Ecology

Morris, G. L. & Fan, J. Reservoir Sedimentation Handbook: Design and Management of Dams, Reservoirs, and Watersheds for Sustainable Use (McGraw Hill Professional, 1998).
Google Scholar 
White, R. Evacuation of Sediments from Reservoirs, HR Wallingford, http://www.thomastelford.com (Thomas Telford Publishing, 2001).Kondolf, G. M. et al. Sustainable sediment management in reservoirs and regulated rivers: Experiences from five continents. Earth’s Future 2, 256–280 (2014).ADS 
Article 

Google Scholar 
Schleiss, A. J., Franca, M. J., Juez, C. & De Cesare, G. Reservoir sedimentation. J. Hydraul. Res. 54, 595–614 (2016).Article 

Google Scholar 
Dahal, S., Crosato, A., Omer, A. Y. A. & Lee, A. A. Validation of model-based optimization of reservoir sediment releases by dam removal. J. Water Resour. Plan. Manag. 147, 04021033 (2021).Article 

Google Scholar 
Williams, G. P. & Wolman, M. G. Effects of dams and reservoirs on surface water hydrology—Changes in rivers downstream from dams. Natl. Water Summ. Hydrol. Events Surf. Water Resour. 2300, 83 (1986).
Google Scholar 
Toffolon, M., Siviglia, A. & Zolezzi, G. Thermal wave dynamics in rivers affected by hydropeaking. Water Resour. Res. https://doi.org/10.1029/2009WR008234 (2010).Article 

Google Scholar 
Stewart, G. B. Patterns and Processes of Sediment Transport Following Sediment-Filled Dam Removal in Gravel Bed Rivers. (PhD Thesis, Oregon State University, Oregon USA, 2006).Major, J. J. et al. Geomorphic Response of the Sandy River, Oregon, to Removal of Marmot Dam. U.S. Geological Survey Professional Paper, 64p https://pubs.usgs.gov/pp/1792/ (2012).Espa, P., Castelli, E., Crosa, G. & Gentili, G. Environmental effects of storage preservation practices: Controlled flushing of fine sediment from a small hydropower reservoir. Environ. Manag. 52, 261–276 (2013).ADS 
Article 

Google Scholar 
Tena, A., Vericat, D. & Batalla, R. J. Suspended sediment dynamics during flushing flows in a large impounded river (the lower River Ebro). J Soils Sediments 14, 2057–2069 (2014).Article 

Google Scholar 
Antoine, G., Camenen, B., Jodeau, M., Némery, J. & Esteves, M. Downstream erosion and deposition dynamics of fine suspended sediments due to dam flushing. J. Hydrol. 585, 124763 (2020).Article 

Google Scholar 
Power, M., Dietrich, W. & Finlay, J. Dams and downstream aquatic biodiversity: Potential food web consequences of hydrologic and geomorphic change. Environ. Manag. 20, 887–895 (1996).ADS 
CAS 
Article 

Google Scholar 
Clarke, K. D., Pratt, T. C., Randall, R. G., Scruton, D. A. & Smokorowski, K. E. Validation of the flow management pathway: Effects of altered flow on fish habitat and fishes downstream from a hydropower dam. Can. Tech. Rep. Fish. Aquat. Sci. 2784, 111 (2008).
Google Scholar 
Poff, N. L. & Zimmerman, J. K. H. Ecological responses to altered flow regimes: A literature review to inform the science and management of environmental flows. Freshw. Biol. 55, 194–205 (2010).Article 

Google Scholar 
Juracek, K. E. The aging of America’s reservoirs: In-reservoir and downstream physical changes and habitat implications. JAWRA J. Am. Water Resour. Assoc. 51, 168–184 (2015).ADS 
Article 

Google Scholar 
Brandt, S. A. & Swenning, J. Sedimentological and geomorphological effects of reservoir flushing: the Cachí Reservoir, Costa Rica, 1996. Geogr. Ann. Ser. B 81, 391–407 (1999).Article 

Google Scholar 
Grant, G. E., Schmidt, J. C. & Lewis, S. L. A geological framework for interpreting downstream effects of dams on rivers. In Water Science and Application (eds O’Connor, J. E. & Grant, G. E.) 203–219 (American Geophysical Union, 2003). https://doi.org/10.1029/007WS13.Chapter 

Google Scholar 
Petts, G. E. & Gurnell, A. M. Dams and geomorphology: Research progress and future directions. Geomorphology 71, 27–47 (2005).ADS 
Article 

Google Scholar 
Newcombe, C. & MacDonald, D. D. Effects of suspended sediments on aquatic ecosystems. J. N. Am. J. Fish. Manag. 11, 72–82 (1991).Article 

Google Scholar 
Gilles, B. & Le Bail, P.-Y. Does light have an influence on fish growth?. Aquaculture 177, 129–152 (1999).Article 

Google Scholar 
Carolli, M., Bruno, M. C., Siviglia, A. & Maiolini, B. Responses of benthic invertebrates to abrupt changes of temperature in flume simulations. River Res. Appl. 28, 678–691 (2012).Article 

Google Scholar 
Bennel, D. H., Connor, W. P. & Eaton, C. A. Substrate composition and emergence success of fall Chinook salmon in the Snake river. Northwest Sci. 77, 93–99 (2003).
Google Scholar 
Jensen, D. W., Steel, E. A., Fullerton, A. H. & Pess, G. R. Impact of fine sediment on egg-to-fry survival of Pacific salmon: A meta-analysis of published studies. Rev. Fish. Sci. 17, 348–359 (2009).CAS 
Article 

Google Scholar 
Bjornn, T. C. & Reiser, D. W. Habitat requirements of salmonids in streams. Am. Fish. Soc. Spec. Publ. 19, 83–138 (1991).
Google Scholar 
ASCE, N. Sediment and aquatic habitat in river systems. J. Hydraul. Eng. 118, 669–687 (1992).Article 

Google Scholar 
Louhi, P., Mäki-Petäys, A. & Erkinaro, J. Spawning habitat of Atlantic salmon and brown trout: General criteria and intragravel factors. River Res. Appl. 24, 330–339 (2008).Article 

Google Scholar 
Baxter, C. V. & Hauer, F. R. Geomorphology, hyporheic exchange, and selection of spawning habitat by bull trout (Salvelinus confluentus). Can. J. Fish. Aquat. Sci. 57, 1470–1481 (2000).Article 

Google Scholar 
Peviani, M., Saccardo, I., Crosato, A. & Gentili, G. Natural and artificial floods connected with river habitat. in Ecohydraulics 2000. Proceedings
of the 2nd International Symposium on Habitat Hydraulics, IAHR- Que´bec,
Canada, vol. B 175–186 (1996).Crosa, G., Castelli, E., Gentili, G. & Espa, P. Effects of suspended sediments from reservoir flushing on fish and macroinvertebrates in an alpine stream. Aquat. Sci. 72, 85 (2009).Article 
CAS 

Google Scholar 
Espa, P., Crosa, G., Gentili, G., Quadroni, S. & Petts, G. Downstream ecological impacts of controlled sediment flushing in an Alpine valley river: A case study. River Res. Appl. 31, 931–942 (2014).Article 

Google Scholar 
Lee, A. Modelling Salmon Spawning Habitat Response to Dam Removal. (MSc Thesis, IHE Delft, the Netherlands, 2017).van Oorschot, M. et al. Impact of dam operations on the habitat suitability of Plecoglossus altivelis downstream of the Funagira dam, Japan. In River Flow 2020 (eds Uijttewaal et al.) (2020 Taylor & Francis Group, CRC Press, 2020).
Google Scholar 
Newcombe, C. P. Suspended sediments in acquatic ecosystem: III effects as a function of concentration and duration of exposure. (1994).Newcombe, C. P. & Jensen, J. O. T. Channel suspended sediment and fisheries: A synthesis for quantitative assessment of risk and impact. N. Am. J. Fish. Manag. 16, 693–727 (1996).Article 

Google Scholar 
Hubert, W. A., Helzner, R. S., Lee, L. A. & Nelson, P. C. Habitat suitability index models and instream flow suitability curves: Arctic grayling riverine populations. Western Energy and Land Use Team, Division of Biological Services, Research and Development, Fish and Wildlife Service, US Department of Interior, Biological report 82 (10.110) (1985).Raleigh, R. F., Miller, W. J. & Nelson, P. C. Habitat suitability index models and instream flow suitability curves: Chinook salmon. Fish and Wildlife Service, US Department of the Interior, Biological Report 82(10.122) www.nwrc.usgs.gov/wdb/pub/hsi/hsi-122.pdf (1986).Fisher, S., Gray, L., Grimm, N. & Busch, D. E. Temporal succession in a desert stream ecosystem following flash flooding. Ecol. Monogr. https://doi.org/10.2307/2937346 (1982).Article 

Google Scholar 
Lapointe, M., Eaton, B., Driscoll, S. & Latulippe, C. Modelling the probability of salmonid egg pocket scour due to floods. Can. J. Fish. Aquat. Sci. 57, 11 (2000).Article 

Google Scholar 
Baldwin, D. & Mitchell, A. M. The effects of drying and re-flooding on the sediment and soil nutrient dynamics of lowland river–floodplain systems: A synthesis. River Res. Appl. 16, 457–467 (2000).
Google Scholar 
Kowalski, D. The effects of stream flow on the trout populations of the Gunnison river. (2007).Konard, C. P. Effects of urban development on floods. U.S. Geological Survey—Water Resources Fact Sheet 076-03 https://pubs.usgs.gov/fs/fs07603/ (2016).Miller, J. D. & Hutchins, M. The impacts of urbanisation and climate change on urban flooding and urban water quality: A review of the evidence concerning the United Kingdom. J. Hydrol. Reg. Stud. 12, 345–362 (2017).Article 

Google Scholar 
Poff, N. L. & Ward, J. V. Implications of streamflow variability and predictability for lotic community structure: A regional analysis of streamflow patterns. Can. J. Fish. Aquat. Sci. 46, 1805–1818 (1989).Article 

Google Scholar 
George, S. D., Baldigo, B. P., Smith, A. J. & Robinson, G. R. Effects of extreme floods on trout populations and fish communities in a Catskill Mountain river. Freshw. Biol. 60, 2511–2522 (2015).Article 

Google Scholar 
Carlson, A. K., Fincel, M. J., Longhenry, C. M. & Graeb, B. D. Effects of historic flooding on fishes and aquatic habitats in a Missouri river delta. J. Freshw. Ecol. 31, 271–288 (2016).Article 

Google Scholar 
Ríos-Pulgarín, M. I., Barletta, M. & Mancera-Rodríguez, N. J. The role of the hydrological cycle on the distribution patterns of fish assemblages in an Andean stream. J. Fish Biol. 89, 102–130 (2016).PubMed 
Article 
CAS 

Google Scholar 
United States Federal energy regulatory Commission (FERC). Application for Surrender of License, Bull Run Hydropower Project: Environmental Impact Statement. https://catalog.hathitrust.org/Record/100940309 (2003).Squier Associates. Sandy river sediment study, Bull Run Hydroelectric Project. (2000).Taylor, B. Salmon and Steelhead Runs and Related Events of the Clackamas River Basin–A Historical Perspective. Portland General Electric Company, 64 https://www.eaglecreekfriends.org/links-references (1999).Trimble, D. E. Geology of Portland, Oregon, and Adjacent Areas. Bulletin U.S. G.P.O. https://pubs.er.usgs.gov/publication/b1119. https://doi.org/10.3133/b1119. (1963).Sandy River basin Working Group. Sandy River basin aquatic habitat restoration strategy: An anchor habitat-based prioritization of restoration opportunities Oregon Trout. Portland, Oregon. Preprint at https://www.fs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb5325660.pdf (2007).Lee, A., Crosato, A., Omer, A. Y. A. & Bregoli, F. Applying a two-dimensional morphodynamic model to assess impacts to Chinook salmon spawning habitat from dam removal. in AGU Fall meeting (2017).Healey, M. C. Life history of Chinook salmon (Oncorhynchus tshawytscha). Pacific Salmon Life Histories 311–394 (1991).Bourret, S. L., Caudill, C. C. & Keefer, M. L. Diversity of juvenile Chinook salmon life history pathways. Rev. Fish. Biol. Fish. 26, 375–403 (2016).Article 

Google Scholar 
Alderdice, D. & Velsen, F. Relation between temperature and incubation time for eggs of Chinook salmon (Oncorhynchus tshawytscha). J. Fish. Res. Board Can. 35, 69–75 (1978).Article 

Google Scholar 
Seattle Aquarium. Redd alert: Our Chinook salmon are hatching! |. Seattle Aquarium https://www.seattleaquarium.org/blog/redd-alert-our-chinook-salmon-are-hatching (2015).Whitman, L., Cannon, B. & Hart, S. Spring Chinook salmon in the Willamette and Sandy rivers: Sandy river basin Spring Chinook salmon spawning surveys. Oregon Department of Fish and Wildlife 4034 Fairview Industrial Drive SE Salem, Oregon 97302, 30 https://odfw.forestry.oregonstate.edu/willamettesalmonidrme/sites/default/files/2016_sandy_basin_spring_chinook_spawning_survey.pdf (2016).Cramer, S. P. Fish and habitat surveys of the lower Sandy and Bull Run rivers. Report of SP Cramer&Associates, Inc. to Portland General Electric and Portland Water bureau, Portland, Oregon (1998).Westley, P. A. Documentation of en route mortality of summer chum salmon in the Koyukuk river, Alaska and its potential linkage to the heatwave of 2019. Ecol. Evol. 10, 10296–10304 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Bowerman, T. E., Keefer, M. L. & Caudill, C. C. Elevated stream temperature, origin, and individual size influence Chinook salmon prespawn mortality across the Columbia River Basin. Fish. Res. 237, 105874 (2021).Article 

Google Scholar 
Beechie, T. J. et al. Process-based principles for restoring river ecosystems. Bioscience 60, 209–222 (2010).Article 

Google Scholar 
Crosato, A. & Saleh, M. S. Numerical study on the effects of floodplain vegetation on river planform style. Earth Surf. Process. Landf. 36, 711–720 (2011).ADS 
Article 

Google Scholar 
Schuurman, F., Marra, W. A. & Kleinhans, M. G. Physics-based modeling of large braided sand-bed rivers: Bar pattern formation, dynamics, and sensitivity. J. Geophys. Res. Earth Surf. 118, 2509–2527 (2013).ADS 
Article 

Google Scholar 
Singh, U., Crosato, A., Giri, S. & Hicks, M. Sediment heterogeneity and mobility in the morphodynamic modelling of gravel-bed braided rivers. Adv. Water Resour. 104, 127–144 (2017).ADS 
Article 

