Ecology

1.Bercik, P. et al. The intestinal microbiota affect central levels of brain-derived neurotropic factor and behavior in mice. Gastroenterology 141, 599–609 (2011).CAS 
PubMed 

Google Scholar 
2.Johnson, K. V.-A. & Foster, K. R. Why does the microbiome affect behaviour? Nat. Rev. Microbiol. 16, 647–655 (2018).CAS 
PubMed 

Google Scholar 
3.Sherwin, E., Bordenstein, S. R., Quinn, J. L., Dinan, T. G. & Cryan, J. F. Microbiota and the social brain. Science 366, eaar2016 (2019).CAS 
PubMed 

Google Scholar 
4.Charbonneau, M. R. et al. A microbial perspective of human developmental biology. Nature 535, 48–55 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
5.Blanton, L. V. et al. Gut bacteria that prevent growth impairments transmitted by microbiota from malnourished children. Science 351, aad3311 (2016).PubMed 

Google Scholar 
6.Matsuoka, K. & Kanai, T. The gut microbiota and inflammatory bowel disease. Semin. Immunopathol. 37, 47–55 (2015).CAS 
PubMed 

Google Scholar 
7.Niu, B., Paulson, J. N., Zheng, X. & Kolter, R. Simplified and representative bacterial community of maize roots. Proc. Natl Acad. Sci. USA 114, E2450–E2459 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
8.Berg, M. & Koskella, B. Nutrient- and dose-dependent microbiome-mediated protection against a plant pathogen. Curr. Biol. 28, 2487–2492 (2018).CAS 
PubMed 

Google Scholar 
9.Wei, Z. et al. Trophic network architecture of root-associated bacterial communities determines pathogen invasion and plant health. Nat. Commun. 6, 8413 (2015).10.Keebaugh, E. S., Yamada, R., Obadia, B., Ludington, W. B. & William, W. J. Microbial quantity impacts Drosophila nutrition, development, and lifespan. iScience 4, 247–259 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
11.Camarinha-Silva, A. et al. Host genome influence on gut microbial composition and microbial prediction of complex traits in pigs. Genetics 206, 1637–1644 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
12.Difford, G. F. et al. Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows. PLoS Genet. 14, e1007580 (2018).PubMed 
PubMed Central 

Google Scholar 
13.Moran, N. A. & Sloan, D. B. The hologenome concept: helpful or hollow? PLoS Biol. 13, e1002311 (2015).PubMed 
PubMed Central 

Google Scholar 
14.Henry, L. P., Bruijning, M., Forsberg, S. K. G. & Ayroles, J. F. The microbiome extends host evolutionary potential. Nat. Commun. 12, 5141 (2021).15.Foster, K. R., Schluter, J., Coyte, K. Z. & Rakoff-Nahoum, S. The evolution of the host microbiome as an ecosystem on a leash. Nature 548, 43–51 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
16.Baumann, P. Biology of bacteriocyte-associated endosymbionts of plant sap-sucking insects. Annu. Rev. Microbiol. 59, 155–189 (2005).CAS 
PubMed 

Google Scholar 
17.Douglas, A. E. Nutritional interactions in insect–microbial symbioses: aphids and their symbiotic bacteria Buchnera. Annu. Rev. Entomol. 43, 17–37 (1998).CAS 
PubMed 

Google Scholar 
18.Roughgarden, J., Gilbert, S. F., Rosenberg, E., Zilber-Rosenberg, I. & Lloyd, E. A. Holobionts as units of selection and a model of their population dynamics and evolution. Biol. Theory 13, 44–65 (2018).
Google Scholar 
19.Fukatsu, T. & Hosokawa, T. Capsule-transmitted gut symbiotic bacterium of the Japanese common plataspid stinkbug, Megacopta punctatissima. Appl. Environ. Microbiol. 68, 389–396 (2002).CAS 
PubMed 
PubMed Central 

Google Scholar 
20.Kaiwa, N. et al. Symbiont-supplemented maternal investment underpinning host’s ecological adaptation. Curr. Biol. 24, 2465–2470 (2014).CAS 
PubMed 

Google Scholar 
21.Jahnes, B. C., Herrmann, M. & Sabree, Z. L. Conspecific coprophagy stimulates normal development in a germ-free model invertebrate. PeerJ 7, e6914 (2019).PubMed 
PubMed Central 

Google Scholar 
22.Estes, A. M. et al. Brood ball-mediated transmission of microbiome members in the dung beetle, Onthophagus taurus (Coleoptera: Scarabaeidae). PLoS ONE 8, e79061 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
23.van Vliet, S. & Doebeli, M. The role of multilevel selection in host microbiome evolution. Proc. Natl Acad. Sci. USA 116, 20591–20597 (2019).PubMed 
PubMed Central 

Google Scholar 
24.Zeng, Q., Wu, S., Sukumaran, J. & Rodrigo, A. Models of microbiome evolution incorporating host and microbial selection. Microbiome 5, 127 (2017).25.Björk, J. R., Diez-Vives, C., Astudillo-Garcia, C., Archie, E. A. & Montoya, J. M. Vertical transmission of sponge microbiota is inconsistent and unfaithful. Nat. Ecol. Evol. 3, 1172–1183 (2019).PubMed 
PubMed Central 

Google Scholar 
26.Douglas, A. E. & Werren, J. H. Holes in the hologenome: why host–microbe symbioses are not holobionts. mBio 7, e02099-15 (2016).PubMed 
PubMed Central 

Google Scholar 
27.Hammer, T. J. & Moran, N. A. Links between metamorphosis and symbiosis in holometabolous insects. Phil. Trans. R. Soc. B 374, 20190068 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
28.Metcalf, C. J. E., Henry, L. P., Rebolleda-Gomez, M. & Koskella, B. Why evolve reliance on the microbiome for timing of ontogeny?. mBio 10, e01496-19 (2019).PubMed 
PubMed Central 

Google Scholar 
29.Bruijning, M., Metcalf, C. J. E., Jongejans, E. & Ayroles, J. F. The evolution of variance control. Trends Ecol. Evol. 35, 22–23 (2020).PubMed 

Google Scholar 
30.Bull, J. J. Evolution of phenotypic variance. Evolution 41, 303–315 (1987).CAS 
PubMed 

Google Scholar 
31.Philippi, T. & Seger, J. Hedging one’s evolutionary bets, revisited. Trends Ecol. Evol. 4, 41–44 (1989).CAS 
PubMed 

Google Scholar 
32.Vasseur, D. A. & Yodzis, P. The color of environmental noise. Ecology 85, 1146–1152 (2004).
Google Scholar 
33.Halley, J. M. Ecology, evolution and 1f-noise. Trends Ecol. Evol. 11, 33–37 (1996).CAS 
PubMed 

Google Scholar 
34.Botero, C. A., Weissing, F. J., Wright, J. & Rubenstein, D. R. Evolutionary tipping points in the capacity to adapt to environmental change. Proc. Natl Acad. Sci. USA 112, 184–189 (2015).CAS 
PubMed 

Google Scholar 
35.Burns, A. R. et al. Contribution of neutral processes to the assembly of gut microbial communities in the zebrafish over host development. ISME J. 10, 655–664 (2016).CAS 
PubMed 

Google Scholar 
36.Kolodny, O. et al. Coordinated change at the colony level in fruit bat fur microbiomes through time. Nat. Ecol. Evol. 3, 116–124 (2019).PubMed 

Google Scholar 
37.Sieber, M. et al. Neutrality in the metaorganism. PLoS Biol. 17, e3000298 (2019).PubMed 
PubMed Central 

Google Scholar 
38.Burns, A. R. et al. Interhost dispersal alters microbiome assembly and can overwhelm host innate immunity in an experimental zebrafish model. Proc. Natl Acad. Sci. USA 114, 11181–11186 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
39.Moeller, A. H., Suzuki, T. A., Phifer-Rixey, M. & Nachman, M. W. Transmission modes of the mammalian gut microbiota. Science 362, 453–457 (2018).CAS 
PubMed 

Google Scholar 
40.Zapién-Campos, R., Sieber, M. & Traulsen, A. Stochastic colonization of hosts with a finite lifespan can drive individual host microbes out of equilibrium. PLoS Comput. Biol. 16, e1008392 (2020).PubMed 
PubMed Central 

Google Scholar 
41.De Vries, E. J., Jacobs, G., Sabelis, M. W., Menken, S. B. J. & Breeuwer, J. A. J. Diet-dependent effects of gut bacteria on their insect host: the symbiosis of Erwinia sp. and western flower thrips. Proc. R. Soc. Lond. B 271, 2171–2178 (2004).
Google Scholar 
42.Johnson, N. C., Graham, J. H. & Smith, F. A. Functioning of mycorrhizal associations along the mutualism–parasitism continuum. N. Phytol. 135, 575–585 (1997).
Google Scholar 
43.Cheney, K. L. & Côté, I. M. Mutualism or parasitism? The variable outcome of cleaning symbioses. Biol. Lett. 1, 162–165 (2005).PubMed 
PubMed Central 

Google Scholar 
44.Russell, J. A. & Moran, N. A. Costs and benefits of symbiont infection in aphids: variation among symbionts and across temperatures. Proc. R. Soc. B 273, 603–610 (2006).PubMed 

Google Scholar 
45.Oliver, K. M., Degnan, P. H., Burke, G. R. & Moran, N. A. Facultative symbionts in aphids and the horizontal transfer of ecologically important traits. Annu. Rev. Entomol. 55, 247–266 (2010).CAS 
PubMed 

Google Scholar 
46.Oliver, K. M., Russell, J. A., Moran, N. A. & Hunter, M. S. Facultative bacterial symbionts in aphids confer resistance to parasitic wasps. Proc. Natl Acad. Sci. USA 100, 1803–1807 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
47.Oliver, K. M., Campos, J., Moran, N. A. & Hunter, M. S. Population dynamics of defensive symbionts in aphids. Proc. R. Soc. B 275, 293–299 (2008).PubMed 

Google Scholar 
48.Ives, A. R. et al. Self-perpetuating ecological–evolutionary dynamics in an agricultural host–parasite system. Nat. Ecol. Evol. 4, 702–711 (2020).PubMed 

