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Funding: Data collection was largely funded by the UK Natural Environment Research Council (NERC) project TREMOR (NE/N004655/1) to D.G., E.G. and O.P., with further funds from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001) to J.V.T. and a University of Leeds Climate Research Bursary Fund to J.V.T. D.G., E.G. and O.P. acknowledge further support from a NERC-funded consortium award (ARBOLES, NE/S011811/1). This paper is an outcome of J.V.T.’s doctoral thesis, which was sponsored by CAPES (GDE 99999.001293/2015-00). J.V.T. was previously supported by the NERC-funded ARBOLES project (NE/S011811/1) and is supported at present by the Swedish Research Council Vetenskapsrådet (grant no. 2019-03758 to R.M.). E.G., O.P. and D.G. acknowledge support from NERC-funded BIORED grant (NE/N012542/1). O.P. acknowledges support from an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. R.S.O. was supported by a CNPq productivity scholarship, the São Paulo Research Foundation (FAPESP-Microsoft 11/52072-0) and the US Department of Energy, project GoAmazon (FAPESP 2013/50531-2). M.M. acknowledges support from MINECO FUN2FUN (CGL2013-46808-R) and DRESS (CGL2017-89149-C2-1-R). C.S.-M., F.B.V. and P.R.L.B. were financed by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001). C.S.-M. received a scholarship from the Brazilian National Council for Scientific and Technological Development (CNPq 140353/2017-8) and CAPES (science without borders 88881.135316/2016-01). Y.M. acknowledges the Gordon and Betty Moore Foundation and ERC Advanced Investigator Grant (GEM-TRAITS, 321131) for supporting the Global Ecosystems Monitoring (GEM) network (gem.tropicalforests.ox.ac.uk), within which some of the field sites (KEN, TAM and ALP) are nested. The authors thank Brazil–USA Collaborative Research GoAmazon DOE-FAPESP-FAPEAM (FAPESP 2013/50533-5 to L.A.) and National Science Foundation (award DEB-1753973 to L. Alves). They thank Serrapilheira Serra-1709-18983 (to M.H.) and CNPq-PELD/POPA-441443/2016-8 (to L.G.) (P.I. Albertina Lima). They thank all the colleagues and grants mentioned elsewhere [8,36] that established, identified and measured the Amazon forest plots in the RAINFOR network analysed here. The authors particularly thank J. Lyod, S. Almeida, F. Brown, B. Vicenti, N. Silva and L. Alves. This work is an outcome approved Research Project no. 19 from ForestPlots.net, a collaborative initiative developed at the University of Leeds that unites researchers and the monitoring of their permanent plots from the world’s tropical forests [61]. The authros thank A. Levesley, K. Melgaço Ladvocat and G. Pickavance for ForestPlots.net management. They thank Y. Wang and J. Baker, respectively, for their help with the map and with the climatic data. The authors acknowledge the invaluable help of M. Brum for kindly providing the comparison of vulnerability curves based on PAD and on PLC shown in this manuscript. They thank J. Martinez-Vilalta for his comments on an early version of this manuscript. The authors also thank V. Hilares and the Asociación para la Investigación y Desarrollo Integral (AIDER, Puerto Maldonado, Peru); V. Saldaña and Instituto de Investigaciones de la Amazonía Peruana (IIAP) for local field campaign support in Peru; E. Chavez and Noel Kempff Natural History Museum for local field campaign support in Bolivia; ICMBio, INPA/NAPPA/LBA COOMFLONA (Cooperativa mista da Flona Tapajós) and T. I. Bragança-Marituba for the research support. Tropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3-5, little is known about how these vary across Earth's largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth-mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink. Publisher PDF

Rapid changes in climate and disturbance regimes, including droughts and hurricanes, are likely to influence tropical forests, but our understanding of the compound effects of disturbances on forest ecosystems is extremely limited. Filling this knowledge gap is necessary to elucidate the future of these ecosystems under a changing climate. We examined the relationship between hurricane response (damage, mortality, and resilience) and four hydraulic traits of 13 dominant woody species in a wet tropical forest subject to periodic hurricanes. Species with high resistance to embolisms (low P

The role of forest biodiversity in supporting ecosystem functioning is remarked to be context-dependent, and changes in environmental conditions could alter the shape of biodiversity-ecosystem functioning (BEF) relationships. However few studies have explored the processes underlying shifts in BEF relationships along abiotic gradients, which limits our ability to predict how the BEF relationship will respond to the rapid future changes in environmental conditions caused by climate change. In this study, we sought to test (i) how a water limitation gradient shapes the functional composition and diversity of forests, (ii) how functional composition and diversity of trees relate to forest productivity, and (iii) if functional diversity is more strongly related to productivity in the Mediterranean or temperate climate. To address these points, we created a functional trait data set covering traits of most of the tree species within the Italian peninsula, using forest surveyed data sets from the National Forest Inventory. We found that functional composition varied with water limitation as tree communities tended to have more `conservative` resource strategies (e.g., low specific leaf area and high wood density) under increased water limitation. Functional diversity´s response was highly variable, however, increased water limitation has been found to enhance also functional diversity in the temperate domain. Biodiversity positively influenced forest productivity through a combination of mass ratio and niche complementary effects in Italian forests, but the relative importance of these effects is dependent on the functional trait and bioclimate considered. Niche complementary effects showed a more predominant effect on productivity in the Mediterranean compared to temperate forests. Overall, our results suggest that biodiversity plays an important role in driving forest productivity under more environmental stressed conditions by promoting beneficial interactions between species and complementarity in resources.

