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The widespread observation that rare species have stronger conspecific plant-soil feedback (PSF) than common species raises more questions than answers on how rare species can possibly win the dance with abundant species. Here, we test soil feedback effect of phylogenetically related species on seedlings of contrasting local abundance in a subtropical forest. The results showed that although rare species suffered strong negative PSF in soils of conspecifics or phylogenetically close relatives, no such feedback was found in the soils of distant relatives. In contrast, although common species had weak conspecific PSF, they suffered consistently strong heterospecific soil feedback. These mechanisms ensure that rare species would fare well in the neighborhood of phylogenetically distant heterospecifics but do poorly under their close relatives, while common species perform relatively well in their own neighborhood but poorly in others’. This phylogenetic conservatism in PSF facilitates the persistence of rare species in a community.

Regionally fitted allometric equations for individual trees and root-to-shoot ratio values are normally used to estimate local aboveground and belowground forest biomass, respectively. However, uncertainties arising from such applications are poorly understood. We developed equations for both aboveground and belowground biomass using destructive sampling for three dominant upland boreal tree species in northwestern Alberta, Canada. Compared with our equations, the diameter-based national equations derived for use across Canada underestimated aboveground biomass for Picea glauca (Moench) Voss but gave reasonable estimates for Populus balsamifera L. and Populus tremuloides Michx. The national equations based on both tree diameter and height overestimated aboveground biomass for the Populus species but underestimated it for Picea glauca in our study area. The approach of root-to-shoot ratio proposed by the Intergovernmental Panel on Climate Change (IPCC) overestimated belowground biomass by 16%–41%, depending on forest cover type, in comparison with our values estimated directly on site, with the greatest bias in deciduous-dominated stands. When the general allometric equations for aboveground biomass and the root-to-shoot ratio for belowground biomass were combined to estimate stand biomass, overestimation could be as high as 18% in our study area. The results of our study support the development of improved regional allometric equations for more accurate local-scale estimations. Incorporating intraspecific variation of important traits such as tree taper may be especially helpful.

Symbiotic nitrogen (N)-fixing trees can provide large quantities of new N to ecosystems, but only if they are sufficiently abundant. The overall abundance and latitudinal abundance distributions of N-fixing trees are well characterised in the Americas, but less well outside the Americas. Here, we characterised the abundance of N-fixing trees in a network of forest plots spanning five continents, ~5,000 tree species and ~4 million trees. The majority of the plots (86%) were in America or Asia. In addition, we examined whether the observed pattern of abundance of N-fixing trees was correlated with mean annual temperature and precipitation. Outside the tropics, N-fixing trees were consistently rare in the forest plots we examined. Within the tropics, N-fixing trees were abundant in American but not Asian forest plots (~7% versus ~1% of basal area and stems). This disparity was not explained by mean annual temperature or precipitation. Our finding of low N-fixing tree abundance in the Asian tropics casts some doubt on recent high estimates of N fixation rates in this region, which do not account for disparities in N-fixing tree abundance between the Asian and American tropics. Synthesis. Inputs of nitrogen to forests depend on symbiotic nitrogen fixation, which is constrained by the abundance of N-fixing trees. By analysing a large dataset of ~4 million trees, we found that N-fixing trees were consistently rare in the Asian tropics as well as across higher latitudes in Asia, America and Europe. The rarity of N-fixing trees in the Asian tropics compared with the American tropics might stem from lower intrinsic N limitation in Asian tropical forests, although direct support for any mechanism is lacking. The paucity of N-fixing trees throughout Asian forests suggests that N inputs to the Asian tropics might be lower than previously thought.

The enemy‐induced Janzen–Connell (JC) effect, a classic model invoking conspecific negative density dependence (CNDD) and distance dependence, is a primary biodiversity maintenance hypothesis. Yet, conflicting evidence for the JC effect leads to disagreement about its role in maintaining forest diversity. We focus this review on soil‐borne pathogens, which are the primary agent inducing the JC effect in many forest ecosystems. Although the test of the pathogen‐induced JC effect in ecology critically rests on the seedling mortality caused by soil pathogens, what has not been explicitly explored in the early literature but has increasingly received attention is the long‐recognized fact that the environment can alter virulence of pathogens and host susceptibility (thus pathogen–host interactions), as predicted by the classic disease triangle framework enlightened by pathology research in agricultural systems. Here, following the disease triangle framework we review evidence on how the pathogen‐induced JC effect may be contingent on context (e.g. environmental conditions, pathogen inoculum load and genetic divergence in host and pathogen populations). The reviewed evidence reveals and clarifies the conditions where pathogens may or may not cause disease to hosts, thus contributing to reconciling the inconsistent results about the pathogen‐induced JC effect in the literature. The context dependence of the disease triangle predicts that the pathogen‐induced JC effect would change under global change. Gaining insights from evidence that the pathogen‐induced JC effect is context‐dependent, we suggest that future tests on the JC hypothesis be conducted under the framework of disease triangle, and we stress the necessity by controlling the effect of context factors on plant–pathogen interactions when testing for the JC effect. We conclude the review by proposing three lines of future research for testing the importance of the JC effect in maintaining global forest tree species diversity, with a particular emphasis on testing the effect of global warming on the strength of pathogen–host interactions for better predicting changes of forest biodiversity under climate change. A plain language summary is available for this article.

Soil plant-pathogenic (PF) and mycorrhizal fungi (MF) are both important in maintaining plant diversity, for example via host-specialized effects. However, empirical knowledge on the degree of host specificity and possible factors affecting the fungal assemblages is lacking. We identified PF and MF in fine roots of 519 individuals across 45 subtropical tree species in southern China in order to quantify the importance of host phylogeny (including via its effects on functional traits), habitat and space in determining fungal communities. We also compared host specificity in PF and MF at different host-phylogenetic scales. In both PF and MF, host phylogeny independently accounted for > 19% of the variation in fungal richness and composition, whereas environmental and spatial factors each explained no more than 4% of the variation. Over 77% of the variation explained by phylogeny was attributable to covariation in plant functional traits. Host specificity was phylogenetically scale-dependent, being stronger in PF than in MF at low host-phylogenetic scales (e.g. within genus) but similar at larger scales. Our study suggests that host-phylogenetic effects dominate the assembly of both PF and MF communities, resulting from phylogenetically clustered plant traits. The scale-dependent host specificity implies that PF were specialized at lower-level and MF at higher-level host taxa.