Google Scholar 
49.Chen, D.-Q., Montllor, C. B. & Purcell, A. H. Fitness effects of two facultative endosymbiotic bacteria on the pea aphid, Acyrthosiphon pisum, and the blue alfalfa aphid, A. kondoi. Entomol. Exp. Appl. 95, 315–323 (2000).
Google Scholar 
50.Montllor, C. B., Maxmen, A. & Purcell, A. H. Facultative bacterial endosymbionts benefit pea aphids Acyrthosiphon pisum under heat stress. Ecol. Entomol. 27, 189–195 (2002).
Google Scholar 
51.Kikuchi, Y. et al. Symbiont-mediated insecticide resistance. Proc. Natl Acad. Sci. USA 109, 8618–8622 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
52.Kikuchi, Y. & Yumoto, I. Efficient colonization of the bean bug Riptortus pedestris by an environmentally transmitted Burkholderia symbiont. Appl. Environ. Microbiol. 79, 2088–2091 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
53.Gould, A. L. et al. Microbiome interactions shape host fitness. Proc. Natl Acad. Sci. USA 115, E11951–E11960 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
54.Ellner, S. P. & Rees, M. Integral projection models for species with complex demography. Am. Nat. 167, 410–428 (2006).PubMed 

Google Scholar 
55.Caswell, H. Matrix Population Models: Construction, Analysis and Interpretation (Sinauer Associates, 2001).56.Asnicar, F. et al. Studying vertical microbiome transmission from mothers to infants by strain-level metagenomic profiling. mSystems 2, e00164-16 (2017).PubMed 
PubMed Central 

Google Scholar 
57.Yassour, M. et al. Strain-level analysis of mother-to-child bacterial transmission during the first few months of life. Cell Host Microbe 24, 146–154 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
58.Ferretti, P. et al. Mother-to-infant microbial transmission from different body sites shapes the developing infant gut microbiome. Cell Host Microbe 24, 133–145 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
59.Nyholm, S. V. & McFall-Ngai, M. The winnowing: establishing the squid-Vibrio symbiosis. Nat. Rev. Microbiol. 2, 632–642 (2004).CAS 
PubMed 

Google Scholar 
60.Kikuchi, Y., Hosokawa, T. & Fukatsu, T. Insect–microbe mutualism without vertical transmission: a stinkbug acquires a beneficial gut symbiont from the environment every generation. Appl. Environ. Microbiol. 73, 4308–4316 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
61.Ibáñez, F., Tonelli, M. L., Muñoz, V., Figueredo, M. S. & Fabra, A. in Endophytes: Biology and Biotechnology (ed. Maheshwari, D.) 25–40 (Springer, 2017).62.Werren, J. H., Baldo, L. & Clark, M. E. Wolbachia: master manipulators of invertebrate biology. Nat. Rev. Microbiol. 6, 741–751 (2008).CAS 
PubMed 

Google Scholar 
63.Teixeira, L., Ferreira, Á. & Ashburner, M. The bacterial symbiont Wolbachia induces resistance to RNA viral infections in Drosophila melanogaster. PLoS Biol. 6, 2753–2763 (2008).CAS 

Google Scholar 
64.Chrostek, E. et al. Wolbachia variants induce differential protection to viruses in Drosophila melanogaster: a phenotypic and phylogenomic analysis. PLoS Genet. 9, e1003896 (2013).PubMed 
PubMed Central 

Google Scholar 
65.Chrostek, E. & Teixeira, L. Mutualism breakdown by amplification of Wolbachia genes. PLoS Biol. 13, e1002065 (2015).PubMed 
PubMed Central 

Google Scholar 
66.Ravel, C., Michalakis, Y. & Charmet, G. The effect of imperfect transmission on the frequency of mutualistic seed-borne endophytes in natural populations of grasses. Oikos 80, 18–24 (1997).
Google Scholar 
67.Buskirk, S. W., Rokes, A. B. & Lang, G. I. Adaptive evolution of nontransitive fitness in yeast. eLife 9, e62238 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
68.Clune, J. et al. Natural selection fails to optimize mutation rates for long-term adaptation on rugged fitness landscapes. PLoS Comput. Biol. 4, e1000187 (2008).PubMed 
PubMed Central 

Google Scholar 
69.King, O. D. & Masel, J. The evolution of bet-hedging adaptations to rare scenarios. Theor. Popul. Biol. 72, 560–575 (2007).PubMed 
PubMed Central 

Google Scholar 
70.Liu, X.-D., Lei, H.-X. & Chen, F.-F. Infection pattern and negative effects of a facultative endosymbiont on its insect host are environment-dependent. Sci. Rep. 9, 4013 (2019).71.Oyserman, B. O. et al. Extracting the GEMs: genotype, environment, and microbiome interactions shaping host phenotypes. Front. Microbiol. 11, 3444 (2021).
Google Scholar 
72.Rock, D. I. et al. Context-dependent vertical transmission shapes strong endosymbiont community structure in the pea aphid, Acyrthosiphon pisum. Mol. Ecol. 27, 2039–2056 (2018).PubMed 

Google Scholar 
73.Osaka, R., Nomura, M., Watada, M. & Kageyama, D. Negative effects of low temperatures on the vertical transmission and infection density of a Spiroplasma endosymbiont in Drosophila hydei. Curr. Microbiol. 57, 335–339 (2008).CAS 
PubMed 

Google Scholar 
74.Gundel, P. E. et al. Imperfect vertical transmission of the endophyte Neotyphodium in exotic grasses in grasslands of the Flooding Pampa. Microb. Ecol. 57, 740 (2009).PubMed 

Google Scholar 
75.Li, L. & Ma, Z. S. Testing the neutral theory of biodiversity with human microbiome datasets. Sci. Rep. 6, 31448 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
76.Foster, K. R. & Bell, T. Competition, not cooperation, dominates interactions among culturable microbial species. Curr. Biol. 22, 1845–1850 (2012).CAS 
PubMed 

Google Scholar 
77.Sprockett, D., Fukami, T. & Relman, D. A. Role of priority effects in the early-life assembly of the gut microbiota. Nat. Rev. Gastroenterol. Hepatol. 15, 197–205 (2018).PubMed 
PubMed Central 

Google Scholar 
78.Stein, R. R. et al. Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota. PLoS Comput. Biol. 9, e1003388 (2013).PubMed 
PubMed Central 

Google Scholar 
79.Scheuring, I. & Yu, D. W. How to assemble a beneficial microbiome in three easy steps. Ecol. Lett. 15, 1300–1307 (2012).PubMed 
PubMed Central 

Google Scholar 
80.Roughgarden, J. Holobiont evolution: Mathematical model with vertical vs. horizontal microbiome transmission. Phil. Theory Pract. Biol. 12, 002 (2020).81.Theis, K. R. et al. Getting the hologenome concept right: an eco-evolutionary framework for hosts and their microbiomes. mSystems 1, e00028-16 (2016).PubMed 
PubMed Central 

Google Scholar 
82.Sloan, W. T. et al. Quantifying the roles of immigration and chance in shaping prokaryote community structure. Environ. Microbiol. 8, 732–740 (2006).PubMed 

Google Scholar 
83.Gillespie, J. Polymorphism in random environments. Theor. Popul. Biol. 4, 193–195 (1973).
Google Scholar 
84.Bruijning, M. Code for: Natural selection for imprecise vertical transmission in host-microbiota systems. Zenodo https://doi.org/10.5281/zenodo.5534317 (2021).85.Sauer, C., Dudaczek, D., Hölldobler, B. & Gross, R. Tissue localization of the endosymbiotic bacterium “Candidatus Blochmannia floridanus” in adults and larvae of the carpenter ant Camponotus floridanus. Appl. Environ. Microbiol. 68, 4187–4193 (2002).CAS 
PubMed 
PubMed Central 

Google Scholar 
86.Koga, R., Meng, X.-Y., Tsuchida, T. & Fukatsu, T. Cellular mechanism for selective vertical transmission of an obligate insect symbiont at the bacteriocyte–embryo interface. Proc. Natl Acad. Sci. USA 109, E1230–E1237 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
87.Brentassi, M. E. et al. Bacteriomes of the corn leafhopper, Dalbulus maidis (DeLong & Wolcott, 1923) (Insecta, Hemiptera, Cicadellidae: Deltocephalinae) harbor Sulcia symbiont: molecular characterization, ultrastructure, and transovarial transmission. Protoplasma 254, 1421–1429 (2017).CAS 
PubMed 

Google Scholar 
88.Picazo, D. R. et al. Horizontally transmitted symbiont populations in deep-sea mussels are genetically isolated. ISME J. 13, 2954–2968 (2019).
Google Scholar 
89.Gilbert, J. A. et al. Current understanding of the human microbiome. Nat. Med. 24, 392–400 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
90.Korpela, K. et al. Selective maternal seeding and environment shape the human gut microbiome. Genome Res. 28, 561–568 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
91.Walters, W. A. et al. Large-scale replicated field study of maize rhizosphere identifies heritable microbes. Proc. Natl Acad. Sci. USA 115, 7368–7373 (2018).PubMed 
PubMed Central 

Google Scholar 
92.Douglas, A. E. Simple animal models for microbiome research. Nat. Rev. Microbiol. 17, 764–775 (2019).CAS 
PubMed 

Google Scholar 
93.Sommer, F. et al. The gut microbiota modulates energy metabolism in the hibernating brown bear Ursus arctos. Cell Rep. 14, 1655–1661 (2016).CAS 
PubMed 

Google Scholar 
94.David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).CAS 
PubMed 

