

56.
Paul, E. A. Soil Microbiology, Ecology and Biochemistry (Academic Press, Cambridge, 2014).
Google Scholar 

57.
DeVault, T. L., Brisbin, I. L. Jr. & Rhodes, O. E. Jr. Factors influencing the acquisition of rodent carrion by vertebrate scavengers and decomposers. Can. J. Zool. 82, 502–509 (2004).
Article  Google Scholar 

58.
DeVault, T. L., Rhodes, O. E. Jr. & Shivik, J. A. Scavenging by vertebrates: behavioral, ecological and evolutionary perspectives on an important energy transfer pathway in terrestrial ecosystems. Oikos 102, 225–234 (2003).
Article  Google Scholar 

59.
DeVault, T. L. & Rhodes, O. E. Identification of vertebrate scavengers of small mammal carcasses in a forested landscape. Acta Theriol. 47, 185–192 (2002).
Article  Google Scholar 

60.
Smith, J. B., Laatsch, L. J. & Beasley, J. C. Spatial complexity of carcass location influences vertebrate scavenger efficiency and species composition. Sci. Rep. 7, 1–8 (2017).
Article  CAS  Google Scholar 

61.
Wilson, D. S. & Fudge, J. Burying beetles: intraspecific interactions and reproductive success in the field. Ecol. Entomol. 9, 195–203 (1984).
Article  Google Scholar 

62.
Keller, M. L., Howard, D. R. & Hall, C. L. Spatiotemporal niche partitioning in a specious silphid community (Coleoptera: Silphidae Nicrophorus). Sci. Nat. 106, 1–12 (2019).
ADS  Article  CAS  Google Scholar 

63.
Owings, C. G. & Picard, C. J. Temporal survey of a carrion beetle (Coleoptera:Silphidae) community in Indiana. Proc. Indiana Acad. Sci. 124, 124–128 (2015).
Google Scholar 

64.
Snyder, D. P. Survival rates, longevity, and population fluctuations in the white-footed mouse, Peromyscus leucopus Southeastern Michigan. Museum Zool. Universty Michigan 95, 1–33 (1956).
Google Scholar 

65.
Stephens, R. B., Hocking, D. J., Yamasaki, M. & Rowe, R. J. Synchrony in small mammal community dynamics across a forested landscape. Ecography 40, 1198–1209 (2017).
Article  Google Scholar 

66.
Leasure, D. R., Rupe, D. M., Phillips, E. A., Opine, D. R. & Huxel, G. R. Efficient new above-ground bucket traps produce comparable data to that of standard transects for the endangered American Burying Beetle, Nicrophorus americanus Olivier (Coleoptera: Silphidae). Coleopt. Bull. 66, 209–218 (2012).
Article  Google Scholar 

67.
Bedick, J. C., Ratcliffe, B. C. & Higley, L. G. A new sampling protocol for the endangered American Burying Beetle, Nicrophorus americanus Olivier (Coleoptera: Silphidae). Coleopt. Bull. 58, 57–70 (2004).
Article  Google Scholar 

68.
Trumbo, S. T. Reproductive success, phenology and biogeography of burying beetles (Silphidae, Nicrophorus). Am. Midl. Nat. 124, 1–11 (1990).
Article  Google Scholar 

69.
Trumbo, S. T. Nesting failure in burying beetles and the origin of communal associations. Evol. Ecol. 9, 125–130 (1995).
Article  Google Scholar 

70.
Braman, R. S. & Hendrix, S. A. Nanogram nitrite and nitrate determination in environmental and biological materials by vanadium (III) reduction with chemiluminescence detection. Anal. Chem. 61, 2715–2718 (1989).
CAS  PubMed  Article  Google Scholar 

71.
Sims, G. K., Ellsworth, T. R. & Mulvaney, R. L. Microscale determination of inorganic nitrogen in water and soil extracts. Commun. Soil Sci. Plant Anal. 26, 303–316 (1995).
CAS  Article  Google Scholar 

72.
Contosta, A. R., Frey, S. D. & Cooper, A. B. Seasonal dynamics of soil respiration and N mineralization in chronically warmed and fertilized soils. Ecosphere 2, 1–21 (2011).
Article  Google Scholar 

73.
Vance, E. D., Brookes, P. C. & Jenkinson, D. S. Microbial biomass measurements in forest soils: the use of the chloroform fumigation-incubation method in strongly acid soils. Soil Biol. Biochem. 19, 697–702 (1987).
CAS  Article  Google Scholar 

74.
Vance, E. D., Brookes, P. C. & Jenkinson, D. S. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem. 19, 703–707 (1987).
CAS  Article  Google Scholar 

75.
Brookes, P. D. C., Landman, A., Pruden, G. & Jenkinson, D. S. Chloroform fumigation and the release of soil nitrogen: a rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol. Biochem. 17, 837–842 (1985).
CAS  Article  Google Scholar 

76.
Bligh, E. G. & Dyer, W. J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917 (1959).
CAS  PubMed  Article  Google Scholar 

77.
White, D. C., Davis, W. M., Nickels, J. S., King, J. D. & Bobbie, R. J. Determination of the sedimentary microbial biomass by extractible lipid phosphate. Oecologia 40, 51–62 (1979).
ADS  CAS  PubMed  Article  Google Scholar 

78.
Guckert, J. B., Antworth, C. P., Nichols, P. D. & White, D. C. Phospholipid, ester-linked fatty acid profiles as reproducible assays for changes in prokaryotic community structure of estuarine sediments. FEMS Microbiol. Lett. 31, 147–158 (1985).
CAS  Article  Google Scholar 

79.
Bardgett, R. D., Hobbs, P. J. & Frostegårde, A. Changes in soil fungal:bacterial biomass ratios following reductions in the intensity of management of an upland grassland. Biol. Fertil. Soils 22, 261–264 (1996).
Article  Google Scholar 

80.
Bååth, E. The use of neutral lipid fatty acids to indicate the physiological conditions of soil fungi. Microb. Ecol. 45, 373–383 (2003).
PubMed  Article  CAS  Google Scholar 

81.
Ekelund, F., Olsson, S. & Johansen, A. Changes in the succession and diversity of protozoan and microbial populations in soil spiked with a range of copper concentrations. Soil Biol. Biochem. 35, 1507–1516 (2003).
CAS  Article  Google Scholar 

82.
Leckie, S. E., Prescott, C. E., Grayston, S. J., Neufeld, J. D. & Mohn, W. W. Characterization of humus microbial communities in adjacent forest types that differ in nitrogen availability. Microb. Ecol. 48, 29–40 (2004).
CAS  PubMed  Article  Google Scholar 

83.
Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).
CAS  PubMed  Article  Google Scholar 

84.
Oksanen, J. et al. Vegan: community ecology package (2019). http://cran.r-project.org/.

85.
Hervé, M. RVAideMemoire: Testing and plotting procedures for biostatistics version 0.9-75 from CRAN. R package version 0.9-75 (2020).

86.
Fox, J. & Weisberg, S. An R Companion to Applied Regression (SAGE Publications Inc, Thousand Oaks, 2018).
Google Scholar  More