Google Scholar 
van ledden, M. Sand-Mud Segregation in Estuaries and Tidal Basins. (PhD Thesis, University of Technology Delft, 2003).Kandiah, A. Fundamental Aspects of Surface Erosion of Cohesive Soils. (University of California, Davis, 1974).Partheniades, E. Cohesive Sediments in Open Channels: Erosion, Transport and Deposition (Butterworth-Heinemann, 2009).
Google Scholar 
Jiang, J. An Examination of Estuarine Lutocline Dynamics. (PhD Thesis, University of Florida, USA, 1999).Exner, F. M. Uber die wechselwirkung zwischen wasser und geschiebe in flussen (about the interaction between water and bedload in rivers). Akad. Wiss. Wien Math. Naturwiss. Kl. 134, 165–204 (1925).
Google Scholar 
Ikeda, S. Incipient motion of sand particles on side slopes. J. Hydraul. Div. 108, 95–114 (1982).Article 

Google Scholar 
Bagnold, R. A. An approach to the sediment transport problem from general physics. Physiographic and hydraulic studies of rivers in US Geological Survey Professional Paper, vol. 422 I, 231–291 (1966).Stillwater Sciences. Numerical modeling of sediment transport in the Sandy river, Oregon following removal of Marmot dam. (2000).Ashida, K. & Michiue, M. Study on hydraulic resistance and bed transport rate in alluvial stream. Proc. Jpn. Soc. Civ. Eng. 201, 59–69 (1972).Article 

Google Scholar 
Panthi, M. Generation and Fate of Fine Sediment from Dam Flushing. (MSc Thesis, IHE Delft, Institute for Water Education, the Netherlands, 2020).Meyer-Peter, E. & Müller, R. Formulas for bed-load transport. in IAHSR 2nd Meeting, Stockholm, Appendix 2 (IAHR, 1948).Podolak, C. & Pittman, S. Marmot Dam Removal Geomorphic Monitoring & Modeling Project: Final Report. Sandy river basin watershed council. (2011).Keith, M. K. Reservoir Evolution Following the Removal of Marmot Dam on the Sandy River, Oregon. (MSc Thesis, Portland State University, Oregon, USA, 2012).Redding, J. M., Schreck, C. B. & Everest, F. H. Physiological effects on coho salmon and steelhead of exposure to suspended solids. Trans. Am. Fish. Soc. 116, 737–744 (1987).Article 

Google Scholar 
Lisle, T. E. Sediment transport and resulting deposition in spawning gravels, north coastal California. Water Resour. Res. 25, 1303–1319 (1989).ADS 
Article 

Google Scholar 
Pitlick, J. & Wilcock, P. Relations between streamflow, sediment transport, and aquatic habitat in regulated rivers. In Geomorphic Processes and Riverine Habitat (eds Dorava, J. M. et al.) 185–198 (American Geophysical Union, 2001).Chapter 

Google Scholar 
Toupin, L. Freshwater Habitats: Life in Freshwater Ecosystems. (Franklin Watts, Watts Library, 2005).Bovee, K. D. A guide to Stream Habitat Analysis Using the Instream Flow Incremental Methodology. IFIP No. 12. FWS/OBS https://pubs.er.usgs.gov/publication/fwsobs82_26 (1982).Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151 (2006).Article 

Google Scholar 
Vadas, R. L. & Orth, D. J. Formulation of habitat suitability models for stream fish guilds: Do the standard methods work?. Trans. Am. Fish. Soc. 130, 217–235 (2001).Article 

Google Scholar 
Moir, H. J., Gibbins, C. N., Soulsby, C. & Youngson, A. F. PHABSIM modelling of Atlantic salmon spawning habitat in an upland stream: Testing the influence of habitat suitability indices on model output. River Res. Appl. 21, 1021–1034 (2005).Article 

Google Scholar 
Hauer, C. et al. State of the art, shortcomings and future challenges for a sustainable sediment management in hydropower: A review. Renew. Sustain. Energy Rev. 98, 40–55 (2018).Article 

Google Scholar 
Koizumi, I., Kanazawa, Y. & Tanaka, Y. The fishermen were right: Experimental evidence for tributary refuge hypothesis during floods. Zool. Sci. 30, 375–379 (2013).Article 

Google Scholar 
Quadroni, S. et al. Effects of sediment flushing from a small Alpine reservoir on downstream aquatic fauna. Ecohydrology 9, 1276–1288 (2016).Article 

Google Scholar 
Bond, M. H., Nodine, T. G., Beechie, T. J. & Zabel, R. W. Estimating the benefits of widespread floodplain reconnection for Columbia river Chinook salmon. Can. J. Fish. Aquat. Sci. 76, 1212–1226 (2019).Article 

Google Scholar 
Stanford, J. A., Lorang, M. S. & Hauer, F. R. The shifting habitat mosaic of river ecosystems. Int. Ver. Theor. Angew. Limnol. Verh. 29, 123–136 (2005).
Google Scholar  More

Cloern, J. E., Foster, S. Q. & Kleckner, A. E. Phytoplankton primary production in the world’s estuarine-coastal ecosystems. Biogeosciences 11, 2477–2501 (2014).ADS 
Article 

Google Scholar 
Field, C. B., Behrenfeld, M. J., Randerson, J. T. & Falkowski, P. Primary production of the biosphere: Integrating terrestrial and oceanic components. Science (80-) 281, 237–240 (1998).ADS 
CAS 
Article 

Google Scholar 
Gervais, C. R., Champion, C. & Pecl, G. T. Species on the move around the Australian coastline: A continental scale review of climate-driven species redistribution in marine systems. Glob. Chang. Biol. 685, 171–181 (2021).
Google Scholar 
Scanes, E., Scanes, P. R. & Ross, P. M. Climate change rapidly warms and acidifies Australian estuaries. Nat. Commun. 11, 1–11 (2020).Article 
CAS 

Google Scholar 
Rodrigues, J. G. et al. Marine and coastal cultural ecosystem services: knowledge gaps and research priorities. One Ecosyst. 2 (2017).O’Brien, T. D., Lorenzoni, L., Isensee, K. & Valdés, L. What are marine ecological time series telling us about the ocean. A status report. IOC Tech. Ser. 129, 1–297 (2017).
Google Scholar 
Ajani, P. A., Davies, C. H., Eriksen, R. S. & Richardson, A. J. Global warming impacts micro-phytoplankton at a long-term Pacific Ocean Coastal Station. Front. Mar. Sci. 7, 878 (2020).Article 

Google Scholar 
Wiltshire, K. H. et al. Helgoland roads, North Sea: 45 years of change. Estuaries Coasts 33, 295–310 (2010).CAS 
Article 

Google Scholar 
Benway, H. M. et al. Ocean time series observations of changing marine ecosystems: An era of integration, synthesis, and societal applications. Front. Mar. Sci. 6, 393 (2019).Article 

Google Scholar 
Wilson, J. M., Chamberlain, E. J., Erazo, N., Carter, M. L. & Bowman, J. S. Recurrent microbial community types driven by nearshore and seasonal processes in coastal Southern California. Environ. Microbiol. 23, 3225 (2021).CAS 
PubMed 
Article 

Google Scholar 
Keeling, C. D. et al. Atmospheric carbon dioxide variations at Mauna Loa observatory, Hawaii. Tellus 28, 538–551 (1976).ADS 
CAS 

Google Scholar 
Doney, S. C., Fabry, V. J., Feely, R. A. & Kleypas, J. A. Ocean acidification: The other CO2 problem. Ann. Rev. Mar. Sci. 1, 169–192 (2009).PubMed 
Article 

Google Scholar 
Falkowski, P. G. Evolution of the nitrogen cycle and its influence on the biological sequestration of CO2 in the ocean. Nature 387, 272–275 (1997).ADS 
CAS 
Article 

Google Scholar 
Brown, M. V. et al. Systematic, continental scale temporal monitoring of marine pelagic microbiota by the Australian Marine Microbial Biodiversity Initiative. Sci. Data 5, 180130 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Buttigieg, P. L. et al. Marine microbes in 4D—Using time series observation to assess the dynamics of the ocean microbiome and its links to ocean health. Curr. Opin. Microbiol. 43, 169–185 (2018).PubMed 
Article 

Google Scholar 
Chow, C.-E.T. et al. Temporal variability and coherence of euphotic zone bacterial communities over a decade in the southern California Bight. ISME J. 7, 2259–2273 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Krabberød, A. K. et al. Long-term patterns of an interconnected core marine microbiota. bioRxiv 2021.03.18.435965. https://doi.org/10.1101/2021.03.18.435965 (2021).Lambert, S. et al. Rhythmicity of coastal marine picoeukaryotes, bacteria and archaea despite irregular environmental perturbations. ISME J. 13, 388–401 (2019).PubMed 
Article 

Google Scholar 
Auladell, A. et al. Seasonal niche differentiation among closely related marine bacteria. ISME J. https://doi.org/10.1038/s41396-021-01053-2 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Robicheau, B. M., Tolman, J., Bertrand, E. M. & LaRoche, J. Highly-resolved interannual phytoplankton community dynamics of the coastal Northwest Atlantic. ISME Commun. 2(1), 1–12 (2022).Article 

Google Scholar 
Legendre, L., Rivkin, R. B., Weinbauer, M. G., Guidi, L. & Uitz, J. The microbial carbon pump concept: Potential biogeochemical significance in the globally changing ocean. Prog. Oceanogr. 134, 432–450 (2015).ADS 
Article 

Google Scholar 
Hutchins, D. A. & Fu, F. Microorganisms and ocean global change. Nat. Microbiol. 2, 1–11 (2017).Article 
CAS 

Google Scholar 
Gross, T., Rudolf, L., Levin, S. A. & Dieckmann, U. Generalized models reveal stabilizing factors in food webs. Science (80-). 325, 747–750 (2009).ADS 
CAS 
Article 

Google Scholar 
Gilbert, J. A. et al. Defining seasonal marine microbial community dynamics. ISME J. 6, 298–308 (2012).CAS 
PubMed 
Article 

Google Scholar 
Karl, D. M. & Church, M. J. Microbial oceanography and the Hawaii Ocean time-series programme. Nat. Rev. Microbiol. 12, 699–713 (2014).CAS 
PubMed 
Article 

Google Scholar 
Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pachiadaki, M. G. et al. Charting the complexity of the marine microbiome through single-cell genomics. Cell 179, 1623–1635 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Walsh, D. A. et al. Metagenome of a versatile chemolithoautotroph from expanding oceanic dead zones. Science (80-). 326, 578–582 (2009).ADS 
CAS 
Article 

Google Scholar 
Shan, S., Sheng, J., Thompson, K. R. & Greenberg, D. A. Simulating the three-dimensional circulation and hydrography of Halifax Harbour using a multi-nested coastal ocean circulation model. Ocean Dyn. 61, 951–976 (2011).ADS 
Article 

Google Scholar 
Petrie, B. & Yeats, P. Simple models of the circulation, dissolved metals, suspended solids and nutrients in Halifax Harbour. Water Qual. Res. J. 25, 325–350 (1990).CAS 
Article 

Google Scholar 
WK, W. L. The State of Phytoplankton and Bacterioplankton at the Compass Buoy Station: Bedford Basin Monitoring Program 1992–2013. (Fisheries and Oceans Canada = Pêches et Océans Canada, 2014).Haas, S. et al. Physical mixing in coastal waters controls and decouples nitrification via biomass dilution. Proc. Natl. Acad. Sci. 118, e2004877118 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ibarbalz, F. M. et al. Global trends in marine plankton diversity across kingdoms of life. Cell 179, 1084-1097.e21 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mittelbach, G. G. et al. What is the observed relationship between species richness and productivity?. Ecology 82, 2381–2396 (2001).Article 

Google Scholar 
Pernthaler, J. Competition and niche separation of pelagic bacteria in freshwater habitats. Environ. Microbiol. 19, 2133–2150 (2017).CAS 
PubMed 
Article 

Google Scholar 
Teeling, H. et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science (80-) 336, 608–611 (2012).ADS 
CAS 
Article 

Google Scholar 
Vallina, S. M. et al. Global relationship between phytoplankton diversity and productivity in the ocean. Nat. Commun. 5, 4299 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Wietz, M. et al. The polar night shift: Annual dynamics and drivers of microbial community structure in the Arctic Ocean. bioRxiv 2021.04.08.436999. https://doi.org/10.1101/2021.04.08.436999 (2021).Ladau, J. et al. Global marine bacterial diversity peaks at high latitudes in winter. ISME J. 7, 1669–1677 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Sunagawa, S. et al. Structure and function of the global ocean microbiome. Science (80-). 348, 1261359 (2015).Article 
CAS 

Google Scholar 
Brown, J. H. Why are there so many species in the tropics?. J. Biogeogr. 41, 8–22 (2014).PubMed 
Article 

Google Scholar 
Raes, E. J. et al. Oceanographic boundaries constrain microbial diversity gradients in the South Pacific Ocean. Proc. Natl. Acad. Sci. 115, E8266–E8275 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Fuhrman, J. A. et al. A latitudinal diversity gradient in planktonic marine bacteria. Proc. Natl. Acad. Sci. 105, 7774–7778 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Raes, E. J., Bodrossy, L., van de Kamp, J., Bissett, A. & Waite, A. M. Marine bacterial richness increases towards higher latitudes in the eastern Indian Ocean. Limnol. Oceanogr. Lett. 3, 10–19 (2018).Article 

Google Scholar 
Oksanen, J. et al. The vegan package. Commun. Ecol. Packag. 10, 719 (2007).
Google Scholar 
Mestre, M. et al. Sinking particles promote vertical connectivity in the ocean microbiome. Proc. Natl. Acad. Sci. 115, E6799–E6807 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
El-Swais, H., Dunn, K. A., Bielawski, J. P., Li, W. K. W. & Walsh, D. A. Seasonal assemblages and short-lived blooms in coastal north-west A tlantic O cean bacterioplankton. Environ. Microbiol. 17, 3642–3661 (2015).CAS 
PubMed 
Article 

Google Scholar 
Raes, E. J. et al. Metabolic pathways inferred from a bacterial marker gene illuminate ecological changes across South Pacific frontal boundaries. Nat. Commun. 12, 2213 (2021).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome datasets are compositional: And this is not optional. Front. Microbiol. 8, 2224 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Musat, N. et al. A single-cell view on the ecophysiology of anaerobic phototrophic bacteria. Proc. Natl. Acad. Sci. 105, 17861–17866 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wong, H. L., MacLeod, F. I., White, R. A., Visscher, P. T. & Burns, B. P. Microbial dark matter filling the niche in hypersaline microbial mats. Microbiome 8, 1–14 (2020).Article 
CAS 

Google Scholar 
De Cáceres, M. How to use the indicspecies package (ver. 1.7.1). R Proj. 2, 29 (2013).
Google Scholar 
Hood, R. R. et al. Pelagic functional group modeling: Progress, challenges and prospects. Deep Sea Res. Part II Top. Stud. Oceanogr. 53, 459–512 (2006).ADS 
Article 

Google Scholar 
Sun, S., Jones, R. B. & Fodor, A. A. Inference-based accuracy of metagenome prediction tools varies across sample types and functional categories. Microbiome 8, 1–9 (2020).CAS 
Article 