Google Scholar  More

Cropland-mapping extent and time intervalsThe global boundaries for the cropland mapping were informed by the US Geological Survey (USGS) Global Food Security-Support Analysis Data at 30 m (GFSAD)11. The cropland mapping extent was defined using the geographic 1° × 1° grid. We included every 1° × 1° grid cell that contains cropland area according to the GFSAD. Small islands were excluded due to the absence of Landsat geometrically corrected data (Supplementary Fig. 1).The cropland mapping was performed at 4-year intervals (2000–2003, 2004–2007, 2008–2011, 2012–2015 and 2016–2019). Use of a long interval (rather than a single year) increased the number of clear-sky satellite observations in the time-series, which improves representation of land-surface phenology and the accuracy of cropland detection. For each 4-year interval, we mapped an area as cropland if a growing crop was detected during any of these years. In this way, we implemented the criterion of the maximum fallow length: if an area was not used as cropland for >4 years, it was not included in the cropland map for the corresponding time interval.Landsat dataWe employed the global 16-day normalized surface reflectance Landsat Analysis Ready Data (Landsat ARD19) as input data for cropland mapping. The Landsat ARD were generated from the entire Landsat archive from 1997 to 2019. The Landsat top-of-atmosphere reflectance was normalized using globally consistent MODIS surface reflectance as a normalization target. Individual Landsat images were aggregated into 16-day composites by prioritizing clear-sky observations.For each 4-year interval, we created a single annualized gap-free 16-day observation time-series. For each 16-day interval, we selected the observation with the highest near-infrared reflectance value (to prioritize observations with the highest vegetation cover) from 4 years of Landsat data. Observations contaminated by haze, clouds and cloud shadows, as indicated by the Landsat ARD quality layer, were removed from the analysis. If no clear-sky data were available for a 16-day interval, we filled the missing reflectance values using linear interpolation.The annualized, 16-day time-series within each 4-year interval were transformed into a set of multitemporal metrics that provide consistent land-surface phenology inputs for global cropland mapping. Metrics include selected ranks, inter-rank averages and amplitudes of surface reflectance and vegetation index values, and surface reflectance averages for selected land-surface phenology stages defined by vegetation indices (that is, surface reflectance for the maximum and minimum greenness periods). The multitemporal metrics methodology is provided in detail19,38. The Landsat metrics were augmented with elevation data39. In this way, we created spatially consistent inputs for each of the 4-year intervals. The complete list of input metrics is presented in Supplementary Table 1.Global cropland mappingGlobal cropland mapping included three stages that enabled extrapolation of visually delineated cropland training data to a temporally consistent, global cropland map time-series using machine learning. At all three stages, we employed bagged decision tree ensembles40 as a supervised classification algorithm that used class presence and absence data as the dependent variables, and a set of multitemporal metrics as independent variables at a Landsat ARD pixel scale. The bagged decision tree results in a per-pixel cropland probability layer, which has a threshold of 0.5 to obtain a cropland map.The first stage consisted of performing individual cropland classifications for a set of 924 Landsat ARD 1° × 1° tiles for the 2016–2019 interval (Supplementary Fig. 1). The tiles were chosen to represent diverse global agriculture landscapes. Classification training data (cropland class presence and absence) were manually selected through visual interpretation of Landsat metric composites and high-resolution data from Google Earth. An individual supervised classification model (bagged decision trees) was calibrated and applied to each tile.At the second stage, we used the 924 tiles that had been classified as cropland/other land and the 2016–2019 metric set to train a series of regional cropland mapping models. The classification was iterated by adding training tiles and assessing the results until the resulting map was satisfactory. We then applied the regional models to each of the preceding 4-year intervals, thus creating a preliminary time-series of global cropland maps.At the third stage, we used the preliminary global cropland maps as training data to generate temporally consistent global cropland data. As the regional models applied at the second stage were calibrated using 2016–2019 data alone, classification errors may arise due to Landsat data inconsistencies before 2016. The goal of this third stage was to create a robust spatiotemporally consistent set of locally calibrated cropland detection models. For each 1° × 1° Landsat ARD tile (13,451 tiles total), we collected training data for each 4-year interval from the preliminary cropland extent maps within a 3° radius of the target tile, with preference to select stable cropland and non-cropland pixels as training. Training data from all intervals were used to calibrate a single decision tree ensemble for each ARD tile. The per-tile models were then applied to each time interval, and the results were post-processed to remove single cropland class detections and omissions within time-series and eliminate cropland patches More

