Search

Abstract Biologists increasingly rely on computer code to collect and analyze their data, reinforcing the importance of published code for transparency, reproducibility, training, and a basis for further work. Here, we conduct a literature review estimating temporal trends in code sharing in ecology and evolution publications since 2010, and test for an influence of code sharing on citation rate. We find that code is rarely published (only 6% of papers), with little improvement over time. We also found there may be incentives to publish code: Publications that share code have tended to be low‐impact initially, but accumulate citations faster, compensating for this deficit. Studies that additionally meet other Open Science criteria, open‐access publication, or data sharing, have still higher citation rates, with publications meeting all three criteria (code sharing, data sharing, and open access publication) tending to have the most citations and highest rate of citation accumulation.

Abstract Alpine grassland vegetation supports globally important biodiversity and ecosystems that are increasingly threatened by climate warming and other environmental changes. Trait-based approaches can support understanding of vegetation responses to global change drivers and consequences for ecosystem functioning. In six sites along a 1314 m elevational gradient in Puna grasslands in the Peruvian Andes, we collected datasets on vascular plant composition, plant functional traits, biomass, ecosystem fluxes, and climate data over three years. The data were collected in the wet and dry season and from plots with different fire histories. We selected traits associated with plant resource use, growth, and life history strategies (leaf area, leaf dry/wet mass, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N, P content, C and N isotopes). The trait dataset contains 3,665 plant records from 145 taxa, 54,036 trait measurements (increasing the trait data coverage of the regional flora by 420%) covering 14 traits and 121 plant taxa (ca. 40% of which have no previous publicly available trait data) across 33 families.

Abstract Trees are pivotal to global biodiversity and nature’s contributions to people, yet accelerating global changes threaten global tree diversity, making accurate species extinction risk assessments necessary. To identify species that require expert-based re-evaluation, we assess exposure to change in six anthropogenic threats over the last two decades for 32,090 tree species. We estimated that over half (54.2%) of the assessed species have been exposed to increasing threats. Only 8.7% of these species are considered threatened by the IUCN Red List, whereas they include more than half of the Data Deficient species (57.8%). These findings suggest a substantial underestimation of threats and associated extinction risk for tree species in current assessments. We also map hotspots of tree species exposed to rapidly changing threats around the world. Our data-driven approach can strengthen the efforts going into expert-based IUCN Red List assessments by facilitating prioritization among species for re-evaluation, allowing for more efficient conservation efforts.

Societal Impact Statement Plants are fundamental to terrestrial and aquatic ecosystems and are key to human livelihoods. To protect plant diversity, systematic approaches to conservation assessment are needed. Many nations have legislation or other policy instruments that seek to protect biodiversity (including plants), and species‐level assessments are essential for identifying the most threatened species that require special and immediate protection measures. Some plants occur in only one place (for instance, a single country) and here we have estimated how many of these ‘endemic’ species have had their threats assessed in each country or close country‐equivalent worldwide. We show that the level of assessment completion is only weakly related to the income of countries or the likely level of threat that species face. Summary The Global Strategy for Plant Conservation ambitiously called for an assessment of the conservation status of all recognised plant taxa by 2020. This target was not met in the short term. Nevertheless, the need for conservation assessments remains urgent as plants go extinct and face increasing threats from human impacts on the biosphere. Here, the completeness of threat assessments for endemic flora in 179 countries or their close equivalents was assessed. To do so, distribution information from the World Checklist of Vascular Plants was combined with assessments collated in the ThreatSearch database. The completeness of assessments was expected to be associated with the objective affluence of countries (measured using inequality‐adjusted Human Development Index (IHDI)) and/or the exposure of their plant species to threats associated with human impacts (measured using Global Human Modification index (GHM)). The number of endemic species per country was also hypothesised to influence the completion of assessments. Overall, 58% of all country‐based endemic species examined have no conservation assessment (127,643 species). Countries' progress toward the completion of threat assessments for endemic plants could not be confidently predicted by IHDI, GHM or the richness of endemic plant flora. The shortfall in threat assessments identified here restricts national regulation of actions which imperil plant species, with particular consequences for endemic plant species subject to local laws. Some nations with high IHDI scores (i.e. wealthier nations) are not systematically assessing extinction risk in their endemic species. Scarce funding should be directed to global hotspots of endemism with few available resources for assessment.