Google Scholar 
Lynam, C. P. et al. Interaction between top-down and bottom-up control in marine food webs. Proc. Natl. Acad. Sci. 114, 1952–1957 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhou, Z. et al. Gammaproteobacteria mediating utilization of methyl-, sulfur- and petroleum organic compounds in deep ocean hydrothermal plumes. ISME J. 14, 3136–3148 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Dede, B. et al. Niche differentiation of sulfur-oxidizing bacteria (SUP05) in submarine hydrothermal plumes. ISME J. 16(6), 1479–1490 (2022).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lavik, G. et al. Detoxification of sulphidic African shelf waters by blooming chemolithotrophs. Nature 457, 581–584 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Swan, B. K. et al. Potential for chemolithoautotrophy among ubiquitous bacteria lineages in the dark ocean. Science (80-) 333, 1296–1300 (2011).ADS 
CAS 
Article 

Google Scholar 
Taguchi, S. & Platt, T. Assimilation of 14CO2 in the dark compared to phytoplankton production in a small coastal inlet. Estuar. Coast. Mar. Sci. 5, 679–684 (1977).ADS 
CAS 
Article 

Google Scholar 
Platt, T. & Irwin, B. Phytoplankton Production and Nutrients in Bedford Basin, 1969–1970. (1971).Vega, S. et al. Morphological plasticity in a sulfur-oxidizing marine bacterium from the SUP05 clade enhances dark carbon fixation. MBio 10, e00216-e219 (2021).
Google Scholar 
Mattes, T. E., Ingalls, A. E., Burke, S. & Morris, R. M. Metabolic flexibility of SUP05 under low DO growth conditions. Environ. Microbiol. 23, 2823 (2020).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Brown, M. V. et al. Global biogeography of SAR11 marine bacteria. Mol. Syst. Biol. 8, 595 (2012).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Martiny, A. C., Coleman, M. L. & Chisholm, S. W. Phosphate acquisition genes in Prochlorococcus ecotypes: Evidence for genome-wide adaptation. Proc. Natl. Acad. Sci. 103, 12552–12557 (2006).Zorz, J. et al. Drivers of regional bacterial community structure and diversity in the Northwest Atlantic Ocean. Front. Microbiol. 10, 281 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Comeau, A. M., Douglas, G. M. & Langille, M. G. I. Microbiome helper: A custom and streamlined workflow for microbiome research. MSystems 2, e00127 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: Assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).CAS 
PubMed 
Article 

Google Scholar 
Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1, e00009-15 (2016).PubMed 
Article 

Google Scholar 
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10 (2011).Article 

Google Scholar 
Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: A fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614–620 (2014).CAS 
PubMed 
Article 

Google Scholar 
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Amir, A. et al. Deblur rapidly resolves single-nucleotide community sequence patterns. MSystems 2, 191–16 (2017).
Google Scholar 
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Langille, M. G. I. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lahti L. & Shetty, S.A. Tools for Microbiome Analysis in R. Microbiome Package Version 1.7.21. R/Bioconductor http://microbiome.github.com/microbiome. (2017).Team, R. C. R: A Language and Environment for Statistical Computing. (2013).Wickham, H. ggplot2. Wiley Interdiscip. Rev. Comput. Stat. 3, 180–185 (2011).Article 

Google Scholar 
Schlitzer, R. Ocean Data View. 2018. Available odv. awi. (2015).Hijmans, R. J., Williams, E., Vennes, C. & Hijmans, M. R. J. Package ‘geosphere’. in Spherical Trigonometry. Vol. 1 (2017).Wickham, H. The split-apply-combine strategy for data analysis. J. Stat. Softw. 40, 1–29 (2011).
Google Scholar 
Groemping, U. & Matthias, L. Package ‘relaimpo’. (2021).Clarke, K. R. & Gorley, R. N. Primer. Prim. Plymouth (2006).Chytrý, M., Tichý, L., Holt, J. & Botta-Dukát, Z. Determination of diagnostic species with statistical fidelity measures. J. Veg. Sci. 13, 79–90 (2002).Article 

Google Scholar 
Tichy, L. & Chytry, M. Statistical determination of diagnostic species for site groups of unequal size. J. Veg. Sci. 17, 809–818 (2006).Article 

Google Scholar  More

Arora, V. K. et al. Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases. Geophys. Res. Lett. https://doi.org/10.1029/2010GL046270 (2011).Article 

Google Scholar 
Tutak, M. & Brodny, J. Renewable energy consumption in economic sectors in the EU-27. The impact on economics, environment and conventional energy sources. A 20-year perspective. J. Clean. Prod. 345, 131076 (2022).Article 

Google Scholar 
Acheampong, A. O. & Boateng, E. B. Modelling carbon emission intensity: Application of artificial neural network. J. Clean. Prod. 225, 833–856 (2019).Article 

Google Scholar 
Zhou, L. A. Governing China’s local officials: An analysis of promotion tournament model. Econ. Res. J. 07, 36–50 (2007) (in Chinese).
Google Scholar 
Luo, Z. & Qi, B. The effects of environmental regulation on industrial transfer and upgrading and banking synergetic development—Evidence from water pollution control in the Yangtze River Basin. Econ. Res. J. 56(02), 174–189 (2021).
Google Scholar 
Blumstein, C., Krieg, B., Schipper, L. & York, C. Overcoming social and institutional barriers to energy conservation. Energy 5(4), 355–371 (1980).Article 

Google Scholar 
Zhang, L. Energy conservation and emission reduction: An inevitable choice of China’s energy strategy. Sustain. Energy 6, 21–30 (2016).ADS 
Article 

Google Scholar 
Bhuiyan, M. A. H., Siwar, C., Ismail, S. M. & Islam, R. The role of government for ecotourism development: Focusing on east coast economic region. J. Soc. Sci. 7(4), 557 (2011).
Google Scholar 
Fan, G., Su, M. & Cao, J. An economic analysis of consumption and carbon emission responsibility. Econ. Res. J. 45(01), 4–14 (2010) (in Chinese).
Google Scholar 
Xie, J. G. & Jiang, P. S. Embodied energy in international trade of China: Calculation and decomposition. China Econ. Q. 13(04), 1365–1392 (2014) (in Chinese).
Google Scholar 
Wu, J., Cui, C., Mei, X., Xu, Q. & Zhang, P. Migration of manufacturing industries and transfer of carbon emissions embodied in trade: Empirical evidence from China and Thailand. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-021-14674-z (2021).Article 

Google Scholar 
Porter, M. E. & Van der Linde, C. Toward a new conception of the environment-competitiveness relationship. J. Econ. Perspect. 9(4), 97–118 (1995).Article 

Google Scholar 
Zhang, X. P. & Cheng, X. M. Energy consumption, carbon emissions, and economic growth in China. Ecol. Econ. 68(10), 2706–2712 (2009).Article 

Google Scholar 
Wang, B. & Liu, G. T. Energy conservation, emission reduction and green economic growth in China: From the perspective of total factor productivity. China Ind. Econ. 05, 57–69 (2015) (in Chinese).
Google Scholar 
Cheng, Y. Q., Wang, Z. Y., Zhang, S. Z., Ye, X. Y. & Jiang, H. M. Spatial econometric analysis of carbon emission intensity and its driving factors from energy consumption in China. Acta Geogr. Sin. 68(10), 1418–1431 (2013) (in Chinese).
Google Scholar 
Peng, X. & Cui, H. R. Research on the effects of energy structure adjustment in China on Carbon Intensity. J. Dalian Univ. Technol. (Soc. Sci. Ed.) 37(01), 11–16 (2016) (in Chinese).
Google Scholar 
Xiao, T. & Liu, H. Empirical research on industrial structure adjustment and energy conservation and emission reduction. Economist 09, 58–68 (2014) (in Chinese).
Google Scholar 
Sheng, P., He, Y. & Guo, X. The impact of urbanization on energy consumption and efficiency. Energy Environ. 28(7), 673–686 (2017).Article 

Google Scholar 
Sun, H., Samuel, C. A., Amissah, J. C. K., Taghizadeh-Hesary, F. & Mensah, I. A. Non-linear nexus between CO2 emissions and economic growth: A comparison of OECD and B&R countries. Energy 212, 118637 (2020).Article 

Google Scholar 
He, J. K. Economic analysis and effectiveness evaluation on China’s CO2 emission mitigation target. Stud. Sci. Sci. 01, 9–17 (2011) (in Chinese).
Google Scholar 
Meng, W. et al. Study on the developmental strategy of the energy saving and environmental protection industry in China. Strat. Study CAE 18(04), 1–8 (2016) (in Chinese).
Google Scholar 
He, J., Wang, M. M., Zhang, Z. L., Li, M. & Shi, H. X. Equal attention should be paid to boyh construction and operation of buildings for energy efficiency and emission reduction: Findings from current data on resource and environment loads in China’s building industry. Sci. Technol. Rev. 36(05), 8–13 (2018) (in Chinese).
Google Scholar 
Xie, C. X. & Gao, Y. B. Research on innovative development path of energy conservation and emission reduction from the perspective of low carbon economy. China Resour. Compr. Util. 37(12), 92–94 (2019) (in Chinese).
Google Scholar 
Dong, J. F., Deng, C., Wang, X. M. & Zhang, X. L. Multilevel index decomposition of energy-related carbon emissions and their decoupling from economic growth in Northwest China. Energies 9(9), 680 (2016).Article 

Google Scholar 
Duan, Y. Q. & Xu, S. L. Command-based environmental regulation and heavy polluters’ investment: incentive or disincentive? A quasi-Natural experiment based on the new environmental protection law. J. Financ. Dev. Res. 07, 54–61 (2021) (in Chinese).
Google Scholar 
Cai, W. & Xu, F. The impact of the new environmental protection law on eco-innovation: Evidence from green patent data of Chinese listed companies. Environ. Sci. Pollut. Res. 29(7), 10047–10062 (2022).Article 

Google Scholar 
Ning, Y. et al. Energy conservation and emission reduction path selection in China: A simulation based on bi-level multi-objective optimization model. Energy Policy 137, 111116 (2020).Article 

Google Scholar 
Hughes, S., Giest, S. & Tozer, L. Accountability and data-driven urban climate governance. Nat. Clim. Change 10(12), 1085–1090 (2020).ADS 
Article 

Google Scholar 
Feng, L., Chen, Z. & Chen, H. Does the central environmental protection inspectorate accountability system improve environmental quality?. Sustainability 14(11), 6575 (2022).Article 

Google Scholar 
Ulucak, R. How do environmental technologies affect green growth? Evidence from BRICS economies. Sci. Total Environ. 712, 136504 (2020).ADS 
PubMed 
Article 

Google Scholar 
Shahbaz, M., Raghutla, C., Chittedi, K. R., Jiao, Z. & Vo, X. V. The effect of renewable energy consumption on economic growth: Evidence from the renewable energy country attractive index. Energy 207, 118162 (2020).Article 

Google Scholar 
Yang, Y. & Niu, X. Impact of the new “Environmental Protection Law” on the efficiency of listed companies in heavily polluting industries in China: Based on the research perspective of “Porter Hypothesis”. Manag. Rev. 33(10), 55–69 (2021).
Google Scholar 
Wong, C. W., Wong, C. Y., Boon-Itt, S. & Tang, A. K. Strategies for building environmental transparency and accountability. Sustainability 13(16), 9116 (2021).Article 

Google Scholar 
Liu, Z. et al. Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature 524(7565), 335–338 (2015).ADS 
PubMed 
Article 

Google Scholar 
Litman, T. Comprehensive evaluation of energy conservation and emission reduction policies. Transp. Res. Part A Policy Pract. 47, 153–166 (2013).Article 

Google Scholar 
Zhou, P., Ang, B. W. & Han, J. Y. Total factor carbon emission performance: A Malmquist index analysis. Energy Econ. 32(1), 194–201 (2010).Article 

Google Scholar 
Steg, L. Promoting household energy conservation. Energy Policy 36(12), 4449–4453 (2008).Article 

Google Scholar 
Yang, Q. & Liu, H. J. Regional difference decomposition and influence factors of China’s carbon dioxide emissions. J. Quant. Tech. Econ. 29(05), 36–49 (2012) (in Chinese).
Google Scholar 
Yao, L. J. & Sun, C. Y. Italy’s low carbon economic development policy. Sci. Technol. Ind. China 11, 58–60 (2007) (in Chinese).
Google Scholar 
Li, L. et al. Energy conservation and emission reduction policies for the electric power industry in China. Energy Policy 39(6), 3669–3679 (2011).Article 

Google Scholar 
Dong, F. et al. Drivers of carbon emission intensity change in China. Resour. Conserv. Recycl. 129, 187–201 (2018).Article 

Google Scholar 
Li, X., Hu, Z., Cao, J. & Xu, X. The impact of environmental accountability on air pollution: A public attention perspective. Energy Policy 161, 112733 (2022).Article 

Google Scholar 
Ehrlich, P. R. & Holdren, J. P. Impact of Population Growth: Complacency concerning this component of man’s predicament is unjustified and counterproductive. Science 171(3977), 1212–1217 (1971).ADS 
PubMed 
Article 

Google Scholar 
York, R., Rosa, E. A. & Dietz, T. STIRPAT, IPAT and ImPACT: Analytic tools for unpacking the driving forces of environmental impacts. Ecol. Econ. 46(3), 351–365 (2003).Article 

Google Scholar 
Shao, S., Yang, L. L. & Cao, J. H. Study on influencing of CO2 emissions from industrial energy consumption: An empirical analysis based on STIRPAT model and industrial sectors’ dynamic panel data in Shanghai. J. Finance Econ. 36(11), 16–27 (2010) (in Chinese).
Google Scholar 
Tseng, S. W. Analysis of energy-related carbon emissions in Inner Mongolia, China. Sustainability 11(24), 7008 (2019).Article 

Google Scholar 
Lin, B. & Ouyang, X. Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry. Energy 68, 688–697 (2014).Article 

Google Scholar 
Wang, D., He, W. & Shi, R. How to achieve the dual-control targets of China’s CO2 emission reduction in 2030? Future trends and prospective decomposition. J. Clean. Prod. 213, 1251–1263 (2019).Article 

Google Scholar 
Card, D., & Krueger, A. B. Minimum wages and employment: A case study of the fast food industry in New Jersey and Pennsylvania (1993).Abadie, A. & Gardeazabal, J. The economic costs of conflict: A case study of the Basque Country. Am. Econ. Rev. 93(1), 113–132 (2003).Article 

Google Scholar 
Kaul, A., Klößner, S., Pfeifer, G. & Schieler, M. Standard synthetic control methods: The case of using all preintervention outcomes together with covariates. J. Bus. Econ. Stat. 40(3), 1362–1376 (2022).MathSciNet 
Article 

Google Scholar 
Lin, B. Q. & Li, J. L. Transformation of China’s energy structure under environmental governance constraints: A peak value analysis of coal and carbon dioxide. Soc. Sci. China 09, 84–107 (2015) (in Chinese).
Google Scholar 
Long, X., Naminse, E. Y., Du, J. & Zhuang, J. Nonrenewable energy, renewable energy, carbon dioxide emissions and economic growth in China from 1952 to 2012. Renew. Sustain. Energy Rev. 52, 680–688 (2015).Article 