1.Paustian, K. et al. Climate-smart soils. Nature 532, 49–57 (2016).
Google Scholar 
2.Jackson, R. B. et al. The ecology of soil carbon: pools, vulnerabilities, and biotic and abiotic controls. Annu. Rev. Ecol. Evol. Syst. 48, 419–445 (2017).
Google Scholar 
3.Lal, R. Global potential of soil carbon sequestration to mitigate the greenhouse effect. CRC Crit. Rev. Plant Sci. 22, 151–184 (2003).
Google Scholar 
4.Scurlock, J. M. O. & Hall, D. O. The global carbon sink: a grassland perspective. Glob. Chang. Biol. 4, 229–233 (1998).
Google Scholar 
5.Pellegrini, A. F. A. et al. Fire frequency drives decadal changes in soil carbon and nitrogen and ecosystem productivity. Nature 553, 194–198 (2018).
Google Scholar 
6.Grace, J. et al. Productivity and carbon fluxes of tropical savannas. J. Biogeogr. 33, 387–400 (2006).
Google Scholar 
7.Walker, X. J. et al. Increasing wildfires threaten historic carbon sink of boreal forest soils. Nature 572, 520–523 (2019).
Google Scholar 
8.Jones, M. W., Santín, C., van der Werf, G. R. & Doerr, S. H. Global fire emissions buffered by the production of pyrogenic carbon. Nat. Geosci. 12, 742–747 (2019).
Google Scholar 
9.Bodí, M. B. et al. Wildland fire ash: production, composition and eco-hydro-geomorphic effects. Earth Sci. Rev. 130, 103–127 (2014).
Google Scholar 
10.Certini, G., Nocentini, C., Knicker, H., Arfaioli, P. & Rumpel, C. Wildfire effects on soil organic matter quantity and quality in two fire-prone Mediterranean pine forests. Geoderma 167–168, 148–155 (2011).
Google Scholar 
11.Jiménez-Morillo, N. T. et al. Fire effects in the molecular structure of soil organic matter fractions under Quercus suber cover. Catena 145, 266–273 (2016).
Google Scholar 
12.Certini, G. Effects of fire on properties of forest soils: a review. Oecologia 143, 1–10 (2005).
Google Scholar 
13.Lehmann, J. et al. Australian climate–carbon cycle feedback reduced by soil black carbon. Nat. Geosci. 1, 832–835 (2008).
Google Scholar 
14.Santin, C. et al. Towards a global assessment of pyrogenic carbon from vegetation fires. Glob. Chang. Biol. 22, 76–91 (2016).
Google Scholar 
15.Czimczik, C. I. & Masiello, C. A. Controls on black carbon storage in soils. Global Biogeochem. Cycles https://doi.org/10.1029/2006GB002798 (2007).16.Bird, M. I., Wynn, J. G., Saiz, G., Wurster, C. M. & McBeath, A. The pyrogenic carbon cycle. Annu. Rev. Earth Planet. Sci. 43, 273–298 (2015).
Google Scholar 
17.Randerson, J. T., Chen, Y., van der Werf, G. R., Rogers, B. M. & Morton, D. C. Global burned area and biomass burning emissions from small fires. J. Geophys. Res. Biogeosci. https://doi.org/10.1029/2012JG002128 (2012).18.Archibald, S., Lehmann, C. E. R., Gómez-Dans, J. L. & Bradstock, R. A. Defining pyromes and global syndromes of fire regimes. Proc. Natl Acad. Sci. USA 110, 6442–6447 (2013).
Google Scholar 
19.Bond, W. J., Woodward, F. I. & Midgley, G. F. The global distribution of ecosystems in a world without fire. New Phytol. 165, 525–538 (2005).
Google Scholar 
20.Chuvieco, E. et al. Historical background and current developments for mapping burned area from satellite Earth observation. Remote Sens. Environ. 225, 45–64 (2019).
Google Scholar 
21.Bowman, D. M. J. S. et al. Fire in the Earth system. Science 324, 481–484 (2009).
Google Scholar 
22.Bowman, D. M. J. S. et al. Vegetation fires in the Anthropocene. Nat. Rev. Earth Environ. 1, 500–515 (2020).
Google Scholar 
23.Friedlingstein, P. et al. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).
Google Scholar 
24.Nave, L. E., Vance, E. D., Swanston, C. W. & Curtis, P. S. Fire effects on temperate forest soil C and N storage. Ecol. Appl. 21, 1189–1201 (2011).
Google Scholar 
25.McKee, W. H. Changes in Soil Fertility Following Prescribed Burning on Coastal Plain Pine Sites Research Paper-RE-234 (US Department of Agriculture, 1982).26.Fynn, R. W. S., Haynes, R. J. & O’Connor, T. G. Burning causes long-term changes in soil organic matter content of a South African grassland. Soil Biol. Biochem. 35, 677–687 (2003).
Google Scholar 
27.Roscoe, R., Buurman, P., Velthorst, E. J. & Pereira, J. A. A. Effects of fire on soil organic matter in a “cerrado sensu-stricto” from southeast Brazil as revealed by changes in δ13C. Geoderma 95, 141–160 (2000).
Google Scholar 
28.Phillips, D. H., Foss, J. E., Buckner, E. R., Evans, R. M. & FitzPatrick, E. A. Response of surface horizons in an oak forest to prescribed burning. Soil Sci. Soc. Am. J. 64, 754–760 (2000).
Google Scholar 
29.Walker, X. J. et al. Fuel availability not fire weather controls boreal wildfire severity and carbon emissions. Nat. Clim. Chang. 10, 1130–1136 (2020).
Google Scholar 
30.Hartford, R. & Frandsen, W. When it’s hot, it’s hot… or maybe it’s not! (Surface flaming may not portend extensive soil heating). Int. J. Wildland Fire 2, 139–144 (1992).
Google Scholar 
31.Pellegrini, A. F. A. et al. Frequent burning causes large losses of carbon from deep soil layers in a temperate savanna. J. Ecol. 108, 1426–1441 (2020).
Google Scholar 
32.Wardle, D. A., Hörnberg, G., Zackrisson, O., Kalela-Brundin, M. & Coomes, D. A. Long-term effects of wildfire on ecosystem properties across an island area gradient. Science 300, 972–975 (2003).
Google Scholar 
33.Mack, M. C. et al. Carbon loss from boreal forest wildfires offset by increased dominance of deciduous trees. Science 372, 280–283 (2021).
Google Scholar 
34.Pellegrini, A. F. A., Hoffmann, W. A. & Franco, A. C. Carbon accumulation and nitrogen pool recovery during transitions from savanna to forest in central Brazil. Ecology 95, 342–352 (2014).
Google Scholar 
35.Johnson, D. W. & Curtis, P. S. Effects of forest management on soil C and N storage: meta analysis. For. Ecol. Manage. 140, 227–238 (2001).
Google Scholar 
36.González-Pérez, J. A., González-Vila, F. J., Almendros, G. & Knicker, H. The effect of fire on soil organic matter—a review. Environ. Int. 30, 855–870 (2004).
Google Scholar 
37.Scharenbroch, B. C., Nix, B., Jacobs, K. A. & Bowles, M. L. Two decades of low-severity prescribed fire increases soil nutrient availability in a Midwestern, USA oak (Quercus) forest. Geoderma 183–184, 80–91 (2012).
Google Scholar 
38.Boyer, W. D. & Miller, J. H. Effect of burning and brush treatments on nutrient and soil physical properties in young longleaf pine stands. For. Ecol. Manage. 70, 311–318 (1994).
Google Scholar 
39.Martin, A., Mariotti, A., balesdent, J., Lavelle, P. & Vuattoux, R. Estimate of organic matter turnover rate in a savanna soil by 13C natural abundance measurements. Soil Biol. Biochem. 22, 517–523 (1990).
Google Scholar 
40.McKee, W. H. & Lewis, C. E. Influence of burning and grazing on soil nutrient properties and tree growth on a Georgia coastal plain site after 40 years. In Proc. Second Biennial Southern Silvicultural Research Station Conference (Ed. Jones, E. P. J.) 79–86 (US Department of Agriculture, 1983).41.Neill, C., Patterson, W. A. & Crary, D. W. Responses of soil carbon, nitrogen and cations to the frequency and seasonality of prescribed burning in a Cape Cod oak-pine forest. For. Ecol. Manage. 250, 234–243 (2007).
Google Scholar 
42.Russell-Smith, J., Whitehead, P. J., Cook, G. D. & Hoare, J. L. Response of Eucalyptus-dominated savanna to frequent fires: lessons from Munmarlary, 1973–1996. Ecol. Monogr. 73, 349–375 (2003).
Google Scholar 
43.Guinto, D. F., Xu, Z. H., House, A. P. N. & Saffigna, P. G. Soil chemical properties and forest floor nutrients under repeated prescribed-burning in eucalypt forests of south-east Queensland, Australia. N. Z. J. For. Sci. 31, 170–187 (2001).
Google Scholar 
44.Köster, K., Berninger, F., Lindén, A., Köster, E. & Pumpanen, J. Recovery in fungal biomass is related to decrease in soil organic matter turnover time in a boreal fire chronosequence. Geoderma 235–236, 74–82 (2014).
Google Scholar 
45.O’Donnell, J. A. et al. The effect of fire and permafrost interactions on soil carbon accumulation in an upland black spruce ecosystem of interior Alaska: implications for post-thaw carbon loss. Glob. Chang. Biol. 17, 1461–1474 (2011).
Google Scholar 
46.Butnor, J. R. et al. Vertical distribution and persistence of soil organic carbon in fire-adapted longleaf pine forests. For. Ecol. Manage. 390, 15–26 (2017).
Google Scholar 
47.Sollins, P., Homann, P. & Caldwell, B. A. Stabilization and destabilization of soil organic matter: mechanisms and controls. Geoderma 74, 65–105 (1996).
Google Scholar 
48.Six, J., Conant, R. T., Paul, E. A. & Paustian, K. Stabilization mechanisms of soil organic matter: implications for C-saturation of soils. Plant Soil 241, 155–176 (2002).
Google Scholar 
49.Shi, Z. et al. The age distribution of global soil carbon inferred from radiocarbon measurements. Nat. Geosci. 13, 555–559 (2020).
Google Scholar 
50.Schmidt, M. W. I. et al. Persistence of soil organic matter as an ecosystem property. Nature 478, 49–56 (2011).
Google Scholar 
51.Lutzow, M. V. et al. Stabilization of organic matter in temperate soils: mechanisms and their relevance under different soil conditions – a review. Eur. J. Soil Sci. 57, 426–445 (2006).
Google Scholar 
52.Keiluweit, M., Wanzek, T., Kleber, M., Nico, P. & Fendorf, S. Anaerobic microsites have an unaccounted role in soil carbon stabilization. Nat. Commun. 8, 1771 (2017).
Google Scholar 
53.Six, J., Bossuyt, H., Degryze, S. & Denef, K. A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics. Soil Tillage Res. 79, 7–31 (2004).
Google Scholar 
54.Mataix-Solera, J., Cerdà, A., Arcenegui, V., Jordán, A. & Zavala, L. M. Fire effects on soil aggregation: a review. Earth Sci. Rev. 109, 44–60 (2011).
Google Scholar 
55.Chen, H. Y. H. & Shrestha, B. M. Stand age, fire and clearcutting affect soil organic carbon and aggregation of mineral soils in boreal forests. Soil Biol. Biochem. 50, 149–157 (2012).
Google Scholar 
56.Arocena, J. M. & Opio, C. Prescribed fire-induced changes in properties of sub-boreal forest soils. Geoderma 113, 1–16 (2003).
Google Scholar 
57.Jian, M., Berhe, A. A., Berli, M. & Ghezzehei, T. A. Vulnerability of physically protected soil organic carbon to loss under low severity fires. Front. Environ. Sci. 6, 66 (2018).
Google Scholar 
58.Debano, L. F. The role of fire and soil heating on water repellency in wildland environments: a review. J. Hydrol. 231, 195–206 (2000).
Google Scholar 
59.Hallett, P. D. et al. Disentangling the impact of AM fungi versus roots on soil structure and water transport. Plant Soil 314, 183–196 (2009).
Google Scholar 
60.Bardgett, R. D., Mommer, L. & De Vries, F. T. Going underground: root traits as drivers of ecosystem processes. Trends Ecol. Evol. 29, 692–699 (2014).
Google Scholar 
61.Hartnett, D. C., Potgieter, A. F. & Wilson, G. W. T. Fire effects on mycorrhizal symbiosis and root system architecture in southern African savanna grasses. Afr. J. Ecol. 42, 328–337 (2004).
Google Scholar 
62.Eom, A.-H., Hartnett, D. C., Wilson, G. W. T. & Figge, D. A. H. The effect of fire, mowing and fertilizer amendment on arbuscular mycorrhizas in tallgrass prairie. Am. Midl. Nat. 142, 55–70 (1999).
Google Scholar 
63.Sankey, J. B. et al. Climate, wildfire, and erosion ensemble foretells more sediment in western USA watersheds. Geophys. Res. Lett. 44, 8884–8892 (2017).
Google Scholar 
64.Van Oost, K. et al. Legacy of human-induced C erosion and burial on soil-atmosphere C exchange. Proc. Natl Acad. Sci. USA 109, 19492–19497 (2012).
Google Scholar 
65.Kleber, M. et al. Mineral-organic associations: formation, properties, and relevance in soil environments. Advances in Agronomy 130, 1–140 (2015).
Google Scholar 
66.Torn, M. S., Trumbore, S. E., Chadwick, O. A., Vitousek, P. M. & Hendricks, D. M. Mineral control of soil organic carbon storage and turnover. Nature 389, 170–173 (1997).
Google Scholar 
67.Baldock, J. A. & Skjemstad, J. O. Role of the soil matrix and minerals in protecting natural organic materials against biological attack. Org. Geochem. 31, 697–710 (2000).
Google Scholar 
68.Kaiser, K. & Guggenberger, G. Mineral surfaces and soil organic matter. Eur. J. Soil Sci. 54, 219–236 (2003).
Google Scholar 
69.Knicker, H. How does fire affect the nature and stability of soil organic nitrogen and carbon? A review. Biogeochemistry 85, 91–118 (2007).
Google Scholar 
70.Ketterings, Q. M., Bigham, J. M. & Laperche, V. Changes in soil mineralogy and texture caused by slash-and-burn fires in Sumatra, Indonesia. Soil Sci. Soc. Am. J. 64, 1108–1117 (2000).
Google Scholar 
71.Ulery, A. L., Graham, R. C. & Bowen, L. H. Forest fire effects on soil phyllosilicates in California. Soil Sci. Soc. Am. J. 60, 309–315 (1996).
Google Scholar 
72.Fernández, I., Cabaneiro, A. & Carballas, T. Organic matter changes immediately after a wildfire in an atlantic forest soil and comparison with laboratory soil heating. Soil Biol. Biochem. 29, 1–11 (1997).
Google Scholar 
73.Heckman, K., Campbell, J., Powers, H., Law, B. & Swanston, C. The influence of fire on the radiocarbon signature and character of soil organic matter in the Siskiyou national forest, Oregon, USA. Fire Ecol. 9, 40–56 (2013).
Google Scholar 
74.Knicker, H., González-Vila, F. J. & González-Vázquez, R. Biodegradability of organic matter in fire-affected mineral soils of Southern Spain. Soil Biol. Biochem. 56, 31–39 (2013).
Google Scholar 
75.Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K. & Paul, E. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob. Chang. Biol. 19, 988–995 (2013).
Google Scholar 
76.Kögel-Knabner, I. The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter: fourteen years on. Soil Biol. Biochem. 105, A3–A8 (2017).
Google Scholar 
77.Neff, J., Harden, J. & Gleixner, G. Fire effects on soil organic matter content, composition, and nutrients in boreal interior Alaska. Can. J. For. 35, 2178–2187 (2005).
Google Scholar 
78.Harden, J. W. et al. Chemistry of burning the forest floor during the FROSTFIRE experimental burn, interior Alaska, 1999. Glob. Biogeochem. Cycles https://doi.org/10.1029/2003GB002194 (2004).79.DeLuca, T. H. & Aplet, G. H. Charcoal and carbon storage in forest soils of the Rocky Mountain West. Front. Ecol. Environ. 6, 18–24 (2008).
Google Scholar 
80.Preston, C. M. & Schmidt, M. W. I. Black (pyrogenic) carbon in boreal forests: a synthesis of current knowledge and uncertainties. Biogeosci. Discuss. 3, 211–271 (2006).
Google Scholar 
81.Krishnaraj, S. J., Baker, T. G., Polglase, P. J., Volkova, L. & Weston, C. J. Prescribed fire increases pyrogenic carbon in litter and surface soil in lowland Eucalyptus forests of south-eastern Australia. For. Ecol. Manage. 366, 98–105 (2016).
Google Scholar 
82.Singh, N., Abiven, S., Torn, M. S. & Schmidt, M. W. I. Fire-derived organic carbon in soil turns over on a centennial scale. Biogeosciences 9, 2847–2857 (2012).
Google Scholar 
83.Knicker, H., Almendros, G., González-Vila, F. J., Martin, F. & Lüdemann, H. D. 13C- and 15N-NMR spectroscopic examination of the transformation of organic nitrogen in plant biomass during thermal treatment. Soil Biol. Biochem. 28, 1053–1060 (1996).
Google Scholar 
84.Waldrop, M. P. & Harden, J. W. Interactive effects of wildfire and permafrost on microbial communities and soil processes in an Alaskan black spruce forest. Glob. Chang. Biol. 14, 2591–2602 (2008).
Google Scholar 
85.Pellegrini, A. F. A. et al. Repeated fire shifts carbon and nitrogen cycling by changing plant inputs and soil decomposition across ecosystems. Ecol. Monogr. 90, e01409 (2020).
Google Scholar 
86.Wang, Q., Zhong, M. & Wang, S. A meta-analysis on the response of microbial biomass, dissolved organic matter, respiration, and N mineralization in mineral soil to fire in forest ecosystems. For. Ecol. Manage. 271, 91–97 (2012).
Google Scholar 
87.Dooley, S. R. & Treseder, K. K. The effect of fire on microbial biomass: a meta-analysis of field studies. Biogeochemistry 109, 49–61 (2012).
Google Scholar 
88.Beringer, J. et al. Fire impacts on surface heat, moisture and carbon fluxes from a tropical savanna in northern Australia. Int. J. Wildland Fire 12, 333–340 (2003).
Google Scholar 
89.Dove, N. C. & Hart, S. C. Fire reduces fungal species richness and in situ mycorrhizal colonization: a meta-analysis. Fire Ecol. 13, 37–65 (2017).
Google Scholar 
90.Pressler, Y., Moore, J. C. & Cotrufo, M. F. Belowground community responses to fire: meta-analysis reveals contrasting responses of soil microorganisms and mesofauna. Oikos 128, 309–327 (2019).
Google Scholar 
91.Holden, S. R., Gutierrez, A. & Treseder, K. K. Changes in soil fungal communities, extracellular enzyme activities, and litter decomposition across a fire chronosequence in Alaskan boreal forests. Ecosystems 16, 34–46 (2013).
Google Scholar 
92.Gongalsky, K. B. et al. Forest fire induces short-term shifts in soil food webs with consequences for carbon cycling. Ecol. Lett. 24, 438–450 (2021).
Google Scholar 
93.Wardle, D. A., Nilsson, M.-C. & Zackrisson, O. Fire-derived charcoal causes loss of forest humus. Science 320, 629 (2008).
Google Scholar 
94.Whitman, T. et al. Soil bacterial and fungal response to wildfires in the Canadian boreal forest across a burn severity gradient. Soil Biol. Biochem. 138, 107571 (2019).
Google Scholar 
95.Harden, J. W. et al. The role of fire in the boreal carbon budget. Glob. Chang. Biol. 6, 174–184 (2000).
Google Scholar 
96.Smith, H. G., Sheridan, G. J., Lane, P. N. J., Nyman, P. & Haydon, S. Wildfire effects on water quality in forest catchments: a review with implications for water supply. J. Hydrol. 396, 170–192 (2011).
Google Scholar 
97.Clemmensen, K. E. et al. Carbon sequestration is related to mycorrhizal fungal community shifts during long-term succession in boreal forests. New Phytol. 205, 1525–1536 (2015).
Google Scholar 
98.Pellegrini, A. F. A. et al. Low-intensity frequent fires in coniferous forests transform soil organic matter in ways that may offset ecosystem carbon losses. Glob. Chang. Biol. 27, 3810–3823 (2021).
Google Scholar 
99.Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).
Google Scholar 
100.Bossio, D. A. et al. The role of soil carbon in natural climate solutions. Nat. Sustain. 3, 391–398 (2020).
Google Scholar 
101.Anderegg, W. R. L. et al. Climate-driven risks to the climate mitigation potential of forests. Science 368, 6497 (2020).
Google Scholar 
102.Walker, R. B., Coop, J. D., Parks, S. A. & Trader, L. Fire regimes approaching historic norms reduce wildfire-facilitated conversion from forest to non-forest. Ecosphere 9, e02182 (2018).
Google Scholar 
103.Wieder, W. R., Boehnert, J., Bonan, G. B. & Langseth, M. Regridded Harmonized World Soil Database v1.2 (Oak Ridge National Laboratory, 2014); https://doi.org/10.3334/ORNLDAAC/1247104.Andela, N. et al. A human-driven decline in global burned area. Science 356, 1356–1362 (2017).
Google Scholar 
105.Oliveras, I. et al. Effects of fire regimes on herbaceous biomass and nutrient dynamics in the Brazilian savanna. Int. J. Wildland Fire 22, 368–380 (2013).
Google Scholar 
106.Newland, J. A. & DeLuca, T. H. Influence of fire on native nitrogen-fixing plants and soil nitrogen status in ponderosa pine – Douglas-fir forests in western Montana. Can. J. For. Res. 30, 274–282 (2000).
Google Scholar 
107.Bormann, B. T., Homann, P. S., Darbyshire, R. L. & Morrissette, B. A. Intense forest wildfire sharply reduces mineral soil C and N: the first direct evidence. Can. J. For. Res. 38, 2771–2783 (2008).
Google Scholar 
108.Reich, P. B., Peterson, D. W., Wedin, D. A. & Wrage, K. Fire and vegetation effects on productivity and nitrogen cycling across a forest-grassland continuum. Ecology 82, 1703–1719 (2001).
Google Scholar 
109.O’Neill, K. P., Richter, D. D. & Kasischke, E. S. Succession-driven changes in soil respiration following fire in black spruce stands of interior Alaska. Biogeochemistry 80, 1–20 (2006).
Google Scholar 
110.Köster, E. et al. Changes in fluxes of carbon dioxide and methane caused by fire in Siberian boreal forest with continuous permafrost. J. Environ. Manage. 228, 405–415 (2018).
Google Scholar 
111.Zhao, H., Tong, D. Q., Lin, Q., Lu, X. & Wang, G. Effect of fires on soil organic carbon pool and mineralization in a Northeastern China wetland. Geoderma 189–190, 532–539 (2012).
Google Scholar 
112.Kuzyakov, Y., Friedel, J. & Stahr, K. Review of mechanisms and quantification of priming effects. Soil Biol. Biochem. 32, 1485–1498 (2000).
Google Scholar 
113.Wang, J., Xiong, Z. & Kuzyakov, Y. Biochar stability in soil: meta‐analysis of decomposition and priming effects. Glob. Change Biol. Bioenergy 8, 512–523 (2016).
Google Scholar 
114.Pellegrini, A. F. A. et al. Decadal changes in fire frequencies shift tree communities and functional traits. Nat. Ecol. Evol. 5, 504–512 (2021).
Google Scholar 
115.Peterson, D. W., Reich, P. B., Wrage, K. J. & Franklin, J. Plant functional group responses to fire frequency and tree canopy cover gradients in oak savannas and woodlands. J. Veg. Sci. 18, 3–12 (2007).
Google Scholar 
116.Reisser, M., Purves, R. S., Schmidt, M. W. I. & Abiven, S. Pyrogenic carbon in soils: A literature-based inventory and a global estimation of its content in soil organic carbon and stocks. Front. Earth Sci. 4, 80 (2016).
Google Scholar 
117.Loades, K. W., Bengough, A. G., Bransby, M. F. & Hallett, P. D. Planting density influence on fibrous root reinforcement of soils. Ecol. Eng. 36, 276–284 (2010).
Google Scholar 
118.Balshi, M. S. et al. The role of historical fire disturbance in the carbon dynamics of the pan-boreal region: a process-based analysis. J. Geophys. Res. 112, G02029 (2007).
Google Scholar 
119.Aaltonen, H. et al. Forest fires in Canadian permafrost region: the combined effects of fire and permafrost dynamics on soil organic matter quality. Biogeochemistry 143, 257–274 (2019).
Google Scholar 
120.Treseder, K. K., Mack, M. C. & Cross, A. Relationships among fires, fungi, and soil dynamics in Alaskan boreal forests. Ecol. Appl. 14, 1826–1838 (2004).
Google Scholar 
121.Kelly, J. et al. Boreal forest soil carbon fluxes one year after a wildfire: effects of burn severity and management. Glob. Chang. Biol. 27, 4181–4195 (2021).
Google Scholar 
122.Aaltonen, H. et al. Temperature sensitivity of soil organic matter decomposition after forest fire in Canadian permafrost region. J. Environ. Manage. 241, 637–644 (2019).
Google Scholar  More