Abstract Across the globe, tree species are under high anthropogenic pressure. Risks of extinction are notably more severe for species with restricted ranges and distinct evolutionary histories. Here, we use a global dataset covering 41,835 species (65.1% of known tree species) to assess the spatial pattern of tree species’ phylogenetic endemism, its macroecological drivers, and how future pressures may affect the conservation status of the identified hotspots. We found that low-to-mid latitudes host most endemism hotspots, with current climate being the strongest driver, and climatic stability across thousands to millions of years back in time as a major co-determinant. These hotspots are mostly located outside of protected areas and face relatively high land-use change and future climate change pressure. Our study highlights the risk from climate change for tree diversity and the necessity to strengthen conservation and restoration actions in global hotspots of phylogenetic endemism for trees to avoid major future losses of tree diversity.

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill, allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Abstract The Arctic is warming at a rate four times the global average, while also being exposed to other global environmental changes, resulting in widespread vegetation and ecosystem change. Integrating functional trait-based approaches with multi-level vegetation, ecosystem, and landscape data enables a holistic understanding of the drivers and consequences of these changes. In two High Arctic study systems near Longyearbyen, Svalbard, a 20-year ITEX warming experiment and elevational gradients with and without nutrient input from nesting seabirds, we collected data on vegetation composition and structure, plant functional traits, ecosystem fluxes, multispectral remote sensing, and microclimate. The dataset contains 1,962 plant records and 16,160 trait measurements from 34 vascular plant taxa, for 9 of which these are the first published trait data. By integrating these comprehensive data, we bridge knowledge gaps and expand trait data coverage, including on intraspecific trait variation. These data can offer insights into ecosystem functioning and provide baselines to assess climate and environmental change impacts. Such knowledge is crucial for effective conservation and management in these vulnerable regions.

Abstract Traits have become a crucial part of ecological and evolutionary sciences, helping researchers understand the function of an organism's morphology, physiology, growth and life history, with effects on fitness, behaviour, interactions with the environment and ecosystem processes. However, measuring, compiling and analysing trait data comes with data‐scientific challenges. We offer 10 (mostly) simple rules, with some detailed extensions, as a guide in making critical decisions that consider the entire life cycle of trait data. This article is particularly motivated by its last rule, that is, to propagate good practice. It has the intention of bringing awareness of how data on the traits of organisms can be collected and managed for reuse by the research community. Trait observations are relevant to a broad interdisciplinary community of field biologists, synthesis ecologists, evolutionary biologists, computer scientists and database managers. We hope these basic guidelines can be useful as a starter for active communication in disseminating such integrative knowledge and in how to make trait data future‐proof. We invite the scientific community to participate in this effort at http://opentraits.org/best‐practices.html.

Measurement(s) plant trait Technology Type(s) various Factor Type(s) none Sample Characteristic - Organism Tracheophyta Sample Characteristic - Environment natural environment Sample Characteristic - Location global

Understanding scaling relations of social and environmental attributes of urban systems is necessary for effectively managing cities. Urban scaling theory (UST) has assumed that population density scales positively with city size. We present a new global analysis using a publicly available database of 933 cities from 38 countries. Our results showed that (18/38) 47% of countries analyzed supported increasing density scaling (pop ~ area) with exponents ~⅚ as UST predicts. In contrast, 17 of 38 countries (~45%) exhibited density scalings statistically indistinguishable from constant population densities across cities of varying sizes. These results were generally consistent in years spanning four decades from 1975 to 2015. Importantly, density varies by an order of magnitude between regions and countries and decreases in more developed economies. Our results (i) point to how economic and regional differences may affect the scaling of density with city size and (ii) show how understanding country- and region-specific strategies could inform effective management of urban systems for biodiversity, public health, conservation and resiliency from local to global scales.200 word statement of contribution: Urban Scaling Theory (UST) is a general scaling framework that makes quantitative predictions for how many urban attributes spanning physical, biological and social dimensions scale with city size; thus, UST has great implications in guiding future city developments. A major assumption of UST is that larger cities become denser. We evaluated this assumption using a publicly available global dataset of 933 cities in 38 countries. Our scaling analysis of population size and area of cities revealed that while many countries analyzed showed increasing densities with city size, about 45% of countries showed constant densities across cities. These results question a key assumption of UST. Our results suggest policies and management strategies for biodiversity conservation, public health and sustainability of urban systems may need to be tailored to national and regional scaling relations to be effective.