Google Scholar 
Zhang, W., Zhu, Q. G. & Gao, H. Upgrading of industrial structure, optimizing of energy structure, and low carbon development of industrial system. Econ. Res. J. 51(12), 62–75 (2016) (in Chinese).
Google Scholar 
Wen, Z., Zhang, L., Hou, J. & Liu, H. Mediating effect test procedure and it application. Acta Psychol. Sin. 36(5), 614–620 (2004).
Google Scholar 
He, Y., Yu, W. L. & Yang, M. Z. CEOs with rich career experience, corporate risk-taking and the value of enterprises. China Ind. Econ. 09, 155–173 (2019) (in Chinese).
Google Scholar 
Zhou, D. Q., Wang, Q., Su, B., Zhou, P. & Yao, L. X. Industrial energy conservation and emission reduction performance in China: A city-level nonparametric analysis. Appl. Energy 166, 201–209 (2016).Article 

Google Scholar 
Waheed, R., Sarwar, S. & Wei, C. The survey of economic growth, energy consumption and carbon emission. Energy Rep. 5, 1103–1115 (2019).Article 

Google Scholar 
Yang, Y., Zhou, Y., Poon, J. & He, Z. China’s carbon dioxide emission and driving factors: A spatial analysis. J. Clean. Prod. 211, 640–651 (2019).Article 

Google Scholar 
Apergis, N. & Payne, J. E. Coal consumption and economic growth: Evidence from a panel of OECD countries. Energy Policy 38(3), 1353–1359 (2010).Article 

Google Scholar 
Mujtaba, A., Jena, P. K., Bekun, F. V. & Sahu, P. K. Symmetric and asymmetric impact of economic growth, capital formation, renewable and non-renewable energy consumption on environment in OECD countries. Renew. Sustain. Energy Rev. 160, 112300 (2022).Article 

Google Scholar 
Wolde-Rufael, Y. Coal consumption and economic growth revisited. Appl. Energy 87(1), 160–167 (2010).Article 

Google Scholar  More

Wibbelt, G., Moore, M. S., Schountz, T. & Voigt, C. C. Emerging diseases in Chiroptera: Why bats?. Biol. Let. 6, 438–440 (2010).Article 

Google Scholar 
Gonzalez, V. & Banerjee, A. Molecular, ecological, and behavioural drivers of the bat-virus relationship. iScience 25, 104779 (2022).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Brook, C. E. & Dobson, A. P. Bats as ‘special’reservoirs for emerging zoonotic pathogens. Trends Microbiol. 23, 172–180 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Kosoy, M. et al. Bartonella spp. in bats, Kenya. Emerg. Infect. Dis. 16, 1875–1881 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
Becker, D. J. et al. Livestock abundance predicts vampire bat demography, immune profiles and bacterial infection risk. Philos. Trans. R. Soc. Biol. Sci. 373, 20170089 (2018).Article 
CAS 

Google Scholar 
Muehldorfer, K. Bats and bacterial pathogens: A review. Zoonoses Public Health 60, 93–103 (2013).Article 

Google Scholar 
Taylor, M. L. et al. Geographical distribution of genetic polymorphism of the pathogen Histoplasma capsulatum isolated from infected bats, captured in a central zone of Mexico. FEMS Immunol. Med. Microbiol. 45, 451–458 (2005).PubMed 
Article 
CAS 

Google Scholar 
Schaer, J. et al. High diversity of West African bat malaria parasites and a tight link with rodent Plasmodium taxa. Proc. Natl. Acad. Sci. 110, 17415–17419 (2013).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Evans, N., Bown, K., Timofte, D., Simpson, V. & Birtles, R. Fatal borreliosis in bat caused by relapsing fever spirochete, United Kingdom. Emerg. Infect. Dis. 15, 1331–1333 (2009).PubMed 
PubMed Central 
Article 

Google Scholar 
Muehldorfer, K., Speck, S. & Wibbelt, G. Diseases in free-ranging bats from Germany. BMC Vet. Res. 7, 61 (2011).Article 

Google Scholar 
Muehldorfer, K., Wibbelt, G., Haensel, J., Riehm, J. & Speck, S. Yersinia species isolated from bats, Germany. Emerg. Infect. Dis. 16, 578–581 (2010).Article 

Google Scholar 
Blehert, D. S. et al. Bat white-nose syndrome: An emerging fungal pathogen?. Science 323, 227–227 (2009).PubMed 
Article 
CAS 

Google Scholar 
Barlow, A., Jolliffe, T., Tomlin, M., Worledge, L. & Miller, H. Mycotic dermatitis in a vagrant parti-coloured bat (Vespertilio murinus) in Great Britain. Vet. Rec. 169, 614–614 (2011).PubMed 
Article 

Google Scholar 
Simpson, V. R., Borman, A. M., Fox, R. I. & Mathews, F. Cutaneous mycosis in a Barbastelle bat (Barbastella barbastellus) caused by Hyphopichia burtonii. J. Vet. Diagn. Invest. 25, 551–554 (2013).PubMed 
Article 

Google Scholar 
Frick, W. F. et al. An emerging disease causes regional population collapse of a common North American bat species. Science 329, 679–682 (2010).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Hecht-Höger, A. et al. Plasma proteomic profiles differ between European and North American myotid bats colonized by Pseudogymnoascus destructans. Mol. Ecol. 29, 1745–1755 (2020).PubMed 
Article 

Google Scholar 
Baker, M., Schountz, T. & Wang, L. F. Antiviral immune responses of bats: A review. Zoonoses Public Health 60, 104–116 (2013).PubMed 
Article 
CAS 

Google Scholar 
Baker, M. L. & Zhou, P. in Bats and Viruses Vol. 1 (eds Lin-Fa Wang & Christopher Cowled) Ch. 14, 327–348 (John Wiley & Sons, Inc., 2015).Wang, L.-F., Walker, P. J. & Poon, L. L. M. Mass extinctions, biodiversity and mitochondrial function: Are bats ‘special’ as reservoirs for emerging viruses?. Curr. Opin. Virol. 1, 649–657 (2011).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Lee, K. A. Linking immune defenses and life history at the levels of the individual and the species. Integr. Comp. Biol. 46, 1000–1015 (2006).PubMed 
Article 
CAS 

Google Scholar 
Murphy, K. Janeway’s Immunobiology 8th edn. (Garland Science, 2012).
Google Scholar 
Gruys, E., Toussaint, M., Niewold, T. & Koopmans, S. Acute phase reaction and acute phase proteins. J. Zhejiang Univ. Sci. B Biomed. Biotechnol. 6, 1045–1056 (2005).CAS 

Google Scholar 
Cray, C., Zaias, J. & Altman, N. H. Acute phase response in animals: A review. Comp. Med. 59, 517–526 (2009).PubMed 
PubMed Central 
CAS 

Google Scholar 
Hart, B. L. Biological basis of the behavior of sick animals. Neurosci. Biobehav. Rev. 12, 123–137 (1988).PubMed 
Article 
CAS 

Google Scholar 
Owen-Ashley, N. T. & Wingfield, J. C. Acute phase responses of passerine birds: Characterization and seasonal variation. J. Ornithol. 148, S583–S591 (2007).Article 

Google Scholar 
Kozak, W., Conn, C. A. & Kluger, M. J. Lipopolysaccharide induces fever and depresses locomotor-activity in unrestrained mice. Am. J. Physiol. 266, R125–R135 (1994).PubMed 
CAS 

Google Scholar 
Copeland, S. et al. Acute inflammatory response to endotoxin in mice and humans. Clin. Diagn. Lab. Immunol. 12, 60–67 (2005).PubMed 
PubMed Central 
CAS 

Google Scholar 
Evans, S. S., Repasky, E. A. & Fisher, D. T. Fever and the thermal regulation of immunity: The immune system feels the heat. Nat. Rev. Immunol. 15, 335–349 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Stockmaier, S., Dechmann, D. K. N., Page, R. A. & Teague O’Mara, M. No fever and leucocytosis in response to a lipopolysaccharide challenge in an insectivorous bat. Biol. Let. 11, 20150576 (2015).Article 
CAS 

Google Scholar 
Martin, L. B., Scheuerlein, A. & Wikelski, M. Immune activity elevates energy expenditure of house sparrows: A link between direct and indirect costs?. Proc. R. Soc. Lond. B Biol. Sci. 270, 153–158 (2003).Article 

Google Scholar 
Sheldon, B. C. & Verhulst, S. Ecological immunology: Costly parasite defences and trade-offs in evolutionary ecology. Trends Ecol. Evol. 11, 317–321 (1996).PubMed 
Article 
CAS 

Google Scholar 
Bonneaud, C. et al. Assessing the cost of mounting an immune response. Am. Nat. 161, 367–379 (2003).PubMed 
Article 

Google Scholar 
Audebert, H. J., Pellkofer, T. S., Wimmer, M. L. & Haberl, R. L. Progression in lacunar stroke is related to elevated acute phase parameters. Eur. Neurol. 51, 125–131 (2004).PubMed 
Article 
CAS 

Google Scholar 
Lee, K. A., Martin, L. B. & Wikelski, M. C. Responding to inflammatory challenges is less costly for a successful avian invader, the house sparrow (Passer domesticus), than its less-invasive congener. Oecologia 145, 244–251 (2005).ADS 
PubMed 
Article 

Google Scholar 
Owen-Ashley, N. T., Turner, M., Hahn, T. P. & Wingfield, J. C. Hormonal, behavioral, and thermoregulatory responses to bacterial lipopolysaccharide in captive and free-living white-crowned sparrows (Zonotrichia leucophrys gambelii). Horm. Behav. 49, 15–29 (2006).PubMed 
Article 
CAS 

Google Scholar 
Coon, C. A. C., Warne, R. W. & Martin, L. B. Acute-phase responses vary with pathogen identity in house sparrows (Passer domesticus). Am. J. Physiol. Regul. Integr. Comp. Physiol. 300, R1418–R1425 (2011).PubMed 
Article 
CAS 

Google Scholar 
Kimura, M. et al. Comparison of acute phase responses induced in rabbits by lipopolysaccharide and double-stranded RNA. Am. J. Physiol. Regul. Integr. Comp. Physiol. 267, R1596–R1605 (1994).Article 
CAS 

Google Scholar 
Gomez, C. R., Goral, J., Ramirez, L., Kopf, M. & Kovacs, E. J. Aberrant acute-phase response in aged interleukin-6 knockout mice. Shock 25, 581–585 (2006).PubMed 
Article 
CAS 

Google Scholar 
Barrientos, R. M., Watkins, L. R., Rudy, J. W. & Maier, S. F. Characterization of the sickness response in young and aging rats following E. coli infection. Brain Behav Immun. 23, 450–454 (2009).PubMed 
PubMed Central 
Article 

Google Scholar 
Sköld-Chiriac, S., Nord, A., Tobler, M., Nilsson, J. -Å. & Hasselquist, D. Body temperature changes during simulated bacterial infection in a songbird: Fever at night and hypothermia during the day. J. Exp. Biol. 218, 2961–2969 (2015).PubMed 

Google Scholar 
Sköld-Chiriac, S., Nord, A., Nilsson, J. -Å. & Hasselquist, D. Physiological and behavioral responses to an acute-phase response in zebra finches: Immediate and short-term effects. Physiol. Biochem. Zool. 87, 288–298 (2014).PubMed 
Article 

Google Scholar 
Fritze, M. et al. Immune response of hibernating European bats to a fungal challenge. Biol. Open 8, bio046078 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Triana-Llanos, C., Guerrero-Chacón, A. L., Rivera-Ruíz, D., Rojas-Díaz, V. & Niño-Castro, A. The acute phase response elicited by a viral-like molecular pattern increases energy expenditure in Artibeus lituratus. Biologia 74, 667–673 (2019).Article 

Google Scholar 
Schneeberger, K., Czirják, G. Á. & Voigt, C. C. Inflammatory challenge increases measures of oxidative stress in a free-ranging, long-lived mammal. J. Exp. Biol. 216, 4514–4519 (2013).PubMed 
CAS 

Google Scholar 
Allen, L. C. et al. Roosting ecology and variation in adaptive and innate immune system function in the Brazilian free-tailed bat (Tadarida brasiliensis). J. Comp. Physiol. B. 179, 315–323 (2009).PubMed 
Article 

Google Scholar 
Otálora-Ardila, A., Herrera, M. L. G., Flores-Martínez, J. J. & Welch, K. C. Jr. Metabolic cost of the activation of immune response in the fish-eating myotis (Myotis vivesi): The effects of inflammation and the acute phase response. PLoS ONE 11, e0164938 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ohmer, M. E. B. et al. Applied ecoimmunology: Using immunological tools to improve conservation efforts in a changing world. Conserv. Physiol. 9, coab074 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Becker, D. J., Seifert, S. N. & Carlson, C. J. Beyond infection: Intergrating competence into reservoir host prediction. Trends Ecol. Evol. 35, P1062–P1065 (2020).Article 

Google Scholar 
Kacprzyk, J. et al. A potent anti-inflammatory response in bat macrophages may be linked to extended longevity and viral tolerance. Acta Chiropterologica 19, 219–228 (2017).Article 

Google Scholar 
Langlois, M. R. & Delanghe, J. R. Biological and clinical significance of haptoglobin polymorphism in humans. Clin. Chem. 42, 1589–1600 (1996).PubMed 
Article 
CAS 

Google Scholar 
Field, K. A. et al. The white-nose syndrome transcriptome: activation of anti-fungal host responses in wing tissue of hibernating little brown myotis. PLoS Pathog. 11, e1005168 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Fritze, M. et al. Determinants of defence strategies of a hibernating European bat species towards the fungal pathogen Pseudogymnoascus destructans. Dev. Comp. Immunol. 119, 104017 (2021).PubMed 
Article 
CAS 

Google Scholar 
Moreno, K. et al. Sick bats stay home alone: Fruit bats practice social distancing when faced with an immunological challenge. Ann. N. Y. Acad. Sci. 1505, 178–190 (2021).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Otálora-Ardila, A., Herrera, M. L. G., Flores-Martínez, J. J. & Welch, K. C. Jr. The effect of short-term food restriction on the metabolic cost of the acute phase response in the fish-eating Myotis (Myotis vivesi). Mamm. Biol. 82, 41–47 (2017).Article 

Google Scholar 
Voigt, C. C. et al. The immune response of bats differs between pre-migration and migration seasons. Sci. Rep. 10, 17384 (2020).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Guerrero-Chacón, A. L., Rivera-Ruíz, D., Rojas-Díaz, V., Triana-Llanos, C. & Niño-Castro, A. Metabolic cost of acute phase response in the frugivorous bat, Artibeus lituratus. Mamm. Res. 63, 397–404 (2018).Article 

Google Scholar 
Weise, P., Czirják, G. Á., Lindecke, O., Bumrungsri, S. & Voigt, C. C. Simulated bacterial infection disrupts the circadian fluctuation of immune cells in wrinkle-lipped bats (Chaerephon plicatus). PeerJ 5, e3570 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Cabrera-Martínez, L. V., Herrera, M. L. G. & Cruz-Neto, A. P. The energetic cost of mounting an immune response for Pallas’s long-tongued bat (Glossophaga soricina). PeerJ 6, e4627 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Cabrera-Martinez, L. V., Herrera, M. L. G. & Cruz-Neto, A. P. Food restriction, but not seasonality, modulates the acute phase response of a neotropical bat. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 229, 93–100 (2019).PubMed 
Article 
CAS 