1.Tihelka et al. Angiosperm pollinivory in a Cretaceous beetle. Nat. Plants. 7, 445–451 (2021).Article 

Google Scholar 
2.Halbritter et al. Illustrated Pollen Terminology (Springer, 2018).3.Friis, E. M., Pedersen, K. R. & Crane, P. R. Early Flowers and Angiosperm Evolution (Cambridge Univ. Press, 2011).4.Seyfullah et al. Revealing the diversity of amber source plants from the Early Cretaceous Crato Formation, Brazil. BMC Evol. Biol. 20, 107 (2020).Article 

Google Scholar 
5.Nation, L. Insect Physiology and Biochemistry (CRC Press, 2002).6.Lupia, R., Herendeen, P. S. & Keller, J. A. A new fossil flower and associated coprolites: evidence for angiosperm–insect interactions in the Santonian (Late Cretaceous) of Georgia, USA. Int. J. Plant Sci. 163, 675–686 (2002).Article 

Google Scholar 
7.Procheş, Ş. & Johnson, S. D. Beetle pollination of the fruit-scented cones of the South African cycad Stangeria eriopus. Am. J. Bot. 96, 1722–1730 (2009).Article 

Google Scholar 
8.Shanker, C., Mohan, M., Sampathkumar, M., Lydia, C. & Katti, G. Functional significance of Micraspis discolor (F.) (Coccinellidae: Coleoptera) in the rice ecosystem. J. Appl. Entomol. 137, 601–609 (2013).Article 

Google Scholar 
9.Lehane, M. J. Peritrophic matrix structure and function. Annu. Rev. Entomol. 42, 525–550 (1997).CAS 
Article 

Google Scholar 
10.Hegedus, D., Erlandson, M., Gillott, C. & Toprak, U. New insights into peritrophic matrix synthesis, architecture, and function. Annu. Rev. Entomol. 54, 285–302 (2009).CAS 
Article 

