Demographic composition, not demographic diversity, predicts biomass and turnover across temperate and tropical forests.

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

A Delphi-method-based consensus guideline for definition of treatment-resistant depression for clinical trials.

Criteria for treatment-resistant depression (TRD) and partially responsive depression (PRD) as subtypes of major depressive disorder (MDD) are not unequivocally defined. In the present document we used a Delphi-method-based consensus approach to define TRD and PRD and to serve as operational criteria for future clinical studies, especially if conducted for regulatory purposes. We reviewed the literature and brought together a group of international experts (including clinicians, academics, researchers, employees of pharmaceutical companies, regulatory bodies representatives, and one person with lived experience) to evaluate the state-of-the-art and main controversies regarding the current classification. We then provided recommendations on how to design clinical trials, and on how to guide research in unmet needs and knowledge gaps. This report will feed into one of the main objectives of the EUropean Patient-cEntric clinicAl tRial pLatforms, Innovative Medicines Initiative (EU-PEARL, IMI) MDD project, to design a protocol for platform trials of new medications for TRD/PRD.

Morphometric study of Kalophrynus palmatissimus at two forest reserves in Malaysia.

A research study on morphometrics of Kalophrynus palmatissimus (commonly known as Lowland Grainy Frog) at Ayer Hitam Forest Reserve (AHFR), Selangor and Pasoh Forest Reserve (PFR), Negeri Sembilan was carried out from 12 November 2016 to 13 September 2017. The study was to examine data on the morphometric traits of K. palmatissimus at the two forest reserves. 15 morphometric traits of K. palmatissimus that were taken by using vernier calipers. Frog surveys were done by using 15 and 18 nocturnal 400 m transect lines with an interval distance of 20 m at AHFR and PFR, respectively. The GPS coordinates for all frog samples were recorded to ensure the precise geographic location. In addition, five climatic data were recorded. The results showed that most morphometric traits in AHFR (n = 34) and PFR (n = 31) were positively correlated with each other. On the other hand, climatic factor, which was soil pH, had a significant positive influence on most of the morphometric traits (p < .01), except for tympanum diameter and upper eyelid width (p ≥ .05). Meanwhile, the temperature had a significantly negative influence on all morphometric traits (p < .01). General linear model (GLM) analysis showed that snout-vent length (SVL) influenced most morphometric traits (F ≤ 80.86, p < .01), except for hand length (HAL: F = 0.299, p > .05). Later, it was found that the snout-vent length of K. palmatissimus at AHFR was slightly larger than at PFR (AHFR: µ = 37.00 mm, SE = 1.16 c.f. PFR: µ = 30.29 mm, SE = 1.07). It showed that there were variations in morphometric traits of K. palmatissimus at AHFR and PFR. From PCA analysis, morphometric traits are grouped into two components for AHFR and PFR, respectively. In AHFR, head length, eye diameter, head width, internarial distance, interorbital distance, forearm length, tibia length, foot length, and thigh length were strongly correlated, while snout length and eye-nostril distance were strongly correlated. In PFR, eye diameter, head width, internarial distance, interorbital distance, foot length, and thigh length were strongly correlated, though snout length and eye-nostril distance were strongly correlated, hence, suggested that all morphometric traits grow simultaneously in K. palmatissimus with eye-nostril distance (EN), and snout length (SL) growing almost simultaneously at AHFR (r = .91) and PFR (r = .97). There is still a lack of available information regarding the distribution and morphometric studies of K. palmatissimus in Malaysia, especially at AHFR and PFR. This study showed 15 different morphometric traits of K. palmatisssimus between AHFR and PFR, with K. palmatissimus at AHFR were found to be slightly larger than at PFR.

Interactions between all pairs of neighboring trees in 16 forests worldwide reveal details of unique ecological processes in each forest, and provide windows into their evolutionary histories.

When Darwin visited the Galapagos archipelago, he observed that, in spite of the islands' physical similarity, members of species that had dispersed to them recently were beginning to diverge from each other. He postulated that these divergences must have resulted primarily from interactions with sets of other species that had also diverged across these otherwise similar islands. By extrapolation, if Darwin is correct, such complex interactions must be driving species divergences across all ecosystems. However, many current general ecological theories that predict observed distributions of species in ecosystems do not take the details of between-species interactions into account. Here we quantify, in sixteen forest diversity plots (FDPs) worldwide, highly significant negative density-dependent (NDD) components of both conspecific and heterospecific between-tree interactions that affect the trees' distributions, growth, recruitment, and mortality. These interactions decline smoothly in significance with increasing physical distance between trees. They also tend to decline in significance with increasing phylogenetic distance between the trees, but each FDP exhibits its own unique pattern of exceptions to this overall decline. Unique patterns of between-species interactions in ecosystems, of the general type that Darwin postulated, are likely to have contributed to the exceptions. We test the power of our null-model method by using a deliberately modified data set, and show that the method easily identifies the modifications. We examine how some of the exceptions, at the Wind River (USA) FDP, reveal new details of a known allelopathic effect of one of the Wind River gymnosperm species. Finally, we explore how similar analyses can be used to investigate details of many types of interactions in these complex ecosystems, and can provide clues to the evolution of these interactions.

