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A prominent signal of the Anthropocene is the extinction and population reduction of the megabiota—the largest animals and plants on the planet. However, we lack a predictive framework for the sensitivity of megabiota during times of rapid global change and how they impact the functioning of ecosystems and the biosphere. Here, we extend metabolic scaling theory and use global simulation models to demonstrate that (i) megabiota are more prone to extinction due to human land use, hunting, and climate change; (ii) loss of megabiota has a negative impact on ecosystem metabolism and functioning; and (iii) their reduction has and will continue to significantly decrease biosphere functioning. Global simulations show that continued loss of large animals alone could lead to a 44%, 18% and 92% reduction in terrestrial heterotrophic biomass, metabolism, and fertility respectively. Our findings suggest that policies that emphasize the promotion of large trees and animals will have disproportionate impact on biodiversity, ecosystem processes, and climate mitigation., Human-driven losses of megafauna and megaflora may have disproportionate ecological consequences. Here, the authors combine metabolic scaling theory and global simulation models to show that past and continued reduction of megabiota have and will continue to decrease ecosystem and biosphere functioning.

Wood anatomical traits can underpin tropical forest structural and functional changes across soil water gradients and therefore could improve our mechanistic understanding of how plants adapt to environmental change.We assessed how the variation in the forest maximum height (Hmax), stem diameter, and wood density (WD) is associated with variation in xylem traits (area of fibers and parenchyma, conductive area [CondA, sum of all vessels lumens], vessel lumen area [VLA], vessel density [VD], and vessel wall reinforcement [VWR]) across 42 plots of a Brazilian Atlantic Forest habitat that span strong soil water gradients.We found that in wetter communities, greater height and lower WD were associated with greater parenchyma area (capacitance), and lower fibers, VD, VWR. Contrastingly, in drier communities, lower height was associated with higher fiber area (xylem reinforcement), WD, VD, and VWR, while parenchyma area and vessels are reduced.Tree communities vary from conservative resource-use and structurally dependent hydraulic safety (Fibers) to acquisitive resource-use and capacitance dependent hydraulic safety (parenchyma). Such a fiber-parenchyma trade-off (FPT) underlies the variation in tree height across a soil water gradient. Wood anatomy is fundamental to understanding and predicting the impacts of environmental change on forest structure.

The last decade has seen a proliferation of studies that use plant functional traits to assess how plants respond to climate change. However, it remains unclear whether there is a global set of traits that can predict plants’ ability to cope or even thrive when exposed to varying manifestations of climate change. We conducted a systematic global review which identified 148 studies to assess whether there is a set of common traits across biomes that best predict positive plant responses to multiple climate changes and associated environmental changes. Eight key traits appear to best predict positive plant responses to multiple climate/environmental changes across biomes: lower or higher specific leaf area (SLA), lower or higher plant height, greater water-use efficiency (WUE), greater resprouting ability, lower relative growth rate, greater clonality/bud banks/below-ground storage, higher wood density, and greater rooting depth. Trait attributes associated with positive responses appear relatively consistent within biomes and climate/environmental changes, except for SLA and plant height, where both lower and higher trait attributes are associated with a positive response depending on the biome and climate/environmental change considered. Overall, our findings illustrate important and general trait-climate responses within and between biomes that help us understand which plant phenotypes may cope with or thrive under current and future climate change. publishedVersion

Significance We explore an extended view of the tropical conservatism hypothesis to account for two often-neglected components of climatic stress: drought and the combined effect of seasonal cold and drought—the latter being a common feature of extratropical dry environments. We show that evolutionary diversity of angiosperm assemblages in extratropical dry biomes is even lower than in biomes subject to only one type of climatic stress. We further show that evolutionary diversity in many assemblages from eastern North America is higher or comparable to that of tropical moist forests, suggesting that some extratropical moist biomes have accumulated angiosperm lineages over deep evolutionary timescales with their flora assembled from lineages that represent the entirety of the angiosperm tree of life., The tropical conservatism hypothesis (TCH) posits that the latitudinal gradient in biological diversity arises because most extant clades of animals and plants originated when tropical environments were more widespread and because the colonization of colder and more seasonal temperate environments is limited by the phylogenetically conserved environmental tolerances of these tropical clades. Recent studies have claimed support of the TCH, indicating that temperate plant diversity stems from a few more recently derived lineages that are nested within tropical clades, with the colonization of the temperate zone being associated with key adaptations to survive colder temperatures and regular freezing. Drought, however, is an additional physiological stress that could shape diversity gradients. Here, we evaluate patterns of evolutionary diversity in plant assemblages spanning the full extent of climatic gradients in North and South America. We find that in both hemispheres, extratropical dry biomes house the lowest evolutionary diversity, while tropical moist forests and many temperate mixed forests harbor the highest. Together, our results support a more nuanced view of the TCH, with environments that are radically different from the ancestral niche of angiosperms having limited, phylogenetically clustered diversity relative to environments that show lower levels of deviation from this niche. Thus, we argue that ongoing expansion of arid environments is likely to entail higher loss of evolutionary diversity not just in the wet tropics but in many extratropical moist regions as well.