Google Scholar 
11.Klavins, S. D., Kellogg, D. W., Krings, M., Taylor, E. L. & Taylor, T. N. Coprolites in a Middle Triassic cycad pollen cone: evidence for insect pollination in early cycads? Evol. Ecol. Res. 7, 479–488 (2005).
Google Scholar 
12.Friis, E. M., Pedersen, K. R. & Crane, P. R. Early angiosperm diversification: the diversity of pollen associated with angiosperm reproductive structures in Early Cretaceous floras from Portugal. Ann. Missouri Bot. Garden 86, 259–296 (1999).Article 

Google Scholar 
13.Brenner, G. J. The Spores and Pollen of the Potomac Group of Maryland (Waverly Press, 1963).14.Labandeira, C. C. The paleobiology of pollination and its precursors. Paleontol. Soc. Pap. 6, 233–270 (2000).Article 

Google Scholar 
15.Peris et al. False Blister Beetles and the expansion of gymnosperm–insect pollination modes before angiosperm dominance. Curr. Biol. 27, 897–904 (2017).CAS 
Article 

Google Scholar  More

Humans have infected a wide range of animals with SARS-CoV-2 viruses1–5, but the establishment of a new natural animal reservoir has not been observed. Here, we document that free-ranging white-tailed deer (Odocoileus virginianus) are highly susceptible to infection with SARS-CoV-2 virus, are exposed to a range of viral diversity from humans, and are capable of sustaining transmission in nature. SARS-CoV-2 virus was detected by rRT-PCR in more than one-third (129/360, 35.8%) of nasal swabs obtained from Odocoileus virginianus in northeast Ohio (USA) during January-March 2021. Deer in 6 locations were infected with 3 SARS-CoV-2 lineages (B.1.2, B.1.582, B.1.596). The B.1.2 viruses, dominant in humans in Ohio at the time, infected deer in four locations. Probable deer-to-deer transmission of B.1.2, B.1.582, and B.1.596 viruses was observed, allowing the virus to acquire amino acid substitutions in the spike protein (including the receptor-binding domain) and ORF1 that are infrequently seen in humans. No spillback to humans was observed, but these findings demonstrate that SARS-CoV-2 viruses have the capacity to transmit in US wildlife, potentially opening new pathways for evolution. There is an urgent need to establish comprehensive “One Health” programs to monitor deer, the environment, and other wildlife hosts globally. More

Isolates and typingThe isolates characterised as well as strain affiliations, geographic origins and clinical presentations are summarised in Table 1. Autopsy images showing typical aspects of putrid infections in some animals are shown in Fig. 1. The complete microarray hybridisation patterns are provided as Supplemental file 2 and some relevant features will be discussed in the descriptions of the respective strains. While all German isolates yielded hybridisation signals for lukF/S-PV, frequently only weak positive or ambiguous results for the lukS-PV probe were observed. This prompted further investigations, including the detection of PVL by lateral flow assay21 (Table 1) and whole genome sequencing (see below).Table 1 Details of animals, isolates and strains.Full size tableFigure 1Pathological lesions of Eurasian beavers (C. fiber) infected with BVL-positive S. aureus. (A) Severe suppurative necrotizing pneumonia (animal B); (B) severe suppurative pyelonephritis (animal G); (C) caseous lymphadenitis, popliteal lymph node (animal E); (D) urinary bladder with pyuria (animal C).Full size imagePhenotypic and genotypic resistance properties of the S. aureus isolatesAntimicrobial susceptibility testing revealed that all beaver isolates from Germany were susceptible to all antimicrobial agents tested. The distribution of minimal inhibitory concentration (MIC) values and test ranges are displayed in Supplemental File 3a. The phenotypic data corresponded well with microarray data, since none of the corresponding resistance genes was identified. In contrast, two of the Austrian isolates showed macrolide resistance with one of them also being lincosamide resistant. One isolate also exhibited tetracycline resistance. These phenotypes corresponded with the detection of genes erm(A), erm(C) and tet(M), respectively (Supplemental file 2 and 3b).The chromosomal variant of the metallothiol transferase gene fosB was present in all CC1956 isolates. Sequence analysis revealed a frame shift at position 108 creating a stop codon at positions (pos.) 146.0.148 compared to the reference sequence (N315, GenBank BA000018.3 [2,389,328.0.2,389,747]). This resulted in a truncated protein of 48 amino acids (aa) rather than 139 aa as for the original fosB gene product. The mutation was present in all available sequences (i.e., Oxford Nanopore and Illumina of WT19 as well as Illumina of WT63, WT64, WT66, WT67a, WT67b, WT68, WT69, WT70, WT71, WT110 and WT111). While fosB was originally implicated in fosfomycin resistance, it appears to be linked to certain CCs. Indeed, it was also present in the CC8 and CC12 beaver isolates (B2, B3, B4) as well as in the reference sequences of the respective CCs (Supplemental File 2). The fosB gene was absent from the CC49 isolate WT65 and from the CC49 reference sequence of Tager 104, GenBank CP012409.1, as well as from the CC398 isolate B1. Moreover, all sequenced isolates (from animals A to G) harboured a gene designated tet(38), encoding a major facilitator superfamily permease. While this gene was implicated in low-level tetracycline resistance when overexpressed22, its mere presence certainly is not associated with phenotypic tetracycline resistance as it can be found in virtually every S. aureus genome.Biocide susceptibility testing of the CC49/1956 isolates revealed unimodal MIC distributions (Supplemental File 3b), with ranges encompassing not more than three to four dilution steps for each of the biocides (benzalkonium chloride, 0.00003–0.00025%; polyhexanide, 0.000125–0.0005%; chlorhexidine, 0.00006–0.00025% and octenidine, 0.00006–0.00025% with percentages given as mass per volume). The four remaining isolates showed MIC values of 0.0000125–0.00025% for benzalkonium chloride, 0.0005–0.001% for polyhexanide, 0.00006–0.000125% for chlorhexidine, and 0.000125–0.00025% for octenidine.The chromosomal heavy metal resistance markers arsB/R and czrB were detected by hybridisation in all four CC1956 isolates tested as well as in the CC49 isolate. This was confirmed by sequencing. There was no evidence for plasmid- or SCC-borne heavy metal resistance markers.The sequence of the phage-borne leukocidin genes in WT19 and WT65As mentioned above, CC49/CC1956 beaver isolates yielded occasionally ambiguous hybridisation intensities for lukS-PV probes prompting further investigation assuming that the specifically designed oligonucleotides were not able to bind optimally at the target due to mismatches, i.e., allelic variants. Sequencing revealed the presence of distinct alleles of phage-borne leukocidin genes (Figs. 2a/b and 3a/b). The sequences from the two sequenced beaver isolates were identical to each other despite their origin from different prophages in different CCs. In general, the beaver alleles, hitherto referred to as “Beaver Leukocidin” or BVL, lukF/S-BV, appeared to be closer related to the PVL genes from human strains of S. aureus than to those from ruminants and horses (see Figs. 2a/b and 3a/b and the percentages of homologies as provided in Supplemental File 4). There was no evidence for recombination/chimerism in lukF-BV and lukS-BV as mismatches compared to other sequences were evenly distributed across the entire sequences. Sequences of lukF-BV and lukS-BV were also related but clearly distinct from core genomic lukF/S-int of S. intermedius/pseudintermedius.Figure 2(a) Alignment of the lukF-BV sequences, of other phage-borne leukocidin F component sequences from S. aureus and of lukF-int from S. intermedius/pseudintermedius. (b) Alignment of the amino acid sequences of the corresponding lukF gene products.Full size imageFigure 3(a) Alignment of the lukS-BV sequences, of other phage-borne leukocidin S component sequences from S. aureus and of lukS-int from S. intermedius/pseudintermedius. (b) Alignment of the amino acid sequences of the corresponding lukS gene products.Full size image
lukF/S-BV and the agr locusTwo isolates from one animal, WT110 and WT111 (Table 1), differed in hemolysis on Columbia blood agar and were thus handled separately although array analysis eventually revealed the same strain affiliations. They also differed in BVL production as shown by lateral flow tests. Sequencing using both, Illumina and Oxford nanopore technologies, revealed a substitution from A to T in position 706 of the agrA gene that results in a premature stop codon at position 236 of the agrA gene product (Supplemental File 5) suggesting that agr played a role in the observed phenotype and the regulation of BVL.Core genome and genomic islands of the CC1956 isolate WT19As revealed by array experiments (Supplemental File 1) and confirmed by genome sequencing of WT19, CC1956 isolates presented with agr IV alleles and capsule type 5. They were positive for cna, but they lacked seh and egc enterotoxin genes, ORF CM14 as well as sasG. Leukocidin genes lukX/Y, lukD/E and lukF/S-hlg were present. This is also in accordance with previously sequenced BVL-negative CC1959 isolates (SAMEA3251370, SAMEA3251372, SAMEA3251377, SAMEA3251376, SAMEA3251380; Supplemental File 2).The WT19 genome (Supplemental Files 6a and 6b) harboured two uncharacterised enterotoxin genes (pos. 1,940,148..1,940,900 and pos. 1,939,378..1,940,121). Both were also found in DAR4145 (CC772) where they also formed a genomic island at approximately the same position within the genome (GenBank CP010526.1: RU53_RS09775, pos. 1,968,336..1,969,061 and RU53_RS09780, pos. 1,969,088..1,969,840). One of these two genes (“seu2” = RU53_RS09780) was covered by the second array-based assay23 and it was found in all four isolates tested with this array.Mobile genetic elements in the CC1956 isolate WT19The lukF/S-BV prophage was integrated into the lipase 2 gene (lip2, “geh”, “sal3”, “salip35”, GenBank CP000253.1 [314,326..316,398]), and spanned pos. 322,629 to 365,636. Besides leukocidin genes, it also included genes associated with the different modules of a typical Siphoviridae genome (lysogeny, DNA metabolism, packaging and capsid morphogenesis, tail morphogenesis, host cell lysis24,25; see Supplemental File 7/Fig. 4).Figure 4Schematic representation of the aligned sequences of the lukF/S-BV prophages from WT19 and WT65.Full size imageFurthermore, there was a small pathogenicity island at pos. 869,706 to 884,748 that included pif encoding a phage interference protein, a gene for a small terminase subunit, genes for “putative proteins” as well as a gene (scn2) coding for a paralog of a complement inhibitor SCIN family protein and a gene for a variant of the von Willebrand factor binding protein Vwb (vwb3). Thus, it is considered a staphylococcal pathogenicity island (SaPI) related to the one in S0385, GenBank AM990992.1.Another prophage integrated between rpmF and isdB, pos. 1,107,447 to 1,146,132. A third prophage was located between a truncated nikB and Q5HG37, pos. 1,425,279 to 1,481,870. Finally, there was a forth prophage between Q5HDU4 and sarV (actually interrupting an MFS transporter between those genes), pos. 2,340,832 to 2,386,591. This prophage sequence corresponded to the phage that was detected by nanopore sequencing after induction by Mitomycin C (see below and Supplemental File 8).Phage morphology and sequencing of phages from the CC1956 isolate WT19In three separate preparations, large numbers of phages were observed that were well contrasted with uranyl acetate and with phosphotungstic acid. Phages had elongated capsids. The non-contractile thin tails were straight or slightly curved and ended in a bulb-shaped base plate. Based on these characteristics, they were assigned to the order Caudovirales, family Siphoviridae.Capsids were measured in 40 phages, tails in 34 and base plates in 33 phages. Based on these measurements, two distinct populations could be differentiated (Fig. 5). In one (Fig. 5A), the prolate, distinctly pentagonal capsids averaged 39 ± 5 nm (range 32–46 nm) in diameter and 92 ± 8 nm (range 80–104 nm) in length. Tails were 276 ± 20 nm (range 243–310 nm) long, had a diameter of 11 ± 1 nm (range 10–12 nm) and had a stacked discs appearance. Their baseplates were 16 nm (range 16–31 nm) by 27 nm (range 19–33 nm). The other population (Fig. 5B) had elongated oval capsids with a maximal diameter of 55 ± 2 nm (range 51–60 nm) diameter and 93 ± 5 nm (range 85–100 nm) length. Their tails measured 287 ± 12 nm (range 275–313 nm) in length and 9 ± 1 nm (8–10) in diameter and had a rail-road-track morphology. Dimensions of baseplates were 25 nm (range 21–30 nm) by 29 nm (range 23–39 nm).Figure 5Transmission electron micrograph of two distinct prolate phages resulting from Mitomycin C treatment of S. aureus CC1956 isolate WT19. A, Phage particle with pentagonal 38 nm in diameter capsid and a 12 nm thick tail with stacked disc appearance; B, Two phage particles (1, 2) with oval capsids of 55 nm in diameter and 9 nm thick tails with rail-road-track morphology. The base plate is separated from the tail by a transversal disc (arrow). Negative contrast preparation with uranyl acetate. Bars = 100 nm.Full size imageOxford Nanopore sequencing of one of these phage preparations (Supplemental File 8) yielded just one circular contig with a coverage of 724. Its sequence was identical to that of the forth prophage, between Q5HDU4 and sarV, except for a loss of a single triplet out of a total length of 46,387 nt.Core genome and genomic islands of the CC49 isolate WT65The CC49 isolate carried agr group II alleles and capsule type 5. It was positive for sasG, but lacked seh and egc enterotoxin genes, ORF CM14 and the collagen adhesion gene cna. A truncated copy of the enterotoxin S gene (GenBank CP000046, pos. 2,203,972.0.2,204,196) was found as well as leukocidin genes lukG/H = lukX/Y, lukD/E and lukF/S-hlg. With regard to presence and alleles of chromosomal markers such as MSCRAMM or ssl genes, the genome of WT65 (Supplemental Files 7a and 7b) is closely related to the CC49 reference sequences such as Tager 104, GenBank CP012409.1 (Supplemental File 2).Mobile genetic elements in the CC49 isolate WT65One prophage was integrated into the lip2 gene spanning pos. 311,401 to 354,724. The prophage included the lukF/S-BV genes as well as genes associated with the different modules of a typical Siphoviridae genome (Supplemental File 7/Fig. 4). Sequences corresponding to the lysogeny and replication modules were clearly different compared to the lukF/S-BV-prophage in the CC1956 isolate WT19 while approximately the second half of the two respective prophage sequences (the lower part of the alignment in Fig. 4) were virtually identical in gene content, order and orientation.Other mobile genetic elements (Supplemental File 9a/b) included a small pathogenicity island, pos. 402,133 to 416,237 (between rpsR encoding 30S ribosomal protein S18 and its terminator), that included hypothetical proteins, a gene of a terminase small subunit, vwb3 (encoding a “von Willebrand factor” binding protein) and the scn2 gene (putative paralog of complement inhibitor). Between the genes ktrB and groL, pos. 2,029,208 to 2,042,866, another SaPI was identified that contained additional, slightly different copies of vwb3 and scn2 genes as well as terminase small subunit, integrase and excisionase (xis-AIO21657) genes. Finally, five genes between pos.1,334,169 and 1,339,503 were annotated as phage capsid genes although no other phage-related genes were found in this region.Phage morphology and sequencing of phages from the CC49 isolate WT65Four separate phage preparations were examined. In one of them, few phage-like structures were detected. These findings could not be confirmed in the following preparations. Thus, they were interpreted as artefacts, also given that it was not possible to induce a sufficient amount of phages for Oxford Nanopore sequencing. More

