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Purpose A better knowledge of how deadwood decomposes is critical for accurately characterizing carbon and nutrient cycling in forests. Fungi dominate this decomposition process, but we still have limited understanding of fungal community structuring that ultimately controls the fate of wood decomposition. This is particularly true in tropical ecosystems. To address this knowledge gap, our study capitalized on an extreme storm event that caused a large and synchronized input of deadwood to the forest floor. Methods Here we report data for the first year of wood decomposition of trees in a Puerto Rican dry forest for nine tree species that were snapped by Hurricane Maria in 2017. We measured wood properties and the associated fungal communities after 12 months of decomposition and compared them with initial wood properties and stem-inhabiting fungal communities to identify the best predictors of wood decomposition rates and chemical changes. Results Changes in wood chemistry were primarily explained by rapid xylan losses, the main hemicellulose component for the studied tree species. Fungal communities were dominated by saprotrophic and plant pathogenic fungi and showed moderate changes over time. The initial relative abundances and ratios of different fungal functional guilds were significant predictors of both xylan and glucan losses, with plant pathogenic fungi accelerating cellulose and hemicellulose decomposition rates compared to saprotrophs. Conclusion Our results confirm that fungi present at the time of treefall are strong drivers of wood decomposition and suggest that plant pathogenic fungi might act as efficient early decomposers of hemicellulose in dry tropical forests. 

Coarse woody debris (CWD) is a significant component of the forest biomass pool; hence a model is warranted to predict CWD decomposition and its role in forest carbon (C) and nutrient cycling under varying management and climatic conditions. A process-based model, CWDDAT (Coarse Woody Debris Decomposition Assessment Tool) was calibrated and validated using data from the FACE (Free Air Carbon Dioxide Enrichment) Wood Decomposition Experiment utilizing pine ( Pinus taeda ), aspen ( Populous tremuloides ) and birch ( Betula papyrifera ) on nine Experimental Forests (EF) covering a range of climate, hydrology, and soil conditions across the continental USA. The model predictions were evaluated against measured FACE log mass loss over 6 years. Four widely applied metrics of model performance demonstrated that the CWDDAT model can accurately predict CWD decomposition. The R 2 (squared Pearson’s correlation coefficient) between the simulation and measurement was 0.80 for the model calibration and 0.82 for the model validation ( P <0.01). The predicted mean mass loss from all logs was 5.4% lower than the measured mass loss and 1.4% lower than the calculated loss. The model was also used to assess the decomposition of mixed pine-hardwood CWD produced by Hurricane Hugo in 1989 on the Santee Experimental Forest in South Carolina, USA. The simulation reflected rapid CWD decomposition of the forest in this subtropical setting. The predicted dissolved organic carbon (DOC) derived from the CWD decomposition and incorporated into the mineral soil averaged 1.01 g C m -2 y -1 over the 30 years. The main agents for CWD mass loss were fungi (72.0%) and termites (24.5%), the remainder was attributed to a mix of other wood decomposers. These findings demonstrate the applicability of CWDDAT for large-scale assessments of CWD dynamics, and fine-scale considerations regarding the fate of CWD carbon. 

Coarse woody debris (CWD) is an important component in forests, hosting a variety of organisms that have critical roles in nutrient cycling and carbon (C) storage. We developed a process-based model using literature, field observations, and expert knowledge to assess woody debris decomposition in forests and the movement of wood C into the soil and atmosphere. The sensitivity analysis was conducted against the primary ecological drivers (wood properties and ambient conditions) used as model inputs. The analysis used eighty-nine climate datasets from North America, from tropical (14.2° N) to boreal (65.0° N) zones, with large ranges in annual mean temperature (26.5°C in tropical to -11.8°C in boreal), annual precipitation (6,143 to 181 mm), annual snowfall (0 to 612 kg m -2 ), and altitude (3 to 2,824 m above mean see level). The sensitivity analysis showed that CWD decomposition was strongly affected by climate, geographical location and altitude, which together regulate the activity of both microbial and invertebrate wood-decomposers. CWD decomposition rate increased with increments in temperature and precipitation, but decreased with increases in latitude and altitude. CWD decomposition was also sensitive to wood size, density, position (standing vs downed), and tree species. The sensitivity analysis showed that fungi are the most important decomposers of woody debris, accounting for over 50% mass loss in nearly all climatic zones in North America. The model includes invertebrate decomposers, focusing mostly on termites, which can have an important role in CWD decomposition in tropical and some subtropical regions. The role of termites in woody debris decomposition varied widely, between 0 and 40%, from temperate areas to tropical regions. Woody debris decomposition rates simulated for eighty-nine locations in North America were within the published range of woody debris decomposition rates for regions in northern hemisphere from 1.6° N to 68.3° N and in Australia. 

Fungi that decay wood have characteristic associations with certain tree species, but the mechanistic bases for these associations are poorly understood. We studied substrate-specific gene expression and RNA editing in six species of wood-decaying fungi from the ‘Antrodia clade’ (Polyporales, Agaricomycetes) on three different wood substrates (pine, spruce, and aspen) in submerged cultures. We identified dozens to hundreds of substrate-biased genes (i.e., genes that are significantly upregulated in one substrate relative to the other two substrates) in each species, and these biased genes are correlated with their host ranges. Evolution of substrate-biased genes is associated with gene family expansion, gain and loss of genes, and variation in cis- and trans- regulatory elements, rather than changes in protein coding sequences. We also demonstrated widespread RNA editing events in the Antrodia clade, which differ from those observed in the Ascomycota in their distribution, substitution types, and the genomic environment. Moreover, we found that substrates could affect editing positions and frequency, including editing events occurring in mRNA transcribed from wood-decay-related genes. This work shows the extent to which gene expression and RNA editing differ among species and substrates, and provides clues into mechanisms by which wood-decaying fungi may adapt to different hosts.