In this paper, we proposed a simple and fast matching shape descriptor, a multi-angle shape descriptor with the distance ratio from the contour point to the vertical bounding rectangle(mADR). Shape descriptors are widely used to describe shape features, especially in shape retrieval and shape classification. Contour point is an important feature of shape. The method used in this paper is to find the ratio of distance from contour points to shape vertical bounding rectangle to the average distance. Because vertical bounding rectangle can reflect the position and size information of shape, and can also be used as a feature of shape. In this method, the shape is rotated 360° according to a certain angle respectively, and the vertical bounding rectangle of the shape after each rotation is obtained, then the distance ratio between the contour of all the rotated shapes and the corresponding vertical bounding rectangle is obtained as the shape features. Compared with the traditional shape descriptor based on contour points such as the shape of the distance based on the centroid and contour descriptor (CCD) and based on the shape of the shape context descriptor (SC) has direction characteristic, can distinguish the outline or rough shape similar to the similar shape, have stronger robustness, simpler process and faster matching speed, more importantly, the experiment results show that the shape descriptor has higher retrieval accuracy.

Arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) associations are critical for host-tree performance. However, how mycorrhizal associations correlate with the latitudinal tree beta-diversity remains untested. Using a global dataset of 45 forest plots representing 2,804,270 trees across 3840 species, we test how AM and EcM trees contribute to total beta-diversity and its components (turnover and nestedness) of all trees. We find AM rather than EcM trees predominantly contribute to decreasing total beta-diversity and turnover and increasing nestedness with increasing latitude, probably because wide distributions of EcM trees do not generate strong compositional differences among localities. Environmental variables, especially temperature and precipitation, are strongly correlated with beta-diversity patterns for both AM trees and all trees rather than EcM trees. Results support our hypotheses that latitudinal beta-diversity patterns and environmental effects on these patterns are highly dependent on mycorrhizal types. Our findings highlight the importance of AM-dominated forests for conserving global forest biodiversity., The relationship of mycorrhizal associations with latitudinal gradients in tree beta-diversity is unexplored. Using a global dataset approach, this study examines how trees with arbuscular mycorrhizal and ectomycorrhizal associations contribute to latitudinal beta-diversity patterns and the environmental controls of these patterns.

The island species area relationship (ISAR) is an important tool for measuring variation in species diversity in variety of insular systems, from true-island archipelagoes to fragmented terrestrial landscapes. However, it suffers from several limitations. For example, due to the sample-area effect, positive relationships between species and area cannot be directly interpreted as evidence for deterministic effects of area per se. Additionally, richness-based analyses may obscure species-level responses to area and isolation that may better inform conservation practice. Here, we use random placement models to control for variation in abundance, occupancy and richness associated with the sample-area effect, allowing deterministic effects of area and isolation, and how they vary with species' functional traits, to be resolved using linear mixed effects models. We demonstrate the utility of this approach using a butterfly assemblage persisting on a naturally fragmented landscape of lake islands. The ISAR did not significantly deviate from random placement in relation to island area, isolation or habitat diversity, supporting stochastic assembly consistent with the sample-area effect. Such inferences support the habitat amount hypothesis, which prioritizes preserving the maximum amount of habitat irrespective of its degree of fragmentation. However, species-level analyses demonstrated that species' abundances were significantly lower on both smaller and more isolated islands than what is predicted by the sample-area effect. Moreover, effects of area per se were significantly greater for smaller, less mobile and rare species. Species' occurrences also significantly deviated from predictions of the sample-area effect in relation to island isolation. Thus, our approach illustrates that richness-based analyses not only result in incorrect inferences on mechanisms underlying ISARs, but also obscure important effects of area per se and isolation on individual species that vary with functional traits. We therefore suggest that these effects should not be solely inferred from richness-based analyses, but rather evaluated on a species-by-species basis.

ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.

1. The dissimilarity and hierarchy of trait values that characterize niche and fitness differences, respectively, have been increasingly applied to infer mechanisms driving community assembly and to explain species co-occurrence patterns. Here, we predict that limiting similarity should result in the spatial segregation of functionally similar species, while functionally similar species will be more likely to co-occur together either due to environmental filtering or competitive exclusion of inferior competitors (hereafter hierarchical competition). 2. We used a fully mapped 50-ha subtropical forest plot in southern China to explore how pairwise spatial associations were influenced by trait dissimilarity and hierarchy between species in order to gain insight into assembly mechanisms. We assessed pairwise spatial associations using two summary statistics of spatial point patterns at different spatial scales and compared the effects of trait dissimilarity and trait hierarchy of different functional traits on the interspecific spatial associations. These comparisons allow us to disentangle the effects of limiting similarity, environmental filtering and hierarchical competition on species co-occurrence. 3. We found that trait dissimilarity was generally negatively correlated with interspecific spatial associations, meaning that species with similar trait values were more likely to co-occur together and thus supporting environmental filtering or hierarchical competition. We further found that leaf area, wood density and maximum height had stronger trait hierarchy effects on the pairwise spatial associations relative to their corresponding trait dissimilarity effects, which suggests that hierarchical competition played a more (or at least equally) important role in structuring our forest community compared to environmental filtering. 4. This study employed a novel method to disentangle the relative importance of multiple assembly mechanisms in structuring co-occurrence patterns, especially the mechanisms of environmental filtering and hierarchical competition, which lead to indistinguishable co-occurrence patterns. This study also reinforced the importance of trait hierarchy rather than trait dissimilarity in driving neighborhood competition.