Tropical forests are some of the most biodiverse ecosystems in the world, yet their functioning is threatened by anthropogenic disturbances and climate change. Global actions to conserve tropical forests could be enhanced by having local knowledge on the forestsʼ functional diversity and functional redundancy as proxies for their capacity to respond to global environmental change. Here we create estimates of plant functional diversity and redundancy across the tropics by combining a dataset of 16 morphological, chemical and photosynthetic plant traits sampled from 2,461 individual trees from 74 sites distributed across four continents together with local climate data for the past half century. Our findings suggest a strong link between climate and functional diversity and redundancy with the three trait groups responding similarly across the tropics and climate gradient. We show that drier tropical forests are overall less functionally diverse than wetter forests and that functional redundancy declines with increasing soil water and vapour pressure deficits. Areas with high functional diversity and high functional redundancy tend to better maintain ecosystem functioning, such as aboveground biomass, after extreme weather events. Our predictions suggest that the lower functional diversity and lower functional redundancy of drier tropical forests, in comparison with wetter forests, may leave them more at risk of shifting towards alternative states in face of further declines in water availability across tropical regions.

Datos disponibles en https://github.com/fmsabatini/sPlotOpen_Code, EU H2020 project BACI, Grant No. 640176 (...), Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E.A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Alvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., de Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El-Sheikh, M.A.E.-R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán-de-Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J.-A., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Peñuelas, J., Pérez-Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas-Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J.-C., Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez-Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., von Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H.-F., Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H.

Tropical forests are important to the regulation of climate and the maintenance of biodiversity on Earth. However, these ecosystems are threatened by climate change, as temperatures rise and droughts' frequency and duration increase. Xylem anatomical traits are an essential component in understanding and predicting forest responses to changes in water availability. We calculated the community-weighted means and variances of xylem anatomical traits of hydraulic and structural importance (plot-level trait values weighted by species abundance) to assess their linkages to local adaptation and community assembly in response to varying soil water conditions in an environmentally diverse Brazilian Atlantic Forest habitat. Scaling approaches revealed community-level tradeoffs in xylem traits not observed at the species level. Towards drier sites, xylem structural reinforcement and integration balanced against hydraulic efficiency and capacitance xylem traits, leading to changes in plant community diversity. We show how general community assembly rules are reflected in persistent fiber-parenchyma and xylem hydraulic tradeoffs. Trait variation across a moisture gradient is larger between species than within species and is realized mainly through changes in species composition and abundance, suggesting habitat specialization. Modeling efforts to predict tropical forest diversity and drought sensitivity may benefit from adding hydraulic architecture traits into the analysis.

While the impact of biodiversity, notably functional diversity, on ecosystem productivity has been extensively studied, little is known about the effect of individual species. Here, we identified species of high importance for productivity (key species) in over 28,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness, and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance than all statistics of functional composition. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of all non-environmental predictors increased considerably, and the relationships between functional composition and productivity varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a better consideration of species’ individual effects on ecosystem functioning in complement to community-level measures.

The severe deforestation of Brazil’s Atlantic Forest and the increasing effects of climate change underscore the need to understand how tree species respond to climate and edaphic factors. To identify the most important environmental drivers of coastal Atlantic Forest diversity and functional composition, we studied 42 plots of coastal Atlantic Forest (restinga), which has a high diversity of plant communities and spans strong environmental gradients. We examined how forest physiognomy and functional composition respond to changes in the environment, hydraulic, and soil properties. We tested different hypotheses relating the roles of nutrients and soil water availability in driving shifts in tropical forest diversity and functioning. We collected wood samples and leaves from ˜85% of the plant species identified in the forest inventory and estimated the community‐weighted tree height, aboveground biomass, basal area of individual plants, specific leaf area, wood density, and the total tree biomass per community by the sum of all trees’ aboveground biomass per plot. We measured water table depth and 24 physicochemical soil parameters. Hypotheses relating to these factors were formalized via both generalized additive models and piecewise structural equation models and null models of community assembly. Increasing drought, as reflected by increasing water table depth, coarse sand, and soil concentration of aluminum (>6 cmol/kg), was found to be a primary driver of shifts in all measured functional traits. Water table depth was found to be the main environmental driver of restinga species diversity, but shifts in species richness were largely decoupled from functional richness and functional dispersion. Our results suggest that decreases in soil water availability are a central driver of local phenotype–environment matching and that increasing water limitation increases the role of environmental filtering on multiple traits. Our results show that drought leads to a strong convergence (standardized effect size < −1.95) in forest function and leads to shifts to smaller statured forest in particular. These findings reveal important differences in the drivers of forest structure and functioning, suggesting that changes in local spatial variation in soil and moisture variables will be a central issue in restinga management and conservation.