AIMPatterns of individual variation are key to testing hypotheses about the mechanisms underlying biogeographic patterns. However, it is challenging to gather data on individual-level variation at large spatial scales. Model organisms are potentially important systems for biogeographical studies, given the available range-wide natural history collections, and the importance of providing biogeographical context to their genetic and phenotypic diversity.LOCATIONGlobalTAXONArabidopsis thaliana(“Arabidopsis”)METHODSWe fit occurrence records to climate data, and then projected the distribution of Arabidopsis under last glacial maximum, current, and future climates. We confronted model predictions with individual performance measured on 2,194 herbarium specimens, and we asked whether predicted suitability was associated with life-history and genomic variation measured on ∼900 natural accessions.RESULTSThe most important climate variables constraining the Arabidopsis distribution were winter cold in northern and high elevation regions and summer heat in southern regions. Herbarium specimens from regions with lower habitat suitability in both northern and southern regions were smaller, supporting the hypothesis that the distribution of Arabidopsis is constrained by climate-associated factors. Climate anomalies partly explained interannual variation in herbarium specimen size, but these did not closely correspond to local limiting factors identified in the distribution model. Late-flowering genotypes were absent from the lowest suitability regions, suggesting slower life histories are only viable closer to the center of the realized niche. We identified glacial refugia farther north than previously recognized, as well as refugia concordant with previous population genetic findings. Lower latitude populations, known to be genetically distinct, are most threatened by future climate change. The recently colonized range of Arabidopsis was well-predicted by our native-range model applied to certain regions but not others, suggesting it has colonized novel climates.MAIN CONCLUSIONSIntegration of distribution models with performance data from vast natural history collections is a route forward for testing biogeographical hypotheses about species distributions and their relationship with evolutionary fitness across large scales.

The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades—including a maturation of relevant theory and key concepts—but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an “Overview” talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.

Tropical forests are converted at an alarming rate for agricultural use and pastureland, but also regrow naturally through secondary succession. For successful forest restoration, it is essential to understand the mechanisms of secondary succession. These mechanisms may vary across forest types, but analyses across broad spatial scales are lacking. Here, we analyse forest recovery using 1,403 plots that differ in age since agricultural abandonment from 50 sites across the Neotropics. We analyse changes in community composition using species-specific stem wood density (WD), which is a key trait for plant growth, survival and forest carbon storage. In wet forest, succession proceeds from low towards high community WD (acquisitive towards conservative trait values), in line with standard successional theory. However, in dry forest, succession proceeds from high towards low community WD (conservative towards acquisitive trait values), probably because high WD reflects drought tolerance in harsh early successional environments. Dry season intensity drives WD recovery by influencing the start and trajectory of succession, resulting in convergence of the community WD over time as vegetation cover builds up. These ecological insights can be used to improve species selection for reforestation. Reforestation species selected to establish a first protective canopy layer should, among other criteria, ideally have a similar WD to the early successional communities that dominate under the prevailing macroclimatic conditions.

１．Quantitative evaluations to optimize complexity have become standard for avoiding overfitting of ecological niche models (ENMs) that estimate species’ potential geographic distributions. ENMeval was the first R package to make such evaluations (often termed model tuning) widely accessible for the Maxent algorithm. It also provided multiple methods for partitioning occurrence data and reported various performance metrics.２．Requests by users, recent developments in the field, and needs for software compatibility led to a major redesign and expansion. We additionally conducted a literature review to investigate trends in ENMeval use (2015–2019).３．ENMeval 2.0 has a new object-oriented structure for adding other algorithms, enables customizing algorithmic settings and performance metrics, generates extensive metadata, implements a null-model approach to quantify significance and effect sizes, and includes features to increase the breadth of analyses and visualizations. In our literature review, we found insufficient reporting of model performance and parameterization, heavy reliance on model selection with AICc and low utilization of spatial cross-validation; we explain how ENMeval 2.0 can help address these issues.４．This redesigned and expanded version can promote progress in the field and improve the information available for decision-making.

While calls for interdisciplinary research in environmental contexts are common, it often remains a struggle to integrate humanities/qualitative social sciences insights with those of bio-physical approaches. We propose that cross-disciplinary historical perspectives can open new avenues for collaboration among social and natural scientists while expanding visions of possible future environments and management scenarios. We make these arguments through attention to woodlands, which are under pressure from complex socio-ecological stressors that can best be understood from interdisciplinary perspectives. By combining deep ecological and shallower social historical approaches, we show how history can both enrich our understandings of woodland pasts and provide a ground for better combining the case-based insights of humanistic history with those of deep-time ecological history. We conclude that such interdisciplinary historical approaches are important not only for research, but also for management (especially rewilding and scenario-building), as the surprisingly large range of past changes reminds us that future conditions can be more varied than typically acknowledged. This Perspective proposes that cross-disciplinary historical approaches can assist in improving collaborations among social and natural scientists and in expanding environmental management imaginaries. Through the example of woodlands, we illustrate how combining natural science insights on deep-time changes with social science research on histories of commercialization and industrialization can generate better understandings of socio-ecological dynamics. We emphasize that qualitative historical case studies have a place alongside other approaches in broadening visions of woodland futures via attention to pasts.

Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191ha) and quantified tree palm (i.e., ≥10cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.

One-third of all Neotropical forests are secondary forests that regrow naturally after agricultural use through secondary succession. We need to understand better how and why succession varies across environmental gradients and broad geographic scales. Here, we analyze functional recovery using community data on seven plant characteristics (traits) of 1,016 forest plots from 30 chronosequence sites across the Neotropics. By analyzing communities in terms of their traits, we enhance understanding of the mechanisms of succession, assess ecosystem recovery, and use these insights to propose successful forest restoration strategies. Wet and dry forests diverged markedly for several traits that increase growth rate in wet forests but come at the expense of reduced drought tolerance, delay, or avoidance, which is important in seasonally dry forests. Dry and wet forests showed different successional pathways for several traits. In dry forests, species turnover is driven by drought tolerance traits that are important early in succession and in wet forests by shade tolerance traits that are important later in succession. In both forests, deciduous and compound-leaved trees decreased with forest age, probably because microclimatic conditions became less hot and dry. Our results suggest that climatic water availability drives functional recovery by influencing the start and trajectory of succession, resulting in a convergence of community trait values with forest age when vegetation cover builds up. Within plots, the range in functional trait values increased with age. Based on the observed successional trait changes, we indicate the consequences for carbon and nutrient cycling and propose an ecologically sound strategy to improve forest restoration success.

Scientists, corporations, mystics, and movie stars have convinced policymakers around the world that a massive campaign to plant trees should be an essential element of global climate policy. Public dialogue has emphasized potential benefits of tree planting while downplaying pitfalls and limitations that are well established by social and ecological research. We argue that if natural climate solutions are to succeed while economies decarbonize (Griscom et al. 2017), policymakers must recognize and avoid the expense, risk, and damage that poorly designed and hastily implemented tree plantings impose on ecosystems and people.

Projected increases in cyclonic storm intensity under a warming climate will have profound effects on forests, potentially changing these ecosystems from carbon sinks to sources. Forecasting storm impacts on these ecosystems requires consideration of risk factors associated with storm meteorology, landscape structure, and forest attributes. Here we evaluate risk factors associated with damage severity caused by Hurricanes María and Irma across Puerto Rican forests. Using field and remote sensing data, total forest aboveground biomass (AGB) lost to the storms was estimated at 10.44 (±2.33) Tg, ca. 23% of island-wide pre-hurricane forest AGB. Storm-related rainfall was a stronger predictor of forest damage than maximum wind speeds. Soil water storage capacity was also an important risk factor, corroborating the influence of rainfall on forest damage. Expected increases of 20% in hurricane-associated rainfall in the North Atlantic highlight the need to consider how such shifts, together with high speed winds, will affect terrestrial ecosystems.

Host-parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica-prone regions and their absence elsewhere implicate potential tradeoffs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and belowground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with tradeoffs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR-Cas9 edited sorghum further indicate the benefit of LGS1-mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.SIGNIFICANCE STATEMENTUnderstanding co-evolution in crop-parasite systems is critical to management of myriad pests and pathogens confronting modern agriculture. In contrast to wild plant communities, parasites in agricultural ecosystems are usually expected to gain the upper hand in co-evolutionary ‘arms races’ due to limited genetic diversity of host crops in cultivation. Here, we develop a framework to characterize associations between genome variants in global landraces (traditional varieties) of the staple crop sorghum with the distribution of the devastating parasitic weed Striga hermonthica. We find long-term maintenance of diversity in genes related to parasite resistance, highlighting an important role of host adaptation for co-evolutionary dynamics in smallholder agroecosystems.

BACKGROUND AND AIMS: Identifying the processes that generate and maintain biodiversity requires understanding of how evolutionary processes interact with abiotic conditions to structure communities. Edaphic gradients are strongly associated with floristic patterns but, compared with climatic gradients, have received relatively little attention. We asked (1) How does the phylogenetic composition of palm communities vary along edaphic gradients within major habitat types? and (2) To what extent are phylogenetic patterns determined by (a) habitat specialists, (b) small versus large palms, and (c) hyperdiverse genera? METHODS: We paired data on palm community composition from 501 transects of 0.25 ha located in two main habitat types (non-inundated uplands and seasonally inundated floodplains) in western Amazonian rain forests with information on soil chemistry, climate, phylogeny and metrics of plant size. We focused on exchangeable base concentration (cmol+ kg-1) as a metric of soil fertility and a floristic index of inundation intensity. We used a null model approach to quantify the standard effect size of mean phylogenetic distance for each transect (a metric of phylogenetic community composition) and related this value to edaphic variables using generalized linear mixed models, including a term for spatial autocorrelation. KEY RESULTS: Overall, we recorded 112 008 individuals belonging to 110 species. Palm communities in non-inundated upland transects (but not floodplain transects) were more phylogenetically clustered in areas of low soil fertility, measured as exchangeable base concentration. In contrast, floodplain transects with more severe flood regimes (as inferred from floristic structure) tended to be phylogenetically clustered. Nearly half of the species recorded (44 %) were upland specialists while 18 % were floodplain specialists. In both habitat types, phylogenetic clustering was largely due to the co-occurrence of small-sized habitat specialists belonging to two hyperdiverse genera (Bactris and Geonoma). CONCLUSIONS: Edaphic conditions are associated with the phylogenetic community structure of palms across western Amazonia, and different factors (specifically, soil fertility and inundation intensity) appear to underlie diversity patterns in non-inundated upland versus floodplain habitats. By linking edaphic gradients with palm community phylogenetic structure, our study reinforces the need to integrate edaphic conditions in eco-evolutionary studies in order to better understand the processes that generate and maintain tropical forest diversity. Our results suggest a role for edaphic niche conservatism in the evolution and distribution of Amazonian palms, a finding with potential relevance for other clades.

