Philippa Kaur

Geochemistry and ecotoxicology of AMDAMD systems are an important source of metal/metalloid pollution to the receiving hydrosphere with devastating consequences on the biological drivers of affected ecosystems. Environmental menaces of AMD have not been exhaustively reported worldwide. Scanty information exists across Africa and many developing economies. The homogenised mixture of detached biofilm and AMD samples from a derelict coal mine at three sampling periods were assayed for geochemical delineation and analysed for pollution intensity against reference background geochemical values. The measured values of the physical properties and contents of selected HMs in drains from a coal mine in Nigeria were as presented in Supplementary Table A.1. Virtually all the measured parameters exceeded the permissible limits of WHO guidelines for potable water. The AMD water was acidic (pH = 3.1 ± 0.265), and contained characteristic anions that are common to AMD including dissolved sulphides (1.37 ± 0.233 mg l−1), sulphates (313.0 ± 15.9 mg l−1), carbonate (253.0 ± 22.4 mg l−1) and nitrate (86.6 ± 41.0 mg l−1) above the allowable limits of WHO. Although the acidic pH of AMD in the present study compares well with those associated with mines in Russia14, more extreme acidic pH values have been reported in other climes. Negative pH values of − 1.56 and − 3.6 were observed in AMD from Iberian Pyrite Belt20 and Richmond Mine at Iron Mountain, USA21, respectively. The values of physicochemical parameters associated with the AMD from Onyeama were similar to data reported for other mine wastewaters in Nigeria22 and elsewhere4. It is known that sulphide minerals, in presence of water and oxygen, oxidise to sulphate as observed in the elevated sulphate concentration (313 ± 15.9 mg l−1) in the present study. The low pH observed in the AMD is due to the formation of sulphuric acid from sulphate in presence of protons (H+). This consequently causes the leaching of metal/metalloid ions into the drains. The concentrations of dissolved organic matter in AMD tends to be relatively low ( Co  > Pb  > As  > Ni  > Cr  > Fe (Table 1). Enrichment of five HMs was exceptionally high (Cd  > Co  > Pb  > As  > Ni), while Cr and Fe were very high and moderately enriched the AMD water, respectively. The astronomically high contamination and enrichment factors of the AMD signified the enrichment potentials the AMD portends on receiving surface waters. The AMD from the Onyeama coal mine has been reportedly impacting the water qualities of rivers within the location25. It is assumed that the extremely high concentrations of toxic metals/metalloids in the AMD dilutes out upon discharges into nearby rivers, contaminating the surface water and raising the bioavailable metals/metalloids beyond safe thresholds. Further reports of toxic metals/metalloids enrichment of surface waters via inflow of AMDs from other mines in Nigeria26 and other climes3,4,27 are worrisome and oblige mitigations.Table 1 Physico-chemistry, pollution and ecological impact determinants of heavy metals and metalloid contained in the AMD from coal mine.Full size tableThe HMs-enriched environments inadvertently exert ecotoxicity unto the drivers of the ecosystems. The level of HMs accumulation to the organic matter in the AMD, through geo-accumulation (Igeo) index of Fe (7.60 ± 0.779) to Cd (20.9 ± 0.075) (Supplementary Table A.2), was very severe and in a similar order to CF. It possibly implies organic matter in the AMD harbours the mobile toxic metal/metalloid concentrations and make them available to the food web28. Thus, biomagnification of the toxic metals/metalloids along the trophic level becomes palpable and a challenge to the biota of any surface water receiving the AMD and to public health21,28. Ecological risk assessments define and categorise the pollution status of ecosystems with the HMs contained in the AMD. Based on the potential ecological risk factor (Er), Cd exerted an extremely high-risk index (36.3 ± 1.96 × 106), and none of the metals/metalloids exercised less than 1000 risk index (Supplementary Table A.2). All the HMs/metalloid contained in the AMD posed very high ecological risks and could be categorised in the order of Cd  > Co  > Pb  > As  > Ni  > Cr  > Fe. The modified potential ecological risk factor (MEr), however, stipulated that five HMs posed a very high risk in the order: Cd  > Co  > Pb  > As  > Ni, whereas Cr and Fe were determined to be of considerate and low risks, respectively. The HMs exerted high risk to the AMD ecosystem as calculated by ecological risk quotient (RQ) in the order: Pb  > Cd  > As  > Ni  > Co  > Fe  > Cr. The ecological risk index of all the HMs as a whole was very high (375,000 ± 22,400) index as stipulated by the modified potential ecological risk index (Table 1). The prodigiously high ecological risks indexes of the HMs/metalloid in the AMD indicated grave danger the AMD would portend on the surface- and ground-waters.Microbial community structure of AMD from Onyeama coal mineA total of 26,160 and 40,403 valid (filtered) sequence reads were obtained for bacteria and eukarya, respectively, after a quality check of biofilm-water amplicon sequence data. The valid sequences were clustered into 2036 and 1002 operational taxonomic units (OTUs) of bacteria and eukarya domains of life, respectively, as presented in Table 2. Microbial community structures are sensitive descriptors of ecological stressors pivotal to understanding ecosystem functions29. The number of clustered high quality, non-chimeric sequences as OTUs based on UCLUST and CD-HIT against the sequence reads was depicted as asymptotic rarefaction curves (Supplementary Fig. A.1). The curves revealed that higher numbers of OTUs were delineated from valid sequence reads of 16S rRNA genes, unlike the lesser number of OTUs obtained from valid sequence reads of ITS2 region located between 5.8S and 28S rRNA genes of eukaryotes. The OTU richness observed in the rarefaction curves established coverage of the majority of species and was further validated with the richness and diversity estimations presented in Table 2. Despite the higher number of valid sequence reads obtained from the amplified ITS2 (40,403) than that of 16S rRNA genes (26,160), the observed OTUs were more in 16S rRNA genes (2036) than those of ITS2 (1002). More than 99.8% and about 98.5% of the microbial community in AMD from the Onyeama coal mine represented eukarya and bacteria OTUs, respectively, based on estimated Good’s library coverage. The coverage degree of the MiSeq sequencing corroborated the rarefaction curves. Furthermore, the estimated OTU richness (based on higher values obtained from ACE, Chao1 and JackKnife indexes) showed that bacterial phylotypes were richer than those of eukarya. Alpha diversity indexes (NPShannon, Shannon, and inverse Simpson) phylogenetic diversity index revealed that bacteria in the AMD were more diverse than eukarya OTUs.Table 2 Alpha diversity of microbiome evenness, richness and varieties of species in the sediments.Full size tableTaxonomy and phylogeny of microbial OTUs in AMD from coal mineThe taxonomic composition and relative abundances of the AMD microbiome, as shown in Fig. 1, revealed that the bacterial community spanned 10 phyla whose sequence reads were at least 1% (Fig. 1a). Whereas the eukarya domain of life (with sequence reads ≥ 1%) found in the AMD include Fungi, Plantae and Animalia kingdoms (Fig. 1b). Ascomycota, unclassified Fungi phylum (Fungi_p), Basidiomycota, and Mucoromycota represented Fungi kingdom, while Ciliophora and Arthropoda phyla were Animalia and Chlorophyta phylum epitomised Plantae kingdom. Association of the domain Eukarya (comprising Alveolates, Chlorophyta and Fungi as observed in this study) with AMD is reported to a lesser extent when compared with Bacteria30. The Fungi, largely represented by Ascomycota and Basidiomycota, are primarily found in sub-surface low-pH biofilms thriving in AMD31. While the Alveolates are suggested to have acted as primary/secondary consumers, the amoebae were secondary grazers in the AMD ecosystem29,32. Fungi taxa must have participated in carbon cycling as the main decomposers in the microbial community of the AMD. The taxonomic composition and relative abundance of phyla regarded as ‘Others’ (sequence reads  50%). Evolutionary analyses were conducted in MEGA6.Full size imageUrease-producing bacteria instigate insoluble metal-carbonate