AIM: The geographic range and ecological niche of species are widely used concepts in ecology, evolution and conservation and many modelling approaches have been developed to quantify each. Niche and distribution modelling methods require a litany of design choices; differences among subdisciplines have created communication barriers that increase isolation of scientific advances. As a result, understanding and reproducing the work of others is difficult, if not impossible. It is often challenging to evaluate whether a model has been built appropriately for its intended application or subsequent reuse. Here, we propose a standardized model metadata framework that enables researchers to understand and evaluate modelling decisions while making models fully citable and reproducible. Such reproducibility is critical for both scientific and policy reports, while international standardization enables better comparison between different scenarios and research groups. INNOVATION: Range modelling metadata (RMMS) address three challenges: they (a) are designed for convenience to encourage use, (b) accommodate a wide variety of applications, and (c) are extensible to allow the research community to steer them as needed. RMMS are based on a metadata dictionary that specifies a hierarchical structure to catalogue different aspects of the range modelling process. The dictionary balances a constrained, minimalist vocabulary to improve standardization with flexibility for users to modify and extend. To facilitate use, we have developed an R package, rangeModelMetaData, to build templates, automatically fill values from common modelling objects, check for inconsistencies with standards, and suggest values. MAIN CONCLUSIONS: Range Modelling Metadata tools foster cross‐disciplinary advances in biogeography, conservation and allied disciplines by improving evaluation, model sharing, model searching, comparisons and reproducibility among studies. Our initially proposed standards here are designed to be modified and extended to evolve with research trends and needs.

Trait-based ecology claims to offer a mechanistic approach for explaining the drivers that structure biological diversity and predicting the responses of species, trophic interactions and ecosystems to environmental change. However, support for this claim is lacking across broad taxonomic groups. A framework for defining ecosystem processes in terms of the functional traits of their constituent taxa across large spatial scales is needed. Here, we provide a comprehensive assessment of the linkages between climate, plant traits and soil microbial traits at many sites spanning a broad latitudinal temperature gradient from tropical to subalpine forests. Our results show that temperature drives coordinated shifts in most plant and soil bacterial traits but these relationships are not observed for most fungal traits. Shifts in plant traits are mechanistically associated with soil bacterial functional traits related to carbon (C), nitrogen (N) and phosphorus (P) cycling, indicating that microbial processes are tightly linked to variation in plant traits that influence rates of ecosystem decomposition and nutrient cycling. Our results are consistent with hypotheses that diversity gradients reflect shifts in phenotypic optima signifying local temperature adaptation mediated by soil nutrient availability and metabolism. They underscore the importance of temperature in structuring the functional diversity of plants and soil microbes in forest ecosystems and how this is coupled to biogeochemical processes via functional traits.

Aims Plant height is a key functional trait related to aboveground biomass, leaf photosynthesis and plant fitness. However, large-scale geographical patterns in community-average plant height (CAPH) of woody species and drivers of these patterns across different life forms remain hotly debated. Moreover, whether CAPH could be used as a predictor of ecosystem primary productivity is unknown. Methods We compiled mature height and distributions of 11 422 woody species in eastern Eurasia, and estimated geographic patterns in CAPH for different taxonomic groups and life forms. Then we evaluated the effects of environmental (including current climate and historical climate change since the Last Glacial Maximum (LGM)) and evolutionary factors on CAPH. Lastly, we compared the predictive power of CAPH on primary productivity with that of LiDAR-derived canopy-height data from a global survey. Important Findings Geographic patterns of CAPH and their drivers differed among taxonomic groups and life forms. The strongest predictor for CAPH of all woody species combined, angiosperms, all dicots and deciduous dicots was actual evapotranspiration, while temperature was the strongest predictor for CAPH of monocots and tree, shrub and evergreen dicots, and water availability for gymnosperms. Historical climate change since the LGM had only weak effects on CAPH. No phylogenetic signal was detected in family-wise average height, which was also unrelated to the tested environmental factors. Finally, we found a strong correlation between CAPH and ecosystem primary productivity. Primary productivity showed a weaker relationship with CAPH of the tallest species within a grid cell and no relationship with LiDAR-derived canopy height reported in the global survey. Our findings suggest that current climate rather than historical climate change and evolutionary history determine the geographical patterns in CAPH. However, the relative effects of climatic factors representing environmental energy and water availability on spatial variations of CAPH vary among plant life forms. Moreover, our results also suggest that CAPH can be used as a good predictor of ecosystem primary productivity.

Latitudinal and elevational richness gradients have received much attention from ecologists but there is little consensus on underlying causes. One possible proximate cause is increased levels of species turnover, or β diversity, in the tropics compared to temperate regions. Here, we leverage a large botanical dataset to map taxonomic and phylogenetic β diversity, as mean turnover between neighboring 100 × 100 km cells, across the Americas and determine key climatic drivers. We find taxonomic and tip-weighted phylogenetic β diversity is higher in the tropics, but that basal-weighted phylogenetic β diversity is highest in temperate regions. Supporting Janzen's ‘mountain passes’ hypothesis, tropical mountainous regions had higher β diversity than temperate regions for taxonomic and tip-weighted metrics. The strongest climatic predictors of turnover were average temperature and temperature seasonality. Taken together, these results suggest β diversity is coupled to latitudinal richness gradients and that temperature is a major driver of plant community composition and change.