The interspecific growth-mortality trade-off is not a general framework for tropical forest community structure.

Resource allocation within trees is a zero-sum game. Unavoidable trade-offs dictate that allocation to growth-promoting functions curtails other functions, generating a gradient of investment in growth versus survival along which tree species align, known as the interspecific growth-mortality trade-off. This paradigm is widely accepted but not well established. Using demographic data for 1,111 tree species across ten tropical forests, we tested the generality of the growth-mortality trade-off and evaluated its underlying drivers using two species-specific parameters describing resource allocation strategies: tolerance of resource limitation and responsiveness of allocation to resource access. Globally, a canonical growth-mortality trade-off emerged, but the trade-off was strongly observed only in less disturbance-prone forests, which contained diverse resource allocation strategies. Only half of disturbance-prone forests, which lacked tolerant species, exhibited the trade-off. Supported by a theoretical model, our findings raise questions about whether the growth-mortality trade-off is a universally applicable organizing framework for understanding tropical forest community structure.

Statistical Issues and Recommendations for Clinical Trials Conducted During the COVID-19 Pandemic.

Abstract-The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.

Temporal population variability in local forest communities has mixed effects on tree species richness across a latitudinal gradient.

Among the local processes that determine species diversity in ecological communities, fluctuation-dependent mechanisms that are mediated by temporal variability in the abundances of species populations have received significant attention. Higher temporal variability in the abundances of species populations can increase the strength of temporal niche partitioning but can also increase the risk of species extinctions, such that the net effect on species coexistence is not clear. We quantified this temporal population variability for tree species in 21 large forest plots and found much greater variability for higher latitude plots with fewer tree species. A fitted mechanistic model showed that among the forest plots, the net effect of temporal population variability on tree species coexistence was usually negative, but sometimes positive or negligible. Therefore, our results suggest that temporal variability in the abundances of species populations has no clear negative or positive contribution to the latitudinal gradient in tree species richness.

Climate sensitive size-dependent survival in tropical trees.

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

Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis.

BACKGROUND: Decision makers often need to assess the real-world effectiveness of new drugs prelaunch, when phase II/III randomized controlled trials (RCTs) but no other data are available. OBJECTIVE: To develop a method to predict drug effectiveness prelaunch and to apply it in a case study in rheumatoid arthritis (RA). METHODS: The approach 1) identifies a market-approved treatment ( S) currently used in a target population similar to that of the new drug ( N); 2) quantifies the impact of treatment, prognostic factors, and effect modifiers on clinical outcome; 3) determines the characteristics of patients likely to receive N in routine care; and 4) predicts treatment outcome in simulated patients with these characteristics. Sources of evidence include expert opinion, RCTs, and observational studies. The framework relies on generalized linear models. RESULTS: The case study assessed the effectiveness of tocilizumab (TCZ), a biologic disease-modifying antirheumatic drug (DMARD), combined with conventional DMARDs, compared to conventional DMARDs alone. Rituximab (RTX) combined with conventional DMARDs was identified as treatment S. Individual participant data from 2 RCTs and 2 national registries were analyzed. The model predicted the 6-month changes in the Disease Activity Score 28 (DAS28) accurately: the mean change was -2.101 (standard deviation [SD] = 1.494) in the simulated patients receiving TCZ and conventional DMARDs compared to -1.873 (SD = 1.220) in retrospectively assessed observational data. It was -0.792 (SD = 1.499) in registry patients treated with conventional DMARDs. CONCLUSION: The approach performed well in the RA case study, but further work is required to better define its strengths and limitations.

Dynamics of Tree Species Diversity in Unlogged and Selectively Logged Malaysian Forests.

Selective logging that is commonly conducted in tropical forests may change tree species diversity. In rarely disturbed tropical forests, locally rare species exhibit higher survival rates. If this non-random process occurs in a logged forest, the forest will rapidly recover its tree species diversity. Here we determined whether a forest in the Pasoh Forest Reserve, Malaysia, which was selectively logged 40 years ago, recovered its original species diversity (species richness and composition). To explore this, we compared the dynamics of secies diversity between unlogged forest plot (18.6 ha) and logged forest plot (5.4 ha). We found that 40 years are not sufficient to recover species diversity after logging. Unlike unlogged forests, tree deaths and recruitments did not contribute to increased diversity in the selectively logged forests. Our results predict that selectively logged forests require a longer time at least than our observing period (40 years) to regain their diversity.