micro-precipitation through urease activity16. The growth-time courses and urease activities of the bacteria consortium in simulated AMD were presented as curves (Fig. 5). It was observed that the impact of high concentrations of HMs cocktails was not pronounced beyond the early 6 h post-inoculation, which was regarded as the lag phase. The bacteria consortium might have activated necessary genes needed to tolerate and sequester the metals/metalloids toxicity during the lag phase without cell multiplications. Afterwards, the bacteria consortium grew steadily with the production of urease, based on increasing measurement of urease activity, as incubation continued. At 30 h post-inoculation, 245.3 (± 23.7) U ml−1 activity of urease was observed in broth without a toxic metal cocktail. However, more urease activity (255 ± 7.6 U ml−1) by the bacteria consortium was observed in medium amended with low concentrations of metal cocktails unlike lesser activities of 235 (± 7.6) U ml−1 and 193.7 (± 10.7) U ml−1 associated with medium and high metal concentrations, respectively. As the growth remains stationary and pH further increased to  > 8.2, urease activities were at least 253 U ml−1 in all the cultures. Although urease activities at acidic pH have been reported in acid-tolerant human pathogens19, the findings in this report were assumedly the first amongst bacterial strains from AMD-polluted environments. The urease activities at acidic pH compared favourably with activities at alkaline pH in previous studies7,16,42,44. Moreover, the pH of the culture system kept increasing, alleviating the acidity condition that initially prevailed in the AMD system.Figure 5Growth kinetics of bacterial consortium via viable counts extrapolated into optical density at 600 nm wavelength (a) and growth-dependent urease activity of bacterial consortium (b) in TGYM broth without heavy metals (HMs) cocktail, and with low, medium, and high concentrations of HMs cocktails. Low HMs concentrations cocktail comprised (per liter) Cd, 27.9 mg; Pb, 118.7 mg; Co, 16.2 mg; Ni, 16.2 mg; and As, 61.5 mg. While medium HMs concentration contained (per liter) Cd, 55.7 mg; Pb, 237.3 mg; Co, 32.4 mg; Ni, 32.3 mg; and As, 123.1 mg. High HMs concentration contained (per liter) Cd, 139.3 mg; Pb, 593.3 mg; Co, 81.1 mg; Ni, 80.7 mg; and As, 307.6 mg. The mean pH at the beginning of experiment was 3.5 and rose to 8.2–8.4 at 48 h post-inoculation. Growth kinetics at exponential growth phase are in the inserts of panel (a), where ‘Td’ represents doubling time and ‘K’ is the growth rate at exponential growth phase. Error bars represent standard error mean (SEM) of triplicate experiments. The culture conditions were as explained in the “Methods” Section (Growth kinetics and urease activity of bacteria consortium; Determination of bacterial growth-dependent HMs/metalloid sequestration in simulated and natural AMD).Full size imageInterestingly, urease activity was observed in low quantity at acidic pH, unlike higher activity when the pH inclined towards alkaline (Fig. 5). It is proposed that urea finds its way into Onyeama coal mine drains through runoff from agricultural soils fortified with urea fertilizers and animal manures, which are common agricultural practices in Nigeria. The products of urea hydrolysis might have equilibrated in water to form bicarbonate, ammonium and hydroxyl ions that serially increased the culture pH. Ultimately, the bicarbonate equilibrium might have shifted to form carbonate ions (HCO3− + H+ + 2NH4+ + 2OH− ↔ CO32− + NH4+  + 2H2O) that enhanced the metal-carbonate micro-precipitation (Me2+  + Cell → Cell-Me2+ + CO32− → Cell-MeCO3). The gradual increase in pH could have further indulged the formation of CO32− from HCO3−, leading to metal-CO3 precipitation around cells and in culture media. Bicarbonates enrichment with inherent ammonia production was thought to have provided additional acid neutralization of the AMD. The growth kinetics after the presumed lag phase in the early 6 h to late exponential phase at 18 h showed that a low concentration of HMs cocktails did not have an impact on the growth of the bacteria consortium. Consequently, the bacteria consortium exhibited excellent sequestration of multi-component toxic HMs in both the simulated toxic metal-rich AMD and the actual AMD obtained from the Onyeama coal mine (Table 3).Table 3 Growth associated sequestration and precipitation of heavy metals/metalloid cocktail and AMD from Onyeama coal mine.Full size tableThe bacteria consortium displayed more than 94% efficiency of Cd and Pb sequestration in natural AMD, while 100% efficiency was observed in all the simulated AMD treatments (Table 3). Low performance was found with Ni and As, but not less than 70% sequestration efficiency was observed in all treatments. Efficient sequestrations of toxic metals, up to 100% removal efficiency of most toxic metals, observed with the bacteria consortium were similar to findings in a previous study13. Mixed-bacterial cultures are known to be able to perform more complex tasks and survive in more unstable environments than a monoculture. Nevertheless, 89.3–98% removal efficiencies of Ni, Pb, Co, and Cd from solution have been reportedly achievable with urease-producing Sporosarcina koreensis45. Similarly, Bacillus sp. KK1 reportedly mitigated lead-contaminated mines tailings containing mobile Pb (1050 mg kg−1) to form insoluble precipitates of PbS and PbSiO334. Growth-dependent sequestration of HMs cocktails by the bacteria consortium was adduced to be via precipitation. The weight of the precipitates was evaluated to be proportional to concentrations of HMs cocktail present. The bacteria consortium was observed to drive the formation of as much as 15.6 (± 0.92) mg ml−1 precipitates (Table 3) that were assumed to be in form of HMs-carbonates in TGYM supplemented with high concentrations of HMs cocktail within 24 h post-inoculation. In natural AMD bio-stimulated with urea and seeded with bacteria consortium for 24 h, 10.5 (± 0.52) mg ml−1 HMs precipitates was observed unlike 8.57 (± 2.52) mg ml−1 precipitates obtained from natural AMD toxic metals sequestration without urea fortification. It appeared that the quantity of toxic metal precipitate was proportional to quantities of available toxic metals, which corresponded to the number of heterogeneous nucleation sites on the surface of the bacterial cells. Omoregie et al.42 reported a relatively similar quantum of precipitation as CaCO3 with species of ureolytic Firmicutes isolated from limestone caves. As such, there was no correlation between urease activity and quantum of toxic metal precipitation since there is a likelihood that other metabolic activities may be linked to urease activities. Nevertheless, the bioremediation strategies demonstrated in the present study exhibited excellent toxic metal sequestrations unlike insignificant (p  > 0.05) natural attenuation process of the autochthonous community without augmentation with bacteria consortium and stimulation with nutrients (as presented in Table 3).In conclusion, AMD from the Onyeama coal mine is a point source of pollution to the surrounding environments because of its richness in anions and toxic metals/metalloids. It has a high potential of enriching the receiving hydrosphere with toxic metals/metalloids and exerts severe ecological risks (Er  > 320) with Cd and Pb wielding a huge critical risk index (38.1 ± 2.18 × 106) on the biological elements of the ecosystems. The dominance of Proteobacteria (50.8%), Bacteroidetes (18.9%), Ascomycota (60.8%), and Ciliophora (12.6%) characterised the microbial community of the AMD, where unclassified OTUs occurred mostly among the species. Enrichment of the AMDs skewed the bacterial community as depicted in the alpha diversity indexes against that of coal AMD leading to the selection of bacteria consortium with an excellent potential of stemming the toxicants in the AMD. The bacteria consortium efficiently removed toxic metals/metalloids ( > 70%) through precipitation and simultaneously neutralised AMD acidity. The bacteria consortium exhibited appreciable urease activity ( > 190 U ml−1), through which the precipitation was assumed possible via the formation of metal/metalloid-carbonates. The bacteria consortium is suggested to be a sustainable biotechnological candidate in designing a bioremediation strategy for decommissioning AMD before discharge into the surrounding environment. More