Linking drought to the timing of physiological processes governing tree growth remains one limitation in forecasting climate change effects on tropical trees. Using dendrometers, we measured fine-scale growth for 96 trees of 25 species from 2013 to 2016 in an everwet forest in Puerto Rico. Rainfall over this time span varied, including an unusual, severe El Niño drought in 2015. We assessed how growing season onset, median day, conclusion, and length varied with absolute growth rate and tree size over time. Stem growth was seasonal, beginning in February, peaking in July, and ending in November. Species growth rates varied between 0 and 8 mm/year and correlated weakly with specific leaf area, leaf phosphorus, and leaf nitrogen, and to a lesser degree with wood specific gravity and plant height. Drought and tree growth were decoupled, and drought lengthened and increased variation in growing season length. During the 2015 drought, many trees terminated growth early but did not necessarily grow less. In the year following drought, trees grew more over a shorter growing season, with many smaller trees showing a post-drought increase in growth. We attribute the increased growth of smaller trees to release from light limitation as the canopy thinned because of the drought, and less inferred hydraulic stress than larger trees during drought. Soil type accounted for interannual and interspecific differences, with the finest Zarzal clays reducing tree growth. We conclude that drought affects the phenological timing of tree growth and favors the post-drought growth of smaller, sub-canopy trees in this everwet forest.

Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait–climate relationships that differ dramatically—27% of significant results change in sign and 71% disagree on sign, significance, or both—from traditional species-weighted methods. We find that ( i ) functional diversity generally declines with increasing latitude and elevation, ( ii ) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and ( iii ) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.

Estimating the distribution of phenotypes in populations and communities is central to many questions in ecology and evolutionary biology. These distributions can be characterized by their moments: the mean, variance, skewness, and kurtosis. Typically, these moments are calculated using a community-weighted approach (e.g. community-weighted mean) which ignores intraspecific variation. As an alternative, bootstrapping approaches can incorporate intraspecific variation to improve estimates, and also quantify uncertainty in the estimate. Here, we compare the performance of different approaches for estimating the moments of trait distributions across a variety of sampling scenarios, taxa, and datasets. We introduce the traitstrap R package to facilitate inferences of trait distributions via bootstrapping. Our results suggest that randomly sampling ~9 individuals per sampling unit and species, focusing on covering all species in the community, and analysing the data using nonparametric bootstrapping generally enables reliable inference on trait distributions, including the central moments, of communities.

Competing phylogenetic models have been proposed to explain the success of species introduced to other communities. Here, we present a study predicting the establishment success of birds introduced to Florida, Hawaii, and New Zealand using several alternative models, considering species’ phylogenetic relatedness to source and recipient range taxa, propagule pressure, and traits. We find consistent support for the predictive ability of source region phylogenetic structure. However, we find that the effects of recipient region phylogenetic structure vary in sign and magnitude depending on inclusion of source region phylogenetic structure, delineation of the recipient species pool, and the use of phylogenetic correction in the models. We argue that tests of alternative phylogenetic hypotheses including the both source and recipient community phylogenetic structure, as well as important covariates such as propagule pressure, are likely to be critical for identifying general phylogenetic patterns in introduction success, predicting future invasions, and for stimulating further exploration of the underlying mechanisms of invasibility.

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature’s contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

Summary Remote sensing capabilities have revolutionized several fields including geology and vegetation ecology. With these new capabilities to observe important interactions between subsurface hydrobiogeochemical properties and surface biological response, there is vast potential to rigorously test theories of ecosystem function and evolution. For example, the functional trait distributions of plants can be quantified at increasingly broader scales allowing ecological theories to be tested across plots to watersheds and beyond. Geophysical methods now allow us to interrogate how regolith properties vary across the same scales and provide an insight into the factors regulating plant species composition and functional trait distributions. Given the fundamental constraints of water, energy and nutrients are shared across biology, and that plants and microorganisms share a long history of coevolution, it is likely that microbial functional traits distributions follow similarly interpretable and predictable patterns at ecosystem scales. In this presentation I will cover our work combining theory, observation and modeling to advance how microbial traits are deciphered from genomic information, as well as approaches to ground truth these hypotheses. I will also discuss how we combine various sensing approaches, including vegetation, geophysical, and microbial to evaluate patterns of co-evolution across a watershed with consequences for ecosystem hydrobiogeochemistry.