Spatial scale changes the relationship between beta diversity, species richness and latitude.

The relationship between ß-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 ß-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 (3-30o) in the Asia-Pacific region. We found that the observed ß-diversity decreased with increasing latitude when sampling local tree communities at small spatial scale (grain size ≤0.1 ha), but the observed ß-diversity did not change with latitude when sampling at large spatial scales (greater than or equal to 0.25 ha). Differences in latitudinal ß-diversity gradients across spatial scales were caused by pooled species richness (γ-diversity), which influenced observed ß-diversity values at small spatial scales, but not at large spatial scales. Therefore, spatial scale changes the relationship between ß-diversity, γ-diversity and latitude, and improving sample representativeness avoids the γ-dependence of ß-diversity.

A review of methods for comparing treatments evaluated in studies that form disconnected networks of evidence.

A network meta-analysis allows a simultaneous comparison between treatments evaluated in randomised controlled trials that share at least one treatment with at least one other study. Estimates of treatment effects may be required for treatments across disconnected networks of evidence, which requires a different statistical approach and modelling assumptions to account for imbalances in prognostic variables and treatment effect modifiers between studies. In this paper, we review and discuss methods for comparing treatments evaluated in studies that form disconnected networks of evidence. Several methods have been proposed but assessing which are appropriate often depends on the clinical context as well as the availability of data. Most methods account for sampling variation but do not always account for others sources of uncertainty. We suggest that further research is required to assess the properties of methods and the use of approaches that allow the incorporation of external information to reflect parameter and structural uncertainty.

Cross-boundary subsidy cascades from oil palm degrade distant tropical forests.

Native species that forage in farmland may increase their local abundances thereby affecting adjacent ecosystems within their landscape. We used two decades of ecological data from a protected primary rainforest in Malaysia to illutrate how subsidies from neighboring oil palm plantations triggered powerful secondary 'cascading' effects on natural habitats located >1.3 km away. We found (i) oil palm fruit drove 100-fold increases in crop-raiding native wild boar (Sus scrofa), (ii) wild boar used thousands of understory plants to construct birthing nests in the pristine forest interior, and (iii) nest building caused a 62% decline in forest tree sapling density over the 24-year study period. The long-term, landscape-scale indirect effects from agriculture suggest its full ecological footprint may be larger in extent than is currently recognized. Cross-boundary subsidy cascades may be widespread in both terrestrial and marine ecosystems and present significant conservation challenges.

Temporal coexistence mechanisms contribute to the latitudinal gradient in forest diversity.

The tropical forests of Borneo and Amazonia may each contain more tree species diversity in half a square kilometre than do all the temperate forests of Europe, North America, and Asia combined. Biologists have long been fascinated by this disparity, using it to investigate potential drivers of biodiversity. Latitudinal variation in many of these drivers is expected to create geographic differences in ecological and evolutionary processes, and evidence increasingly shows that tropical ecosystems have higher rates of diversification, clade origination, and clade dispersal. However, there is currently no evidence to link gradients in ecological processes within communities at a local scale directly to the geographic gradient in biodiversity. Here, we show geographic variation in the storage effect, an ecological mechanism that reduces the potential for competitive exclusion more strongly in the tropics than it does in temperate and boreal zones, decreasing the ratio of interspecific-to-intraspecific competition by 0.25% for each degree of latitude that an ecosystem is located closer to the Equator. Additionally, we find evidence that latitudinal variation in climate underpins these differences; longer growing seasons in the tropics reduce constraints on the seasonal timing of reproduction, permitting lower recruitment synchrony between species and thereby enhancing niche partitioning through the storage effect. Our results demonstrate that the strength of the storage effect, and therefore its impact on diversity within communities, varies latitudinally in association with climate. This finding highlights the importance of biotic interactions in shaping geographic diversity patterns, and emphasizes the need to understand the mechanisms underpinning ecological processes in greater detail than has previously been appreciated.

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia.

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon.

Limited carbon and biodiversity co-benefits for tropical forest mammals and birds.