Google Scholar 
Stockmaier, S., Bolnick, D. I., Page, R. A. & Carter, G. G. An immune challenge reduces social grooming in vampire bats. Anim. Behav. 140, 141–149 (2018).Article 

Google Scholar 
Scheiermann, C., Kunisaki, Y. & Frenette, P. S. Circadian control of the immune system. Nat. Rev. Immunol. 13, 190–198 (2013).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Schneeberger, K., Czirják, G. Á. & Voigt, C. C. Measures of the constitutive immune system are linked to diet and roosting habits of Neotropical bats. PLoS ONE 8, e54023 (2013).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Hasselquist, D. Comparative immunoecology in birds: Hypotheses and tests. J. Ornithol. 148, 571–582 (2007).Article 

Google Scholar 
Becker, D. J. et al. Leukocyte profiles reflect geographic range limits and local food abundance in a widespread Neotropical bat. Integr. Comp. Biol. 59, 1176–1189 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Vermeulen, A., Eens, M., Zaid, E. & Müller, W. Baseline innate immunity does not affect the response to an immune challenge in female great tits (Parus major). Behav. Ecol. Sociobiol. 70, 585–592 (2016).Article 

Google Scholar 
Melhado, G., Herrera, M. L. G. & Cruz-Neto, A. P. Bats respond to simulated bacterial infection during the active phase by reducing food intake. J. Exp. Zool. A 333, 536–542 (2020).Article 
CAS 

Google Scholar 
Costantini, D. et al. Induced bacterial sickness causes inflammation but not blood oxidative stress in Egyptian fruit bats (Rousettus aegyptiacus). Conserv. Physiol. 10, coac028 (2022).PubMed 
PubMed Central 
Article 

Google Scholar 
Viljoen, H., Bennett, N. C. & Lutermann, H. Life-history traits, but not season, affect the febrile response to a lipopolysaccharide challenge in highveld mole-rats. J. Zool. 285, 222–229 (2011).Article 

Google Scholar 
Ahn, M., Cui, J., Irving, A. T. & Wang, L. F. Unique loss of the PYHIN gene family in bats amongst mammals: Implications for inflammasome sensing. Sci. Rep. 6, 21722 (2016).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Lilley, T. et al. Immune responses in hibernating little brown myotis (Myotis lucifugus) with white-nose syndrome. Proc. R. Soc. Lond. B Biol. Sci. 284, 20162232 (2017).
Google Scholar 
Mayberry, H. W., McGuire, L. P. & Willis, C. K. Body temperatures of hibernating little brown bats reveal pronounced behavioural activity during deep torpor and suggest a fever response during white-nose syndrome. J. Comp. Physiol. B. 188, 333–343 (2018).PubMed 
Article 
CAS 

Google Scholar 
Watkins, L. R., Maier, S. F. & Goehler, L. E. Immune activation: The role of pro-inflammatory cytokines in inflammation, illness responses and pathological pain states. Pain 63, 289–302 (1995).PubMed 
Article 

Google Scholar 
Grimble, R. F. Interaction between nutrients, pro-inflammatory cytokines and inflammation. Clin. Sci. 91, 121–130 (1996).Article 
CAS 

Google Scholar 
Schultz, E. M., Hahn, T. P. & Klasing, K. C. Photoperiod but not food restriction modulates innate immunity in an opportunistic breeder, Loxia curvirostra. J. Exp. Biol. 220, 722–730 (2016).PubMed 

Google Scholar 
Brinkmann, V. & Zychlinsky, A. Neutrophil extracellular traps: Is immunity the second function of chromatin?. J. Cell Biol. 198, 773–783 (2012).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Davis, A. K., Maney, D. L. & Maerz, J. C. The use of leukocyte profiles to measure stress in vertebrates: A review for ecologists. Funct. Ecol. 22, 760–772 (2008).Article 

Google Scholar 
Bouma, H. R., Carey, H. V. & Kroese, F. G. Hibernation: The immune system at rest?. J. Leukoc. Biol. 88, 619–624 (2010).PubMed 
Article 
CAS 

Google Scholar 
Crameri, G. et al. Establishment, immortalisation and characterisation of pteropid bat cell lines. PLoS ONE 4, e8266 (2009).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Neely, B. A. et al. Surveying the vampire bat (Desmodus rotundus) serum proteome: A resource for identifying immunological proteins and detecting pathogens. J. Proteome Res. 20, 2547–2559 (2021).PubMed 
Article 
CAS 

Google Scholar 
Hecht, A. M. et al. Plasma proteomic analysis of active and torpid greater mouse-eared bats (Myotis myotis). Sci. Rep. 5, 16604 (2015).ADS 
PubMed 
PubMed Central 
Article 
CAS 

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 (1996).Article 

Google Scholar 
Pap, P. L., Czirják, G. Á., Vágási, C. I., Barta, Z. & Hasselquist, D. Sexual dimorphism in immune function changes during the annual cycle in house sparrows. Naturwissenschaften 97, 891–901 (2010).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Heinrich, S. K. et al. Feliform carnivores have a distinguished constitutive innate immune response. Biol. Open 5, 550–555 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Heinrich, S. K. et al. Cheetahs have a stronger constitutive innate immunity than leopards. Sci. Rep. 7, 44837 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Morell, V., Lundgren, E. & Gillott, A. Predicting severity of trauma by admission white blood cell count, serum potassium level, and arterial pH. South. Med. J. 86, 658–659 (1993).PubMed 
Article 
CAS 

Google Scholar 
R Core Team. A Language and Environment for Statistical Computing. (R foundation for statistical computing, 2018).Pinheiro, J., Bates, D., DebRoy, S. & Sarkar, D. Linear and nonlinear mixed effects models. R Package Version 3, 57 (2007).
Google Scholar 
Fox, J. & Weisberg, S. An R Companion to Applied Regression (SAGE, 2011).
Google Scholar 
Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biom. J. 50, 346–363 (2008).MathSciNet 
PubMed 
MATH 
Article 

Google Scholar  More

Carson, R. The Sea Around Us. Oxford University Press, Oxford, UK 1951.Beverton, R. J. H. & Holt, S. J. A review of the lifespans and mortality rates of fish in nature, and their relation to growth and other physiological characteristics. In: Ciba Foundation Symposium – The Lifespan of Animals (Colloquia on Ageing, Vol. 5) 142–180 (John Wiley & Sons, Ltd, 2008).Kiørboe, T., Visser, A. & Andersen, K. H. A trait-based approach to ocean ecology. ICES Journal of Marine Science 75, 1849–1863 (2018).Article 

Google Scholar 
Froese, R. Cube law, condition factor and weight-length relationships: History, meta-analysis and recommendations. Journal of Applied Ichthyology 22, 241–253 (2006).Article 

Google Scholar 
Juan-Jordá, M. J., Mosqueira, I., Freire, J. & Dulvy, N. K. Life in 3-D: Life history strategies in tunas, mackerels and bonitos. Reviews in Fish Biology and Fisheries 23, 135–155 (2012).Article 

Google Scholar 
Beukhof, E. et al. Marine fish traits follow fast-slow continuum across oceans. Scientific Reports 9 (2019).Pauly, D. Tropical fishes: patterns and propensities. Journal of Fish Biology 53, 1–17 (1998).ADS 

Google Scholar 
Munch, S. B. & Salinas, S. Latitudinal variation in lifespan within species is explained by the metabolic theory of ecology. Proceedings of the National Academy of Sciences 106, 13860–13864 (2009).ADS 
CAS 
Article 

Google Scholar 
Gislason, H., Daan, N., Rice, J. C. & Pope, J. G. Size, growth, temperature and the natural mortality of marine fish. Fish and Fisheries 11, 149–158 (2010).Article 

Google Scholar 
Froese, R. & Pauly, D. FishBase https://fishbase.org/ (2021).Winemiller, K. O. & Rose, K. A. Patterns of life-history diversification in North American Fishes: implications for population regulation. Canadian Journal of Fisheries and Aquatic Sciences 49, 2196–2218 (1992).Article 

Google Scholar 
Cortés, E. Life History patterns and correlations in sharks. Reviews in Fisheries Science 8, 299–344 (2000).Article 

Google Scholar 
Juan-Jordá, M. J., Mosqueira, I., Freire, J., Ferrer-Jordá, E. & Dulvy, N. K. Global scombrid life history data set. Ecology 97, 809–809 (2016).Article 

Google Scholar 
Kindsvater, H. K., Mangel, M., Reynolds, J. D. & Dulvy, N. K. Ten principles from evolutionary ecology essential for effective marine conservation. Ecology and Evolution 6, 2125–2138 (2016).Article 

Google Scholar 
Kindsvater, H. K. et al. Overcoming the data crisis in biodiversity conservation. Trends in Ecology & Evolution 33, 676–688 (2018).Article 

Google Scholar 
Ricard, D., Minto, C., Jensen, O. P. & Baum, J. K. Examining the knowledge base and status of commercially exploited marine species with the RAM Legacy Stock Assessment Database. Fish and Fisheries 13, 380–398 (2011).Article 

Google Scholar 
Maureaud, A. et al. Are we ready to track climate‐driven shifts in marine species across international boundaries? ‐ A global survey of scientific bottom trawl data. Global Change Biology 27, 220–236 (2020).ADS 
Article 

Google Scholar 
Sherley, R. B. et al. Estimating IUCN Red List population reduction: JARA-A decision‐support tool applied to pelagic sharks. Conservation Letters 13 (2019).McAllister, M. K., Pikitch, E. K. & Babcock, E. A. Using demographic methods to construct Bayesian priors for the intrinsic rate of increase in the Schaefer model and implications for stock rebuilding. Canadian Journal of Fisheries and Aquatic Sciences 58, 1871–1890 (2001).Article 

Google Scholar 
Froese, R., Demirel, N., Coro, G. & Kleisner, K. M. & Winker, H. Estimating fisheries reference points from catch and resilience. Fish and Fisheries 18, 506–526 (2016).Article 

Google Scholar 
Jones, K. E. et al. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90, 2648–2648 (2009).Article 

Google Scholar 
Oliveira, B. F., São-Pedro, V. A., Santos-Barrera, G., Penone, C. & Costa, G. C. AmphiBIO, a global database for amphibian ecological traits. Scientific Data 4 (2017).Inchausti, P. & Halley, J. Investigating Long-Term Ecological Variability Using the Global Population Dynamics Database. Science 293, 655–657 (2001).CAS 
Article 

Google Scholar 
Collen, B. et al. Monitoring change in vertebrate abundance: the Living Planet Index. Conservation Biology 23, 317–327 (2009).Article 

Google Scholar 
Thorson, J. T., Munch, S. B., Cope, J. M. & Gao, J. Predicting life history parameters for all fishes worldwide. Ecological Applications 27, 2262–2276 (2017).Article 

Google Scholar 
Heinicke, S. et al. Advancing conservation planning for western chimpanzees using IUCN SSC A.P.E.S.-the case of a taxon-specific database. Environmental Research Letters 14, 064001 (2019).ADS 
Article 

Google Scholar 
Horswill, C. et al. Global reconstruction of life‐history strategies: A case study using tunas. Journal of Applied Ecology 56, 855–865 (2019).Article 

Google Scholar 
Thorson, J. T. Predicting recruitment density dependence and intrinsic growth rate for all fishes worldwide using a data‐integrated life‐history model. Fish and Fisheries 21, 237–251 (2019).Article 

Google Scholar 
Brown, C. J. & Roff, G. Life-history traits inform population trends when assessing the conservation status of a declining tiger shark population. Biological Conservation 239, 108230 (2019).Article 

Google Scholar 
Walls, R. H. L. & Dulvy, N. K. Eliminating the dark matter of data deficiency by predicting the conservation status of Northeast Atlantic and Mediterranean Sea sharks and rays. Biological Conservation 246, 108459 (2020).Article 

Google Scholar 
Guy, C. S. et al. A paradoxical knowledge gap in science for critically endangered fishes and game fishes during the sixth mass extinction. Scientific Reports 11 (2021).Compagno, L. J. V. Alternative life-history styles of cartilaginous fishes in time and space. In Alternative life-history styles of fishes 33–75 (Springer Netherlands, 1990).Stein, R. W. et al. Global priorities for conserving the evolutionary history of sharks, rays and chimaeras. Nature Ecology & Evolution 2, 288–298 (2018).ADS 
Article 

Google Scholar 
Yopak, K. E. et al. A conserved pattern of brain scaling from sharks to primates. Proceedings of the National Academy of Sciences 107, 12946–12951 (2010).ADS 
CAS 
Article 

Google Scholar 
Mull, C. G., Yopak, K. E. & Dulvy, N. K. Maternal Investment, Ecological Lifestyle, and Brain Evolution in Sharks and Rays. The American Naturalist 195, 1056–1069 (2020).Article 

Google Scholar 
Mull, C. G., Pennel, M. W., Yopak, K. E. & Dulvy, N. K. Maternal investment evolves with larger body size and higher diversification rate in sharks and rays. BioRxiv TBC (2022).Dulvy, N. D. & Reynolds, J. D. Evolutionary transitions among egg-laying, live-bearing, and maternal inputs in sharks and rays. Proceedings of the Royal Society B: Biological Sciences 264, 1309–1315 (1997).ADS 
Article 

Google Scholar 
Heithaus, M. R. et al. Advances in our understanding of the ecological importance of sharks and their relatives. In: Biology of sharks and their relatives, 3rd Ed. Carrier, J. C., Simpfendorfer, C. A., Heithaus, M. R., & Yopak, K. E. (Ed).Simpfendorfer, C. A., Heupel, M. R., White, W. T. & Dulvy, N. K. The importance of research and public opinion to conservation management of sharks and rays: a synthesis. Marine and Freshwater Research 62, 518 (2011).CAS 
Article 

Google Scholar 
Dulvy, N. K. et al. Overfishing drives over one-third of all sharks and rays toward a global extinction crisis. Current Biology 31, 4773–4787.e8 (2021).CAS 
Article 

Google Scholar 
Cortés, E., Brooks, E. N. & Shertzer, K. W. Risk assessment of cartilaginous fish populations. ICES Journal of Marine Science 72, 1057–1068 (2014).Article 

Google Scholar 
D’Alberto, B. M., Carlson, J. K., Pardo, S. A. & Simpfendorfer, C. A. Population productivity of shovelnose rays: Inferring the potential for recovery. PLOS ONE 14, e0225183 (2019).Article 

Google Scholar 
Sharkipedia: elasmobranch traits & trends http://www.sharkipedia.org.Bibliography Database. Shark-References http://www.shark-references.com.Weigmann, S. Annotated checklist of the living sharks, batoids and chimaeras (Chondrichthyes) of the world, with a focus on biogeographical diversity. Journal of Fish Biology 88, 837–1037 (2016).CAS 
Article 