Abstract As Open Science practices become more commonplace, there is a need for the next generation of scientists to be well versed in these aspects of scientific research. Yet, many training opportunities for early career researchers (ECRs) could better emphasize or integrate Open Science elements. Field courses provide opportunities for ECRs to apply theoretical knowledge, practice new methodological approaches, and gain an appreciation for the challenges of real‐life research, and could provide an excellent platform for integrating training in Open Science practices. Our recent experience, as primarily ECRs engaged in a field course interrupted by COVID‐19, led us to reflect on the potential to enhance learning outcomes in field courses by integrating Open Science practices and online learning components. Specifically, we highlight the opportunity for field courses to align teaching activities with the recent developments and trends in how we conduct research, including training in: publishing registered reports, collecting data using standardized methods, adopting high‐quality data documentation, managing data through reproducible workflows, and sharing and publishing data through appropriate channels. We also discuss how field courses can use online tools to optimize time in the field, develop open access resources, and cultivate collaborations. By integrating these elements, we suggest that the next generation of field courses will offer excellent arenas for participants to adopt Open Science practices.

Abstract The COVID‐19 crisis has forced researchers in Ecology to change the way we work almost overnight. Nonetheless, the pandemic has provided us with several novel components for a new way of conducting science. In this perspective piece, we summarize eight central insights that are helping us, as early career researchers, navigate the uncertainties, fears, and challenges of advancing science during the COVID‐19 pandemic. We highlight how innovative, collaborative, and often Open Science‐driven developments that have arisen from this crisis can form a blueprint for a community reinvention in academia. Our insights include personal approaches to managing our new reality, maintaining capacity to focus and resilience in our projects, and a variety of tools that facilitate remote collaboration. We also highlight how, at a community level, we can take advantage of online communication platforms for gaining accessibility to conferences and meetings, and for maintaining research networks and community engagement while promoting a more diverse and inclusive community. Overall, we are confident that these practices can support a more inclusive and kinder scientific culture for the longer term.

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.

Abstract Tropical dry forests (TDFs) have experienced pronounced droughts and increased temperatures for the last century. To assess whether these climatic shifts have influenced dry forest vegetation and ecosystem functioning, we integrated ground observations from a Costa Rican long‐term forest dynamics monitoring plot with remotely sensed measures of forest productivity and canopy functioning from a diverse set of satellite data. Previously reported long‐term climate data (1921–1997) show a reduction in annual rainfall, but since 1980 there has been no directional change in mean annual precipitation. However, the 2015 El Niño Southern Oscillation (ENSO)‐induced drought was unprecedented. Temperatures have increased by 1.1°C since 1931. However, the Landsat wet season (1987–2017) Enhanced Vegetation Index (EVI) (canopy greenness) and the dry season (1985–2017) fraction of non‐photosynthetic canopy cover all indicate that TDFs have become more deciduous but also more productive during the wet season. These changes are consistent with a shift in the functional composition observed in the long‐term plot as more drought‐deciduous tree species have increased in abundance. Nonetheless, more continuous 16‐d MODIS (the Moderate Resolution Imaging Spectroradiometer) measures of the EVI over the past 17 yr (2001–2017) showed no change in the total annual forest productivity. Further, while the 2015 ENSO event temporarily reduced forest EVI, it did not cause a longer‐term impact on forest productivity. Instead, high spatial resolution Worldview‐2 satellite imagery showed that forest phenology shifted in the subsequent years even though the region returned to normal precipitation. Our results indicate that while the species composition of TDFs may be sensitive to the long‐term trend of gradually increasing temperatures and aridity, the annual forest functioning has so far been resilient to long‐term drying and a large episodic extreme drought event. This study demonstrates the feasibility of synthesizing satellite images of different characteristics to study the vegetation dynamics of a long‐term forest dynamics plot. Our synoptically sensed results show that the longer‐term changing climate has been and is currently shifting the ecological functioning, and also provide a baseline to assess the impacts of an extreme drought year on TDFs.