Abtract 1.Scientific research increasingly calls for open-source software that is flexible, interactive, and expandable, while providing methodological guidance and reproducibility. Currently, many analyses in ecology are implemented with “black box” graphical user interfaces that lack flexibility or command-line interfaces that are infrequently used by non-specialists. 2.To help remedy this situation in the context of species distribution modeling, we created Wallace, an open and modular application with a richly documented graphical user interface to underlying R scripts that is flexible and highly interactive. 3.Wallace guides users from acquiring and processing data to building models and examining predictions. Additionally, it is designed to grow via community contributions of new modules to expand functionality. All results are downloadable, along with code to reproduce the analysis. 4.Wallace provides an example of an innovative platform to increase access to cutting-edge methods and encourage plurality in science and collaboration in software development. This article is protected by copyright. All rights reserved.

Western Amazonia is a global biodiversity hotspot that encompasses extensive variation in geologic, climatic, and biotic features. Palms (Arecaceae) are among the most diverse and iconic groups of plants in the region with more than 150 species that exhibit extraordinary variation of geographical distributions, regional abundance patterns, and life history strategies and growth forms, and provide myriad ecosystem services. Understanding the ecological and evolutionary drivers that underpin palm distribution and abundance patterns may shed light on the evolution and ecology of the tropical forest biomes more generally. Edaphic conditions, in particular, are increasingly recognized as critical drivers of tropical plant diversity and distributions but data deficiencies inhibit our understanding of plant–soil relationships at broad scales, especially in the tropics. We present data from 546, 0.25‐ha (5 × 500 m) georeferenced transects located throughout western Amazonia where all individual palms were identified, counted, and assigned to a life‐history stage. Several environmental covariates were recorded along each transect and surface soil samples were collected from multiple points in N = 464 of transects. Altogether, the transects include 532,602 individuals belonging to 135 species. Variation among transects in terms of palm species richness and abundance is associated with major habitat types and soil properties. The soil properties including pH, acidity, all macronutrients for all samples, and texture, carbon, nitrogen, and micronutrients for some transects vary substantially across the study area, providing insight to broad‐scale variation of tropical surface soils. The data provided here will help advance our understanding of plant distributions and abundance patterns, and associations with soil conditions. No copyright restrictions are associated with this data set but please cite this paper if data are used for publication.

Land-use change occurs nowhere more rapidly than in the tropics, where the imbalance between deforestation and forest regrowth has large consequences for the global carbon cycle(1). However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates are influenced by climate, landscape, and prior land use(2-4). Here we analyse aboveground biomass recovery during secondary succession in 45 forest sites and about 1,500 forest plots covering the major environmental gradients in the Neotropics. The studied secondary forests are highly productive and resilient. Aboveground biomass recovery after 20 years was on average 122 megagrams per hectare (Mg ha(-1)), corresponding to a net carbon uptake of 3.05 Mg C ha(-1) yr(-1), 11 times the uptake rate of old-growth forests. Aboveground biomass stocks took a median time of 66 years to recover to 90% of old-growth values. Aboveground biomass recovery after 20 years varied 11.3-fold ( from 20 to 225 Mg ha(-1)) across sites, and this recovery increased with water availability (higher local rainfall and lower climatic water deficit). We present a biomass recovery map of Latin America, which illustrates geographical and climatic variation in carbon sequestration potential during forest regrowth. The map will support policies to minimize forest loss in areas where biomass resilience is naturally low (such as seasonally dry forest regions) and promote forest regeneration and restoration in humid tropical lowland areas with high biomass resilience.

Modeling climate change effects on species and communities is critical especially in isolated islands. We analyzed the potential effects of climate change on 200 plant species in Puerto Rico under two emission scenarios and in four periods over the twenty-first century. Our approach was based on ensemble bioclimatic modeling using eight modeling algorithms and community richness analysis. Our findings showed that the probabilities of environmental suitability decline for wet climate species and increase for drier and warm climate species in the future periods under both emission scenarios, with stronger effects under the higher emission scenario. Expansion of dry climate species to higher elevations appears to be a prominent response of species to climatic change in the island based on changes in environmental suitability but the actual species redistribution will be influenced by their life histories, potential adaptation, dispersal abilities, species introductions, and species interactions. This potential movement leads to a spatial pattern of species richness at site level that shows a positive relationship with elevation, which becomes stronger in the later periods of the century. The spatial pattern of species richness, if combined with single species projections, can provide critical information for conservation management in the island. Conservation management can support island-wide biological diversity by protecting the wet climate species on the uplands.