The scandent shrub plant form is a variant of liana that has upright and self-supporting stems when young but later becomes a climber. We aimed to explore the associations of stem and leaf traits among sympatric lianas, scandent shrubs and trees, and the effects of growth form and leaf habit on variation in stem or leaf traits. We measured 16 functional traits related to stem xylem anatomy, leaf morphology and nutrient stoichiometry in eight liana, eight scandent shrub and 21 tree species co-occurring in a subalpine cold temperate forest at an elevation of 2600–3200 m in Southwest China. Overall, lianas, scandent shrubs and trees were ordered along a fast–slow continuum of stem and leaf functional traits, with some traits overlapping. We found a consistent pattern of lianas > scandent shrubs > trees for hydraulically weighted vessel diameter, maximum vessel diameter and theoretical hydraulic conductivity. Vessel density and sapwood density showed a pattern of lianas = scandent shrubs < trees, and lianas < scandent shrubs = trees, respectively. Lianas had significantly higher specific leaf area and lower carbon concentration than co-occurring trees, with scandent shrubs showing intermediate values that overlapped with lianas and trees. The differentiation among lianas, scandent shrubs and trees was mainly explained by variation in stem traits. Additionally, deciduous lianas were positioned at the fast end of the trait spectrum, and evergreen trees at the slow end of the spectrum. Our results showed for the first time clear differentiation in stem and leaf traits among sympatric liana, scandent shrub and tree species in a subalpine cold temperate forest. This work will contribute to understanding the mechanisms responsible for variation in ecological strategies of different growth forms of woody plants.

Population density is the most basic ecological parameter for understanding population dynamics and biological conservation. Distance-based methods (or plotless methods) are considered as a more efficient but less robust approach than quadrat-based counting methods in estimating plant population density. The low robustness of distance-based methods mainly arises from the oversimplistic assumption of completely spatially random (CSR) distribution of a population in the conventional distance-based methods for estimating density of non-CSR populations in natural communities. In this study we derived two methods to improve on density estimation for plant populations of non-CSR distribution. The first method modified an existing composite estimator to correct for the long-recognized bias associated with that estimator. The second method was derived from the negative binomial distribution (NBD) that directly deals with aggregation in the distribution of a species. The performance of these estimators was tested and compared against various distance-based estimators by both simulation and empirical data of three large-scale stem-mapped forests. Results showed that the NBD point-to-tree distance estimator has the best and most consistent performance across populations with vastly different spatial distributions. This estimator offers a simple, efficient and robust method for estimating density for empirical populations of plant species.

Understanding the mechanisms that shape the geographic distribution of plant species is a central theme of biogeography. Although seed mass, seed dispersal mode and phylogeny have long been suspected to affect species distribution, the link between the sources of variation of these attributes and their joint effects to the distribution of seed plants remain poorly documented. This study aims to quantify the joint effects of key seed traits and phylogeny on the species' distribution. We collected seed mass and seed dispersal mode from 1,616 species of seed plants representing 554 genera of 130 families. We used 5,639,009 specimens to calculate species range size through ArcGIS10.2. Phylogenetic generalized least squares regression modeling and variation partitioning were performed to estimate the joint effects of seed mass, seed dispersal mode and phylogeny on species distribution. We found that species range size was constrained by seed dispersal mode and phylogeny. Seed mass and its intraspecific variation were also important in limiting species distribution, but their effects were different among species with different dispersal modes. Variation partitioning revealed that seed mass, seed mass variability, seed dispersal mode and phylogeny together explained 40.44 % of the variance in species range size. Seed traits are not typically used to model the geographic distributions of seed plants. This study provides direct evidence that seed mass, seed dispersal modes and phylogeny explain species distribution variation on a large geographic scale. Our findings underscore the necessity to include seed traits and the phylogenetic history of species, together with existing climate-based niche models, in predicting the response of plant geographic distribution to climate change.

Top-down and bottom-up controls regulate the structure and stability of ecosystems, but their relative roles in terrestrial systems have been debated. Here we studied a hydro-inundated land-bridge system in subtropical China and tested the relative importance of these two controls in determining the rodent-mediated regeneration of a locally dominant tree species. Our results showed that both controls operated in terrestrial habitats and that their relative importance switched as habitat size changed. Habitat loss initially removed predators of rodents that released rodent populations and triggered massive seed predation (top-down control), leading to reduced seedling establishment. A further reduction in habitat size led to decrease in rodent population that was supposed to increase seedling survival of the tree species, but the decline in habitat size deteriorated the abiotic environments (bottom-up control) that severely prevented seedling recruitment. As the ongoing global land use change is creating increasing number of small-sized forest fragments, our findings provide novel insights into the restoration of seriously fragmented forests.

AIM: The Tibetan Plateau harbours the highest alpine and endemic plant diversity in the world, attributed to rapid diversification during the plateau uplift and Quaternary climate fluctuations. However, there is little understanding of which hypotheses associated with these geological and climatic processes garner strong support as explanations for the observed diversity patterns. Here, we test support for hypotheses related to uplift and climate changes that could account for the high endemicity and phylogenetic diversity of the world’s highest plateau. LOCATION: Tibetan Plateau (TP). TIME PERIOD: Neogene, Quaternary and current period. MAJOR TAXA STUDIED: Tibetan endemic seed plants. METHODS: We collated data on endemic seed‐plant distribution based on county‐level mapping from published monographs and online databases. We calculated species richness (SR) and phylogenetic diversity for endemic herbs, shrubs, trees, and all plants for 0.5‐degree × 0.5‐degree grid cells covering the TP. We derived environmental and evolutionary predictors to evaluate eight biogeographical hypotheses associated with plateau uplift and climate fluctuations, and used partial regression analysis and mixed conditional autoregressive (CAR) models to assess the relative contribution of each predictor to the extant diversity of the TP. RESULTS: We found plateau uplift independently explained more variance in diversity than climate fluctuations, but there were also strong interaction effects. The full CAR models including all predictors explained 37%–75% of the total variation across diversity measures and life forms. The predictor representing the montane museum hypothesis explained the most variation (c. 25%), but each predictor explained at least 6%. MAIN CONCLUSIONS: These results demonstrate that both the plateau uplift and Quaternary climate fluctuations had large impacts on current patterns of species diversity, but the influence of plateau uplift was more pronounced than that of climate changes. Our study suggests that plateau uplift and climate changes are the original drivers of complex biogeographical processes accounting for the biodiversity of the TP.