Convergence is a common feature of evolution and has great effect on the succession of microbial communities. For natural microbial communities such as the microbiome of gut [1], soil [2], sediment [3], rhizosphere [4], and phyllosphere [5], convergence generally means that different communities converge towards a similar species composition, which is accompanied by species loss and acquisition. Such a convergence can be reproduced in simplified synthetic communities [6,7,8], or even in single-species populations, in which convergence can still be achieved at sub-species level [9, 10]. Unlike the convergence of natural microbial community, those experiments carried out in a sterile laboratory environment only involves the loss of species. Specifically, the main manifestation of convergence in the synthetic community containing stably coexisting species lies in that the relative proportion of species tend to become consistent [7, 8]. Nonetheless, synthetic community opens a window for us to investigate the ecological mechanism. Previous studies of synthetic communities have revealed that the convergence of bacterial community can be regulated by pH [11], mortality [12], and particularly nutrient availability [13, 14]. Most existing studies focus on the changes in species proportions, but there is a lack of in-depth understanding of the gene expression changes driven by the community species interaction.In this study, we constructed a synthetic community with two model microorganisms, Escherichia coli K-12 (EC) and Pseudomonas putida KT2440 (PP), and reproduced a convergent community assembly in closed broth-culture system. In monocultures, the growth curves of both E. coli and P. putida fitted well with the bacterial growth model, and fell into a logarithmic phase at the first 4 h of bacterium culture and a stationary phase at subsequent 20 h (after the first 4 h) (Fig. 1a). When same quantities of bacteria were grown in cocultures, their quantities were basically similar to those in monocultures, particularly in the logarithmic phase (Fig. 1b–d). By contrast, the quantities of minority species in cocultures continued to increase, and they were close to the quantities in monocultures at 24 h post co-cultivation (Fig. 1b–d). Besides, statistical analysis showed that the quantities of P. putida in all three cocultures were overall greater than that in monoculture, while E. coli quantities were no more than its monoculture (Fig. 1b–d), suggesting that P. putida has a negative effect on the growth of E. coli, but E. coli promotes that of P. putida.Fig. 1: Convergence of community structure and gene expression.a–d Growth curves of E. coli and P. putida in monoculture (a) and the “1:1000”, “1:1”, “1000:1” cocultures (b–d). In b–d subplots, the growth curves of monocultures were placed on the background layer (dashed lines), and the significant differences in cell quantity between coculture and corresponding monoculture were shown (ns, non-significant; *p  More