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha–1) at spatial scales ranging from 5 to 250 m (0.025–6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20–400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

© 2018 The Author(s). The nutrient demands of regrowing tropical forests are partly satisfied by nitrogen-fixing legume trees, but our understanding of the abundance of those species is biased towards wet tropical regions. Here we show how the abundance of Leguminosae is affected by both recovery from disturbance and large-scale rainfall gradients through a synthesis of forest inventory plots from a network of 42 Neotropical forest chronosequences. During the first three decades of natural forest regeneration, legume basal area is twice as high in dry compared with wet secondary forests. The tremendous ecological success of legumes in recently disturbed, water-limited forests is likely to be related to both their reduced leaflet size and ability to fix N2, which together enhance legume drought tolerance and water-use efficiency. Earth system models should incorporate these large-scale successional and climatic patterns of legume dominance to provide more accurate estimates of the maximum potential for natural nitrogen fixation across tropical forests.

Models of species ecological niches and geographic distributions now represent a widely used tool in ecology, evolution, and biogeography. However, the very common situation of species with few available occurrence localities presents major challenges for such modeling techniques, in particular regarding model complexity and evaluation. Here, we summarize the state of the field regarding these issues and provide a worked example using the technique Maxent for a small mammal endemic to Madagascar (the nesomyine rodent Eliurus majori). Two relevant model-selection approaches exist in the literature (information criteria, specifically AICc; and performance predicting withheld data, via a jackknife), but AICc is not strictly applicable to machine-learning algorithms like Maxent. We compare models chosen under each selection approach with those corresponding to Maxent default settings, both with and without spatial filtering of occurrence records to reduce the effects of sampling bias. Both selection approaches chose simpler models than those made using default settings. Furthermore, the approaches converged on a similar answer when sampling bias was taken into account, but differed markedly with the unfiltered occurrence data. Specifically, for that dataset, the models selected by AICc had substantially fewer parameters than those identified by performance on withheld data. Based on our knowledge of the study species, models chosen under both AICc and withheld-data-selection showed higher ecological plausibility when combined with spatial filtering. The results for this species intimate that AICc may consistently select models with fewer parameters and be more robust to sampling bias. To test these hypotheses and reach general conclusions, comprehensive research should be undertaken with a wide variety of real and simulated species. Meanwhile, we recommend that researchers assess the critical yet underappreciated issue of model complexity both via information criteria and performance on withheld data, comparing the results between the two approaches and taking into account ecological plausibility. This article is protected by copyright. All rights reserved.

Predicting the fate of tropical forests under a changing climate requires understanding species responses to climatic variability and extremes. Seedlings may be particularly vulnerable to climatic stress given low stored resources and undeveloped roots; they also portend the potential effects of climate change on future forest composition. Here we use data for ca. 50,000 tropical seedlings representing 25 woody species to assess (i) the effects of interannual variation in rainfall and solar radiation between 2007 and 2016 on seedling survival over 9 years in a subtropical forest; and (ii) how spatial heterogeneity in three environmental factors-soil moisture, understory light, and conspecific neighborhood density-modulate these responses. Community-wide seedling survival was not sensitive to interannual rainfall variability but interspecific variation in these responses was large, overwhelming the average community response. In contrast, community-wide responses to solar radiation were predominantly positive. Spatial heterogeneity in soil moisture and conspecific density were the predominant and most consistent drivers of seedling survival, with the majority of species exhibiting greater survival at low conspecific densities and positive or nonlinear responses to soil moisture. This environmental heterogeneity modulated impacts of rainfall and solar radiation. Negative conspecific effects were amplified during rainy years and at dry sites, whereas the positive effects of radiation on survival were more pronounced for seedlings existing at high understory light levels. These results demonstrate that environmental heterogeneity is not only the main driver of seedling survival in this forest but also plays a central role in buffering or exacerbating impacts of climate fluctuations on forest regeneration. Since seedlings represent a key bottleneck in the demographic cycle of trees, efforts to predict the long-term effects of a changing climate on tropical forests must take into account this environmental heterogeneity and how its effects on regeneration dynamics play out in long-term stand dynamics.

In the southwestern USA, recent large‐scale die‐offs of conifers raise the question of their resilience and mortality under droughts. To date, little is known about the interannual structural response to droughts. We hypothesized that piñon pines (Pinus edulis) respond to drought by reducing the drop of leaf water potential in branches from year to year through needle morphological adjustments. We tested our hypothesis using a 7‐year experiment in central New Mexico with three watering treatments (irrigated, normal, and rain exclusion). We analyzed how variation in “evaporative structure” (needle length, stomatal diameter, stomatal density, stomatal conductance) responded to watering treatment and interannual climate variability. We further analyzed annual functional adjustments by comparing yearly addition of needle area (LA) with yearly addition of sapwood area (SA) and distance to tip (d), defining the yearly ratios SA:LA and SA:LA/d. Needle length (l) increased with increasing winter and monsoon water supply, and showed more interannual variability when the soil was drier. Stomatal density increased with dryness, while stomatal diameter was reduced. As a result, anatomical maximal stomatal conductance was relatively invariant across treatments. SA:LA and SA:LA/d showed significant differences across treatments and contrary to our expectation were lower with reduced water input. Within average precipitation ranges, the response of these ratios to soil moisture was similar across treatments. However, when extreme soil drought was combined with high VPD, needle length, SA:LA and SA:LA/d became highly nonlinear, emphasizing the existence of a response threshold of combined high VPD and dry soil conditions. In new branch tissues, the response of annual functional ratios to water stress was immediate (same year) and does not attempt to reduce the drop of water potential. We suggest that unfavorable evaporative structural response to drought is compensated by dynamic stomatal control to maximize photosynthesis rates. ISSN:2045-7758