NATURE PODCAST
22 December 2021

The Nature Podcast annual holiday spectacular

Games, seasonal science songs, and Nature’s 10.

Benjamin Thompson

&

Noah Baker

Benjamin Thompson

View author publications

You can also search for this author in PubMed
 Google Scholar

Noah Baker

View author publications

You can also search for this author in PubMed
 Google Scholar

Twitter

Facebook

Email

Subscribe
Subscribe

iTunes
Google Podcast
acast
RSS

Benjamin Thompson and Noah Baker get festive!

Your browser does not support the audio element.

Download MP3

In this episode:01:12 “Oh powered flight”In the first of our festive songs, We pay tribute to NASA’s Ingenuity craft — which took the first powered flight on another planet earlier this year. Lyrics by Noah Baker and performed by The Simon Langton School choir, directed by Emily Renshaw-Kidd.Scroll to the bottom of the page for the lyrics.Video: Flying a helicopter on Mars: NASA’s IngenuityNews: Lift off! First flight on Mars launches new way to explore worlds07:40 Communicating complex science with common wordsIn this year’s festive challenge, our competitors try to describe some of the biggest science stories of the year, using only the 1,000 most commonly used words in the English language. Find out how they get on …Test your skills communicating complex science with simple words with the Up-Goer Five Text Editor18:04 Alphafold oh AlphafoldOur second song brings some Hanukkah magic to Deep Mind’s protein-solving algorithm Alphafold. Lyrics by Kerri Smith and Noah Baker, arranged and performed by Phil Self.Scroll to the bottom of the page for the lyrics.News: ‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures21:01 Nature’s 10Every year, Nature’s 10 highlights some of the people who played key roles in science. We hear about a few of the people who made the 2021 list.Nature’s 10 — Ten people who helped shape science in 2021

doi: https://doi.org/10.1038/d41586-021-03784-w

Related Articles

Nature’s 10: ten people who helped shape science in 2021

Subjects

Communication

SARS-CoV-2

Planetary science

Biodiversity

Latest on:

Communication

The science news that shaped 2021: Nature’s picks
News 14 DEC 21

Call to join the decentralized science movement
Correspondence 07 DEC 21

From the archive
News & Views 30 NOV 21

SARS-CoV-2

Local and systemic responses to SARS-CoV-2 infection in children and adults
Article 22 DEC 21

Enhanced fitness of SARS-CoV-2 variant of concern Alpha but not Beta
Article 22 DEC 21

Omicron overpowers key COVID antibody treatments in early tests
News 21 DEC 21

Planetary science

On the liquid–liquid phase transition of dense hydrogen
Matters Arising 15 DEC 21

Deep-mantle krypton reveals Earth’s early accretion of carbonaceous matter
Article 15 DEC 21

Sublimation-driven convection in Sputnik Planitia on Pluto
Article 15 DEC 21

Jobs

Postdoctoral Scientist

University of California San Francisco (UCSF)
San Francisco, CA, United States

Postdoctoral Fellow – Pediatric Cancer Biology/Genomics

Research Institute of the McGill University Health Centre (RI-MUHC)
Montreal, Quebec, Canada

Assistant/Associate Professor in Pathology

Yale School of Medicine (YSM)
New Haven, CT, United States

Faculty Positions in Neuroscience

University of Minnesota Twin Cities (UMTC)
Minneapolis, MN, United States More

EDITORIAL
21 December 2021

Sustainability at the crossroads

A look back at 2021 through the Sustainable Development Goals.

Twitter

Facebook

Email

Download PDF

A medical worker observes people with COVID-19 inside a makeshift care facility at the Commonwealth Games Village in New Delhi in May 2021.Credit: Getty

There were high hopes for 2021. The year promised progress on the push for sustainable development after months of pandemic-induced delays and uncertainty. We heard ambitious talk of a ‘green recovery’, and world leaders were due to gather for meetings of the United Nations conventions on biological diversity and on climate to set future agendas.How did the year’s sustainability debates evolve? We take a look through Nature’s science lens.2021: a year of multiple crisesAs 2021 draws to a close, the world is facing numerous crises. The COVID-19 pandemic is far from over. A year after the first vaccines began to clear regulatory hurdles, the emergence of the SARS-CoV-2 Omicron variant is challenging the fragile and unequal gains in bringing the virus under control. Progress is slow on mitigating and adapting to climate change, protecting biodiversity and ending hunger — parts of the Sustainable Development Goals (SDGs), the United Nations’ flagship plan to end poverty and promote a healthier planet by 2030. The plan, already off track before the pandemic, has been all but derailed by COVID-19.
More floods, fires and cyclones — plan for domino effects on sustainability goals
Nature has argued1 that the setback requires a more rapid response by the researchers who are writing the latest UN Global Sustainable Development Report — the scientific input to the SDGs, which runs on a four-year cycle. But attempts to feed science into policy have come up against strong barriers. Democracy and multilateralism are in retreat, undermining the commitment needed to make progress on sustainability goals. Still, this should not be a reason to disengage. On the contrary, researchers generally need to redouble their efforts.Fighting the climate crisisEarly November was marked by a momentous climate summit, the 26th UN Climate Change Conference of the Parties (COP26) in Glasgow, UK. For the first time, the final agreement included mention of a phase down of coal-fired power, although phase out was the original aim. It also called for the ending of some public subsidies for other fossil fuels — one of the biggest financial barriers to the shift to renewable energy. More than 100 countries pledged to cut methane emissions, flagged for their role in global warming in the latest report from the Intergovernmental Panel on Climate Change (IPCC)2. Richer nations committed to doubling their funding by 2025 to help low- and middle-income countries (LMICs) deal with the damage already caused by climate change, and they agreed to set up an office to research a long-proposed fund to compensate LMICs for that damage.But even if the pledges announced are implemented, temperatures are still projected to rise to a catastrophic 2.4 °C by 2100. And below the surface lay disagreements on definitions and the detail of implementation. And this is where research must continue to offer essential input. ‘Net-zero’ is one example. There is no agreed definition or measure of it, and without this, it’s impossible to know whether pledges will actually stop global warming. There is also no agreed definition of climate finance for LIMCs. This means that richer countries can make up their quotas with loans or official development aid that links to climate change only indirectly. Arguments have persisted for years over the funding promised more than a decade ago — what has been disbursed and who owes what — and this has undermined trust and has cast a shadow over negotiations, including those in the lead-up to the Glasgow meeting.