1. Although nitrogen‐fixing plants play a crucial role in maintaining high ecosystem productivity, their effects on forest diversity are greatly debated. Legumes can reduce local diversity because of the fertilization effect; however, they can also facilitate species coexistence through complementary resource utilization. 2. In natural forests, nitrogen requirements and biological nitrogen fixation (BNF) vary widely among legumes. We used leaf nitrogen isotopic composition to differentiate the level of BNF activity among seven legumes across a steep gradient of soil available nitrogen within a 60‐ha stem‐mapping plot in a montane tropical rainforest in Hainan Island, China, and we evaluated their spatial distribution and neighbourhood diversity. 3. Results show that the levels of BNF activity are tightly correlated with legume association to available soil nitrogen, where legumes associated with nitrogen‐rich habitats exhibit surprisingly greater BNF activity and a more diverse neighbourhood. 4. Synthesis. These findings indicate that legumes satisfy their nitrogen‐demanding metabolism through a synergy of habitat preference and BNF activity. High BNF activity drives local diversity by promoting complementary resource utilization rather than intensifying above‐ground competition. This may be achieved by improving litter quality and stimulating mycorrhizal and microbial diversity. The abundance of nitrogen fixers in nitrogen‐rich habitats also explains how legumes contribute to maintaining high levels of soil nitrogen in tropical forests.

Long-term sustainability of forest resources is in question given wide-spread use of conventional clear-cut silviculture. In response, variable retention (VR) harvest has been increasingly promoted as a landscape-based approach to enhance sustainability by maintaining biodiversity and other ecosystem functions in managed forests. Although the success of the VR approach depends on post-harvest stand dynamics, little is known about growth and mortality of residual trees after harvest and how such trees respond to interactions between amount of retention and tree or site level covariates. We use data from three censuses distributed over a 10-year period of the main merchantable species to study the effects of retention level (i.e., percent of trees retained), mixedwood cover type, tree species, and three tree or terrain covariates (tree stem diameter, percent live crown, and soil wetness) on survival and growth of residual trees in a retention harvest experiment in NW Alberta, Canada. Both mortality and growth of residual trees were negatively related to retention levels. During the first five-year period after harvest, effects of retention levels on mortality were more evident for white spruce (Picea glauca) than for Populus spp., but effects on growth were weaker for white spruce. Tree mortality decreased through time following VR harvest for all species and in most cover types, while trends in tree growth varied by species. During the second five-year period after harvest, growth of residual Populus spp. had decreased from high levels observed in the first period. In contrast, growth of residual white spruce was greater in the second five-year period than in the first period. After the original harvest, re-entry of stands for additional harvest focused mainly on hardwoods may be economically rewarding and ecologically justified, depending on the overall objectives for retention. The positive effect of increased retention level on tree survival was strongest for trees with larger diameter and longer crowns. Thus, retention patches are a management option to protect large trees and trees with greater crown length when retaining such trees is a management goal.

Spatial processes underlie major species coexistence mechanisms. A range of spatial analysis techniques are increasingly applied to data of fully mapped communities to quantify spatial structures in species and phylogenetic and functional diversity at some given spatial scale with the goal of gaining insights into processes of community assembly and dynamics. We review these techniques, including spatial point pattern analysis, quadrat-based analyses, and individual-based neighborhood models, and provide a practical roadmap for ecologists in the analysis of local spatial structures in species and phylogenetic and functional diversity. We show how scale-dependent metrics of spatial diversity can be used in concert with ecological null models, statistical models, and dynamic community simulation models to detect spatial patterns, reveal the influence of the biotic neighborhood on plant performance, and quantify the relative contribution of species interactions, habitat heterogeneity, and stochastic processes to community assembly across scale. Future works should integrate these approaches into a dynamic spatiotemporal framework.

Local spatial variation in species distributions is driven by a mix of abiotic and biotic factors, and understanding such hierarchical variation is important for conservation of biodiversity across larger scales. We sought to understand how variation in species composition of understory vascular plants, spiders, and carabid beetles is associated with concomitant spatial variation in forest structure on a 1-ha permanent plot in a never-cut mixedwood forest in central Alberta (Canada). Using correlations among dendrograms produced by cluster analysis we associated data about mapped distribution of all living and dead stems > 1 cm diameter at breast height with distributions of the three focal taxa sampled from regular grids across the plot. Variation in each of these species assemblages were significantly associated with several forest structure variables at various spatial scales, but the scale of the associations varied among assemblages. Variation in species richness and abundance was explained mostly by changes in basal area of trees across the plot; however, other variables (e.g., snag density and tree density) were also important, depending on assemblage. We conclude that fine-scale habitat variation is important in structuring spatial distribution of the species of the forest floor, even within a relatively homogeneous natural forest. Thus, assessments that ignore within-stand heterogeneity and management that ignores its maintenance will have limited utility as conservation measures for these taxa, which are major elements of forest biodiversity. This article is protected by copyright. All rights reserved.

Maintaining tree diversity Negative interaction among plant species is known as conspecific negative density dependence (CNDD). This ecological pattern is thought to maintain higher species diversity in the tropics. LaManna et al. tested this hypothesis by comparing how tree species diversity changes with the intensity of local biotic interactions in tropical and temperate latitudes (see the Perspective by Comita). Stronger local specialized biotic interactions seem to prevent erosion of biodiversity in tropical forests, not only by limiting populations of common species, but also by strongly stabilizing populations of rare species, which tend to show higher CNDD in the tropics. Science , this issue p. 1389 ; see also p. 1328

Quantifying the risk of extinction due to habitat loss is an increasingly urgent task for the design and implementation of effective conservation interventions. Methods based on species- and endemics-area relationships are well developed, but applications to date have concentrated primarily on the fragmentation of formerly continuous habitats such as forests and woodlands. Applying these area-based methods to predict extinction risk in habitat types occurring naturally as spatially discrete patches has been largely ignored. We address this knowledge gap using a network of seasonally connected wetlands. We modelled the risk of extinction associated with native wetland plant communities under two alternative scenarios: the loss of ( i ) entire wetlands ( patch loss ) versus ( ii ) an equivalent area distributed across the wetlands ( area loss ). Patch-loss scenarios resulted in more than twice the number of species going extinct than the equivalent loss of area. Extinction due to patch loss was highest when wetlands were removed in increasing size order (smallest to largest) – a plausible scenario arising from forecast climatic drying in the region. Small wetlands contained > 16% of endemic species in only