Tropical forest ecosystems are undergoing rapid transformation as a result of changing environmental conditions and direct human impacts. However, we cannot adequately understand, monitor or simulate tropical ecosystem responses to environmental changes without capturing the high diversity of plant functional characteristics in the species-rich tropics. Failure to do so can oversimplify our understanding of ecosystems responses to environmental disturbances. Innovative methods and data products are needed to track changes in functional trait composition in tropical forest ecosystems through time and space. This study aimed to track key functional traits by coupling Sentinel-2 derived variables with a unique data set of precisely located in-situ measurements of canopy functional traits collected from 2434 individual trees across the tropics using a standardised methodology. The functional traits and vegetation censuses were collected from 47 field plots in the countries of Australia, Brazil, Peru, Gabon, Ghana, and Malaysia, which span the four tropical continents. The spatial positions of individual trees above 10 cm diameter at breast height (DBH) were mapped and their canopy size and shape recorded. Using geo-located tree canopy size and shape data, community-level trait values were estimated at the same spatial resolution as Sentinel-2 imagery (i.e. 10 m pixels). We then used the Geographic Random Forest (GRF) to model and predict functional traits across our plots. We demonstrate that key plant functional traits can be accurately predicted across the tropicsusing the high spatial and spectral resolution of Sentinel-2 imagery in conjunction with climatic and soil information. Image textural parameters were found to be key components of remote sensing information for predicting functional traits across tropical forests and woody savannas. Leaf thickness (R2 = 0.52) obtained the highest prediction accuracy among the morphological and structural traits and leaf carbon content (R2 = 0.70) and maximum rates of photosynthesis (R2 = 0.67) obtained the highest prediction accuracy for leaf chemistry and photosynthesis related traits, respectively. Overall, the highest prediction accuracy was obtained for leaf chemistry and photosynthetic traits in comparison to morphological and structural traits. Our approach offers new opportunities for mapping, monitoring and understanding biodiversity and ecosystem change in the most species-rich ecosystems on Earth.

Forests are integral to global carbon cycling but are threatened by anthropogenic degradation and climate change. Assessing this global threat has been hindered by a lack of clear, flexible, and easy-to-use productivity models along with a lack of functional trait and productivity data for parameterizing and testing those models. Current productivity models are either extremely complex requiring up to hundreds of parameters, many sub-models, and considerable computational expense or rely on statistical trait-growth relationships that can be hard to extrapolate to new systems or climates. Here we provide a simple alternative: a remote sensing canopy functional model (RS-CFM) that uses remotely-sensed foliar traits and canopy structure data to efficiently map productivity at high-resolution and large spatial scales. We test this model by quantifying net primary productivity (NPP) at 0.01-ha resolution in 30,040 hectares of Peruvian tropical rainforest along a 3,322-m Amazon-to-Andes elevation gradient. Our model predicts local NPP and elevational shifts in NPP much more accurately and in greater detail than a prominent alternative method—NASA’s MODIS NPP product. Furthermore, we show how NPP estimates depend on light competition and identify the appropriate spatial resolution for remote productivity estimation. Our framework opens up possibilities to fully harness remote sensing data and reliably scale up from traits to map regional or global productivity in a more direct, efficient, and cost-effective manner.

The sizes and shapes of tree crowns are of fundamental importance in ecology, yet understanding the forces that determine them remains elusive. A cardinal question facing ecologists is the degree to which general and non-specific versus ecological and context-dependent processes are responsible for shaping tree crowns. Here, we test this question for the first time across diverse tropical ecosystems. Using trees from 20 plots varying in elevation, precipitation, and ecosystem type (savanna-forest transitions) across the paleo- and neo-tropics, we test the relationship between crown dimensions and tree size. By analyzing these scaling relationships across environmental gradients, biogeographic regions, and phylogenetic distance, we extend Metabolic Scaling Theory (MST) predictions to include how local selective pressures shape variation in crown dimensions. Across all sites, we find strong agreement between mean trends and MST predictions for the scaling of crown size and shape, but large variation around the mean. While MST explained approximately half of the observed variation in tree crown dimensions, we find that local, ecosystem, and phylogenetic predictors account for the half of the residual variation. Crown scaling does not change significantly across regions, but does change across ecosystem types, where savanna tree crowns grow more quickly with tree girth than forest tree crowns. Crowns of legumes were wider and more voluminous than those of other taxa. Thus, while MST can accurately describe the central tendency of tree crown size, local ecological conditions and evolutionary history appear to modify the scaling of crown shape. Importantly, our extension of MST incorporating these differences accounts for the mechanisms driving variation in the scaling of crown dimensions across the tropics. We present allometric equations for the prediction of crown dimensions across tropical ecosystems. These results are critical when scaling the function of individual trees to larger spatial scales or incorporating the size and shape of tree crowns in global biogeochemical models.

Synthesis has become ubiquitous in ecology. Despite its widespread application to a broad range of research topics, it remains unclear how synthesis has affected the discipline. Using a case study of publications (n = 2304) from the National Center for Ecological Analysis and Synthesis compared with papers with similar keywords from the Web of Science (n = 320,000), we address several questions about the comparative impact of synthesis, the role of synthesis in driving key research themes, and whether synthesis is focused on different topics than is the broader ecological literature. We found much higher citation rates for synthesis papers overall (fivefold more) and within eleven key topic themes (e.g., species richness, biodiversity, climate change, global change). Synthesis papers often played key roles in driving, redirecting, or resolving core questions and exhibited much greater cross-theme connectivity. Together, these results indicate that synthesis in science has played a crucial role in accelerating and advancing ecological knowledge.