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NEWS AND VIEWS
01 September 2021

Policy, drought and fires combine to affect biodiversity in the Amazon basin

Analysis of the ranges of nearly 15,000 plant and vertebrate species in the Amazon basin reveals that, from 2001 to 2019, a majority were affected by fire. Drought and forest policy were the best predictors of fire outcomes.

Thomas W. Gillespie

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Thomas W. Gillespie

Thomas W. Gillespie is in the Department of Geography and at the Institute of the Environment and Sustainability at the University of California, Los Angeles, Los Angeles, California 90095, USA.

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The Amazon basin contains the largest continuous area of tropical rainforests in the world, and has a crucial role in regulating Earth’s climate1. Rates of tropical-rainforest deforestation and the impacts of fire and drought there are well established2,3. Less is known, however, about how these factors might interact to affect biodiversity, and about the role that forest policy and its enforcement have had over time. Writing in Nature, Feng et al.4 address these issues.

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doi: https://doi.org/10.1038/d41586-021-02320-0

References1.Marengo, J. A., Tomasella, J., Soares, W. R., Alves, L. M. & Nobre, C. A. Theor. Appl. Climatol. 107, 73–85 (2012).Article 

Google Scholar 
2.Nepstad, D. C. et al. Nature 398, 505–508 (1999).Article 

Google Scholar 
3.Davidson, E. A. et al. Nature 481, 321–328 (2012).PubMed 
Article 

Google Scholar 
4.Feng, X. et al. Nature https://doi.org/10.1038/s41586-021-03876-7 (2021).Article 

Google Scholar 
5.Nepstad, D. Science 344, 1118–1123 (2014).PubMed 
Article 

Google Scholar 
6.Hansen, M. C. et al. Science 342, 850–853 (2013).PubMed 
Article 

Google Scholar 
7.Libonati, R. et al. Sci. Rep. 11, 4400 (2021).PubMed 
Article 

Google Scholar 
8.Hopkins, M. J. G. J. Biogeogr. 34, 1400–1411 (2007).Article 

Google Scholar 
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NATURE PODCAST
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Dead trees play an under-appreciated role in climate change

How insects help release carbon stored in forests, and the upcoming biodiversity summit COP 15.

