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Rising temperatures are influencing forests on many scales, with potentially strong variation vertically across forest strata. Using published research and new analyses, we evaluate how microclimate and leaf temperatures, traits, and gas exchange vary vertically in forests, shaping tree, and ecosystem ecology. In closed-canopy forests, upper canopy leaves are exposed to the highest solar radiation and evaporative demand, which can elevate leaf temperature (Tleaf ), particularly when transpirational cooling is curtailed by limited stomatal conductance. However, foliar traits also vary across height or light gradients, partially mitigating and protecting against the elevation of upper canopy Tleaf . Leaf metabolism generally increases with height across the vertical gradient, yet differences in thermal sensitivity across the gradient appear modest. Scaling from leaves to trees, canopy trees have higher absolute metabolic capacity and growth, yet are more vulnerable to drought and damaging Tleaf than their smaller counterparts, particularly under climate change. By contrast, understory trees experience fewer extreme high Tleaf 's but have fewer cooling mechanisms and thus may be strongly impacted by warming under some conditions, particularly when exposed to a harsher microenvironment through canopy disturbance. As the climate changes, integrating the patterns and mechanisms reviewed here into models will be critical to forecasting forest-climate feedback.

The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.

Deep-water access is arguably the most effective, but under-studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep-water access may delay plant dehydration. Here, we tested the role of deep-water access in enabling survival within a diverse tropical forest community in Panama using a novel data-model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990-2015) to vapor pressure deficit, water potentials in the whole-soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water-access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981-2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress-related mortality risk through deep-water access. The role of deep-water access in mitigating mortality of hydraulically-vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

Plant diversity varies immensely over large-scale gradients in temperature, precipitation, and seasonality at global and regional scales. This relationship may be driven in part by climatic variation in the relative importance of abiotic and biotic interactions to the diversity and composition of plant communities. In particular, biotic interactions may become stronger and more host specific with increasing precipitation and temperature, resulting in greater plant species richness in wetter and warmer environments. This hypothesis predicts that the many defensive compounds found in plants’ metabolomes should increase in richness and decrease in interspecific similarity with precipitation, temperature, and plant diversity. To test this prediction, we compared patterns of chemical and morphological trait diversity of 140 woody plant species among seven temperate forests in North America representing 16.2°C variation in mean annual temperature (MAT), 2,115 mm variation in mean annual precipitation (MAP), and from 10 to 68 co-occurring species. We used untargeted metabolomics methods based on data generated with liquid chromatography-tandem mass spectrometry to identify, classify, and compare 13,480 unique foliar metabolites and to quantify the metabolomic similarity of species in each community with respect to the whole metabolome and each of five broad classes of metabolites. In addition, we compiled morphological trait data from existing databases and field surveys for three commonly measured traits (specific leaf area [SLA], wood density, and seed mass) for comparison with foliar metabolomes. We found that chemical defense strategies and growth and allocation strategies reflected by these traits largely represented orthogonal axes of variation. In addition, functional dispersion of SLA increased with MAP, whereas functional richness of wood density and seed mass increased with MAT. In contrast, chemical similarity of co-occurring species decreased with both MAT and MAP, and metabolite richness increased with MAT. Variation in metabolite richness among communities was positively correlated with species richness, but variation in mean chemical similarity was not. Our results are consistent with the hypothesis that plant metabolomes play a more important role in community assembly in wetter and warmer climates, even at temperate latitudes, and suggest that metabolomic traits can provide unique insight to studies of trait-based community assembly.

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN.

Survival rates of large trees determine forest biomass dynamics. Survival rates of small trees have been linked to mechanisms that maintain biodiversity across tropical forests. How species survival rates change with size offers insight into the links between biodiversity and ecosystem function across tropical forests. We tested patterns of size-dependent tree survival across the tropics using data from 1,781 species and over 2 million individuals to assess whether tropical forests can be characterized by size-dependent life-history survival strategies. We found that species were classifiable into four 'survival modes' that explain life-history variation that shapes carbon cycling and the relative abundance within forests. Frequently collected functional traits, such as wood density, leaf mass per area and seed mass, were not generally predictive of the survival modes of species. Mean annual temperature and cumulative water deficit predicted the proportion of biomass of survival modes, indicating important links between evolutionary strategies, climate and carbon cycling. The application of survival modes in demographic simulations predicted biomass change across forest sites. Our results reveal globally identifiable size-dependent survival strategies that differ across diverse systems in a consistent way. The abundance of survival modes and interaction with climate ultimately determine forest structure, carbon storage in biomass and future forest trajectories.

