The amount of carbon stored in deadwood is equivalent to about 8 per cent of the global forest carbon stocks1. The decomposition of deadwood is largely governed by climate2,3,4,5 with decomposer groups—such as microorganisms and insects—contributing to variations in the decomposition rates2,6,7. At the global scale, the contribution of insects to the decomposition of deadwood and carbon release remains poorly understood7. Here we present a field experiment of wood decomposition across 55 forest sites and 6 continents. We find that the deadwood decomposition rates increase with temperature, and the strongest temperature effect is found at high precipitation levels. Precipitation affects the decomposition rates negatively at low temperatures and positively at high temperatures. As a net effect—including the direct consumption by insects and indirect effects through interactions with microorganisms—insects accelerate the decomposition in tropical forests (3.9% median mass loss per year). In temperate and boreal forests, we find weak positive and negative effects with a median mass loss of 0.9 per cent and −0.1 per cent per year, respectively. Furthermore, we apply the experimentally derived decomposition function to a global map of deadwood carbon synthesized from empirical and remote-sensing data, obtaining an estimate of 10.9 ± 3.2 petagram of carbon per year released from deadwood globally, with 93 per cent originating from tropical forests. Globally, the net effect of insects may account for 29 per cent of the carbon flux from deadwood, which suggests a functional importance of insects in the decomposition of deadwood and the carbon cycle.
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).
Bradford, M. A. et al. Climate fails to predict wood decomposition at regional scales. Nat. Clim. Change 4, 625–630 (2014).
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).
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).
Stokland, J., Siitonen, J. & Jonsson, B. G. Biodiversity in Dead Wood (Cambridge Univ. Press, 2012).
Lustenhouwer, N. et al. A trait-based understanding of wood decomposition by fungi. Proc. Natl Acad. Sci. USA 117, 11551–11558 (2020).
Ulyshen, M. D. Wood decomposition as influenced by invertebrates. Biol. Rev. Camb. Philos. Soc. 91, 70–85 (2016).
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).
Büntgen, U. et al. Limited capacity of tree growth to mitigate the global greenhouse effect under predicted warming. Nat. Commun. 10, 2171 (2019).
Seidl, R. et al. Forest disturbances under climate change. Nat. Clim. Change 7, 395–402 (2017).
Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).
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).
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).
Keenan, T. F. et al. Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise. Nature 499, 324–327 (2013).
Stephenson, N. L. et al. Rate of tree carbon accumulation increases continuously with tree size. Nature 507, 90–93 (2014).
Martin, A., Dimke, G., Doraisami, M. & Thomas, S. Carbon fractions in the world’s dead wood. Nat. Commun. 12, 889 (2021).
Friedlingstein, P. et al. Global carbon budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).
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).
Buczkowski, G. & Bertelsmeier, C. Invasive termites in a changing climate: a global perspective. Ecol. Evol. 7, 974–985 (2017).
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).
van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420 (2020).
Seibold, S. et al. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature 574, 671–674 (2019).
Harris, N. L. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Change 11, 234–240 (2021).
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).
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).
Wu, D., Seibold, S., Ruan, Z., Weng, C. & Yu, M. Island size affects wood decomposition by changing decomposer distribution. Ecography 44, 456–468 (2021).
Harmon, M. E. et al. Release of coarse woody detritus-related carbon: a synthesis across forest biomes. Carbon Balance Manag. 15, 1 (2020).
Wall, D. H. et al. Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent. Glob. Change Biol. 14, 2661–2677 (2008).
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).
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).
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).
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).
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).
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).
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).
Birkemoe, T., Jacobsen, R. M., Sverdrup-Thygeson, A. & Biedermann, P. H. W. in Saproxylic Insects (ed. Ulyshen, M. D.) 377–427 (Springer, 2018).
Harvell, M. C. E. et al. Climate warming and disease risks for terrestrial and marine biota. Science 296, 2158–2162 (2002).
Berkov, A. in Saproxylic Insects (ed. Ulyshen, M. D.) 547–580 (Springer, 2018).
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).
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).
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).
van Leeuwen, T. T. et al. Biomass burning fuel consumption rates: a field measurement database. Biogeosciences 11, 7305–7329 (2014).
McDowell, N. G. et al. Pervasive shifts in forest dynamics in a changing world. Science 368, eaaz9463 (2020).
Ulyshen, M. D. & Wagner, T. L. Quantifying arthropod contributions to wood decay. Methods Ecol. Evol. 4, 345–352 (2013).
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).
Ryvarden, L. & Gilbertson, R. L. The Polyporaceae of Europe (Fungiflora, 1994).