Limiting climate change to less than 2°C is the focus of international policy under the climate convention (UNFCCC), and is essential to preventing extinctions, a focus of the Convention on Biological Diversity (CBD). The post-2020 biodiversity framework drafted by the CBD proposes conserving 30% of both land and oceans by 2030. However, the combined impact on extinction risk of species from limiting climate change and increasing the extent of protected and conserved areas has not been assessed. Here we create conservation spatial plans to minimize extinction risk in the tropics using data on 289 219 species and modeling two future greenhouse gas concentration pathways (RCP2.6 and 8.5) while varying the extent of terrestrial protected land and conserved areas from

The competition for light has long been regarded as a key axis of niche partitioning that promotes forest diversity, but available evidence is contradictory. Despite strong tradeoffs between growth and survival with light, field tests suggest neutral forces govern tree composition across forest gaps and resource use across size classes. Here we integrate scaling and niche theory, and use data from >114,000 woody plants in a tropical, old growth forest to test and predict patterns of niche partitioning with size and light. Consistent with predictions, the relative abundance, production, light capture, and richness of species in life histories with fast growth follow a power law relationship, increasing 1–2 orders of magnitude along a solar and size gradient. Competitive neutrality between size classes emerges above the sapling layer, where increasing access to light is counterbalanced by stronger self-shading. Convergent power law patterns of resource partitioning across taxa and spatial scale suggest general life history tradeoffs drive the organization of diverse communities.

Trees are of vital importance for ecosystem functioning and services at local to global scales, yet we still lack a detailed overview of the global patterns of tree diversity and the underlying drivers, particularly the imprint of paleoclimate. Here, we present the high-resolution (110 km) worldwide mapping of tree species richness, functional and phylogenetic diversities based on ∼7 million quality-assessed occurrences for 46,752 tree species (80.5% of the estimated total number of tree species), and subsequent assessments of the influence of paleo-climate legacies on these patterns. All three tree diversity dimensions exhibited the expected latitudinal decline. Contemporary climate emerged as the strongest driver of all diversity patterns, with Pleistocene and deeper-time (>107 years) paleoclimate as important co-determinants, and, notably, with past cold and drought stress being linked to reduced current diversity. These findings demonstrate that tree diversity is affected by paleoclimate millions of years back in time and highlight the potential for tree diversity losses from future climate change.

Although trees are key to ecosystem functioning, many forests and tree species across the globe face strong threats. Preserving areas of high biodiversity is a core priority for conservation; however, different dimensions of biodiversity and varied conservation targets make it difficult to respond effectively to this challenge. Here, we (i) identify priority areas for global tree conservation using comprehensive coverage of tree diversity based on taxonomy, phylogeny, and functional traits; and (ii) compare these findings to existing protected areas and global biodiversity conservation frameworks. We find that ca. 51% of the top-priority areas for tree biodiversity are located in current protected areas. The remaining half top-priority areas are subject to moderate to high human pressures, indicating conservation actions are needed to mitigate these human impacts. Our findings emphasize the effectiveness of using tree conservation priority areas for future global conservation planning.

Deconstructing functional trait variation and co-variation across a wide range of environmental conditions is necessary to increase the mechanistic understanding of community assembly processes and improve current parameterization of dynamic vegetation models. Here, we present a study that deconstructs leaf trait variation and co-variation into within-species, taxonomic-, and plot-environment components along three tropical environmental gradients in Peru, Brazil, and Ghana. To do so, we measured photosynthetic, chemical, and structural leaf traits using a standardized sampling protocol for more than 1,000 individuals belonging to 367 species. Variation associated with the taxonomic component (species + genus + family) for most traits was relatively consistent across environmental gradients, but within-species variation and plot-environment variation was strongly dependent on the environmental gradient. Trait-trait co-variation was strongly linked to the environmental gradient where traits were measured, although some traits had consistent co-variation components irrespective of gradient. Our results demonstrate that filtering along these tropical gradients is mostly expressed through trait taxonomic variation, but that trait co-variation is strongly dependent on the local environment, and thus global trait co-variation relationships might not always apply at smaller scales and may quickly change under future climate scenarios. Fil: Oliveras, Imma. University of Oxford; Reino Unido Fil: Bentley, Lisa. Sonoma State University; Estados Unidos Fil: Fyllas, Nikolaos M.. University Of The Aegean; Grecia Fil: Gvozdevaite, Agne. University of Oxford; Reino Unido Fil: Shenkin, Alexander Frederick. University of Oxford; Reino Unido Fil: Peprah, Theresa. Forestry Research Institute Of Ghana; Ghana Fil: Morandi, Paulo. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Peixoto, Karine Silva. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Boakye, Mickey. Forestry Research Institute Of Ghana; Ghana Fil: Adu-Bredu, Stephen. Csir - Forestry Research Institute Of Ghana; Ghana Fil: Schwantes Marimon, Beatriz. Universidade Do Estado de Mato Grosso; Brasil Fil: Marimon Junior, Ben Hur. Universidade Do Estado de Mato Grosso; Brasil Fil: Salinas, Norma. Pontificia Universidad Católica de Perú; Perú Fil: Martin, Roberta. Arizona State University; Estados Unidos Fil: Asner, Gregory. Arizona State University; Estados Unidos Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enquist, Brian J.. University of Arizona; Estados Unidos Fil: Malhi, Yadvinder. University of Oxford; Reino Unido