Predictions from species distribution models (SDMs) are commonly used in support of environmental decision-making to explore potential impacts of climate change on biodiversity. However, because future climates are likely to differ from current climates, there has been ongoing interest in understanding the ability of SDMs to predict species responses under novel conditions (i.e., model transferability). Here, we explore the spatial and environmental limits to extrapolation in SDMs using forest inventory data from 11 model algorithms for 108 tree species across the western United States. Algorithms performed well in predicting occurrence for plots that occurred in the same geographic region in which they were fitted. However, a substantial portion of models performed worse than random when predicting for geographic regions in which algorithms were not fitted. Our results suggest that for transfers in geographic space, no specific algorithm was better than another as there were no significant differences in predictive performance across algorithms. There were significant differences in predictive performance for algorithms transferred in environmental space with GAM performing best. However, the predictive performance of GAM declined steeply with increasing extrapolation in environmental space relative to other algorithms. The results of this study suggest that SDMs may be limited in their ability to predict species ranges beyond the environmental data used for model fitting. When predicting climate-driven range shifts, extrapolation may also not reflect important biotic and abiotic drivers of species ranges, and thus further misrepresent the realized shift in range. Future studies investigating transferability of process based SDMs or relationships between geodiversity and biodiversity may hold promise.

Abstract 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.

The U.S. Department of Energy's Watershed Function Scientific Focus Area (SFA), centered in the East River, Colorado, generates diverse datasets including hydrological, geological, geochemical, geophysical, ecological, microbiological and remote sensing data. The project has deployed extensive field infrastructure involving hundreds of sensors that measure highly diverse phenomena (e.g. stream and groundwater hydrology, water quality, soil moisture, weather) across the watershed. Data from the sensor network are telemetered and automatically ingested into a queryable database. The data are subsequently quality checked, integrated with the United States Geological Survey's stream monitoring network using a custom data integration broker, and published to a portal with interactive visualizations. The resulting data products are used in a variety of scientific modeling and analytical efforts. This paper describes the SFA's end-to-end infrastructure and services that support the generation of integrated datasets from a watershed sensor network. The development and maintenance of this infrastructure, presents a suite of challenges from practical field logistics to complex data processing, which are addressed through various solutions. In particular, the SFA adopts a holistic view for data collection, assessment and integration, which dramatically improves the products generated, and enables a co-design approach wherein data collection is informed by model results and vice-versa.

Recent vegetation changes in arctic-alpine tundra ecosystems may affect several ecosystem processes that regulate microbe and soil functions. Such changes can alter ecosystem carbon (C) cycling with positive feedback to the atmosphere if plant C uptake is less than the amount of soil C released. Here, we examine how differences in plant functional traits, microbial activity, and soil processes within and across Salix-dominated shrub, dwarf shrub–dominated heath, and herb- and cryptogam-dominated meadow communities influence C cycling. We develop a hypothesized framework based on a priori model selection of variation in daytime growing season gross ecosystem photosynthesis (GEP) and above- and belowground respiration. The fluxes were standardized to light and temperature. Gross ecosystem photosynthesis was primarily related to soil moisture and secondarily to plant functional traits and aboveground biomass, and belowground respiration was dependent on the community weighted mean of specific leaf area (SLACWM). Similarly, microbial activity was linked with SLACWM and was highest in meadows, and carbon-degrading microbial activity decreased with vegetation woodiness. These results suggest that shrub expansion may influence summer C cycling differently depending on plant community, as belowground respiration might increase in the heath and decrease in the meadow communities.

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 vs. 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 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.

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.