Aim The estimation of regional species richness has been a major challenge in ecology but is crucial for setting up conservation priorities. Discovery curves are a principal tool for estimating regional richness, but they have been criticized for being too sensitive to historical fluctuations in species discovery. In this study we propose a new discovery model that considers historical influences. We have applied the model to estimate the number of vascular plant species in China, a country of mega-biodiversity that has also suffered endless wars and social turmoil in its modern history. Location China. Time period 1755–2000. Major taxa studied Vascular plant species. Methods We compiled the discovery time for each vascular species from the complete volumes of Flora of China, leading to 31,220 valid species names. We applied our model to these data and compared the performance of our model with existing discovery models and two other methods (species–area relationships and a taxonomic rank curve model). We also tested our model with three other independent datasets and one simulation study. Results Our new method estimated there to be 36,554 (± 2,708) vascular plant species in China. Our model accounted very well for the effect of historical events and was robust to different periods of data that were used to estimate the total richness. Our model outperformed all other models that were compared. We found that 5,334 species remained to be discovered in China and it would take about 50 years to discover all the species should the current discovery rate of 110 species per year persist. Main conclusions Species discovery curves, with historical effects being properly accounted for, offer a promising tool for estimating regional species richness. Our model is robust to the effect of historical events and provides by far the most accurate and reliable estimates of species richness of test data, including vascular plant richness in China.

Temporal dynamics of plant-pollinator interactions inform the mechanisms of community assembly and stability. However, most studies on the dynamics of pollination networks do not consider plant reproductive traits thus offering poor understanding of the mechanism of how networks maintain stable structure under seasonal changes in flower community. We studied seasonal dynamics of pollination networks in a subtropical monsoon forest in China with a clear rainy season (April-September) and dry season (October-March) over 2 consecutive years. We constructed dioecy-ignored networks (combining visitations to dioecious male and female plants by ignoring the difference between dioecious and hermaphroditic plants) and dioecy-considered networks (excluding those visitations that only occurred either on dioecious male or female plants) for eight sampling sessions for each season. Although flower richness and flower abundance were higher in the rainy season than in the dry season, no pronounced seasonal difference was found in network specialization, nestedness and modularity for both networks. There were only significant differences in plant community robustness and pollinator specialization between seasons for dioecy-considered networks but not for dioecy-ignored networks. Furthermore, we found the flower abundance of dioecious and hermaphrodite plants mostly showed trade-off variation between rainy and dry seasons. Our results suggest various plant reproductive traits affect the temporal dynamics of pollination networks, which should be considered for conservation of plant-pollinator interactions in forest communities.

Climate change could alter plant aboveground and belowground resource allocation. Compared with shoots, we know much less about how roots, especially root system architecture (RSA) and their interactions, may respond to temperature changes. Such responses could have great influence on species'acquisition of resources and their competition with neighbors. We used a gel-based transparent growth system to in situ observe the responses of RSA and root interactions of three common subtropical plant species seedlings in Asia differing in growth forms (herb, shrub, and tree) under a wide growth temperature range of 18-34°C, including low and supra-optimal temperatures. Results showed that the RSA, especially root depth and root width, of the three species varied significantly in response to increased temperature although the response of their aboveground shoot traits was very similar. Increased temperature was also observed to have little impact on shoot/root resource allocation pattern. The variations in RSA responses among species could lead to both the intensity and direction change of root interactions. Under high temperature, negative root interactions could be intensified and species with larger root size and fast early root expansion had competitive advantages. In summary, our findings indicate that greater root resilience play a key role in plant adapting to high temperature. The varied intensity and direction of root interactions suggest changed temperatures could alter plant competition. Seedlings with larger root size and fast early root expansion may better adapt to warmer climates.

There is mounting evidence that many taxa respond in non-linear ways to perturbation (i.e. deviations from a natural trajectory brought on by an external agent), and many statistical, physical and ecological methods have been developed to detect the critical points or thresholds of perturbation. The majority of these methods define thresholds as the perturbation points causing abrupt ecological response, but in reality most species or ecosystems do not show a break point response but more gradual transitional change to perturbation. We develop a new method which delineates thresholds as a region in which the slope of the relationship between ecological response (y) and perturbation (x; e.g. habitat loss) is larger than 1: |dy/dx|≥1, where both x and y-axes are scaled to (0, 1) range. The lower end of threshold zones so defined is of particular ecological interest because it is the smallest x that may trigger impending catastrophic response to a small change in x. We derived two landscape models (edge length and the number of patches of species distribution) and two biodiversity models (endemics-area relationship and half-population curve) to test this method. We applied our zonal thresholding method to these four models fit to empirical data of two forest plots to detect thresholds of species distribution to habitat loss. The two landscape metric models predict that no species could tolerate more than 40% of habitat loss and these thresholds can be much lower for relatively rare species with occupancy

Aim Protected areas are an important tool for conserving species. In this study, we assessed the effectiveness of protected areas to conserve amphibian biodiversity in response to future changes in climate and land use. Location China. Methods Range maps and occurrence records of amphibian species in China were analysed separately using ensemble species distribution modelling across three spatial scales to assess scale dependency. Climate velocity and corresponding residence time in protected areas and species’ ranges were calculated, together with a number of other effectiveness indices. Results Predicted declines in amphibian richness, endemism, phylogenetic diversity, phylogenetic endemism and suitable habitat were lower in protected than in unprotected areas, complementary-priority sites or richness hotspots. However, less-disturbed amphibian habitat, calculated from current and future projected land use data, in both protected and unprotected areas were consistently lost over time although this reduction was lower in protected areas. Although residence time of precipitation was longer in protected areas and within species’ ranges in protected areas, resident time of temperature was significantly shorter in both. These results were consistent regardless of data sources and spatial scales. Main conclusions China's current protected areas are predicted to maintain future amphibian distribution and diversity, but are insufficient in preventing the losses of suitable climate and areas of less-disturbed habitat. The top 10% of future conservation gaps for amphibians were identified in China based on performance of effectiveness indices. The two largest gaps prioritized for future protected areas include the southern parts of Tibet and the Hengduan Mountains.