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In this episode:00:44 Fungi, insects, dead trees and the carbon cycleAcross the world forests play a huge role in the carbon cycle, removing enormous amounts of carbon dioxide from the atmosphere. But when those trees die, some of that carbon goes back into the air. A new project studies how fast dead wood breaks down in different conditions, and the important role played by insects.Research Article: Seibold et al.09:37 Research HighlightsMassive stars make bigger planets, and melting ice moves continents.Research Highlight: Why gassy planets are bigger around more-massive starsResearch Highlight: So much ice is melting that Earth’s crust is moving12:04 The UN’s Convention on Biological DiversityAfter several delays, the fifteenth Conference of the Parties (COP 15) to the United Nations Convention on Biological Diversity, is now slated to take place next year. Even communicating the issues surrounding biodiversity loss has been a challenge, and reaching the targets due to be set at the upcoming meeting will be an even bigger one.Editorial: The scientific panel on biodiversity needs a bigger role 19:32 Briefing ChatWe discuss some highlights from the Nature Briefing. This time, cannibal cane toads and a pterosaur fossil rescued from smugglers.News: Australia’s cane toads evolved as cannibals with frightening speedResearch Highlight: A plundered pterosaur reveals the extinct flyer’s extreme headgearNational Geographic: Stunning fossil seized in police raid reveals prehistoric flying reptile’s secretsSubscribe to Nature Briefing, an unmissable daily round-up of science news, opinion and analysis free in your inbox every weekday.Never miss an episode: Subscribe to the Nature Podcast on Apple Podcasts, Google Podcasts, Spotify or your favourite podcast app. Head here for the Nature Podcast RSS feed.

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1.Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).ADS 
CAS 

Google Scholar 
2.Bradford, M. A. et al. Climate fails to predict wood decomposition at regional scales. Nat. Clim. Change 4, 625–630 (2014).ADS 
CAS 

Google Scholar 
3.Chambers, J. Q., Higuchi, N., Schimel, J. P. J., Ferreira, L. V. & Melack, J. M. Decomposition and carbon cycling of dead trees in tropical forests of the central Amazon. Oecologia 122, 380–388 (2000).ADS 
CAS 

Google Scholar 
4.González, G. et al. Decay of aspen (Populus tremuloides Michx.) wood in moist and dry boreal, temperate, and tropical forest fragments. Ambio 37, 588–597 (2008).
Google Scholar 
5.Stokland, J., Siitonen, J. & Jonsson, B. G. Biodiversity in Dead Wood (Cambridge Univ. Press, 2012).6.Lustenhouwer, N. et al. A trait-based understanding of wood decomposition by fungi. Proc. Natl Acad. Sci. USA 117, 11551–11558 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
7.Ulyshen, M. D. Wood decomposition as influenced by invertebrates. Biol. Rev. Camb. Philos. Soc. 91, 70–85 (2016).
Google Scholar 
8.Pretzsch, H., Biber, P., Schütze, G., Uhl, E. & Rötzer, T. Forest stand growth dynamics in Central Europe have accelerated since 1870. Nat. Commun. 5, 4967 (2014).ADS 
CAS 

Google Scholar 
9.Büntgen, U. et al. Limited capacity of tree growth to mitigate the global greenhouse effect under predicted warming. Nat. Commun. 10, 2171 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
10.Seidl, R. et al. Forest disturbances under climate change. Nat. Clim. Change 7, 395–402 (2017).ADS 

Google Scholar 
11.Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).ADS 
CAS 

Google Scholar 
12.Portillo-Estrada, M. et al. Climatic controls on leaf litter decomposition across European forests and grasslands revealed by reciprocal litter transplantation experiments. Biogeosciences 13, 1621–1633 (2016).ADS 
CAS 

Google Scholar 
13.Christenson, L. et al. Winter climate change influences on soil faunal distribution and abundance: implications for decomposition in the northern forest. Northeast. Nat. 24, B209–B234 (2017).
Google Scholar 
14.Keenan, T. F. et al. Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise. Nature 499, 324–327 (2013).ADS 
CAS 

Google Scholar 
15.Stephenson, N. L. et al. Rate of tree carbon accumulation increases continuously with tree size. Nature 507, 90–93 (2014).ADS 
CAS 

Google Scholar 
16.Martin, A., Dimke, G., Doraisami, M. & Thomas, S. Carbon fractions in the world’s dead wood. Nat. Commun. 12, 889 (2021).17.Friedlingstein, P. et al. Global carbon budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).ADS 

Google Scholar 
18.Marshall, D. J., Pettersen, A. K., Bode, M. & White, C. R. Developmental cost theory predicts thermal environment and vulnerability to global warming. Nat. Ecol. Evol. 4, 406–411 (2020).
Google Scholar 
19.Buczkowski, G. & Bertelsmeier, C. Invasive termites in a changing climate: a global perspective. Ecol. Evol. 7, 974–985 (2017).PubMed 
PubMed Central 

Google Scholar 
20.Diaz, S., Settele, J. & Brondizio, E. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovermental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES, 2019).21.van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420 (2020).ADS 

Google Scholar 
22.Seibold, S. et al. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature 574, 671–674 (2019).ADS 
CAS 