Question Understanding how the relative importance of different community assembly processes changes during secondary succession of diverse systems remains elusive. Functional and phylogenetic approaches that place species along continuous axes of niche differentiation and evolutionary relatedness, however, are deepening our understanding of the mechanisms that drive successional dynamics. We ask whether successional shifts in the functional and phylogenetic composition of post-agricultural tropical forests provide evidence for niche partitioning or competitive dominance hierarchies as drivers of successional change. Location Subtropical wet forests, Puerto Rico. Methods We combined data on four functional traits [leaf dry mass per area (LMA), wood density (WD), maximum height (Hmax), seed dry mass] and a well-resolved molecular phylogeny to characterize taxonomic, functional and phylogenetic composition of sapling and adult tree communities along a regionally replicated chronosequence. We used a null model approach to assess how functional and phylogenetic diversity change with forest age. Results Corresponding increases of community-weighted mean LMA, Hmax and seed mass with forest age reflected a shift in dominance of species with acquisitive resource-use strategies and small seeds towards species with more conservative resource use and larger seeds. A negative relationship between forest age and local diversity of Hmax and seed mass suggested increased importance of competitive hierarchies for light capture and shade-tolerant regeneration in older forests. In contrast, the colonization of palms in older forest plots led to a positive relationship between forest age and local phylogenetic diversity, suggesting functional convergence of distantly related lineages on traits that confer competitive dominance under low resource conditions. Conclusions We linked both functional and phylogenetic dimensions of community diversity with successional trajectories of post-agricultural tropical forests. Contrasting patterns of these dimensions of diversity shed light on the underlying community assembly processes. We argue that integrating traits and phylogeny with specific hypotheses about physiological and historical mechanisms is essential for advancing our understanding of the drivers of community change during succession.

Identifying the processes that maintain highly diverse plant communities remains a central goal in ecology. Species variation in growth and survival rates across ontogeny, represented by tree size classes and life history stage-specific niche partitioning, are potentially important mechanisms for promoting forest diversity. However, the role of ontogeny in mediating competitive dynamics and promoting functional diversity is not well understood, particular in high-diversity systems such as tropical forests. The interaction between interspecific functional trait variation and ontogenetic shifts in competitive dynamics may yield insights into the ecophysiological mechanisms promoting community diversity. We investigated how functional trait (seed size, maximum height, SLA, leaf N, and wood density) associations with growth, survival, and response to competing neighbors differ among seedlings and two size classes of trees in a subtropical rain forest in Puerto Rico. We used a hierarchical Bayes model of diameter growth and survival to infer trait relationships with ontogenetic change in competitive dynamics. Traits were more strongly associated with average growth and survival than with neighborhood interactions, and were highly consistent across ontogeny for most traits. The associations between trait values and tree responses to crowding by neighbors showed significant shifts as trees grew. Large trees exhibited greater growth as the difference in species trait values among neighbors increased, suggesting trait-associated niche partitioning was important for the largest size class. Our results identify potential axes of niche partitioning and performance-equalizing functional trade-offs across ontogeny, promoting species coexistence in this diverse forest community.

Predicting biotic responses to environmental change requires understanding the joint effects of abiotic conditions and biotic interactions on community dynamics. One major challenge is to separate the potentially confounding effects of abiotic environmental variation and local biotic interactions on individual performance. The stress gradient hypothesis (SGH) addresses this issue directly by predicting that the effects of biotic interactions on performance become more positive as the abiotic environment becomes more stressful. It is unclear, however, how the predictions of the SGH apply to plants of differing functional strategies in diverse communities. We asked (1) how the effect of crowding on performance (growth and survival) of trees varies across a precipitation gradient, and (2) how functional strategies (as measured by two key traits: wood density and leaf mass per area, LMA) mediate average demographic rates and responses to crowding across the gradient. We built trait-based neighborhood models of growth and survival across a regional precipitation gradient where increasing precipitation is associated with reduced abiotic stress. In total, our dataset comprised ~170,000 individual trees belonging to 252 species. The effect of crowding on tree performance varied across the gradient; crowding negatively affected growth across plots and positively affected survival in the wettest plot. Functional traits mediated average demographic rates across the gradient, but we did not find clear evidence that the strength of these responses depends on species’ traits. Our study lends support to the SGH and demonstrates how a trait-based perspective can advance these concepts by linking the diversity of species interactions with functional variation across abiotic gradients.