Despite the many studies using trait-based approaches to assess the impact of environmental gradients in forest trait composition, the relative roles of (i) intraspecific variation in community assembly and (ii) microclimatic or fine scale abiotic variation in shaping local trait diversity remain poorly understood. To advance their understanding we tested several assumptions and predictions of trait driver theory (TDT). We quantified the shape of trait distributions related to tree carbon, nutrient economics and stem hydraulics across a small-scale but steep gradient of soil water availability. We utilized a unique and steep environmental gradient in the coastal Brazilian Atlantic forest (restinga) communities that spans a very short distance (207 +/-60 meters). We collected leaf and wood samples of tree species across 42 patches (or plots) of restinga forest. Furthermore, to detect if species directionally shift in niche space, we analyzed species composition in multidimensional hypervolume space. Despite short geographic distances, we observed large shifts in species replacement and intraspecific variation reflected by a directional shift in plant function. Consistent with TDT, we observe (i) trait distributions that are skewed in directions consistent with a forest responding to recent hotter and drier; (ii) peaked trait distributions, indicating strong functional convergence; and (iii) conditions decreasing means and variances of several leaf carbon and nutrient economic traits as well as stem hydraulic traits. Synthesis: Observed species replacements along the water table gradient and interspecific measures of functional diversity (community kurtosis and skewness) are consistent with strong phenotype/environmental matching of plant carbon, nutrient, and hydraulic strategies. We observe environmental filtering in both extremities of the gradient, selecting for acquisitive (wet) to conservative (dry) setup of traits. Similarly, species that span the entire water availability gradient are characterized by directional intraspecific shifts in multi-trait space that mirror interspecific shifts. Strong environmental gradients across short spatial scales provide unique systems to accurately assess assembly processes and address long-held assumptions and timely hypothesis predicted by trait driver theory.

A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size‒primary productivity functions based on the Chinese dataset can predict productivity in North America and vice‐versa. In addition to advancing understanding of the relationship between a climate‐driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo‐primary productivity of woody ecosystems., Based on leaf size and distribution data for 10 480 woody dicots in China and 2374 in North America, we found that leaf size of woody dicots well predicts ecosystem primary productivity both in China and North America, and its independent and direct effects on primary productivity is higher than (or in a few cases comparable to) those of climate, soil characteristics and leaf area index. Our results suggest that leaf size provides a promising surrogate to reconstruct palaeo‐primary productivity of terrestrial woody ecosystems based on fossil leaf deposits.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Summary paragraphTo meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and nature’s contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

[Aim] Intraspecific trait variation (ITV) within natural plant communities can be large, influencing local ecological processes and dynamics. Here, we shed light on how ITV in vegetative and floral traits responds to large‐scale abiotic and biotic gradients (i.e., climate and species richness). Specifically, we tested whether associations of ITV with temperature, precipitation and species richness were consistent with any of four hypotheses relating to stress tolerance and competition. Furthermore, we estimated the degree of correlation between ITV in vegetative and floral traits and how they vary along the gradients., [Location] Global., [Time period] 1975–2016., [Major taxa studied] Herbaceous and woody plants., [Methods] We compiled a dataset of 18,401 measurements of the absolute extent of ITV (measured as the coefficient of variation) in nine vegetative and seven floral traits from 2,822 herbaceous and woody species at 2,372 locations., [Results] Large‐scale associations between ITV and climate were trait specific and more prominent for vegetative traits, especially leaf morphology, than for floral traits. The ITV showed pronounced associations with climate, with lower ITV values in colder areas and higher values in drier areas. The associations of ITV with species richness were inconsistent across traits. Species‐specific associations across gradients were often idiosyncratic, and covariation in ITV was weaker between vegetative and floral traits than within the two trait groups. [Main conclusions] Our results show that, depending on the traits considered, ITV either increased or decreased with climate stress and species richness, suggesting that both factors can constrain or enhance ITV, which might foster plant‐population persistence in stressful conditions. Given the species‐specific responses and covariation in ITV, associations can be hard to predict for traits and species not yet studied. We conclude that consideration of ITV can improve our understanding of how plants cope with stressful conditions and environmental change across spatial and biological scales., Open Access funding was provided by Ulm University under the DEAL‐agreement.

Tropical forest leaf albedo (reflectance) greatly impacts how much energy the planet absorbs; however; little is known about how it might be impacted by climate change. Here, we measure leaf traits and leaf albedo at ten 1-ha plots along a 3,200-m elevation gradient in Peru. Leaf mass per area (LMA) decreased with warmer temperatures along the elevation gradient; the distribution of LMA was positively skewed at all sites indicating a shift in LMA towards a warmer climate and future reduced tropical LMA. Reduced LMA was significantly (P

Remote sensing of trait-based ecology can improve our understanding of the effect of trait diversity on ecosystem functioning., Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotely sensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivity could be predicted by remotely sensed functional diversity. Functional richness of the community decreased with increasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play an important role in explaining the range of trait variation within each site and along elevation. Single- and multitrait remotely sensed measures of functional diversity were important predictors of variation in rates of net and gross primary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.

