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As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth's surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth's albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth's climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth's surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity.

Planting diverse forests has been proposed as a means to increase long‐term carbon (C) sequestration while providing many co‐benefits. Positive tree diversity–productivity relationships are well established, suggesting more diverse forests will lead to greater aboveground C sequestration. However, the effects of tree diversity on belowground C storage have the potential to either complement or offset aboveground gains, especially during early stages of afforestation when potential exists for large losses in soil C due to soil decomposition. Thus, experimental tests of the effects of planted tree biodiversity on changes in whole‐ecosystem C balance are needed. Here, we present changes in above‐ and belowground C pools 6 years after the initiation of the Forests and Biodiversity experiment (FAB1), consisting of high‐density plots of one, two, five, or 12 tree species planted in a common garden. The trees included a diverse range of native species, including both needle‐leaf conifer and broadleaf angiosperm species, and both ectomycorrhizal and arbuscular mycorrhizal species. We quantified the effects of species richness, phylogenetic diversity, and functional diversity on aboveground woody C, as well as on mineral soil C accumulation, fine root C, and soil aggregation. Surprisingly, changes in aboveground woody C pools were uncorrelated to changes in mineral soil C pools, suggesting that variation in soil C accumulation was not driven by the quantity of plant litter inputs. Aboveground woody C accumulation was strongly driven by species and functional identity; however, plots with higher species richness and functional diversity accumulated more C in aboveground wood than expected based on monocultures. We also found weak but significant effects of tree species richness, identity, and mycorrhizal type on soil C accumulation. To assess the role of the microbial community in mediating these effects, we further compared changes in soil C pools to phospholipid fatty acid (PLFA) profiles. Soil C pools and accumulation were more strongly correlated with specific microbial clades than with total microbial biomass or plant diversity. Our results highlight rapidly emerging and microbially mediated effects of tree biodiversity on soil C storage in the early years of afforestation that are independent of gains in aboveground woody biomass. [ABSTRACT FROM AUTHOR]

We introduce a new "ecosystem‐scale" experiment at the Cedar Creek Ecosystem Science Reserve in central Minnesota, USA to test long‐term ecosystem consequences of tree diversity and composition. The experiment—the largest of its kind in North America—was designed to provide guidance on forest restoration efforts that will advance carbon sequestration goals and contribute to biodiversity conservation and sustainability.The new Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long‐term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of 12 species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie‐grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes.Within the first 6 years, mortality in 400 m2 monoculture plots was higher than in 100 m2 plots. The highest mortality occurred in Tilia americana and Acer negundo monocultures, but mortality for both species decreased with increasing plot diversity. These results demonstrate the importance of forest diversity in reducing mortality in some species and point to potential mechanisms, including light and drought stress, that cause tree mortality in vulnerable monocultures. The experiment highlights challenges to maintaining monoculture and low‐diversity treatments in tree mixture experiments of large extent.FAB2 provides a long‐term platform to test the mechanisms and processes that contribute to forest stability and ecosystem productivity in changing environments. Its ecosystem‐scale design, and accompanying R package, are designed to discern species and lineage effects and multiple dimensions of diversity to inform restoration of ecosystem functions and services from forests. It also provides a platform for improving remote sensing approaches, including Uncrewed Aerial Vehicles (UAVs) equipped with LiDAR, multispectral and hyperspectral sensors, to complement ground‐based monitoring. We aim for the experiment to contribute to international efforts to monitor and manage forests in the face of global change. [ABSTRACT FROM AUTHOR]

Measuring the chemical traits of leaf litter is important for understanding plants' influence on nutrient cycles, including through nutrient resorption and litter decomposition, but conventional leaf trait measurements are often destructive and labor-intensive. Here, we develop and evaluate the performance of partial least-squares regression models that use reflectance spectra of intact or ground leaves to estimate leaf litter traits, including carbon and nitrogen concentration, carbon fractions, and leaf mass per area (LMA). Our analyses included more than 300 samples of senesced foliage from 11 species of temperate trees, including both needleleaf and broadleaf species. Across all samples, we could predict each trait with moderate-to-high accuracy from both intact-leaf litter spectra (validation R2 = 0.543–0.941; %root mean squared error (RMSE) = 7.49–18.5) and ground-leaf litter spectra (validation R2 = 0.491–0.946; %RMSE = 7.00–19.5). Notably, intact-leaf spectra yielded better predictions of LMA. Our results support the feasibility of building models to estimate multiple chemical traits from leaf litter of a range of species. In particular, intact-leaf spectral models allow non-destructive trait estimation in a matter of seconds, which could enable researchers to measure the same leaves over time in studies of nutrient resorption. [ABSTRACT FROM AUTHOR]

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Premise of the Study: Evolutionary and biogeographic history, including past environmental change and diversification processes, are likely to have influenced the expansion, migration, and extinction of populations, creating evolutionary legacy effects that influence regional species pools and the composition of communities. We consider the consequences of the diversification process in shaping trait evolution and assembly of oak‐dominated communities throughout the continental United States (U.S.). Methods: Within the U.S. oaks, we tested for phylogenetic and functional trait patterns at different spatial scales, taking advantage of a dated phylogenomic analysis of American oaks and the U.S. Forest Service (USFS) Forest Inventory and Analysis (FIA). Key Results: We find (1) phylogenetic overdispersion at small grain sizes throughout the U.S. across all spatial extents and (2) a shift from overdispersion to clustering with increasing grain sizes. Leaf traits have evolved in a convergent manner, and these traits are clustered in communities at all spatial scales, except in the far west, where species with contrasting leaf types co‐occur. Conclusions: Our results support the hypotheses that (1) interspecific interactions were important in parallel adaptive radiation of the genus into a range of habitats across the continent and (2) that the diversification process is a critical driver of community assembly. Functional convergence of complementary species from distinct clades adapted to the same local habitats is a likely mechanism that allows distantly related species to coexist. Our findings contribute to an explanation of the long‐term maintenance of high oak diversity and the dominance of the oak genus in North America. [ABSTRACT FROM AUTHOR]

Reflectance spectra provide integrative measures of plant phenotypes by capturing chemical, morphological, anatomical and architectural trait information. Here, we investigate the linkages between plant spectral variation, and spectral and resource-use complementarity that contribute to ecosystem productivity. In both a forest and prairie grassland diversity experiment, we delineated n -dimensional hypervolumes using wavelength bands of reflectance spectra to test the association between the spectral space occupied by individual plants and their growth, as well as between the spectral space occupied by plant communities and ecosystem productivity. We show that the spectral space occupied by individuals increased with their growth, and the spectral space occupied by plant communities increased with ecosystem productivity. Furthermore, ecosystem productivity was better explained by inter-individual spectral complementarity than by the large spectral space occupied by productive individuals. Our results indicate that spectral hypervolumes of plants can reflect ecological strategies that shape community composition and ecosystem function, and that spectral complementarity can reveal resource-use complementarity.