Google Scholar 
23.Harris, N. L. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Change 11, 234–240 (2021).ADS 

Google Scholar 
24.Jacobsen, R. M., Sverdrup-Thygeson, A., Kauserud, H., Mundra, S. & Birkemoe, T. Exclusion of invertebrates influences saprotrophic fungal community and wood decay rate in an experimental field study. Funct. Ecol. 32, 2571–2582 (2018).
Google Scholar 
25.Skelton, J. et al. Fungal symbionts of bark and ambrosia beetles can suppress decomposition of pine sapwood by competing with wood-decay fungi. Fungal Ecol. 45, 100926 (2020).
Google Scholar 
26.Wu, D., Seibold, S., Ruan, Z., Weng, C. & Yu, M. Island size affects wood decomposition by changing decomposer distribution. Ecography 44, 456–468 (2021).
Google Scholar 
27.Harmon, M. E. et al. Release of coarse woody detritus-related carbon: a synthesis across forest biomes. Carbon Balance Manag. 15, 1 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
28.Wall, D. H. et al. Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent. Glob. Change Biol. 14, 2661–2677 (2008).ADS 

Google Scholar 
29.Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. M. & Charnov, E. L. Effects of size and temperature on metabolic rate. Science 293, 2248–2251 (2001).ADS 
CAS 

Google Scholar 
30.Baldrian, P. et al. Responses of the extracellular enzyme activities in hardwood forest to soil temperature and seasonality and the potential effects of climate change. Soil Biol. Biochem. 56, 60–68 (2013).CAS 

Google Scholar 
31.A’Bear, A. D., Jones, T. H., Kandeler, E. & Boddy, L. Interactive effects of temperature and soil moisture on fungal-mediated wood decomposition and extracellular enzyme activity. Soil Biol. Biochem. 70, 151–158 (2014).
Google Scholar 
32.IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. (IPCC, 2014).33.Smyth, C. E., Kurz, W. A., Trofymow, J. A. & CIDET Working Group. Including the effects of water stress on decomposition in the Carbon Budget Model of the Canadian Forest Sector CBM-CFS3. Ecol. Modell. 222, 1080–1091 (2011).
Google Scholar 
34.Weedon, J. T. et al. Global meta-analysis of wood decomposition rates: a role for trait variation among tree species? Ecol. Lett. 12, 45–56 (2009).
Google Scholar 
35.Griffiths, H. M., Ashton, L. A., Evans, T. A., Parr, C. L. & Eggleton, P. Termites can decompose more than half of deadwood in tropical rainforest. Curr. Biol. 29, R118–R119 (2019).CAS 

Google Scholar 
36.Birkemoe, T., Jacobsen, R. M., Sverdrup-Thygeson, A. & Biedermann, P. H. W. in Saproxylic Insects (ed. Ulyshen, M. D.) 377–427 (Springer, 2018).37.Harvell, M. C. E. et al. Climate warming and disease risks for terrestrial and marine biota. Science 296, 2158–2162 (2002).ADS 
CAS 

Google Scholar 
38.Berkov, A. in Saproxylic Insects (ed. Ulyshen, M. D.) 547–580 (Springer, 2018).39.Wang, C., Bond-Lamberty, B. & Gower, S. T. Environmental controls on carbon dioxide flux from black spruce coarse woody debris. Oecologia 132, 374–381 (2002).ADS 

Google Scholar 
40.Peršoh, D. & Borken, W. Impact of woody debris of different tree species on the microbial activity and community of an underlying organic horizon. Soil Biol. Biochem. 115, 516–525 (2017).
Google Scholar 
41.Campbell, J., Donato, D., Azuma, D. & Law, B. Pyrogenic carbon emission from a large wildfire in Oregon, United States. J. Geophys. Res. 112, G04014 (2007).ADS 

Google Scholar 
42.van Leeuwen, T. T. et al. Biomass burning fuel consumption rates: a field measurement database. Biogeosciences 11, 7305–7329 (2014).ADS 

Google Scholar 
43.McDowell, N. G. et al. Pervasive shifts in forest dynamics in a changing world. Science 368, eaaz9463 (2020).CAS 