Google Scholar 
Pacoureau, N. et al. Half a century of global decline in oceanic sharks and rays. Nature 589, 567–571 (2021).ADS 
CAS 
Article 

Google Scholar 
Spalding, M. D. et al. Marine Ecoregions of the World: A Bioregionalization of Coastal and Shelf Areas. BioScience 57, 573–583 (2007).Article 

Google Scholar 
Spalding, M. D. et al. Pelagic provinces of the world: A biogeographic classification of the world’s surface pelagic waters. Ocean & Coastal Management 60, 19–30 (2012).Article 

Google Scholar 
Rohatgi, A. WebPlotDigitizer. Extract data from plots, images, and maps https://automeris.io/WebPlotDigitizer/.Mull, C. G. et al. Sharkipedia: A database of shark and ray life history traits and abundance time-series. Zenodo https://doi.org/10.5281/zenodo.6656525 (2012). More

Effects of light intensity and temperatureThe germination of P. paradoxa (91 to 95%) and wheat (93 to 97%) was not affected by light intensity (data not shown). Our results conform to previous studies which revealed that light intensity had little role in influencing P. paradoxa germination24.The germination of wheat and P. paradoxa was influenced by temperature regimes (Fig. 1). At temperature regimes of 15/5 °C and 20/10 °C, germination of wheat and P. paradoxa did not vary. Seed germination in wheat remained similar at temperatures ranging between 15/5 °C to 30/20 °C. However, in P. paradoxa, germination was reduced at higher temperature regimes (35/25 C) compared with lower temperature regimes (15/5 °C to 25/15 °C). At the highest temperature regime (35/25 °C), the germination of wheat was 79%, while, at this temperature regime, the germination of P. paradoxa was only 1%. This suggests that wheat can germinate at high-temperature ranges, while, germination of P. paradoxa may be reduced at high temperatures (35/25 °C). These results implied that at the time of planting wheat in Australia if the air temperature is low, the chances of emergence of P. paradoxa are very high. This suggests that efforts should be made towards early control of P. paradoxa in wheat if the air temperature in the winter season falls early. These results also suggest that early planting of wheat could reduce the emergence of P. paradoxa as the prevailing temperature conditions are relatively high in early planting (e.g., end of April). In the Indo-Gangetic Plains, better control of P. minor was observed in the early planting of wheat (high-temperature conditions) due to less emergence of P. minor25.Figure 1Effect of alternating day/night temperatures (15/5 to 35/25 °C) on germination of Phalaris paradoxa and wheat seeds (incubated for 21 d) under light/dark (12-h photoperiod). LSD: Least significant difference at the 5% level of significance.Full size imagePrevious studies have also revealed that germination of P. paradoxa was highest at 10 °C and then failed to germinate at 30 °C 24,26, however, these studies were conducted at constant temperatures and the germination response of P. paradoxa was not studied in comparison with wheat in those studies.Effect of radiant heatThe germination of P. paradoxa seeds that were stored at room temperature (25 °C) was 97%, which reduced to 88% after exposure to the 100 °C pretreatment for 5 min and became nil at 150 °C (Fig. 2). About 88% of P. paradoxa at 100 °C suggests that it can tolerate heat stress for short periods.Figure 2Effect of high-temperature pretreatment for 5 min (℃) on germination of Phalaris paradoxa seeds. LSD: Least significant difference at the 5% level of significance.Full size imageGermination was nil at 150 °C and above, suggesting that burning could help in managing P. paradoxa, particularly in a no-till field where seeds are on the soil surface or at shallow depths. Exposure of seeds to fire could inhibit germination by desiccating the seed coat or by damaging the embryo27,28,29.Burning of residue in the fields could kill weed seeds and other pests in the topsoil layer30. Windrow burning proved to be an effective tool for killing weed seeds in paddocks31. However, the crop residue burning may cause environmental destruction by killing microbes and polluting the air. Also, it reduces the amount of soil organic matter due to the high heat, causing soil degradation. Therefore, these aspects should also be considered while formulating weed management strategies through crop residue burning. Burning may also release the dormancy of other weed seeds present in the subsoil and thus may increase infestation; therefore, this technique should be used cautiously32,33.Effect of osmotic stressGermination of P. paradoxa was highest (95%) in the control treatment and germination reduced to 75% at an osmotic potential of −0.8 MPa, and became nil at −1.6 MPa (Fig. 3). However, in wheat, germination did not reduce with an increase in water potential and it was 94% in the control treatment.Figure 3Effect of osmotic potential on germination of Phalaris paradoxa and wheat seeds at alternating day/night temperatures of 20/10 °C under 12 h photoperiod. Seeds were incubated for 21 d. LSD: Least significant difference at the 5% level of significance.Full size imageAt a very high concentration of PEG, the metabolic activity of P. paradoxa might be reduced due to water stress. Seed germination is affected when seeds are not able to get critical moisture threshold levels for imbibitions34,35. These results indicate that high water stress may inhibit the seed germination of P. paradoxa. However, under no water stress or mild water stress conditions, P. paradoxa may infest the wheat crop.Contrary to these results, previous studies reported that germination of P. paradoxa was reduced by 90% at an osmotic potential of −0.25 MPa25. Good germination of wheat at high osmotic potential indicates that the wheat variety used in this study may have water stress tolerance traits for germination. It was observed that wheat could germinate well (75%) at a high-water stress level (−1.6 MPa)36. This suggests that it is possible to menace P. paradoxa by growing stress-tolerant varieties of wheat and manipulating irrigation. In a previous study, less infestation of P. paradoxa was observed in drip-irrigated wheat crops due to optimal soil moisture conditions for the crop37.Effect of salt stressGermination of P. paradoxa was highest (93%) in the control treatment, and at a NaCl of 150 mM, germination was reduced to 76% (Fig. 4). Similarly, in wheat, germination was highest (94%) in the control treatment and at a salt concentration of 150 and 200 mM, germination was reduced to 84 and 79%, respectively. These results suggest that at a high salt concentration, P. paradoxa may infest the wheat crop owing to its ability to germinate under high salt concentrations.Figure 4Effect of sodium chloride concentration on germination of Phalaris paradoxa and wheat seeds at alternating day/night temperatures of 20/10 °C under 12 h photoperiod. Seeds were incubated for 21 d. LSD: Least significant difference at the 5% level of significance.Full size imageContrary to this, in Iran, it was observed that germination of P. paradoxa was reduced by 70% at a NaCl of 160 mM24. Most of the Australian soils are saline; therefore, it is quite possible that P. paradoxa in Australia might have developed traits for salt tolerance38. The variable response of populations of P. paradoxa to salt concentrations in Iran and Australia might be due to genetic differences between the P. paradoxa populations38. These observations suggest that P. paradoxa could invade the agroecosystem under the saline conditions of Australia.Effect of seed burial depth on emergenceGermination of P. paradoxa was very low (10%) on the soil surface, and seedling emergence was highest (74%) at a soil burial depth of 0.5 cm (Fig. 5). Seedling emergence was similar when seeds were buried in the soil at a depth ranging from 0.5 to 4 cm. Seedling emergence was 32% at a burial depth of 8 cm.Figure 5Effect of seed burial depth on seedling emergence of Phalaris paradoxa. LSD: Least significant difference at the 5% level of significance.Full size imageThe results from this experiment suggest that a no-till production system may inhibit the germination of P. paradoxa. This study also suggests that deep tillage ( > 4 cm) could reduce the emergence of P. paradoxa to some extent; therefore, inversion tillage could be a weed management strategy if the seedbank is in the shallow layer of the soil. It has been reported that the emergence of small-seeded weeds is reduced from deeper burial depths, as the soil-gas exchange is limited 21. However, it is important to know the seed longevity of this weed in different soil and environmental conditions when considering tillage operations39.Likewise, previous studies also reported that seed germination of P. paradoxa was lowest on the soil surface and no seedlings emerged from a soil depth of 10-cm2,40. Contrary to this in Iran, germination of P. paradoxa was found to be  > 65% on the soil surface 24.Evaluation of PRE-herbicidesResults revealed that cinmethylin, pyroxasulfone, and trifluralin provided 100% control of P. paradoxa. Atrazine, bixlozone, imazethapyr, isoxaflutole, prosulfocarb + s-metolachlor, and s-metolachlor were not found to be effective against P. paradoxa (Table 1). Pendimethalin and triallate controlled P. paradoxa by 80 and 42%, respectively, compared with the nontreated control.Table 1 Effect of PRE herbicides on the survival of Phalaris paradoxa and wheat seedlings (28 d after spray).Full size tableIn wheat, all tested herbicides performed similarly for plant survival except dimethenamid-P and prosulfocarb + s-metolachlor, which caused wheat mortality by 41 and 16%, respectively, compared with the nontreated control. These results suggest that pyroxasulfone, pendimethalin, and trifluralin can be successfully used for the management of P. paradoxa in wheat. Alternative use of these herbicides in wheat crops could provide sustainable weed control of P. paradoxa. In previous studies conducted in Australia, herbicides namely cinmethylin, pyroxasulfone, and trifluralin were found safe for wheat and provided excellent grass weed control41.Efficacy of PRE-herbicides in relation to crop residue coverCinmethylin, pendimethalin, and pyroxasulfone were proven to be very effective against P. paradoxa under no residue cover conditions (Table 2). However, at the residue cover of 6 t ha-1 (high output systems), the efficacy of these herbicides decreased and these three herbicides failed to provide effective control of P. paradoxa. At the residue cover of 2 t ha-1 (low output systems), the efficacy of pyroxasulfone in controlling P. paradoxa was not affected; however, cinmethylin and pendimethalin at the residue load of 2 t ha-1 did not control P. paradoxa. These results suggest that in a residue-retained, no-till system, pyroxasulfone could provide better control of P. paradoxa compared with cinmethylin and pendimethalin.Table 2 The interaction of PRE herbicides and wheat residue amount on the survival of Phalaris paradoxa seedlings at 28 d after spray.Full size tableThe crop residue binds some herbicides, which results in a reduced dose to target weeds and provides poor weed control42. A crop residue cover of 1 t ha-1 may prevent 50% of the herbicide from reaching the target weed seeds in the soil and thus provide poor weed control43.Efficacy of POST herbicides in relation to plant sizeWhen plants were sprayed at the 4-leaf stage, the herbicides clodinafop and propaquizafop were not effective against P. paradoxa compared with the other tested herbicides (Table 3). The efficacy of clethodim, glyphosate, haloxyfop, and paraquat in controlling P. paradoxa was not decreased even when plants were sprayed at the 10-leaf stage. In previous studies, poor control of P. paradoxa was observed with ACCase-inhibiting herbicides44,45. These results also suggest that under noncropped or fallow situations, early and late cohorts of P. paradoxa can be controlled successfully by delaying applications of clethodim, paraquat, haloxyfop, and glyphosate.Table 3 The interaction effect of plant size (large plants-10 leaves and small plants-4 leaves) and herbicide treatments on the survival of Phalaris paradoxa seedlings at 28 d after spray.Full size tableGermination of P. paradoxa at 25/15 °C (day/night) was lower compared with 20/10 °C. This suggests that early sowing of wheat (relatively high-temperature conditions) could reduce the emergence of P. paradoxa in fields. Phalaris paradoxa did not germinate after exposure to radiant heat of 150 °C (for 5 min), which suggests that burning may be a useful tool for managing P. paradoxa, particularly when seeds are on the soil surface or at the shallow surface. A high level of tolerance of P. paradoxa to water and salt stress was observed. These observations suggest that this weed can dominate under saline and water stress conditions in Australia. Low germination of P. paradoxa was observed on the soil surface, suggesting that a no-till system could provide better control of P. paradoxa. PRE herbicides cinmethylin, pyroxasulfone, pendimethalin, and trifluralin were effective for control of P. paradoxa in wheat; however, under a conservation tillage system, pyroxasulfone provided better control of P. paradoxa compared with other herbicides. Haloxyfop and clethodim were the most effective herbicides among the ACCase-inhibiting herbicides. Under noncropped or fallow land situations, larger plants of P. paradoxa can be successfully controlled with the application of clethodim, glyphosate, and paraquat. More

Leng G, Hall J. Crop yield sensitivity of global major agricultural countries to droughts and the projected changes in the future. Sci Total Environ. 2019;654:811–21.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hueso S, García C, Hernández T. Severe drought conditions modify the microbial community structure, size and activity in amended and unamended soils. Soil Biol Biochem. 2012;50:167–73.CAS 
Article 

Google Scholar 
Alster CJ, German DP, Lu Y, Allison SD. Microbial enzymatic responses to drought and to nitrogen addition in a southern California grassland. Soil Biol Biochem. 2013;64:68–79.CAS 
Article 

Google Scholar 
Bouskill NJ, Lim HC, Borglin S, Salve R, Wood TE, Silver WL, et al. Pre-exposure to drought increases the resistance of tropical forest soil bacterial communities to extended drought. ISME J. 2013;7:384–94.CAS 
PubMed 
Article 

Google Scholar 
Acosta-Martinez V, Cotton J, Gardner T, Moore-Kucera J, Zak J, Wester D, et al. Predominant bacterial and fungal assemblages in agricultural soils during a record drought/heat wave and linkages to enzyme activities of biogeochemical cycling. Appl Soil Ecol. 2014;84:69–82.Article 

Google Scholar 
O’Connell CS, Ruan L, Silver WL. Drought drives rapid shifts in tropical rainforest soil biogeochemistry and greenhouse gas emissions. Nat Commun. 2018;9:1348.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Schimel JP. Life in dry soils: Effects of drought on soil microbial communities and processes. Annu Rev Ecol Evol Syst. 2018;49:409–32.Article 

Google Scholar 
Naylor D, Colemann-Derr D. Drought stress and root-associated bacterial communities. Front Plant Sci. 2018;8:2223.PubMed 
PubMed Central 
Article 

Google Scholar 
de Vries FT, Griffiths RI, Knight CG, Nicolitch O, Williams A. Harnessing rhizosphere microbiomes for drought-resilient crop production. Science. 2020;368:270–4.PubMed 
Article 
CAS 

Google Scholar 
Smith SE, Read D. Mycorrhizal symbiosis. 3rd ed. London: Academic Press; 2008. p. 145–90.Kakouridis A, Hagen JA, Kan MP, Mambelli S, Feldman LJ, Herman DJ, et al. Routes to roots: direct evidence of water transport by arbuscular mycorrhizal fungi to host plants. New Phytol. 2022; https://doi.org/10.1111/nph.18281.Rillig MC, Mummey DL. Mycorrhizas and soil structure. N Phytol. 2006;171:41–53.CAS 
Article 

Google Scholar 
Gong M, You X, Zhang Q. Effects of Glomus intraradices on the growth and reactive oxygen metabolism of foxtail millet under drought. Ann Microbiol. 2015;65:595–602.CAS 
Article 

Google Scholar 
Ruiz-Lozano JM. Arbuscular mycorrhizal symbiosis and alleviation of osmotic stress. N Perspect Mol Stud Mycorrhiza. 2003;13:309–17.Article 