The conservation of tropical forest carbon stocks offers the opportunity to curb climate change by reducing greenhouse gas emissions from deforestation and simultaneously conserve biodiversity. However, there has been considerable debate about the extent to which carbon stock conservation will provide benefits to biodiversity in part because whether forests that contain high carbon density in their aboveground biomass also contain high animal diversity is unknown. Here, we empirically examined medium to large bodied ground-dwelling mammal and bird (hereafter "wildlife") diversity and carbon stock levels within the tropics using camera trap and vegetation data from a pantropical network of sites. Specifically, we tested whether tropical forests that stored more carbon contained higher wildlife species richness, taxonomic diversity, and trait diversity. We found that carbon stocks were not a significant predictor for any of these three measures of diversity, which suggests that benefits for wildlife diversity will not be maximized unless wildlife diversity is explicitly taken into account; prioritizing carbon stocks alone will not necessarily meet biodiversity conservation goals. We recommend conservation planning that considers both objectives because there is the potential for more wildlife diversity and carbon stock conservation to be achieved for the same total budget if both objectives are pursued in tandem rather than independently. Tropical forests with low elevation variability and low tree density supported significantly higher wildlife diversity. These tropical forest characteristics may provide more affordable proxies of wildlife diversity for future multi-objective conservation planning when fine scale data on wildlife are lacking.

GetReal: from efficacy in clinical trials to relative effectiveness in the real world.

The GetReal consortium ("incorporating real-life data into drug development") addresses the efficacy-effectiveness gap that opens between the data from well-controlled randomized trials in selected patient groups submitted to regulators and the real-world evidence on effectiveness and safety of drugs required by decision makers. Workpackage 4 of GetReal develops evidence synthesis and modelling approaches to generate the real-world evidence. In this commentary, we discuss how questions change when moving from the well-controlled randomized trial setting to real-life medical practice, the evidence required to answer these questions, the populations to which estimates will be applicable to and the methods and data sources used to produce these estimates. We then introduce the methodological reviews written by GetReal authors and published in Research Synthesis Methods on network meta-analysis, individual patient data meta-analysis and mathematical modelling to predict drug effectiveness. The critical reviews of key methods are a good starting point for the ambitious programme of work GetReal has embarked on. The different strands of work under way in GetReal have great potential to contribute to making clinical trials research as relevant as it can be to patients, caregivers and policy makers. Copyright © 2016 John Wiley & Sons, Ltd.

Best practice for analysis of shared clinical trial data.

BACKGROUND: Greater transparency, including sharing of patient-level data for further research, is an increasingly important topic for organisations who sponsor, fund and conduct clinical trials. This is a major paradigm shift with the aim of maximising the value of patient-level data from clinical trials for the benefit of future patients and society. We consider the analysis of shared clinical trial data in three broad categories: (1) reanalysis - further investigation of the efficacy and safety of the randomized intervention, (2) meta-analysis, and (3) supplemental analysis for a research question that is not directly assessing the randomized intervention. DISCUSSION: In order to support appropriate interpretation and limit the risk of misleading findings, analysis of shared clinical trial data should have a pre-specified analysis plan. However, it is not generally possible to limit bias and control multiplicity to the extent that is possible in the original trial design, conduct and analysis, and this should be acknowledged and taken into account when interpreting results. We highlight a number of areas where specific considerations arise in planning, conducting, interpreting and reporting analyses of shared clinical trial data. A key issue is that that these analyses essentially share many of the limitations of any post hoc analyses beyond the original specified analyses. The use of individual patient data in meta-analysis can provide increased precision and reduce bias. Supplemental analyses are subject to many of the same issues that arise in broader epidemiological analyses. Specific discussion topics are addressed within each of these areas. Increased provision of patient-level data from industry and academic-led clinical trials for secondary research can benefit future patients and society. Responsible data sharing, including transparency of the research objectives, analysis plans and of the results will support appropriate interpretation and help to address the risk of misleading results and avoid unfounded health scares.

Reproducing static and dynamic biodiversity patterns in tropical forests: the critical role of environmental variance.

Ecological communities are subjected to stochasticity in the form of demographic and environmental variance. Stochastic models that contain only demographic variance (neutral models) provide close quantitative fits to observed species-abundance distributions (SADs) but substantially underestimate observed temporal species-abundance fluctuations. To provide a holistic assessment of whether models with demographic and environmental variance perform better than neutral models, the fit of both to SADs and temporal species-abundance fluctuations at the same time has to be tested quantitatively. In this study, we quantitatively test how closely a model with demographic and environmental variance reproduces total numbers of species, total abundances, SADs and temporal species-abundance fluctuations for two tropical forest tree communities, using decadal data from long-term monitoring plots and considering individuals larger than two size thresholds for each community. We find that the model can indeed closely reproduce these static and dynamic patterns of biodiversity in the two communities for the two size thresholds, with better overall fits than corresponding neutral models. Therefore, our results provide evidence that stochastic models incorporating demographic and environmental variance can simultaneously capture important static and dynamic biodiversity patterns arising in tropical forest communities.