In cleared landscapes, wetlands can represent important reservoirs of native plant diversity, which include terrestrial species. Depending on study aims, non-wetland plants might be removed before analysis, affecting conclusions around biodiversity and community structure. We compared the native plant communities of seasonal wetlands in a predominately agricultural landscape as defined geographically (including all species) with that of the obligate wetland assemblage. We were primarily concerned with determining how this design decision affects ecological and conservation conclusions. We analysed a survey database containing >12,900 flora records from South Australia, developing a new area-based method to remove sampling bias to include only wetlands with a near-complete census. We modelled occupancy, species-area relationships, β-diversity and nestedness under our contrasting community definitions. Terrestrial species were 57.4 % of total richness. Removing these species reduced wetland α-diversity by 45 %, but did not affect the scaling of richness with area (power-law species-area relationship z = 0.21 ± 0.01). Occupancies for wetland plants were relatively uniform, but were heavily dominated by rare (satellite) species when terrestrial plants were included, and this also increased β-diversity. Nestedness for terrestrial species occupancies was marginally lower than predicted under null models, suggesting that rare species often do not co-occur with common species. An implication of these occupancy patterns is that twice as many wetlands (and 50 % more wetland area) would be needed to include every native species within at least one wetland compared with wetland-only species.

In tropical plant communities with diverse species, many congeners are found to coexist. Do environment or biotic interactions structure the coexistence of congeners in tropical forest communities? In this paper, we aimed to disentangle the effect of environment (first-order effects) and species interactions (second-order effects) on the spatial distributions of tree species. We used a classification scheme and torus-translation to test the first-order interaction of 48 species from 17 genera in a fully mapped 20-ha dipterocarp tropical seasonal rain-forest plot in Xishuangbanna, south-west China. Then we used heterogeneous Poisson null models to reveal significant uni- and bivariate second-order interactions. The results demonstrated that (1) 34 of the 48 studied species showed a significant relation with at least one topographic variable. This confirmed that topographical heterogeneity is important for distribution of these congeners. Spatial segregation (36.6%) and partial overlap (34.8%) were the most common bivariate association types in Xishuangbanna plot, which indicated first-order effects (environment) were strong. (2) For small-scale associations, 51% saplings (1 to ≤ 5 cm) (68.8% for large trees with dbh > 5 cm) of the species showed non-significant associations. For large-scale associations, 61.6% saplings (81.2% for large trees) of the species showed non-significant associations. Lack of significant species interactions provides evidence for the unified neutral theory. In conclusion, both environment and biotic interactions structure congeneric species' coexistence in tropical seasonal rain forest in this region.

Several small habitat patches typically contain more species than a single large patch of comparable area. This pattern has fueled controversy over reserve design (the SLOSS debate); yet its causes remain poorly understood, limiting discussion of any broader biodiversity implications. Using 44 published faunal metacommunity datasets from fragments, islands and habitat islands, we test four hypotheses to explain differences in species richness (SRd) between several small patches and a single large patch: (i) beta diversity (BD); (ii) evenness of species abundance distributions (EV); (iii) size bias in sampling efficiency (SE); and (iv) taxonomy. We used individual-based null models and confirmatory path analysis to compare direct and indirect support for these non-exclusive hypotheses. Broad taxonomic grouping (invertebrates > birds = non-volant vertebrates) accounted for most of the variation in SRd, while BD, EV and SE had smaller, but comparable, direct effects (standardized coefficients = 0.42, 0.31 and −0.26 respectively). Within a taxonomic group, larger SRd occurred when both BD and EV increase. Although sampling bias probably overstates the difference in SRd, it does not explain the pattern. Beyond reserve design, the SLOSS pattern implies potential principles for managing biodiversity in fragmented landscapes. Whether this pattern should inform conservation requires greater understanding. We confirm beta diversity is the major contributor, but it is mediated by increases and decreases in evenness among small patches. Attention to how sub-division alters relative abundances (e.g., by biotic relaxation or altering competitive outcomes) might help clarify how the SLOSS pattern arises.

Significance Human impacts and climatic changes are widely considered to be responsible for rapid species extinction. However, determining their effects is challenging owing to the lack of long-term spatial–temporal data. In this study, we quantified the distinctive associations of anthropogenic and climatic stressors with the local extinction of 11 medium- or large-sized mammals using historical records over the past 3 centuries. We found that the increased local extinction of mammals was associated with intensified human disturbance (particularly for large-sized mammals) and with extreme temperature change (both cooling and warming). Our results provide insight into biodiversity conservation during the Anthropocene., Accelerated anthropogenic impacts and climatic changes are widely considered to be responsible for unprecedented species extinction. However, determining their effects on extinction is challenging owing to the lack of long-term data with high spatial and temporal resolution. In this study, using historical occurrence records of 11 medium- to large-sized mammal species or groups of species in China from 905 BC to AD 2006, we quantified the distinctive associations of anthropogenic stressors (represented by cropland coverage and human population density) and climatic stressors (represented by air temperature) with the local extinction of these mammals. We found that both intensified human disturbances and extreme climate change were associated with the increased local extinction of the study mammals. In the cold phase (the premodern period of China), climate cooling was positively associated with increased local extinction, while in the warm phase (the modern period) global warming was associated with increased local extinction. Interactive effects between human disturbance and temperature change with the local extinction of elephants, rhinos, pandas, and water deer were found. Large-sized mammals, such as elephants, rhinos, and pandas, showed earlier and larger population declines than small-sized ones. The local extinction sensitivities of these mammals to the human population density and standardized temperature were estimated during 1700 to 2000. The quantitative evidence for anthropogenic and climatic associations with mammalian extinction provided insights into the driving processes of species extinction, which has important implications for biodiversity conservation under accelerating global changes.

Plant–herbivore interaction networks provide information about community organization. Two methods are currently used to document pairwise interactions among plants and insect herbivores. One is the traditional method that collects plant–herbivore interaction data by field observation of insect occurrence on host plants. The other is the increasing application of newly developed molecular techniques based on DNA barcodes to the analysis of gut contents. The second method is more appealing because it documents realized interactions. To construct complete interaction networks, each technique of network construction is urgent to be assessed. We addressed this question by comparing the effectiveness and reliability of the two methods in constructing plant–Lepidoptera larval network in a 50 ha subtropical forest in China. Our results showed that the accuracy of diet identification by observation method increased with the number of observed insect occurrences on food plants. In contrast, the molecular method using three plant DNA markers were able to identify food residues for 35.6% larvae and correctly resolved 77.3% plant (diet) species. Network analysis showed molecular networks had threefold more unique host plant species but fewer links than the traditional networks had. The molecular method detected plants that were not sampled by the traditional method, for example, bamboos, bryophytes and lianas in the diets of insect herbivores. The two networks also possessed significantly different structural properties. Our study indicates the traditional observation of co‐occurrence is inadequate, while molecular method can provide higher species resolution of ecological interactions.