The neotropical palm genus Wendlandiella (Arecoideae: chamaedoreeae) is here revised based on a thorough study of 119 samples deposited in 18 international herbaria, as well as the analysis...

Arbuscular mycorrhizal (AM) fungi in the soil may influence tropical tree dynamics and forest succession. The mechanisms are poorly understood, because the functional characteristics and abundances of tree species and AM fungi are likely to be codependent. We used generalized joint attribute modeling to evaluate if AM fungi are associated with three forest community metrics for a sub-tropical montane forest in Puerto Rico. The metrics chosen to reflect changes during forest succession are the abundance of seedlings of different successional status, the amount of foliar damage on seedlings of different successional status, and community-weighted mean functional trait values (adult specific leaf area [SLA], adult wood density, and seed mass). We used high-throughput DNA sequencing to identify fungal operational taxonomic units (OTUs) in the soil. Model predictions showed that seedlings of mid- and late-successional species had less leaf damage when the 12 most common AM fungi were abundant compared to when these fungi were absent. We also found that seedlings of mid-successional species were predicted to be more abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. In contrast, early-successional tree seedlings were predicted to be less abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. Finally, we showed that, among the 12 most common AM fungi, different AM fungi were correlated with functional trait characteristics of early- or late-successional species. Together, these results suggest that early-successional species might not rely as much as mid- and late-successional species on AM fungi, and AM fungi might accelerate forest succession.

Summary Recent studies have demonstrated a need for increased rigour in building and evaluating ecological niche models (ENMs) based on presence-only occurrence data. Two major goals are to balance goodness-of-fit with model complexity (e.g. by ‘tuning’ model settings) and to evaluate models with spatially independent data. These issues are especially critical for data sets suffering from sampling bias, and for studies that require transferring models across space or time (e.g. responses to climate change or spread of invasive species). Efficient implementation of procedures to accomplish these goals, however, requires automation. We developed ENMeval, an R package that: (i) creates data sets for k-fold cross-validation using one of several methods for partitioning occurrence data (including options for spatially independent partitions), (ii) builds a series of candidate models using Maxent with a variety of user-defined settings and (iii) provides multiple evaluation metrics to aid in selecting optimal model settings. The six methods for partitioning data are n−1 jackknife, random k-folds ( = bins), user-specified folds and three methods of masked geographically structured folds. ENMeval quantifies six evaluation metrics: the area under the curve of the receiver-operating characteristic plot for test localities (AUCTEST), the difference between training and testing AUC (AUCDIFF), two different threshold-based omission rates for test localities and the Akaike information criterion corrected for small sample sizes (AICc). We demonstrate ENMeval by tuning model settings for eight tree species of the genus Coccoloba in Puerto Rico based on AICc. Evaluation metrics varied substantially across model settings, and models selected with AICc differed from default ones. In summary, ENMeval facilitates the production of better ENMs and should promote future methodological research on many outstanding issues.

Mechanisms of community assembly and ecosystem function are often analyzed using community-weighted mean trait values (CWMs). We present a novel conceptual framework to quantify the contribution of demographic processes (i.e., growth, recruitment, and mortality) to temporal changes in CWMs. We used this framework to analyze mechanisms of secondary succession in wet tropical forests in Mexico. Seed size increased over time, reflecting a trade-off between colonization by small seeds early in succession, to establishment by large seeds later in succession. Specific leaf area (SLA) and leaf phosphorus content decreased over time, reflecting a trade-off between fast growth early in succession vs. high survival late in succession. On average, CWM shifts were driven mainly (70%) by growth of surviving trees that comprise the bulk of standing biomass, then mortality (25%), and weakly by recruitment (5%). Trait shifts of growing and recruiting trees mirrored the CWM trait shifts, and traits of dying trees did not change during succession, indicating that these traits are important for recruitment and growth, but not for mortality, during the first 30 yr of succession. Identifying the demographic drivers of functional composition change links population dynamics to community change, and enhances insights into mechanisms of succession.

The distributions of arbuscular mycorrhizal (AM) fungal communities are driven by climate, soil nutrients, and plant community composition. However, these distributions are estimated at the community level and AM fungal taxa will respond to selection pressure of global change at the species level. Thus, ecological niche models of individual AM fungal taxa may be an informative approach to predict AM fungal composition and function under future climates at the global scale. Here we present the first attempt to model AM fungal distributions with ecological niche models for the widespread AM fungal taxon Rhizophagus irregularis (formerly Glomus intraradices). We show that despite varying the definition of the operational taxonomic unit (OTU) for R. irregularis, the predicted distributions of this species complex are consistently affected by a positive association with soil moisture. The spatial extent of ecological niche models affected the predicted distribution of R. irregularis, with climatic drivers and resources affecting its distribution more strongly in the northern and southern hemispheres, respectively. Given that AM fungi are not dispersal limited and coexist at the landscape scale relevant for ecological niche model predictions, this widely distributed fungal clade provides a robust case study to apply hypothesis-driven distributional models to predict the biogeography of microorganisms.