Google Scholar 
Morte A, Lovisolo C, Schubert A. Effect of drought stress on growth and water relations of the mycorrhizal association Helianthemum almeriense–Terfezia claveryi. Mycorrhiza. 2000;10:115–9.CAS 
Article 

Google Scholar 
Birhane E, Sterck F, Fetene M, Bongers F, Kuyper T. Arbuscular mycorrhizal fungi enhance photosynthesis, water use efficiency, and growth of frankincense seedlings under pulsed water availability conditions. Oecologia. 2012;169:895–904.PubMed 
PubMed Central 
Article 

Google Scholar 
Duan X, Neuman DS, Reiber JM, Green CD, Saxton AM, Augé RM. Mycorrhizal influence on hydraulic and hormonal factors implicated in the control of stomatal conductance during drought. J Exp Bot. 1996;47:1541–50.CAS 
Article 

Google Scholar 
Emmett BD, Levesque-Tremblay V, Harrison MJ. Conserved and reproducible bacterial communities associate with extraradical hyphae of arbuscular mycorrhizal fungi. ISME J. 2021;15:2276–88.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Toljander JF, Artursson V, Paul LR, Jansson JK, Finlay RD. Attachment of different soil bacteria to arbuscular mycorrhizal fungal extraradical hyphae is determined by hyphal vitality and fungal species. FEMS Microbiol Lett. 2006;254:34–40.CAS 
PubMed 
Article 

Google Scholar 
Svenningsen NB, Watts-Williams SJ, Joner EJ, Battini F, Efthymiou A, Cruz-Paredes C, et al. Suppression of the activity of arbuscular mycorrhizal fungi by the soil microbiota. ISME J. 2018;12:1296–307.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cruz-Paredes C, Svenningsen NB, Nybroe O, Kjøller R, Frøslev TG, Jakobsen I. Suppression of arbuscular mycorrhizal fungal activity in a diverse collection of non-cultivated soils. FEMS Microbiol Ecol. 2019;95:fiz020.CAS 
PubMed 
Article 

Google Scholar 
Nuccio EE, Hodge A, Pett-Ridge J, Herman DJ, Weber PK, Firestone MK. An arbuscular mycorrhizal fungus significantly modifies the soil bacterial community and nitrogen cycling during litter decomposition. Environ Microbiol. 2013;15:1870–81.CAS 
PubMed 
Article 

Google Scholar 
Verbruggen E, Jansa J, Hammer EC, Rillig MC. Do arbuscular mycorrhizal fungi stabilize litter-derived carbon in soil? J Ecol. 2016;104:261–9.CAS 
Article 

Google Scholar 
Kaiser C, Kilburn MR, Clode PL, Fuchslueger L, Koranda M, Cliff JP, et al. Exploring the transfer of recent plant photosynthates to soil microbes: mycorrhizal pathway vs direct root exudation. N Phytol. 2015;205:1537–51.CAS 
Article 

Google Scholar 
Zhang L, Shi N, Fan J, Wang F, George TS, Feng G. Arbuscular mycorrhizal fungi stimulate organic phosphate mobilization associated with changing bacterial community structure under field conditions. Environ Microbiol. 2018a;20:2639–51.CAS 
PubMed 
Article 

Google Scholar 
Hodge A, Campbell CD, Fitter AH. An arbuscular mycorrhizal fungus accelerates decomposition and acquires nitrogen directly from organic matter. Nature. 2001;413:297–9.CAS 
PubMed 
Article 

Google Scholar 
Hestrin R, Hammer EC, Mueller CW, Lehmann J. Synergies between mycorrhizal fungi and soil microbial communities increase plant nitrogen acquisition. Commun Biol. 2019;2:233.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Medina A, Probanza A, Gutierrez Mañero FJ, Azcón R. Interactions of arbuscular-mycorrhizal fungi and Bacillus strains and their effects on plant growth, microbial rhizosphere activity (thymidine and leucine incorporation) and fungal biomass (ergosterol and chitin). Appl Soil Ecol. 2003;22:15–28.Article 

Google Scholar 
Drigo B, Pijl AS, Duyts H, Kielak AM, Gamper HA, Houtekamer MJ, et al. Shifting carbon flow from roots into associated microbial communities in response to elevated atmospheric CO2. Proc Natl Acad Sci USA. 2010;107:10938–42.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Jakobsen I, Rosenthal L. Carbon flow into soil and external hyphae from roots of mycorrhizal cucumber plants. N Phytol. 1990;115:77–83.Article 

Google Scholar 
Zhou J, Chai X, Zhang L, George TS, Wang F, Feng G. Different arbuscular mycorrhizal fungi cocolonizing on a single plant root system recruit distinct microbiomes. mSystems. 2020;5:e00929–0.CAS 
PubMed 
PubMed Central 

Google Scholar 
See CR, Keller AB, Hobbie SE, Kennedy PG, Weber PK, Pett-Ridge J. Hyphae move matter and microbes to mineral microsites: Integrating the hyphosphere into conceptual models of soil organic matter stabilization. Glob Change Biol. 2022;28:2527–40.CAS 
Article 

Google Scholar 
Carini P, Marsden P, Leff J, Morgan E, Strickland M, Fierer N. Relic DNA is abundant in soil and obscures estimates of soil microbial diversity. Nat Microbiol. 2017;2:16242.CAS 
Article 

Google Scholar 
Lennon JT, Muscarella ME, Placella MA, Lehmkuhl BK. How, when, and where relic DNA affects microbial diversity. mBio. 2018;9:e00637–18.PubMed 
PubMed Central 

Google Scholar 
Hungate BA, Mau RL, Schwartz E, Caporaso JG, Dijkstra P, van Gestel N, et al. Quantitative microbial ecology through stable isotope probing. Appl Environ Microbiol. 2015;81:7570–81.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Neufeld JD, Vohra J, Dumont MG, Lueders T, Manefield M, Friedrich MW, et al. DNA stable-isotope probing. Nat Protoc. 2007;2:860–6.CAS 
PubMed 
Article 

Google Scholar 
Koch BJ, McHugh TA, Hayer M, Schwartz E, Blazewicz SJ, Dijkstra P, et al. Estimating taxon-specific population dynamics in diverse microbial communities. Ecosphere. 2018;9:e02090–15.Article 

Google Scholar 
Blazewicz SJ, Hungate BA, Koch BJ, Nuccio EE, Morrissey E, Brodie EL, et al. Taxon-specific microbial growth and mortality patterns reveal distinct temporal population responses to rewetting in a California grassland soil. ISME J. 2020;14:1520–32.PubMed 
PubMed Central 
Article 

Google Scholar 
Kilronomos JN. Host-specificity and functional diversity among arbuscular mycorrhizal fungi. In: Proceedings of the 8th International Symposium on Microbial Ecology. Bell CR, Brylinski M, Johnson-Green P, editors. Halifax: Atlantic Canada Society from Microbial Ecology; 2000. p. 845–51.Ray P, Guo Y, Chi MH, Krom N, Saha MC, Craven KD. Serendipita bescii promotes winter wheat growth and modulates the host root transcriptome under phosphorus and nitrogen starvation. Environ Microbiol. 2021;23:1876–88.CAS 
PubMed 
Article 

Google Scholar 
Lee MR, Hawkes CV. Widespread co-occurrence of Sebacinales and arbuscular mycorrhizal fungi in switchgrass roots and soils has limited dependence on soil carbon or nutrients. Plants People Planet. 2021;3:614–26.Article 

Google Scholar 
Ruiz-Lozano JM, Azcon R, Gomez M. Effects of arbuscular-mycorrhizal glomus species on drought tolerance: physiological and nutritional plant responses. Appl Environ Microbiol. 1995;61:456–60.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
He F, Sheng M, Tang M. Effects of Rhizophagus irregularis on photosynthesis and antioxidative enzymatic system in Robinia pseudoacacia L. under drought stress. Front Plant Sci. 2017;8:183.PubMed 
PubMed Central 

Google Scholar 
Ghimire SR, Craven KD. Enhancement of switchgrass (Panicum virgatum L.) biomass production under drought conditions by the ectomycorrhizal fungus Sebacina vermifera. Appl Environ Microbiol. 2011;77:7063–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Tisserant E, Malbreil M, Kuo A, Kohler A, Symeonidi A, Balestrini R, et al. Genome of an arbuscular mycorrhizal fungus provides insight into the oldest plant symbiosis. Proc Natl Acad Sci USA. 2013;110:20117–22.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kamel L, Keller-Pearson M, Roux C, Ané JM. Biology and evolution of arbuscular mycorrhizal symbiosis in the light of genomics. N Phytol. 2017;213:531–6.CAS 
Article 

Google Scholar 
Bukovská P, Bonkowski M, Konvalinková T, Beskid O, Hujslová M, Püschel D, et al. Utilization of organic nitrogen by arbuscular mycorrhizal fungi-is there a specific role for protists and ammonia oxidizers? Mycorrhiza. 2018;28:269–83.PubMed 
Article 
CAS 

Google Scholar 
Zhang L, Feng G, Declerck S. Signal beyond nutrient, fructose, exuded by an arbuscular mycorrhizal fungus triggers phytate mineralization by a phosphate solubilizing bacterium. ISME J. 2018;12:2339.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zuccaro A, Lahrmann U, Güldener U, Langen G, Pfiffi S, Biedenkopf D, et al. Endophytic life strategies decoded by genome and transcriptome analyses of the mutualistic root symbiont Piriformospora indica. PLoS Pathog. 2011;7:e1002290.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ray P, Chi MH, Guo Y, Chen C, Adam C, Kuo A, et al. Genome sequence of the plant growth promoting fungus Serendipita vermifera subsp. bescii: The first native strain from North America. Phytobiomes J. 2018;2:62–3.Article 

Google Scholar 
Dias T, Pimentel V, Cogo AJD, Costa R, Bertolazi AA, Miranda C, et al. The free-living stage growth conditions of the endophytic fungus Serendipita indica may regulate its potential as plant growth promoting microbe. Front Microbiol. 2020;11:562238.PubMed 
PubMed Central 
Article 

Google Scholar 
Moffatt HH. Soil Survey of Caddo County, Oklahoma. Washington, D.C.: United States Department of 836 Agriculture Soil Conservation Service; 1973.Sher Y, Baker NR, Herman NR, Fossum C, Hale L, Zhang XX, et al. Microbial extracellular polysaccharide production and aggregate stability controlled by Switchgrass (Panicum virgatum) root biomass and soil water potential. Soil Biol Biochem. 2020;143:107742.CAS 
Article 

Google Scholar 
Seki K. SWRC fit—a nonlinear fitting program with a water retention curve for soils having unimodal and bimodal pore structure. Hydrol Earth Syst Sci Discuss. 2007;4:407–37.
Google Scholar 
Ray P, Ishiga T, Decker SR, Turner GB, Craven KD. A novel delivery system for the root symbiotic fungus, Sebacina vermifera, and consequent biomass enhancement of low lignin COMT switchgrass lines. BioEnerg Res. 2015;8:922–33.CAS 
Article 

Google Scholar 
Blazewicz SJ, Schwartz E, Firestone MK. Growth and death of bacteria and fungi underlie rainfall-induced carbon dioxide pulses from seasonally dried soil. Ecology. 2014;95:1162–72.PubMed 
Article 

Google Scholar 
Nuccio EE, Blazewicz SJ, Lafler M, Campbell AN, Kakouridis A, Kimbrel JA, et al. HT-SIP: a semi-automated Stable Isotope Probing pipeline identifies interactions in the hyphosphere of arbuscular mycorrhizal fungi. bioRxiv. 2022; https://biorxiv.org/cgi/content/short/2022.07.01.498377v1.Buckley DH, Huangyutitham V, Hsu SF, Nelson TA. Stable isotope probing with 15N achieved by disentangling the effects of genome G+C content and isotope enrichment on DNA density. Appl Environ Microbiol. 2007;73:3189–95.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Parada AE, Needham DM, Fuhrman JA. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2016;18:1403–14.CAS 
PubMed 
Article 

Google Scholar 
Apprill A, McNally S, Parsons R, Weber L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat Micro Ecol. 2015;75:129–37.Article 

Google Scholar 
Badri A, Stefani FOP, Lachance G, Roy-Arcand L, Beaudet D, Vialle A, et al. Molecular diagnostic toolkit for Rhizophagus irregularis isolate DAOM-197198 using quantitative PCR assay targeting the mitochondrial genome. Mycorrhiza. 2016;26:721–33.CAS 
PubMed 
Article 

Google Scholar 
Gamper HA, Young JP, Jones DL, Hodge A. Real-time PCR and microscopy: are the two methods measuring the same unit of arbuscular mycorrhizal fungal abundance? Fungal Genet Biol. 2008;45:581–96.CAS 
PubMed 
Article 

Google Scholar 
Tellenbach C, Grünig CR, Sieber TN. Suitability of quantitative real-time PCR to estimate the biomass of fungal root endophytes. Appl Environ Microbiol. 2010;76:5764–72.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Schildkraut CL, Marmur J, Doty P. Determination of the base composition of deoxyribonucleic acid from its buoyant density in CsCl. J Mol Biol. 1962;4:430–43.CAS 
PubMed 
Article 

Google Scholar 
Martin-Laurent F, Phillipot L, Hallet S, Chaussod R, Germon JC, Soulas G, et al. DNA extraction from soils: old bias for new microbial diversity analysis methods. Appl Environ Microbiol. 2001;67:2354–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Louca S, Doebeli M, Parfrey LW. Correcting for 16S rRNA gene copy numbers in microbiome surveys remains an unsolved problem. Microbiome. 2018;6:41.PubMed 
PubMed Central 
Article 

Google Scholar 
Kanagawa T. Bias and artifacts in multitemplate polymerase chain reactions (PCR). J Biosci Bioeng. 2003;96:317–23.CAS 
PubMed 
Article 

Google Scholar 
Kozarewa I, Ning Z, Quail MA, Sanders MJ, Berriman M, Turner DJ. Amplification-free Illumina sequencing-library preparation facilitates improved mapping and assembly of (G+C)-biased genomes. Nat Methods. 2009;6:291–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Manzoni S, Taylor P, Richter A, Porporato A, Ågren GI. Environmental and stoichiometric controls on microbial carbon-use efficiency in soils. N Phytol. 2012;196:79–91.CAS 
Article 

Google Scholar 
Geyer KM, Dijkstra P, Sinsabaugh R, Frey SD. Clarifying the interpretation of carbon use efficiency in soil through methods comparison. Soil Biol Biochem. 2019;128:79–88.CAS 
Article 

Google Scholar 
R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2019.Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, OHara RB, et al. vegan: Community Ecology Package R package version 2.3-0. 2015. http://CRAN.R-project.org/package=vegan.Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 2011;5:169–72.PubMed 
Article 

Google Scholar 
Harris RF. Effect of water potential on microbial growth and activity. In: Water Potential Relations in Soil Microbiology. Parr JF, Gardner WR, Elliott LF, editors. Madison, WI: Am Soc Agron; 1981. p. 23–95.Wagg C, Dudenhöffer JH, Widmer F, van der Heijden MGA. Linking diversity, synchrony and stability in soil microbial communities. Funct Ecol. 2018;32:1280–92.Article 