Foliar trait adaptation to sun and shade has been extensively studied in the context of photosynthetic performance of plants, focusing on nitrogen allocation, light capture and use via chlorophyll pigments and leaf morphology; however, less is known about the potential sun-shade dichotomy of other functionally important foliar traits. In this study, we measured 19 traits in paired sun and shade leaves along a 3,500-m elevation gradient in southern Peru to test whether the traits differ with canopy position, and to assess if relative differences vary with species composition and/or environmental filters. We found significant sun-shade differences in leaf mass per area (LMA), photosynthetic pigments (Chl ab and Car), and δ13C. Sun-shade offsets among these traits remained constant with elevation, soil substrates, and species compositional changes. However, other foliar traits related to structure and chemical defense, and those defining general metabolic processes, did not differ with canopy position. Our results suggest that whole-canopy function is captured in many traits of sun leaves; however, photosynthesis-related traits must be scaled based on canopy light extinction. These findings show that top-of-canopy measurements of foliar chemistry from spectral remote sensing approaches map directly to whole-canopy foliar traits including shaded leaves that cannot be directly observed from above.

Abstract Background Shrub cover in arctic and alpine ecosystems has increased in recent decades, and is predicted to further increase with climate change. Changes in shrub abundance may alter ecosystem carbon (C) sequestration and storage, with potential positive feedback on global C cycling. Small and large herbivores may reduce shrub expansion and thereby counteract the positive feedback on C cycling, but herbivore pressures have also changed in the alpine-arctic tundra; the increased shrub cover together with changes in herbivore pressure is leading to unpredictable changes in carbon sequestration and storage. In this study we investigate the importance of herbivory and shrub introduction for carbon sequestration in the short term. We measured standing biomass and daytime mid-growing season carbon fluxes in plots in a full factorial design where we excluded small and large mammalian herbivores and introduced Salix by planting Salix transplants. We used three study sites: one Empetrum-dominated heath, one herb- and cryptogam-dominated meadow, and one Salix-dominated shrub community in the low-alpine zone of the Dovre Mountains, Central Norway. Results After 2 years, significant treatment effects were recorded in the heath community, but not in the meadow and shrub communities. In the heath community cessation of herbivory increased standing biomass due to increased biomass of dwarf shrubs. Cessation of herbivory also reduced biomass of bryophytes and ecosystem respiration (ER). Except for an increase in biomass of deciduous shrubs caused by the Salix introduction, the only effect of Salix introduction was an increase in biomass of graminoids in the heath. Conclusions Our short-term study demonstrated that herbivore exclusion had small but still significant effects on heath vegetation, whereas such effects were not apparent in the herb-and cryptogam-dominated meadow and the Salix-dominated shrub community. Following the treatments over more years is needed to estimate the long-term effects on community structure and the consequences for C sequestration in the three plant communities. Such data are important for predicting the impact of shrub expansion on C budgets from alpine regions.

Abstract Background Trees play crucial roles in the biosphere and societies worldwide, with a total of 60,065 tree species currently identified. Increasingly, a large amount of data on tree species occurrences is being generated worldwide: from inventories to pressed plants. While many of these data are currently available in big databases, several challenges hamper their use, notably geolocation problems and taxonomic uncertainty. Further, we lack a complete picture of the data coverage and quality assessment for open/public databases of tree occurrences. Methods We combined data from five major aggregators of occurrence data (e.g. Global Biodiversity Information Facility, Botanical Information and Ecological Network v.3, DRYFLOR, RAINBIO and Atlas of Living Australia) by creating a workflow to integrate, assess and control data quality of tree species occurrences for species distribution modeling. We further assessed the coverage – the extent of geographical data – of five economically important tree families (Arecaceae, Dipterocarpaceae, Fagaceae, Myrtaceae, Pinaceae). Results Globally, we identified 49,206 tree species (84.69% of total tree species pool) with occurrence records. The total number of occurrence records was 36.69 M, among which 6.40 M could be considered high quality records for species distribution modeling. The results show that Europe, North America and Australia have a considerable spatial coverage of tree occurrence data. Conversely, key biodiverse regions such as South-East Asia and central Africa and parts of the Amazon are still characterized by geographical open-public data gaps. Such gaps are also found even for economically important families of trees, although their overall ranges are covered. Only 15,140 species (26.05%) had at least 20 records of high quality. Conclusions Our geographical coverage analysis shows that a wealth of easily accessible data exist on tree species occurrences worldwide, but regional gaps and coordinate errors are abundant. Thus, assessment of tree distributions will need accurate occurrence quality control protocols and key collaborations and data aggregation, especially from national forest inventory programs, to improve the current publicly available data.