Aims: Patterns of spatial community dissimilarity have inspired a large body of theory in ecology and biogeography. Yet key gaps remain in our understanding of the local-scale ecological processes underlying species replacement and species nestedness, the two fundamental components of spatial community dissimilarity. Here, we examined the relative influence of dispersal limitation, habitat filtering and interspecific species interactions on local-scale patterns of the replacement and nestedness components in eight stem-mapped temperate forest mega-plots at different ontogenetic stages (large versus small trees). Location: Eight large (20–35 ha), fully mapped temperate forest plots in northern China and northern U.S.A. Time period: 2004–2016. Major taxa studied: Woody plants. Methods: We combined decomposition of community dissimilarity (based on the Ružička index) and spatial point-pattern analysis to compare the spatial (i.e., distance-dependent) replacement and nestedness components of each plot with that expected under five spatially explicit null models representing different hypotheses on community-assembly mechanisms. Results: Our analyses revealed complex results. In all eight forests, spatial community dissimilarity was best explained by species replacement among local tree assemblages and by a null model based on dispersal limitation. In contrast, spatial nestedness for large and small trees was best explained by random placement and habitat filtering, respectively, in addition to dispersal limitation. However, interspecific interactions did not contribute to local replacement and nestedness. Main conclusions: Species replacement is the predominant process accounting for spatial community dissimilarity in these temperate forests and caused largely by local-scale species clustering associated with dispersal limitation. Nestedness, in contrast, is less prevalent and primarily associated with larger variation in local species richness as caused by spatial richness gradients or ‘hotspots’ of local species richness. The novel use of replacement and nestedness measures in point pattern analysis is a promising approach to assess local-scale biodiversity patterns and to explore their causes.

To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide.sup.1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon.sup.3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates.sup.2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC).sup.4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported.sup.3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy. A one-kilometre-resolution map of aboveground carbon accumulation rates of forest regrowth shows 100-fold variation across the globe, with rates 32% higher on average than IPCC estimates., Author(s): Susan C. Cook-Patton [sup.1] [sup.2] , Sara M. Leavitt [sup.1] , David Gibbs [sup.3] , Nancy L. Harris [sup.3] , Kristine Lister [sup.3] , Kristina J. Anderson-Teixeira [sup.4] [sup.5] [...]

Sustainable forest management needs information on spatial distribution of species richness. The objectives of this study were to understand whether knowledge, method, and effort of a rapid assessment affected accuracy and consistency in mapping species richness. A simulation study was carried out with nine 25-50 ha census plots located in tropical, subtropical, and temperate zones. Each forest site was first tessellated into non-overlapping cells. Rapid assessment was conducted in all cells to generate a complete coverage of proxies of the underlying species richness. Cells were subsampled for census, where all plant individuals were identified to species in these census cells. An artificial neural network model was built using the census cells that contain rapid assessment and census information. The model then predicted species richness of cells that were not censused. Results showed that knowledge level did not improve the accuracy and consistency in mapping species richness. Rapid assessment effort and method significantly affected the accuracy and consistency. Increasing rapid assessment effort from 10 to 40 plant individuals could improve the accuracy and consistency up to 2.2% and 2.8%, respectively. Transect reduced accuracy and consistency by up to 0.5% and 0.8%, respectively. This study suggests that knowing at least half of the species in a forest is sufficient for a rapid assessment. At least 20 plant individuals per cell is recommended for rapid assessment. Lastly, a rapid assessment could be carried out by local communities that are familiar with their forests; thus, further supporting sustainable forest management. [ABSTRACT FROM AUTHOR]

Emerging satellite radar and lidar platforms are being developed to produce gridded aboveground biomass (AGB) predictions that are poised to expand our understanding of global carbon stocks and changes. However, the spatial resolution of AGB map products from these platforms is often larger than the available field plot data underpinning model calibration and validation efforts. Intermediate-resolution/extent remotely sensed data, like airborne lidar, can serve as a bridge between small plots and map resolution, but methods are needed to estimate and propagate uncertainties with multiple layers of data. Here, we introduce a workflow to estimate the pixel-level mean and variance in AGB maps by propagating uncertainty from a lidar-based model using small plots, taking into account prediction uncertainty, residual uncertainty, and residual spatial autocorrelation. We apply this workflow to estimate AGB uncertainty at a 100 m map resolution (1 ha pixels) using 0.04 ha field plots from 11 sites across four ecoregions. We compare uncertainty estimates using site-specific models, ecoregion-specific models, and a general model using all sites. The estimated AGB uncertainty for 1 ha pixels increased with mean AGB, reaching 7.8–33.3 Mg ha−1 for site-specific models (one standard deviation), 11.1–28.2 Mg ha−1 for ecoregion-specific models, and 21.1–22.1 Mg ha−1 for the general model for pixels in the AGB range of 80–100 Mg ha−1. Only 3 of 11 site-specific models had a total uncertainty of <15 Mg ha−1 in this biomass range, suitable for the calibration or validation of AGB map products. Using two additional sites with larger field plots, we show that lidar-based models calibrated with larger field plots can substantially reduce 1 ha pixel AGB uncertainty for the same range from 18.2 Mg ha−1 using 0.04 ha plots to 10.9 Mg ha−1 using 0.25 ha plots and 10.1 Mg ha−1 using 1 ha plots. We conclude that the estimated AGB uncertainty from models estimated from small field plots may be unacceptably large, and we recommend coordinated efforts to measure larger field plots as reference data for the calibration or validation of satellite-based map products at landscape scales (≥0.25 ha). [ABSTRACT FROM AUTHOR]