Google Scholar 
Malik AA, Martiny JBH, Brodie EL, Martiny AC, Treseder KK, Allison SD. Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change. ISME J. 2020;14:1–9.CAS 
PubMed 
Article 

Google Scholar 
Tiemann LK, Billings SA. Changes in variability of soil moisture alter microbial community C and N resource use. Soil Biol Biochem. 2011;43:1837–47.CAS 
Article 

Google Scholar 
Domeignoz-Horta LA, Pold G, Liu XJA, Frey SD, Melillo JM, DeAngelis KM. Microbial diversity drives carbon use efficiency in a model soil. Nat Commun. 2020;11:3684.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gefen O, Balaban NQ. The importance of being persistent: heterogeneity of bacterial populations under antibiotic stress. FEMS Microbiol Rev. 2009;33:704–17.CAS 
PubMed 
Article 

Google Scholar 
Fridman O, Goldberg O, Ronin I, Shoresh N, Balaban NQ. Optimization of lag time underlies antibiotic tolerance in evolved bacterial populations. Nature. 2014;513:418–21.CAS 
PubMed 
Article 

Google Scholar 
Bouskill NJ, Wood TE, Baran R, Hao Z, Ye Z, Bowen BP, et al. Belowground response to drought in a tropical forest soil. II. Change in microbial function impacts carbon composition. Front Microbiol. 2016;7:323.PubMed 
PubMed Central 

Google Scholar 
Sutcliffe IC. A phylum level perspective on bacterial cell envelope architecture. Trends Microbiol. 2010;18:464–70.CAS 
PubMed 
Article 

Google Scholar 
Tocheva EI, Ortega DR, Jensen GJ. Sporulation, bacterial cell envelopes and the origin of life. Nat Rev Microbiol. 2016;14:535–42.PubMed 
PubMed Central 
Article 

Google Scholar 
Xu L, Naylor D, Dong Z, Simmons T, Pierroz G, Hixson KK, et al. Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria. Proc Natl Acad Sci USA. 2018;115:E4284–93.CAS 
PubMed 
PubMed Central 

Google Scholar 
Santos-Medellín C, Liechty Z, Edwards J, Nguyen B, Huang B, Weimer BC, et al. Prolonged drought imparts lasting compositional changes to the rice root microbiome. Nat Plants. 2021;7:1065–77.PubMed 
Article 
CAS 

Google Scholar 
Otoguro M, Yamamura H, Quintana ET The Family Streptosporangiaceae. In: The Prokaryotes. Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F, editors. Berlin, Heidelberg: Springer; 2104. p. 1011–45.Barnard RL, Osborne CA, Firestone MK. Responses of soil bacterial and fungal communities to extreme desiccation and rewetting. ISME J. 2013;7:2229–41.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cruz AF, Ishii T. Arbuscular mycorrhizal fungal spores host bacteria that affect nutrient biodynamics and biocontrol of soil-borne plant pathogens. Biol Open. 2012;1:52–7.PubMed 
Article 

Google Scholar 
Rillig MC, Lutgen ER, Ramsey PW, Klironomos JN, Gannon JE. Microbiota accompanying different arbuscular mycorrhizal fungal isolates influence soil aggregation. Pedobiologia. 2005;49:251–9.Article 

Google Scholar 
Jiang F, Zhang L, Zhou J, George TS, Feng G. Arbuscular mycorrhizal fungi enhance mineralisation of organic phosphorus by carrying bacteria along their extraradical hyphae. N Phytol. 2021;230:304–15.CAS 
Article 

Google Scholar 
Hernandez DJ, David AS, Menges ES, Searcy CA, Afkhami ME. Environmental stress destabilizes microbial networks. ISME J. 2021;15:1722–34.PubMed 
PubMed Central 
Article 

Google Scholar 
Leigh J, Fitter AH, Hodge A. Growth and symbiotic effectiveness of an arbuscular mycorrhizal fungus in organic matter in competition with soil bacteria. FEMS Microbiol Ecol. 2011;76:428–38.CAS 
PubMed 
Article 

Google Scholar 
Leifheit EF, Verbruggen E, Rillig MC. Arbuscular mycorrhizal fungi reduce decomposition of woody plant litter while increasing soil aggregation. Soil Biol Biochem. 2015;81:323–8.CAS 
Article 

Google Scholar 
Bronstein JL. Conditional outcomes in mutualistic interactions. Trends Ecol Evol. 1994;9:214–7.CAS 
PubMed 
Article 

Google Scholar 
Toljander JF, Lindahl BD, Paul LR, Elfstrand M, Finlay RD. Influence of arbuscular mycorrhizal mycelial exudates on soil bacterial growth and community structure. FEMS Microbiol Ecol. 2007;61:295–304.CAS 
PubMed 
Article 

Google Scholar 
Zhang L, Zhou J, George TS, Limpens E, Feng G. Arbuscular mycorrhizal fungi conducting the hyphosphere bacterial orchestra. Trends Plant Sci. 2022;27:402–11.CAS 
PubMed 
Article 

Google Scholar 
Zhalnina K, Louie KB, Hao Z, Mansoori N, Nunes da Rocha U, Shi S, et al. Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nat Microbiol. 2018;3:470–80.CAS 
PubMed 
Article 

Google Scholar 
Chaparro JM, Badri DV, Bakker MG, Sugiyama A, Manter DK, Vivanco JM. Root exudation of phytochemicals in Arabidopsis follows specific patterns that are developmentally programmed and correlate with soil microbial functions. PLoS ONE. 2013;8:e55731.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Shi S, Richardson AE, O’Callaghan M, DeAngelis KM, Jones EE, Stewart A, et al. Effects of selected root exudate components on soil bacterial communities. FEMS Microbiol Ecol. 2011;77:600–10.CAS 
PubMed 
Article 

Google Scholar  More

The giant panda’s preference for culm over leaves occurred even though leaves had far more protein than did culm, which is inconsistent with the suggestion that giant pandas are high protein carnivores1. The giant panda’s preference for culm over leaves in the spring was likely driven by the increased availability of mono- and polysaccharides in culm relative to leaves31. This preference by giant pandas for a high-carbohydrate, low protein diet is similar to the brown bear’s preference for carbohydrate-rich but protein-poor berries or apples over protein- and energy-rich salmon, although both needed to be consumed to produce the most efficient diet2,10. The preference for culm over leaves created a protein ME in the diet of giant pandas from January to March (~ 20%) when digestible carbohydrates were most plentiful and for the entire year (27 ± 10%) that was comparable to the macronutrient proportions in giant panda milk and the milk and diets selected by other ursids (Table 1, Fig. 3) that minimize energy expenditure and maximize the efficiency of gain3.Table 1 The protein and fat metabolizable energy concentrations (%) in ursid milks and in the diets selected by brown bears, polar bears, and sloth bears when given ad libitum access to foods rich in protein, fat, and digestible carbohydrates (PFC) or protein and fat only (PF)1,3,4,29,32,40,54,55.Full size tableRelative to the suggestion that giant pandas are not well adapted to consuming the more omnivorous macronutrient proportions characteristic of the diets of other ursids1, captive giant pandas are often fed various combinations of bamboo and high-carbohydrate supplements that include rice, baby cereal, bread, beans, wheat, millet, apples, carrots, ground corn, sorghum, sugar cane, and sugar in addition to milk, eggs, vegetables, and various meats5,32,33. The dry matter of giant panda diets in five Chinese zoos in which successful reproduction occurred (i.e., Beijing Zoo, Chengdu Zoo, China Conservation and Research Center, Fuzhou Zoo, and Xian Zoo) averaged 11.6 ± 2.4% protein, 39.0 ± 13.6% neutral detergent fiber (NDF) or cell wall, 5.0 ± 2.0% fat, and 5.4 ± 0.6% ash32. If we estimate soluble carbohydrates as 100 – (NDF + protein + fat + ash)3, the soluble carbohydrate content was 39.0 ± 11.2%. This approach likely underestimates digestible carbohydrates in that it assumes a zero digestibility for the hemicellulose fraction of the NDF. However, even with these assumptions, the average macronutrient ME distribution was 19 ± 4% protein, 18 ± 7% fat, and 63 ± 18% carbohydrate, or again a low-protein macronutrient ratio typical of the other ursid diets (Table 1).Several errors may have been made in the previous giant panda study1 that likely influenced their conclusion. These included initially air-drying their bamboo samples in a dark room prior to laboratory drying and analyses34. When plants are cut and allowed to dry slowly, soluble carbohydrates are lost as they are metabolized to carbon dioxide, water, and energy until death of the plant cells35,36. The loss of soluble carbohydrates increases when drying occurs slowly, as would occur with air-drying in a dark room. Protein also may be metabolized, but the nitrogen remains and is only converted to different nitrogen-containing compounds, such as amides, free amino acids and peptides that would be part of a crude protein estimate36.Thus, if there are significant amounts of soluble carbohydrates in fresh bamboo, air-drying of bamboo samples will lead to an underestimate of the importance of carbohydrates and thereby an overestimate of the importance of protein. Indeed, starch accounted for 16 ± 11% of the digestible macronutrients and 23 ± 13% of the digestible carbohydrates in bamboo during the current study. Also, the previous study1 assumed a hemicellulose digestibility of 22%37, which significantly underestimated that found in our digestion studies (46 ± 9%).Another potential error in the previous study1 was in using a concept they termed “relative efficiencies” of macronutrient absorption in which the macronutrient profiles of bamboo were directly compared to that of giant panda feces. Such a comparison is often meaningless without knowing the amounts of food consumed and feces produced because the proportions of macronutrients in the feces reflect the extraordinarily complex interaction between the variable absorption of digestible products, passage of indigestible components, and excretion of metabolic products. Thus, only by providing data showing a close linkage between relative efficiencies and digestibility or measuring digestibility as we did can one be certain of estimating the relative importance of macronutrients.The macronutrient intake of wild sloth bears has not been measured, although the dietary proportions and energy content of termites, ants, and fruits have been estimated17. Soldiers and worker termites and ants are generally low in fat and high in protein (excluding the nitrogen in their chitin exoskeleton), whereas alate and alate nymphs (winged reproductive termites) can be very low in protein and high in fat (i.e.,  > 50% fat)38. Joshi et al.17 surmised that sloth bears consumed primarily termite eggs and defending soldiers based on the residues in bear feces and the absence of eggs and soldiers at termite mounds after sloth bear feeding bouts. Although not measured, the dry matter of termite eggs is likely high in both protein and fat, which would create a high fat ME because of the much greater energy content of fat than protein39. The high fruit diet of the summer will be low in protein and fat and high in carbohydrates if not supplemented with other fat-rich foods (e.g., grubs or insect larvae)17. Thus, depending on season and which stage of the ant and termite life cycle the bears consume, wild sloth bears could be consuming either high or low-protein or fat diets.The preference for fat that we observed differs markedly from current zoo diets. Zoo diets can be classified into two macronutrient types: 1) high carbohydrate, low protein, low fat diets that use grains, often in cooked porridges or soups, with fruits and vegetables or 2) diets having more modest or intermediate levels of protein, fat, and carbohydrates that include dog food, bear chows, or omnivore dry or canned products supplemented with fruits and vegetables (Fig. 3). Examples of the first type of diet are more common in Germany [e.g., Leipzig Zoo (ME protein 11%, fat 5%, and carbohydrate 84%)] and the various bear rescue centers in India [e.g., Bannerghatta Bear Rescue Centre (ME protein 10%, fat 9%, and carbohydrate 81%)]. Examples of the second type of diet are more common in US and other European zoos and have more protein and fat than the high grain diets but are much lower in fat than what bears selected in the current study22 (Fig. 3). Nevertheless, bears consuming all past and current zoo diets are prone to developing hepatobiliary cancer and inflammatory bowel disease.If these problems are dietary in origin and not due to something unique to feeding on termites and ants (e.g., development of a unique gastrointestinal microbiome or consumption of formic acid in ants or chitin in both ants and termites), there are two broad types of diets not fed in captivity (i.e., high protein diets and high fat diets) (Fig. 3). In evaluating if either one of those might be more suitable for sloth bears, the protein ME ratios of ursid milks and the diets voluntarily selected by brown bears, polar bears, giant pandas, and sloth bears are low and do not differ from each other (t(3) = 2.449, p = 0.092), which minimizes maintenance energy requirements and maximizes the efficiency of gain1,3,4,29,40 (Table 1). Additionally, brown bears and sloth bears prefer high fat, low carbohydrate diets when given a choice between foods rich in either carbohydrates or fats3 (Table 1, Fig. 3). This fat preference in the adult ursid diet is virtually identical to that occurring in ursid milks (t(2) = -0.726, p = 0.543) even though omnivorous ursids likely have a strong preference for sweet flavors41.While an understanding of the link between dietary macronutrient content and biliary cancer is lacking, we hypothesize that bears, such as polar bears and apparently sloth bears that prefer or evolved to consume high-fat diets, have high resting rates of bile production. Consequently, when sloth bears consume a high-carbohydrate, low-fat diet long term, bile is not secreted into the digestive tract as fast as it is being produced and may back up in the bile ducts, cause bile duct dilation and inflammation, and ultimately biliary cancer. An example of this process is a rare congenital disease in humans and other animals known as choledochal cyst disease. Sacs or outpocketings may develop along the bile ducts in this disease. Bile sitting in those sacs or in the bile ducts causes inflammation of the duct walls and, if not treated by surgical excision, biliary cancer42.If we assume the macronutrient characteristics of ursid milks and the preferences for low protein, low carbohydrate, high fat diets exhibited by brown bears, polar bears, and sloth bears are healthy, current and past sloth bear zoo diets have provided too little fat, too much digestible carbohydrate, and often too much protein (Fig. 3). While this mismatch between the diets fed in captivity and what sloth bears prefer might explain the high incidence of hepatobiliary cancer, inflammatory bowel disease, and poor reproduction world-wide, we cannot dismiss the possibility that the bears’ preference for avocados and fat and the avoidance of apples, baked yams, and digestible carbohydrates in the current study has nothing to do with their macronutrient content and would be unhealthy long-term. Thus, additional feeding studies are needed to determine if a high fat, low protein, low carbohydrate diet might be the key to improving the health, reproduction, and longevity of captive sloth bears.Finally, the selection of lower protein diets by giant pandas, polar bears, sloth bears, and brown bears and the often low-protein omnivorous diets of the other four ursids indicate that all ursids can modulate liver catabolic enzyme activity when needed to conserve protein. This would suggest that this ability to conserve protein occurred early in the evolution of ursids from a high protein carnivore ancestor and may have been critical to the spread of ursids world-wide by opening niches that could not be filled by another high protein carnivore. While all ursids at times may consume foods with a much higher protein content than that of a low protein omnivore, that selection process can only be evaluated relative to the other available dietary choices interacting with foraging and metabolic constraints and does not indicate their preferred diet is that of a high protein carnivore2,43,44. More