Abstract The inverse relationship between size and abundance is a well‐documented pattern in forests, and the form of size–density relationships depends on the balance between growth and mortality rates in the community. Traditionally, studies of plant size distributions have focused on single‐species populations and forests, but here we examine diverse communities dominated by plants with varied life histories, including grasses, forbs, shrubs, and succulents. In particular, we test whether the parameters of the individual size distribution differ systematically across community types, whether they fit the contrasting predictions of metabolic or demographic theories, and whether they share a common cross‐community scaling relationship with forest communities and crop populations. All thirteen of our study sites better fit the predictions of demographic equilibrium theory, but interestingly, fits of both demographic and metabolic models showed little systematic variation across community types, despite large differences in environmental conditions and dominant life forms. Finally, analysis of the cross‐community scaling relationship demonstrates that natural and restored non‐forest communities conform to patterns of size and abundance observed among forest, plantation, and crop systems. Taken together, our results suggest that common ecological mechanisms govern plant community size structure across broad environmental gradients, regardless of the dominant plant life forms or limiting resources.

The concept of the biome has a long history dating back to Carl Ludwig Willdenow and Alexander von Humboldt. However, while the association between climate and the structure and diversity of vegetation has a long history, scientists have only recently begun to develop a more synthetic understanding of biomes based on the evolution of plant diversity, function, and community assembly. At the broadest scales, climate filters species based on their functional attributes, and the resulting functional differences in dominant vegetation among biomes are important to modeling the global carbon cycle and the functioning of the Earth system. Nevertheless, across biomes, plant species have been shown to occupy a common set of global functional “spectra”, reflecting variation in overall plant size, leaf economics, and hydraulics. Still, comprehensive measures of functional diversity and assessments of functional similarity have not been compared across biomes at continental to global scales. Here, we examine distributions of functional diversity of plant species across the biomes of North and South America, based on distributional information for > 80,000 vascular plant species and functional trait data for ca. 8,000 of those species. First, we show that despite progress in data integration and synthesis, significant knowledge shortfalls persist that limit our ability to quantify the functional biodiversity of biomes. Second, our analyses of the available data show that all the biomes in North and South America share a common pattern–most geographically common, widespread species in any biome tend to be functionally similar whereas the most functionally distinctive species are restricted in their distribution. Third, when only the widespread and functionally similar species in each biome are considered, biomes can be more readily distinguished functionally, and patterns of dissimilarity between biomes appear to reflect a correspondence between climate and functional niche space. Taken together, our results suggest that while the study of the functional diversity of biomes is still in its formative stages, further development of the field will yield insights linking evolution, biogeography, community assembly, and ecosystem function.

Climate warming has a wide range of effects on biodiversity. Here, Zhou et al. show that although variation in environmental temperature is a primary driver of soil microbial biodiversity, microbes show much lower rates of turnover across temperature gradients than other major taxa.

In a rapidly changing climate, alpine plants may persist by adapting to new conditions. However, the rate at which the climate is changing might exceed the rate of adaptation through evolutionary processes in long-lived plants. Persistence may depend on phenotypic plasticity in morphology and physiology. Here we investigated patterns of leaf trait variation including leaf area, leaf thickness, specific leaf area, leaf dry matter content, leaf nutrients (C, N, P) and isotopes (δ13C and δ15N) across an elevation gradient on Gongga Mountain, Sichuan Province, China. We quantified inter- and intra-specific trait variation and the plasticity in leaf traits of selected species to experimental warming and cooling by using a reciprocal transplantation approach. We found substantial phenotypic plasticity in most functional traits where δ15N, leaf area, and leaf P showed greatest plasticity. These traits did not correspond with traits with the largest amount of intraspecific variation. Plasticity in leaf functional traits tended to enable plant populations to shift their trait values toward the mean values of a transplanted plants’ destination community, but only if that population started with very different trait values. These results suggest that leaf trait plasticity is an important mechanism for enabling plants to persist within communities and to better tolerate changing environmental conditions under climate change.