Providing science and society with an integrated, up-to-date, high quality, open, reproducible and sustainable plant tree of life would be a huge service that is now coming within reach. However, synthesizing the growing body of DNA sequence data in the public domain and disseminating the trees to a diverse audience are often not straightforward due to numerous informatics barriers. While big synthetic plant phylogenies are being built, they remain static and become quickly outdated as new data are published and tree-building methods improve. Moreover, the body of existing phylogenetic evidence is hard to navigate and access for non-experts. We propose that our community of botanists, tree builders, and informaticians should converge on a modular framework for data integration and phylogenetic analysis, allowing easy collaboration, updating, data sourcing and flexible analyses. With support from major institutions, this pipeline should be re-run at regular intervals, storing trees and their metadata long-term. Providing the trees to a diverse global audience through user-friendly front ends and application development interfaces should also be a priority. Interactive interfaces could be used to solicit user feedback and thus improve data quality and to coordinate the generation of new data. We conclude by outlining a number of steps that we suggest the scientific community should take to achieve global phylogenetic synthesis.

Author(s): Weiser, MD; Swenson, NG; Enquist, BJ; Michaletz, S; Waide, RB; Zhou, J; Kaspari, M | Abstract: Aim: To test the latitudinal gradient in plant species diversity for self-similarity across taxonomic scales and amongst taxa. Location: North America. Methods: We used species richness data from 245 local vascular plant floras to quantify the slope and shape of the latitudinal gradients in species diversity (LGSD) across all plant species as well as within each family and order. We calculated the contribution of each family and order to the empirical LGSD. Results: We observed the canonical LGSD when all plants were considered with floras at the lowest latitudes having, on average, 451 more species than floras at the highest latitudes. When considering slope alone, most orders and families showed the expected negative slope, but 31.7% of families and 27.7% of orders showed either no significant relationship between latitude and diversity or a reverse LGSD. Latitudinal patterns of family diversity account for at least 14% of this LGSD. Most orders and families did not show the negative slope and concave-down quadratic shape expected by the pattern for all plant species. A majority of families did not make a significant contribution in species to the LGSD with 53% of plant families contributing little to nothing to the overall gradient. Ten families accounted for more than 70% of the gradient. Two families, the Asteraceae and Fabaceae, contributed a third of the LGSD. Main Conclusions: The empirical LGSD we describe here is a consequence of a gradient in the number of families and diversification within relative few plant families. Macroecological studies typically aim to generate models that are general across taxa with the implicit assumption that the models are general within taxa. Our results strongly suggest that models of the latitudinal gradient in plant species richness that rely on environmental covariates (e.g. temperature, energy) are likely not general across plant taxa.

Aim: Tropical forests account for a quarter of the global carbon storage and a third of the terrestrial productivity. Few studies have teased apart the relative importance of environmental factors and forest attributes for ecosystem functioning, especially for the tropics. This study aims to relate aboveground biomass (AGB) and biomass dynamics (i.e., net biomass productivity and its underlying demographic drivers: biomass recruitment, growth and mortality) to forest attributes (tree diversity, community-mean traits and stand basal area) and environmental conditions (water availability, soil fertility and disturbance). Location: Neotropics. Methods: We used data from 26 sites, 201 1-ha plots and >92,000 trees distributed across the Neotropics. We quantified for each site water availability and soil total exchangeable bases and for each plot three key community-weighted mean functional traits that are important for biomass stocks and productivity. We used structural equation models to test the hypothesis that all drivers have independent, positive effects on biomass stocks and dynamics. Results: Of the relationships analysed, vegetation attributes were more frequently associated significantly with biomass stocks and dynamics than environmental conditions (in 67 vs. 33% of the relationships). High climatic water availability increased biomass growth and stocks, light disturbance increased biomass growth, and soil bases had no effect. Rarefied tree species richness had consistent positive relationships with biomass stocks and dynamics, probably because of niche complementarity, but was not related to net biomass productivity. Community-mean traits were good predictors of biomass stocks and dynamics. Main conclusions: Water availability has a strong positive effect on biomass stocks and growth, and a future predicted increase in (atmospheric) drought might, therefore, potentially reduce carbon storage. Forest attributes, including species diversity and community-weighted mean traits, have independent and important relationships with AGB stocks, dynamics and ecosystem functioning, not only in relatively simple temperate systems, but also in structurally complex hyper-diverse tropical forests.

UK Natural Environment Research Council [NE/J023418/1, NE/M019160/1]; European Research Council [321131, 291585]; John D. and Catherine T. MacArthur Foundation; U.S. National Science Foundation [DEB - 1209287]; Carnegie Institution for Science; National Science Foundation [DEB - 1146206]; Leverhulme Trust, UK; Jackson Foundation; European Community [290605]; John Fell Fund; Google Earth Engine award