Determining how the relative strength of community assembly processes varies along resource gradients is critical for understanding community responses to environmental change. A key challenge for addressing this issue at regional scales is that environmental gradients typically encompass multiple coupled resource gradients (e.g. water, light, soils), which can complicate hypotheses about the drivers of community variation. We used data on functional traits and phylogenetic relatedness to infer assembly processes of tree communities across regional environmental gradients in Puerto Rico. We censused trees in 24, 0.25-ha mature plots located along a precipitation gradient and on soils derived from two parent materials (limestone and volcanic). In each plot, we quantified abiotic conditions in terms of mean annual precipitation, canopy openness, and soil nutrients. We used three functional traits with relevance for drought tolerance and resource acquisition strategies (wood density [WD], leaf mass per area [LMA], and maximum height [Hmax]), and a molecular phylogeny, to characterize tree community composition in terms of (i) community-weighted mean trait values (i.e., plot average trait values, weighted by relative basal area), (ii) functional diversity, and (iii) phylogenetic diversity. Mean annual precipitation was negatively correlated with understory light availability (for plots on both soil types), and soil fertility (among plots on limestone soils). Soil fertility varied substantially between plots on each parent material, and was generally higher among plots on limestone-derived soils. Among the limestone soil plots, which occur on the drier half of the precipitation gradient, increasing mean annual precipitation was associated with lower community-weighted mean WD and LMA, and taller Hmax. Additionally, functional diversity (of WD and Hmax) and phylogenetic diversity increased with precipitation among limestone soil plots, suggesting an important role for abiotic filtering in driving functional and phylogenetic convergence in arid conditions. In contrast, we did not find significant relationships between environmental conditions and community-weighted mean traits or diversity metrics among plots on volcanic-derived soils, which occur along the wetter half of the precipitation gradient. Together, our results suggest that drought tolerance is the dominant assembly mechanism controlling tree composition in dry forests. In wetter forests, functional diversity appears to be maintained by a combination of hierarchical competition for light and niche partitioning. Overall, our results exhibit geographic variation in the mechanisms governing composition of tropical forests across regional environmental gradients, and highlight the importance of considering complex environmental gradients at large spatial scales.

The notion that relationships between community-weighted mean (CWM) traits (i.e. plot-level trait values weighted by species abundances) and environmental conditions reflect selection towards locally optimal phenotypes is challenged by the large amount of interspecific trait variation typically found within ecological communities. Reconciling these contrasting patterns is a key to advancing predictive theories of functional community ecology. We combined data on geographical distributions and three traits (wood density, leaf mass per area and maximum height) of 173 tree species in Puerto Rico. We tested the hypothesis that species are more likely to occur where their trait values are more similar to the local CWM trait values (the ‘ CWM-optimality’ hypothesis) by comparing species occurrence patterns (as a proxy for fitness) with the functional composition of forest plots across a precipitation gradient. While 70% of the species supported CWM-optimality for at least one trait, nearly 25% significantly opposed it for at least one trait, thereby contributing to local functional diversity. The majority (85%) of species that opposed CWM-optimality did so only for one trait and few species opposed CWM-optimality in multivariate trait space. Our study suggests that constraints to local functional variation act more strongly on multivariate phenotypes than on univariate traits.

The seed-to-seedling transition constitutes a critical bottleneck in the life history of plants and represents a major determinant of species composition and abundance. However, we have surprisingly little knowledge regarding the forces driving this ontogenetic transition. Here we utilize information regarding organismal function to investigate the strength of intra-and interspecific negative density dependence during the seed-to-seedling transition in Puerto Rican tree species. Our analyses were implemented at individual sites and across an entire 16-ha forest plot, spanning 6 years. The functional richness of seedling assemblages was significantly lower than expected given the seed assemblages, but the functional evenness was significantly higher than expected, indicating the simultaneous importance of constraints on the overall phenotypic space and trait differences for successful transitions from seed to seedling. The results were consistent across years. Within species, we also found evidence for strong intraspecific negative density dependence, where the probability of transition was proportionally lower when in a site with high conspecific density. These results suggest that filtering of similar phenotypes across species and strong negative density dependence within and among species are simultaneously driving the structure and dynamics of tropical tree assemblages during this critical life-history transition.

Biodiversity is inherently multidimensional, encompassing taxonomic, functional, phylogenetic, genetic, landscape and many other elements of variability of life on the Earth. However, this fundamental principle of multidimensionality is rarely applied in research aimed at understanding biodiversity's value to ecosystem functions and the services they provide. This oversight means that our current understanding of the ecological and environmental consequences of biodiversity loss is limited primarily to what unidimensional studies have revealed. To address this issue, we review the literature, develop a conceptual framework for multidimensional biodiversity research based on this review and provide a case study to explore the framework. Our case study specifically examines how herbivory by whitetail deer ( Odocoileus virginianus ) alters the multidimensional influence of biodiversity on understory plant cover at Black Rock Forest, New York. Using three biodiversity dimensions (taxonomic, functional and phylogenetic diversity) to explore our framework, we found that herbivory alters biodiversity's multidimensional influence on plant cover; an effect not observable through a unidimensional approach. Although our review, framework and case study illustrate the advantages of multidimensional over unidimensional approaches, they also illustrate the statistical and empirical challenges such work entails. Meeting these challenges, however, where data and resources permit, will be important if we are to better understand and manage the consequences we face as biodiversity continues to decline in the foreseeable future.