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Plant litter decomposition is a primary control on carbon fluxes in terrestrial ecosystems around the world. Individually, the key mediators of decomposition rates—litter traits, temperature, and moisture—are relatively well understood. However, our understanding of how combined drivers influence decomposition remains limited. To test how multiple, interactive climate change factors directly alter decomposition rates and indirectly influence leaf litter decomposition rates by altering substrate chemistry, we conducted two decomposition experiments within the Boreal Forest Warming at an Ecotone in Danger (B4WarmED) study in Minnesota, USA. Our first experiment decomposed ambient-grown leaf litter from eight common tree species under a factorial combination of warming and rainfall reduction treatments. We found that the direct effects of combined warming and rainfall reduction increased litter half-life by 42% ± 11% in comparison to ambient plots with no warming or rainfall reduction. In contrast, only rainfall reduction influenced litter mean residence time, which increased by 37% ± 18% in comparison to ambient rainfall plots. Our second experiment decomposed ambient- and warm-grown leaf litter from the same eight species under ambient and warmed conditions. We found that warming slowed decomposition of both litter types, but warm-grown litter had a 22% ± 6.5% shorter half-life than ambient-grown leaf tissue under ambient environmental conditions. Warm grown litter half-life then increased by 36% ± 11% with warmed environmental conditions. Our results highlight that climate change could slow carbon and nutrient cycling in systems where moisture becomes a limiting factor. In addition, our study demonstrates that there may be an overlooked relationship between the growth conditions of plants and the temperature of decomposition. This nuanced understanding of decomposition can then support carbon cycling models and more effective nature-based climate mitigation efforts. 

Abstract In our changing world, understanding plant community responses to global change drivers is critical for predicting future ecosystem composition and function. Plant functional traits promise to be a key predictive tool for many ecosystems, including grasslands; however, their use requires both complete plant community and functional trait data. Yet, representation of these data in global databases is sparse, particularly beyond a handful of most used traits and common species. Here we present the CoRRE Trait Data, spanning 17 traits (9 categorical, 8 continuous) anticipated to predict species’ responses to global change for 4,079 vascular plant species across 173 plant families present in 390 grassland experiments from around the world. The dataset contains complete categorical trait records for all 4,079 plant species obtained from a comprehensive literature search, as well as nearly complete coverage (99.97%) of imputed continuous trait values for a subset of 2,927 plant species. These data will shed light on mechanisms underlying population, community, and ecosystem responses to global change in grasslands worldwide. 

Termites are important ecosystem engineers in tropical habitats, with different feeding groups able to decompose wood, grass, litter, and soil organic matter. In most tropical regions, termite abundance and species diversity are assumed to increase with rainfall, with highest levels found in rainforests. However, in the Australian tropics, this pattern is thought to be reversed, with lower species richness and termite abundance found in rainforest than drier habitats. The potential mechanisms underlying this pattern remain unclear. We compared termite assemblages (abundance, activity, diversity, and feeding group composition) across five sites along a precipitation gradient (ranging from ∼800 to 4,000 mm annual rainfall), spanning dry and wet savanna habitats, wet sclerophyll, and lowland and upland rainforests in tropical North Queensland. Moving from dry to wet habitats, we observed dramatic decreases in termite abundance in both mounds and dead wood occupancy, with greater abundance and activity at savanna sites (low precipitation) compared with rainforest or sclerophyll sites (high precipitation). We also observed a turnover in termite species and feeding group diversity across sites that were close together, but in different habitats. Termite species and feeding group richness were highest in savanna sites, with 13 termite species from wood-, litter-, grass-, dung-, and soil-feeding groups, while only five termite species were encountered in rainforest and wet sclerophyll sites—all wood feeders. These results suggest that the Australian termite diversity anomaly may be partly driven by how specific feeding groups colonized habitats across Australia. Consequently, termites in Australian rainforests may be less important in ecosystem processes, such as carbon and nutrient cycling during decomposition, compared with termites in other tropical rainforests. 