Protesters hold a ‘Biodiversity Emergency’ banner during the demonstration outside the Bank of England in London in November 2021.Credit: Vuk Valcic/SOPA Images/LightRocket/Getty

Elusive biodiversity protectionJust days before COP26, at a separate COP hosted by China in Kunming in Yunnan province, governments debated measures to protect the diversity and richness of plant and animal species. In the first sessions of a two-part UN summit on biological diversity, due to conclude in May 2022, discussions centred on a widely supported target to protect 30% of the world’s land and sea areas by 2030 — up from the previous ‘Aichi target’ of 17%. Among other targets under debate was the provision of greater financial support to low-income countries to preserve biodiversity.
The world’s species are playing musical chairs: how will it end?
Progress on biodiversity protection has proved elusive since the first ‘Earth Summit’ in Rio de Janeiro in 1992. The Kunming summit ended with a modest boost in funding for projects that help to preserve biodiversity — unlike climate change, funding for biodiversity comes mostly from the public sector. We argued that these contributions should be given as grants, rather than loans that saddle poor countries with debt3. This is now more important than ever, as the pandemic piles perilous debt on the developing world.Protecting biodiversity goes hand in hand with managing land and water resources sustainably, and in this way aligns with tackling climate change. And if nature continues to degrade, sooner or later economic output will suffer. This link is captured by debates over assigning monetary and other values to ecosystems, an idea no longer theoretical or controversial. In March, we welcomed a move by members of the UN Statistical Commission to finalize a set of principles that will help national statisticians record ecosystem health and work out payments for ecosystem services4.

Icebergs that calved from the Sermeq Kujalleq glacier in Greenland this year help mark one of Greenland’s biggest ice-melt years in recorded history.Credit: Mario Tama/Getty

Revamping food systemsLike biodiversity protection, the world’s food system needs fixing. One in ten people is undernourished and one in four is overweight. The number of people going hungry is rising fast, a trend fuelled by the pandemic. Nature’s coverage emphasizes the fact that science needs to guide the transformation of the food system. The task is challenging, because food spans many disciplines. We have yet to pin down what diets that are both healthy and sustainable should look like. And an IPCC-like system of scientific advice to inform policymaking has so far been missing from food and agriculture.
What humanity should eat to stay healthy and save the planet
That changed in September, when António Gutteres, the UN secretary-general, convened a controversial but historic Food Systems Summit. A group of scientists was tasked with ensuring that the science underpinning the summit was robust, broad and independent. Writing in Nature, this scientific group issued seven priorities for research, among them a greater focus on sustainable aquatic foods5. Soil-based agriculture tends to dominate discussions on food, with ‘blue foods’ — organisms such as fish, shellfish and seaweeds — rarely considered.Nature joined the scientific group’s call to argue that it’s time to change that (see go.nature.com/3e3ss6r). We published the Blue Food Assessment — the first systematic evaluation of how aquatic food contributes to food security — which explores how research can help transform the global food system. This work also shows some pitfalls of a greater reliance on blue foods without sustainable management, as a rapidly increasing demand for fish adds to risks for coastal ecosystems and the people of coastal communities.

Volunteers prepare meals for distribution in the Paraisopolis favela in São Paulo, Brazil, in March 2021Credit: Jonne Roriz/Bloomberg/Getty

Strong moves from the UN’s centreThe year 2021 also saw various arms of the UN consider how their own governance needs to respond and adapt to changing times. Guterres is set to appoint a new board of scientific advisers to his office, a decision that Nature welcomed6. The decision is part of the organization’s 25-year vision, laid out in the secretary-general’s report, Our Common Agenda (see go.nature.com/3egrudq), in September. Specialized agencies also needed to stocktake. Over the fifty years since its founding, the UN Environment Programme has pushed important initiatives that bring science into ‘green’ policy — co-founding the IPCC, for one — and we urged it to do more to bring together researchers from across environmental sciences to tackle interconnected challenges7. Nature also urged the International Monetary Fund’s shareholders to lend money to strengthen universities, so that science can better work towards global goals8.
The broken $100-billion promise of climate finance – and how to fix it
The right moves at the top echelons of global governance matter – but support for science and collaboration within and between countries matter just as much. In some ways, LMICs are leading the way. A 700-page report by the UN science and cultural organization UNESCO is a first attempt to understand the impact of the SDGs on research priorities9. It found that, unlike richer nations, lower-income countries’ share of research publications jumped in areas such as photovoltaics and climate-resilient crops. Individual countries need to do better to boost innovation, but collaboration will prove crucial. We need look no further than the pandemic for examples of how researchers working across borders, cultures and disciplines can benefit science and society.Collaboration and inclusionWe need — and can — do better on collaboration. Global problems need diverse teams to help navigate social and geopolitical challenges. Our COVID-19 coverage comes with a host of inspiring stories of scientists joining forces to tackle the crisis. It serves as a reminder of what can be done. But it’s not easy. Collaboration means spending less time achieving metrics of performance and more time nurturing relationships. Link-ups between science and industry suffer without rules around data ownership and intellectual property. And mounting geopolitical tensions, particularly between the United States and China, are limiting exchanges of people and knowledge10.
How the COVID pandemic is changing global science collaborations
The benefits of international research are worth the effort for both LIMCs and wealthy nations. But collaborations often come with concerns over equity and who benefits. Concerns over inclusion extend to policy forums too. At COP26, Nature found that researchers were frequently prevented by the organizers from accessing negotiations. Representatives from civil society and the global south also complained of exclusion. That experience must not be repeated. We’ve also argued that forums such as the G7 group of wealthy nations and the World Health Organization should regard emerging economies as equals. And UN bodies that solicit scientific input need to reach out beyond their usual expert networks to involve under-represented communities. The Food Systems Dialogues (see go.nature.com/3ykm2ye) could be a model: this initiative has engaged hundreds of participants across six continents since 2018, becoming an official mechanism to build international consensus at the UN food summit.An eye on the futureLooking ahead to 2022, we’re keeping our finger on the pulse. Nature will maintain a focus on climate, global health and sustainability. We expect more attention to the food crisis and climate-related migration, and more debate on solutions and trade-offs tied up with the energy transition.
Why fossil fuel subsidies are so hard to kill
The fallout from the pandemic will be a key focus. It includes the burden of disability from long COVID, lost ground in the fight against polio, malaria, tuberculosis and HIV, the lifelong impact of the loss of education for millions of children, and rising violence against women and girls. As economies struggle to get back on their feet, the financing of sustainability goals is an urgent issue that needs resolving. Researchers should also work towards resolving some of the long-standing tensions between climate, biodiversity conservation and food provision.The SDGs remain a holistic framework for guiding priorities for sustainable development. In the shorter term, we look to next year’s conclusion of the biodiversity summit, and the climate summit in Cairo. And we stand ready to support science as it responds to global challenges by engaging with policy and the public.

Nature 600, 569-570 (2021)
doi: https://doi.org/10.1038/d41586-021-03781-z

References1.Nature 589, 329–330 (2021).PubMed 
Article 

Google Scholar 
2.Intergovernmental Panel on Climate Change. Sixth Assessment Report — Climate Change 2021: The Physical Science Basis (IPCC, 2021).
Google Scholar 
3.Nature 598, 539–540 (2021).PubMed 
Article 

Google Scholar 
4.Nature 591, 178 (2021).PubMed 
Article 

Google Scholar 
5.von Braun, J., Afsana, K., Fresco, L. O. & Hassan, M. Nature 597, 28–30 (2021).PubMed 
Article 

Google Scholar 
6.Nature 600, 189-190 (2021).PubMed 
Article 

Google Scholar 
7.Nature 591, 8 (2021).PubMed 
Article 

Google Scholar 
8.Nature 592, 325–326 (2021).PubMed 
Article 

Google Scholar 
9.UNESCO. The Race Against Time for Smarter Development (UNESCO, 2021).
Google Scholar 
10.Nature 593, 477 (2021).PubMed 
Article 

Google Scholar 
Download references

Related Articles

Why fossil fuel subsidies are so hard to kill

The broken $100-billion promise of climate finance – and how to fix it

More floods, fires and cyclones — plan for domino effects on sustainability goals

How the COVID pandemic is changing global science collaborations

The world’s species are playing musical chairs: how will it end?

What humanity should eat to stay healthy and save the planet

Subjects

Sustainability

Nutrition

Climate change

Conservation biology

Latest on:

Sustainability

The UN must get on with appointing its new science board
Editorial 08 DEC 21

Battery-powered trains offer a cost-effective ride to a cleaner world
Research Highlight 22 NOV 21

All aboard the climate train! Scientists join activists for COP26 trip
News 02 NOV 21

Nutrition

AI mathematician and a planetary diet — the week in infographics
News 03 DEC 21

What humanity should eat to stay healthy and save the planet
News Feature 01 DEC 21

From the archive
News & Views 16 NOV 21

Climate change

The science events to watch for in 2022
News 17 DEC 21

What Biden’s $2-trillion spending bill could mean for climate change
News 17 DEC 21

Nature’s 10: ten people who helped shape science in 2021
News Feature 15 DEC 21

Jobs

Director, Laboratory for Laser Energetics

University of Rochester (UR)
Rochester, NY, United States

Postdoctoral Research Scientist

Columbia University in the City of New York (CU)
New York, NY, United States

Adult Gastroenterologist Opportunities with Kaiser Permanente

Kaiser Permanente
Northern & Central California, CA, United States

GENERAL ADULT GASTROENTEROLOGISTS

Kaiser Permanente
Central Valley, CA, United States More