Uncertainties in the estimation of tree biomass carbon storage across large areas pose challenges for the study of forest carbon cycling at regional and global scales. In this study, we attempted to estimate the present aboveground biomass (AGB) in Alberta, Canada, by taking advantage of a spatially explicit data set derived from a combination of forest inventory data from 1968 plots and spaceborne light detection and ranging (lidar) canopy height data. Ten climatic variables, together with elevation, were used for model development and assessment. Four approaches, including spatial interpolation, non-spatial and spatial regression models, and decision-tree-based modeling with random forests algorithm (a machine-learning technique), were compared to find the "best" estimates. We found that the random forests approach provided the best accuracy for biomass estimates. Non-spatial and spatial regression models gave estimates similar to random forests, while spatial interpolation greatly overestimated the biomass storage. Using random forests, the total AGB stock in Alberta forests was estimated to be 2.26 × 109 Mg (megagram), with an average AGB density of 56.30 ± 35.94 Mg ha−1. At the species level, three major tree species, lodgepole pine, trembling aspen and white spruce, stocked about 1.39 × 109 Mg biomass, accounting for nearly 62% of total estimated AGB. Spatial distribution of biomass varied with natural regions, land cover types, and species. Furthermore, the relative importance of predictor variables on determining biomass distribution varied with species. This study showed that the combination of ground-based inventory data, spaceborne lidar data, land cover classification, and climatic and environmental variables was an efficient way to estimate the quantity, distribution and variation of forest biomass carbon stocks across large regions.

The relationship between β-diversity and latitude still remains to be a core question in ecology because of the lack of consensus between studies. One hypothesis for the lack of consensus between studies is that spatial scale changes the relationship between latitude and β-diversity. Here, we test this hypothesis using tree data from 15 large-scale forest plots (greater than or equal to 15 ha, diameter at breast height ≥ 1 cm) across a latitudinal gradient (3–30 o ) in the Asia-Pacific region. We found that the observed β-diversity decreased with increasing latitude when sampling local tree communities at small spatial scale (grain size ≤0.1 ha), but the observed β-diversity did not change with latitude when sampling at large spatial scales (greater than or equal to 0.25 ha). Differences in latitudinal β-diversity gradients across spatial scales were caused by pooled species richness (γ-diversity), which influenced observed β-diversity values at small spatial scales, but not at large spatial scales. Therefore, spatial scale changes the relationship between β-diversity, γ-diversity and latitude, and improving sample representativeness avoids the γ-dependence of β-diversity.

Aim (1) To understand geographic patterns of species discovery by examining the effect of growth form, range size, and geographic distribution on discovery probability of vascular plant species in China; (2) to find out which taxa harbor the largest number of undiscovered species and where those species locate; and (3) to find out the determinants of province‐level mean discovery time and inventory completeness. Location China. Methods We compiled the discovery time and province‐level geographic distributions of ~31,000 vascular plant species described between 1753 and 2013 from Flora of China. We used a Cox proportional hazard model to determine the biological and geographic correlates of discovery probability. Accumulation curves of species discoveries were fitted by a logistic discovery model to estimate inventory completeness of different growth forms and of different provinces. We then used linear regression to identify the determinants of mean discovery time and beta regression to identify the determinants of inventory completeness. Results We found that species with larger range size and distributed in northeastern part of China have a higher discovery probability. Coastal species were discovered earlier than inland species. Trees and shrubs of seed plants have the highest discovery probability while ferns have the lowest discovery probability. Herbs have the largest number of undiscovered species in China. Most undiscovered species will be found in southwest China, where three global biodiversity hot spots locate. Spatial patterns of mean discovery time and inventory completeness are mainly driven by the total number of species, human population density in an area, and latitude and longitude of a province. Main Conclusions Socioeconomic factors primarily determine the discovery patterns of vascular plants in China. Undiscovered species are most likely to be narrow‐ranged, inconspicuous endemic species such as herbs and ferns, which are prone to extinctions and locate in biodiversity hot spots in southwestern China., Botanical discoveries in China were shaped by historical events and socioeconomic factors, and driven by plant species' range size and growth forms. We highlight that ferns and herbs are the most underdiscovered groups, and future discoveries are most likely to be made in the southwestern China.

Hülsmann and Hartig suggest that ecological mechanisms other than specialized natural enemies or intraspecific competition contribute to our estimates of conspecific negative density dependence (CNDD). To address their concern, we show that our results are not the result of a methodological artifact and present a null-model analysis that demonstrates that our original findings—(i) stronger CNDD at tropical relative to temperate latitudes and (ii) a latitudinal shift in the relationship between CNDD and species abundance—persist even after controlling for other processes that might influence spatial relationships between adults and recruits.

Under many global-change scenarios, small habitat patches are the most vulnerable to destruction. For example, smaller ponds are at greater risk in a drying climate and their loss would remove any obligate aquatic individuals present. We asked what proportional loss of species diversity from metacommunities comprised of discrete habitat patches should be expected from attrition (complete loss) of only the smallest patches under such a premise. We analyzed 175 published datasets for different taxonomic groups (vertebrates, invertebrates, and plants) and habitat types (islands, habitat islands, and fragments). We simulated the destruction of only the smallest patches to an approximate 20% of total area (range: 15.2%-24.2%) and analyzed species loss. Mean [± 95% CI] species loss was 12.7% [10.8, 14.6], although 18.3% of datasets lost no species. Four broad patterns of species loss were evident, reflecting underlying differences in minimum area requirements and the degree of species turnover among patches. Regression modeling showed species loss increased with greater species turnover among patches (βSIM ) and decreased with greater area scaling of diversity (i.e., larger power-law island species-area relationship exponents). Losses also increased with greater numbers of single-patch endemics and with increasing proportions of patches destroyed. After accounting for these predictors, neither taxonomic group nor habitat type increased explained variation in species loss. Attrition of the smallest patches removed species in >80% of metacommunities, despite all larger patches and >75% of total area remaining intact. At both 10% and 20% area reduction, median species loss across all datasets was around 50% higher than predicted from methods based on the species-area relationship. We conclude that any mechanism of global change that selectively destroys small habitat patches will lead to imminent extinctions in most discrete metacommunities.