Eriksson, J. & Ryvarden, L. The Corticiaceae of North Europe Parts 1–8 (Fungiflora, 1987).
Boddy, L., Hynes, J., Bebber, D. P. & Fricker, M. D. Saprotrophic cord systems: dispersal mechanisms in space and time. Mycoscience 50, 9–19 (2009).
Moore, D. Fungal Morphogenesis (Cambridge Univ. Press, 1998).
Clemencon, H. Anatomy of the Hymenomycetes (Univ. Lausanne, 1997).
R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, 2020).
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).
Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Wood, S. N. Generalized Additive Models: an Introduction with R 2nd edn (Chapman and Hall/CRC, 2017).
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).
Food and Agriculture Organization. Global Ecological Zones for FAO Forest Reporting: 2010 Update, Forest Resource Assessment Working Paper (Food and Agriculture Organization, 2012).
Food and Agriculture Organization. Global Forest Resources Assessment 2015 (Food and Agriculture Organization, 2016).
Christensen, M. et al. Dead wood in European beech (Fagus sylvatica) forest reserves. For. Eco. Man. 210, 267–282 (2005).
Kobayashi, T. et al. Production of global land cover data – GLCNMO2013. J. Geogr. Geol. 9, 1–15 (2017).
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).
Hararuk, O., Kurz, W. A. & Didion, M. Dynamics of dead wood decay in Swiss forests. For. Ecosyst. 7, 36 (2020).
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).
Hérault, B. et al. Modeling decay rates of dead wood in a neotropical forest. Oecologia 164, 243–251 (2010).
Thünen-Institut für Waldökosysteme. Der Wald in Deutschland - Ausgewählte Ergebnisse der dritten Bundeswaldinventur (Bundesministerium für Ernährung und Landwirtschaft, 2014).
Puletti, N. et al. A dataset of forest volume deadwood estimates for Europe. Ann. For. Sci. 76, 68 (2019).
Richardson, S. J. et al. Deadwood in New Zealand’s indigenous forests. For. Ecol. Manage. 258, 2456–2466 (2009).
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).
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).
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).
Saugier, B., Roy, J. & Mooney, H. A. in Terrestrial Global Productivity (eds J. Roy, B. Saugier & H. A. Mooney) 543–557 (Academic Press, 2001).
We thank the administration of the Bavarian Forest National Park for financing the set-up of the experiment and all members of the local teams for their contribution in the field and laboratory. We especially thank D. Blair who operated the site in Victoria, Australia, until his unexpected death in 2019. We thank B. von Rentzel, J. Ganzhorn, A. Gruppe, M. Harmon, S. Muller and S. Irwin, Makiling Center for Mountain Ecosystems, University of the Philippines Los Banos, the Ministerio del Ambiente de Ecuador, the Instituto Nacional de Biodiversidad de Ecuador and the foundation “Nature and Culture International” for their support. S. Seibold was supported by the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research and the People Programme of the European Union (Marie Curie Actions; grant number 605728). N.F. was supported by the German Research Foundation (FA925/7-1, FA925/11-1).
The authors declare no competing interests.
Peer review information Nature thanks Robert M. Ewers and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Each site received three installations of three treatments randomly assigned to a 3 × 3 grid. b–d, Treatments included closed cages to exclude insects (b), open cages providing similar microclimatic conditions as closed cages but giving access to insects (c) and uncaged bundles of logs (d). Cages measured 40 cm × 40 cm × 60 cm and were made of white polyester with honeycomb-shaped meshes with a side length of approximately 0.5 mm. Open cages had four rectangular openings measuring 3 cm × 12 cm at both front sides and four rectangular openings measuring 10 cm × 15 cm at the bottom representing in total 6% of the surface area of the cage as well as a total of ten 12-cm slits at the top and long sides. All cages were placed on a stainless-steel mesh (0.5 mm mesh width), which had the same openings as the bottom side of the cages in the open-cage treatment. Photographs show the site in the Bavarian Forest National Park, Germany.