Abstract Variation in decay rates across woody species is a key uncertainty in predicting the fate of carbon stored in deadwood, especially in the tropics. Quantifying the relative contributions of biotic decay agents, particularly microbes and termites, under different climates and across species with diverse wood traits could help explain this variation.To fill this knowledge gap, we deployed woody stems from 16 plant species native to either rainforest (n = 10) or savanna (n = 6) in northeast Australia, with and without termite access. For comparison, we also deployed standardized, non‐native pine blocks at both sites. We hypothesized that termites would increase rates of deadwood decay under conditions that limit microbial activity. Specifically, termite contributions to wood decay should be greater under dry conditions and in wood species with traits that constrain microbial decomposers.Termite discovery of stems was surprisingly low with only 17.6% and 22.6% of accessible native stems discovered in the rainforest and savanna respectively. Contrary to our hypothesis, stems discovered by termites decomposed faster only in the rainforest. Termites discovered and decayed pine blocks at higher rates than native stems in both the rainforest and savanna.We found significant variation in termite discovery and microbial decay rates across native wood species within the same site. Although wood traits explained 85% of the variation in microbial decay, they did not explain termite‐driven decay. For stems undiscovered by termites, decay rates were greater in species with higher wood nutrient concentrations and syringyl:guiacyl lignin ratios but lower carbon concentrations and wood densities.Synthesis. Ecosystem‐scale predictions of deadwood turnover and carbon storage should account for the impact of wood traits on decomposer communities. In tropical Australia, termite‐driven decay was lower than expected for native wood on the ground. Even if termites are present, they may not always increase decomposition rates of fallen native wood in tropical forests. Our study shows how the drivers of wood decay differ between Australian tropical rainforest and savanna; further research should test whether such differences apply world‐wide. 

A globally distributed field experiment shows that wood decay, particularly by termites, depends on temperature. 

Abstract Transitioning across biological scales is a central challenge in land surface models. Processes that operate at the scale of individual leaves must be scaled to canopies, and this is done using dedicated submodels. Here, we focus on a submodel that prescribes how light and nitrogen are distributed through plant canopies. We found a mathematical inconsistency in a submodel implemented in the Community and Energy Land Models (CLM and ELM), which incorporates twigs, branches, stems, and dead leaves in nitrogen scaling from leaf to canopy. The inconsistency leads to unrealistic (physically impossible) values of the nitrogen scaling coefficient. The mathematical inconsistency is a general mistake, that is, would occur in any model adopting this particular submodel. We resolve the inconsistency by allowing distinct profiles of stems and branches versus living leaves. We implemented the updated scheme in the ELM and find that the correction reduces global mean gross primary production (GPP) by 3.9 Pg C (3%). Further, when stems and branches are removed from the canopy in the updated model (akin to models that ignore shading from stems), global GPP increases by 4.1 Pg C (3.2%), because of reduced shading. Hence, models that entirely ignore stem shading also introduce errors in the global spatial distribution of GPP estimates, with a strong signal in the tropics, increasing GPP there by over 200 g C m⁻² yr⁻¹. Appropriately incorporating stems and other nonphotosynthesizing material into the light and nitrogen scaling routines of global land models, will improve their biological realism and accuracy. 

Abstract Fine root decomposition constitutes a critical yet poorly understood flux of carbon and nutrients in terrestrial ecosystems. Here, we present the first large‐scale synthesis of species trait effects on the early stages of fine root decomposition at both global and local scales. Based on decomposition rates for 279 plant species across 105 studies and 176 sites, we found that mycorrhizal association and woodiness are the best categorical traits for predicting rates of fine root decomposition. Consistent positive effects of nitrogen and phosphorus concentrations and negative effects of lignin concentration emerged on decomposition rates within sites. Similar relationships were present across sites, along with positive effects of temperature and moisture. Calcium was not consistently related to decomposition rate at either scale. While the chemical drivers of fine root decomposition parallel those of leaf decomposition, our results indicate that the best plant functional groups for predicting fine root decomposition differ from those predicting leaf decomposition.