Premise of the study Habitat filtering and non-habitat processes are two major processes affecting spatial distributions of species. Because trees at different life stages perform differently, the life stage of tree species could play an important role in shaping the spatial distribution of species and community assembly. Here, we examined the possible changes of spatial distributions of species and evaluated the shifts in the relative importance of habitat filtering and non-habitat processes across life stages in a 50-ha subtropical forest plot in China. Methods We modeled species distribution with and without life stages using three point process models. The performance of these models, with and without considering life stages, was evaluated by comparing the species-area curve and the degree of clustering. The relative effects of habitat filtering and non-habitat processes across life stages were quantified using a spatial variance decomposition method. Key results The incorporation of life stage considerably improved the goodness-of-fit of these point process models at both the community and species levels. Non-habitat processes explained about 90% of the total variation in spatial distribution, while habitat filtering explained about 10%. The relative importance of habitat filtering only increased slightly from sapling to adult stages. Conclusions Point process models performed better when life stages are included, indicating the importance of considering life stage when modeling spatial distributions for understanding community assembly. The finding that habitat acts weakly and non-habitat processes act dominantly in determining spatial distributions of species suggests a strong dependence of spatial patterns on non-habitat processes.

The need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (Mtot ) and stand age (a). The authors of that study concluded that the length of the growing season (lgs ) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re-analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum-likelihood model selection, independent-effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by Mtot combined with climate variables and supported strong and direct influences of climate independently of Mtot , both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that lgs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (Tann and Pann ), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale.

Summary 1. The extent to which tropical rain forests recover tree species richness, composition and community structure after clear-cutting or selective harvest is controversial. Thus, the conservation value of forests regenerated after harvest remains unclear, but critically important for biodiversity. 2. We sampled trees from 164 25 9 25 m quadrats across a 160-km 2 tropical rain forest landscape on Hainan Island, China, which had been clear-cut or selectively harvested and left to recover without management for up to 50 years. Species richness and species abundance distributions were compared among five successional categories to investigate changes in species richness and species abundance over time. Basal areas and three different species similarity indices were compared to reveal temporal changes in species composition and community structure. 3. Species richness recovered faster than species composition and structure in both selectively logged and clear-cut forests. Both total number of species and number of rare species tended to increase from younger harvested forests through older harvested forests to old-growth intact forests. Within 20–40 years after harvest species composition of harvested forests tended towards that of old-growth forests, community similarity between harvested and oldgrowth forests decreased subsequently and basal area did not recover, given even a half-century of succession undisturbed by anthropogenic forces. 4. Shortly after harvest, pioneer species increased rapidly, but shade-tolerant species required much more time to recover to former abundances. The shift from pioneer species to shadetolerant species indicates significant recovery of logged forests. 5. Selectively logged forests recovered more quickly and had higher conservation values than clear-cut forests. 6. Synthesis and applications. Our findings indicate that logged tropical forests only partially recovered the characteristics of pre-harvest, primary forest after a half-century of succession. Recovery of the original tree biodiversity on such post-harvest landscapes will be slow at best, if measured by species composition or stand structure. Our study amplifies the importance of conserving tropical forest integrity and developing harvest and management approaches that facilitate full recovery of logged tropical forests.

Niche-driven effects on demographic processes generated in response to habitat heterogeneity partly shape local distributions of species. Thus, tree distributions are commonly studied in relation to habitat conditions to understand how niche differentiation contributes to species coexistence in forest communities. Many such studies implicitly assume that local abundance reflects habitat suitability, and that abundance is relatively stable over time. We compared models based on abundance with those based on demographic performance for making inferences about habitat association for 287 tree species from three large dynamic plots located in tropical, subtropical and temperate forests. The correlation between the predictions of the abundance-based models and the demography-based models varied widely, with correlation coefficients ranging nearly from –1 to 1.This suggests that the two types of models capture different information about species–habitat associations. Demography-based models evaluate habitat quality by focusing on population processes and thus should be preferred for understanding responses of tree species to habitat conditions, especially when habitat conditions are changing and species–habitat interactions cannot be considered to be at equilibrium.

The challenge of biodiversity upscaling, estimating the species richness of a large area from scattered local surveys within it, has attracted increasing interest in recent years, producing a wide range of competing approaches. Such methods, if successful, could have important applications to multi-scale biodiversity estimation and monitoring. Here we test 19 techniques using a high quality plant data set: the GB Countryside Survey 1999, detailed surveys of a stratified random sample of British landscapes. In addition to the full data set, a set of geographical and statistical subsets was created, allowing each method to be tested on multiple data sets with different characteristics. The predictions of the models were tested against the “true” species–area relationship for British plants, derived from contemporaneously surveyed national atlas data. This represents a far more ambitious test than is usually employed, requiring 5–10 orders of magnitude in upscaling. The methods differed greatly in their performance; while there are 2,326 focal plant taxa recorded in the focal region, up-scaled species richness estimates ranged from 62 to 11,593. Several models provided reasonably reliable results across the 16 test data sets: the Shen and He and the Ulrich and Ollik models provided the most robust estimates of total species richness, with the former generally providing estimates within 10% of the true value. The methods tested proved less accurate at estimating the shape of the species–area relationship (SAR) as a whole; the best single method was Hui's Occupancy Rank Curve approach, which erred on average by

Climate is widely recognised as an important determinant of the latitudinal diversity gradient. However, most existing studies make no distinction between direct and indirect effects of climate, which substantially hinders our understanding of how climate constrains biodiversity globally. Using data from 35 large forest plots, we test hypothesised relationships amongst climate, topography, forest structural attributes (stem abundance, tree size variation and stand basal area) and tree species richness to better understand drivers of latitudinal tree diversity patterns. Climate influences tree richness both directly, with more species in warm, moist, aseasonal climates and indirectly, with more species at higher stem abundance. These results imply direct limitation of species diversity by climatic stress and more rapid (co-)evolution and narrower niche partitioning in warm climates. They also support the idea that increased numbers of individuals associated with high primary productivity are partitioned to support a greater number of species.

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25ha), all stems 1cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 degrees S-61 degrees N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 degrees C), changes in precipitation (up to +/- 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8g Nm(-2)yr(-1) and 3.1g Sm(-2)yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.