Google Scholar 
44.Ulyshen, M. D. & Wagner, T. L. Quantifying arthropod contributions to wood decay. Methods Ecol. Evol. 4, 345–352 (2013).
Google Scholar 
45.Bässler, C., Heilmann-Clausen, J., Karasch, P., Brandl, R. & Halbwachs, H. Ectomycorrhizal fungi have larger fruit bodies than saprotrophic fungi. Fungal Ecol. 17, 205–212 (2015).
Google Scholar 
46.Ryvarden, L. & Gilbertson, R. L. The Polyporaceae of Europe (Fungiflora, 1994).47.Eriksson, J. & Ryvarden, L. The Corticiaceae of North Europe Parts 1–8 (Fungiflora, 1987).48.Boddy, L., Hynes, J., Bebber, D. P. & Fricker, M. D. Saprotrophic cord systems: dispersal mechanisms in space and time. Mycoscience 50, 9–19 (2009).
Google Scholar 
49.Moore, D. Fungal Morphogenesis (Cambridge Univ. Press, 1998).50.Clemencon, H. Anatomy of the Hymenomycetes (Univ. Lausanne, 1997).51.R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, 2020).52.Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
Google Scholar 
53.Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Google Scholar 
54.Wood, S. N. Generalized Additive Models: an Introduction with R 2nd edn (Chapman and Hall/CRC, 2017).55.Robinson, D. Implications of a large global root biomass for carbon sink estimates and for soil carbon dynamics. Proc. R. Soc. B 274, 2753–2759 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
56.Food and Agriculture Organization. Global Ecological Zones for FAO Forest Reporting: 2010 Update, Forest Resource Assessment Working Paper (Food and Agriculture Organization, 2012).57.Food and Agriculture Organization. Global Forest Resources Assessment 2015 (Food and Agriculture Organization, 2016).58.Christensen, M. et al. Dead wood in European beech (Fagus sylvatica) forest reserves. For. Eco. Man. 210, 267–282 (2005).
Google Scholar 
59.Kobayashi, T. et al. Production of global land cover data – GLCNMO2013. J. Geogr. Geol. 9, 1–15 (2017).
Google Scholar 
60.Harmon, M. E., Woodall, C. W., Fasth, B., Sexton, J. & Yatkov, M. Differences between Standing and Downed Dead Tree Wood Density Reduction Factors: A Comparison across Decay Classes and Tree Species Research Paper NRS-15 (US Department of Agriculture, Forest Service, Northern Research Station, 2011).61.Hararuk, O., Kurz, W. A. & Didion, M. Dynamics of dead wood decay in Swiss forests. For. Ecosyst. 7, 36 (2020).
Google Scholar 
62.Gora, E. M., Kneale, R. C., Larjavaara, M. & Muller-Landau, H. C. Dead wood necromass in a moist tropical forest: stocks, fluxes, and spatiotemporal variability. Ecosystems 22, 1189–1205 (2019).CAS 

Google Scholar 
63.Hérault, B. et al. Modeling decay rates of dead wood in a neotropical forest. Oecologia 164, 243–251 (2010).ADS 

Google Scholar 
64.Thünen-Institut für Waldökosysteme. Der Wald in Deutschland – Ausgewählte Ergebnisse der dritten Bundeswaldinventur (Bundesministerium für Ernährung und Landwirtschaft, 2014).65.Puletti, N. et al. A dataset of forest volume deadwood estimates for Europe. Ann. For. Sci. 76, 68 (2019).
Google Scholar 
66.Richardson, S. J. et al. Deadwood in New Zealand’s indigenous forests. For. Ecol. Manage. 258, 2456–2466 (2009).
Google Scholar 
67.Shorohova, E. & Kapitsa, E. Stand and landscape scale variability in the amount and diversity of coarse woody debris in primeval European boreal forests. For. Ecol. Manage. 356, 273–284 (2015).
Google Scholar 
68.Szymañski, C., Fontana, G. & Sanguinetti, J. Natural and anthropogenic influences on coarse woody debris stocks in Nothofagus–Araucaria forests of northern Patagonia, Argentina. Austral Ecol. 42, 48–60 (2017).
Google Scholar 
69.Link, K. G. et al. A local and global sensitivity analysis of a mathematical model of coagulation and platelet deposition under flow. PLoS One 13, e0200917 (2018).70.Saugier, B., Roy, J. & Mooney, H. A. in Terrestrial Global Productivity (eds J. Roy, B. Saugier & H. A. Mooney) 543–557 (Academic Press, 2001). More