a, b, Coefficients and confidence intervals from post hoc tests assessing all three pairwise comparisons between the uncaged, closed-cage and open-cage treatments for annual mass loss (a; same structure as the model shown in Table 1 based on 3,578 logs) and insect colonization (b; binomial model for insect presence and absence based on 3,430 logs) of wood of native tree species. The 95% confidence intervals that do not intersect the zero line (dashed) indicate significant differences. c, Pairwise comparison of fitted annual mass loss (%) between each of the three treatments in the global deadwood decomposition experiment. Points represent the predicted values for angiosperm species at 55 sites and gymnosperm species at 21 sites based on three Gaussian generalized linear mixed log-link models for 3,758 logs with site-specific random effects and temperature, precipitation, treatment (closed cage versus uncaged, open cage versus uncaged and closed cage versus open cage), host division, as well as their interactions, as fixed effects. In a and b, the largest differences in both response variables were observed between uncaged and closed-cage treatments. Annual mass loss was higher in the uncaged than open-cage treatment and higher in the open-cage than in closed-cage treatment, although the latter was not significant. This indicates that the open cage, despite its openings for insects, has a clearly reduced decomposition rate compared with the uncaged treatment. Insect colonization for the open cage differed significantly from both uncaged and closed-cage treatment, but was more similar to the uncaged than closed-cage treatment. This indicates that open cages were colonized by insects, but not as frequently as the uncaged treatment. Open cages thus excluded parts of the wood-decomposing insect community, which may explain the rather small difference in annual mass loss between closed cages and open cages. These results suggest that the comparison of uncaged wood versus closed cages provides a more reliable estimate of the net effect of insects on wood decomposition than the comparison of closed-cage versus open-cage treatments, which is likely to underestimate the net effect of insects. In c, the difference between annual mass loss in closed-cage and both treatments with insect access (uncaged and open cage) increased from boreal to tropical biomes, whereas the difference between uncaged wood and open cages hardly deviated from the 1:1 line. This indicates that the reported mass loss differences between closed-cage and uncaged treatments, as well as the accelerating effect of temperature and precipitation (Table 1), can be attributed to insects and are not an artefact of potential microclimatic effects of the cages (Supplementary Information section 1).
a, b, Predictions based on the model presented in Table 1 for annual mass loss of deadwood of native tree species (2,533 logs at 55 sites), considering all possible groups of decomposers (uncaged treatment) (a), and annual mass loss attributed to insects (difference in mass loss between uncaged and closed-cage treatments) (b), relative to temperature and precipitation. The length of the lines is limited to the gradients in precipitation covered by the sites.
Comparison of 157 independent observations of annual deadwood decomposition rates measured for larger diameter wood in previous deadwood surveys27 (red dots) with the predictions from our model for the same locations (blue triangles). Lines indicate the relationship between the decomposition rate and mean annual temperature from Harmon et al.27 (red dashed line; k = 0.0184e0.0787×temperature) and for our model (blue line; k = 0.0171e0.0812×temperature). Good correspondence of both curves indicates that our models of global carbon release from deadwood provide robust estimates despite being based on experimental deadwood with a diameter of around 3 cm (for detailed discussion, see Supplementary Information section 1).
a, b, Total annual release of deadwood carbon from decomposition including all decomposers (a) and annual release of deadwood carbon due to the net effect of insects (b). Light grey areas indicate values of ±0.1 Mg C ha−1 yr−1 and white areas are non-forest systems. c, Latitudinal distribution of global deadwood carbon fluxes per hectare.
a, Aboveground forest biomass (Mg ha−1) aggregated to 5′ from the GlobBiom dataset. b, Total live carbon (Mg ha−1) by extending a with root biomass55 and conversion to carbon. c, Proportion of gymnosperm forests derived from the GLCNMO201359 dataset. The proportion of angiosperm cover is 1 − gymnosperm cover. White indicates non-forested area.
a, b, Climate conditions outside of the range of prediction models for angiosperm (a) and gymnosperm (b) species in climate space (left) and mapped (right). Left, dark blue points are outside of the range defined by a convex hull around the experimental sites (black triangles). Right, the colours on the maps indicate the absolute difference between the local climate and the climate used for prediction for temperature (red colour channel) and precipitation (blue colour channel) with black indicating no difference. White areas indicate that no gymnosperm or angiosperm forest, respectively, occurs there. Experimental sites are indicated by yellow dots. Temperatures outside of the range are mainly located in northeastern Siberia and northern Canada, whereas offsets in precipitation are stronger for gymnosperms in southeastern Asia, Indonesia and in the Amazon region. The land surface area not covered by our experimental data is 23.5% for gymnosperms and 17.7% for angiosperms, representing together 13.2% of the carbon stored in deadwood. These areas were included in our upscaling by mapping them to the nearest point at the convex hull in climate space.
This Supplementary Information file contains the following sections: (1) methodological aspects of the wood decomposition experiment; (2) challenges related to the upscaling from experimental data to global deadwood carbon fluxes; (3) overview of tree species and exposure time per site; and the Supplementary References.
About this article
Cite this article
Seibold, S., Rammer, W., Hothorn, T. et al. The contribution of insects to global forest deadwood decomposition. Nature 597, 77–81 (2021). https://doi.org/10.1038/s41586-021-03740-8