We acknowledge the herbaria that contributed data to this work: HA, FCO, MFU, UNEX, VDB, ASDM, BPI, BRI, CLF, L, LPB, AD, TAES, FEN, FHO, A, ANSM, BCMEX, RB, TRH, AAH, ACOR, AJOU, UI, AK, ALCB, AKPM, EA, AAU, ALU, AMES, AMNH, AMO, ANA, GH, ARAN, ARM, AS, CICY, ASU, BAI, AUT, B, BA, BAA, BAB, BACP, BAF, BAL, COCA, BARC, BBS, BC, BCN, BCRU, BEREA, BG, BH, BIO, BISH, SEV, BLA, BM, MJG, BOL, CVRD, BOLV, BONN, BOUM, BR, BREM, BRLU, BSB, BUT, C, CAMU, CAN, CANB, CAS, CAY, CBG, CBM, CEN, CEPEC, CESJ, CHR, ENCB, CHRB, CIIDIR, CIMI, CLEMS, COA, COAH, COFC, CP, COL, COLO, CONC, CORD, CPAP, CPUN, CR, CRAI, FURB, CU, CRP, CS, CSU, CTES, CTESN, CUZ, DAO, HB, DAV, DLF, DNA, DS, DUKE, DUSS, E, HUA, EAC, ECU, EIF, EIU, GI, GLM, GMNHJ, K, GOET, GUA, EKY, EMMA, HUAZ, ERA, ESA, F, FAA, FAU, UVIC, FI, GZU, H, FLAS, FLOR, HCIB, FR, FTG, FUEL, G, GB, GDA, HPL, GENT, GEO, HUAA, HUJ, CGE, HAL, HAM, IAC, HAMAB, HAS, HAST, IB, HASU, HBG, IBUG, HBR, IEB, HGI, HIP, IBGE, ICEL, ICN, ILL, SF, NWOSU, HO, HRCB, HRP, HSS, HU, HUAL, HUEFS, HUEM, HUSA, HUT, IAA, HYO, IAN, ILLS, IPRN, FCQ, ABH, BAFC, BBB, INPA, IPA, BO, NAS, INB, INEGI, INM, MW, EAN, IZTA, ISKW, ISC, GAT, IBSC, UCSB, ISU, IZAC, JBAG, JE, SD, JUA, JYV, KIEL, ECON, TOYA, MPN, USF, TALL, RELC, CATA, AQP, KMN, KMNH, KOR, KPM, KSTC, LAGU, UESC, GRA, IBK, KTU, KU, PSU, KYO, LA, LOMA, SUU, UNITEC, NAC, IEA, LAE, LAF, GMDRC, LCR, LD, LE, LEB, LI, LIL, LINN, AV, HUCP, MBML, FAUC, CNH, MACF, CATIE, LTB, LISI, LISU, MEXU, LL, LOJA, LP, LPAG, MGC, LPD, LPS, IRVC, MICH, JOTR, LSU, LBG, WOLL, LTR, MNHN, CDBI, LYJB, LISC, MOL, DBG, AWH, NH, HSC, LMS, MELU, NZFRI, M, MA, UU, UBT, CSUSB, MAF, MAK, MB, KUN, MARY, MASS, MBK, MBM, UCSC, UCS, JBGP, OBI, BESA, LSUM, FULD, MCNS, ICESI, MEL, MEN, TUB, MERL, CGMS, FSU, MG, HIB, TRT, BABY, ETH, YAMA, SCFS, SACT, ER, JCT, JROH, SBBG, SAV, PDD, MIN, SJSU, MISS, PAMP, MNHM, SDSU, BOTU, MPU, MSB, MSC, CANU, SFV, RSA, CNS, JEPS, BKF, MSUN, CIB, VIT, MU, MUB, MVFA, SLPM, MVFQ, PGM, MVJB, MVM, MY, PASA, N, HGM, TAM, BOON, MHA, MARS, COI, CMM, NA, NCSC, ND, NU, NE, NHM, NHMC, NHT, UFMA, NLH, UFRJ, UFRN, UFS, ULS, UNL, US, NMNL, USP, NMR, NMSU, XAL, NSW, ZMT, BRIT, MO, NCU, NY, TEX, U, UNCC, NUM, O, OCLA, CHSC, LINC, CHAS, ODU, OKL, OKLA, CDA, OS, OSA, OSC, OSH, OULU, OXF, P, PACA, PAR, UPS, PE, PEL, SGO, PEUFR, PH, PKDC, SI, PMA, POM, PORT, PR, PRC, TRA, PRE, PY, QMEX, QCA, TROM, QCNE, QRS, UH, R, REG, RFA, RIOC, RM, RNG, RYU, S, SALA, SANT, SAPS, SASK, SBT, SEL, SING, SIU, SJRP, SMDB, SNM, SOM, SP, SRFA, SPF, STL, STU, SUVA, SVG, SZU, TAI, TAIF, TAMU, TAN, TEF, TENN, TEPB, TI, TKPM, TNS, TO, TU, TULS, UADY, UAM, UAS, UB, UC, UCR, UEC, UFG, UFMT, UFP, UGDA, UJAT, ULM, UME, UMO, UNA, UNM, UNR, UNSL, UPCB, UPNA, USAS, USJ, USM, USNC, USZ, UT, UTC, UTEP, UV, VAL, VEN, VMSL, VT, W, WAG, WII, WELT, WIS, WMNH, WS, WTU, WU, Z, ZSS, ZT, CUVC, AAS, AFS, BHCB, CHAM, FM, PERTH and SAN. X.F., D.S.P., E.A.N., A.L. and J.R.B. were supported by the University of Arizona Bridging Biodiversity and Conservation Science program. Z.L. was supported by NSFC (41922006) and K. C. Wong Education Foundation. The BIEN working group was supported by the National Center for Ecological Analysis and Synthesis, a centre funded by NSF EF-0553768 at the University of California, Santa Barbara, and the State of California. Additional support for the BIEN working group was provided by iPlant/Cyverse via NSF DBI-0735191. B.J.E., B.M. and C.M. were supported by NSF ABI-1565118. B.J.E. and C.M. were supported by NSF ABI-1565118 and NSF HDR-1934790. B.J.E., L.H. and P.R.R. were supported by the Global Environment Facility SPARC project grant (GEF-5810). D.D.B. was supported in part by NSF DEB-1824796 and NSF DEB-1550686. S.R.S. was supported by NSF DEB-1754803. X.F. and A.L. were partly supported by NSF DEB-1824796. B.J.E. and D.M.N. were supported by NSF DEB-1556651. M.M.P. is supported by the São Paulo Research Foundation (FAPESP), grant 2019/25478-7. D.M.N. was supported by Instituto Serrapilheira/Brazil (Serra-1912-32082). E.I.N. was supported by NSF HDR-1934712. We thank L. López-Hoffman and L. Baldwin for constructive comments. More