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Lianas, climbing woody plants, influence the structure and function of tropical forests. Climbing traits have evolved multiple times, including ancestral groups such as gymnosperms and pteridophytes, but the genetic basis of the liana strategy is largely unknown. Here, we use a comparative transcriptomic approach for 47 tropical plant species, including ten lianas of diverse taxonomic origins, to identify genes that are consistently expressed or downregulated only in lianas. Our comparative analysis of full-length transcripts enabled the identification of a core interactomic network common to lianas. Sets of transcripts identified from our analysis reveal features related to functional traits pertinent to leaf economics spectrum in lianas, include upregulation of genes controlling epidermal cuticular properties, cell wall remodeling, carbon concentrating mechanism, cell cycle progression, DNA repair and a large suit of downregulated transcription factors and enzymes involved in ABA-mediated stress response as well as lignin and suberin synthesis. All together, these genes are known to be significant in shaping plant morphologies through responses such as gravitropism, phyllotaxy and shade avoidance.

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.

Deep-water access is arguably the most effective, but under-studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep-water access may delay plant dehydration. Here, we tested the role of deep-water access in enabling survival within a diverse tropical forest community in Panama using a novel data-model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990-2015) to vapor pressure deficit, water potentials in the whole-soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water-access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981-2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress-related mortality risk through deep-water access. The role of deep-water access in mitigating mortality of hydraulically-vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

Plant diversity varies immensely over large-scale gradients in temperature, precipitation, and seasonality at global and regional scales. This relationship may be driven in part by climatic variation in the relative importance of abiotic and biotic interactions to the diversity and composition of plant communities. In particular, biotic interactions may become stronger and more host specific with increasing precipitation and temperature, resulting in greater plant species richness in wetter and warmer environments. This hypothesis predicts that the many defensive compounds found in plants’ metabolomes should increase in richness and decrease in interspecific similarity with precipitation, temperature, and plant diversity. To test this prediction, we compared patterns of chemical and morphological trait diversity of 140 woody plant species among seven temperate forests in North America representing 16.2°C variation in mean annual temperature (MAT), 2,115 mm variation in mean annual precipitation (MAP), and from 10 to 68 co-occurring species. We used untargeted metabolomics methods based on data generated with liquid chromatography-tandem mass spectrometry to identify, classify, and compare 13,480 unique foliar metabolites and to quantify the metabolomic similarity of species in each community with respect to the whole metabolome and each of five broad classes of metabolites. In addition, we compiled morphological trait data from existing databases and field surveys for three commonly measured traits (specific leaf area [SLA], wood density, and seed mass) for comparison with foliar metabolomes. We found that chemical defense strategies and growth and allocation strategies reflected by these traits largely represented orthogonal axes of variation. In addition, functional dispersion of SLA increased with MAP, whereas functional richness of wood density and seed mass increased with MAT. In contrast, chemical similarity of co-occurring species decreased with both MAT and MAP, and metabolite richness increased with MAT. Variation in metabolite richness among communities was positively correlated with species richness, but variation in mean chemical similarity was not. Our results are consistent with the hypothesis that plant metabolomes play a more important role in community assembly in wetter and warmer climates, even at temperate latitudes, and suggest that metabolomic traits can provide unique insight to studies of trait-based community assembly.

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.

Seasonal dynamics in the vertical distribution of leaf area index (LAI) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine-scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine-scale variation in leaf area with seasonality and drought we conducted monthly ground-based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015-2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function.

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.

Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change.

As population-level patterns of interest in forests emerge from individual vital rates, modelling forest dynamics requires making the link between the scales at which data are collected (individual stems) and the scales at which questions are asked (e.g. populations and communities). Structured population models (e.g. integral projection models (IPMs)) are useful tools for linking vital rates to population dynamics. However, the application of such models to forest trees remains challenging owing to features of tree life cycles, such as slow growth, long lifespan and lack of data on crucial ontogenic stages. We developed a survival model that accounts for size-dependent mortality and a growth model that characterizes individual heterogeneity. We integrated vital rate models into two types of population model; an analytically tractable form of IPM and an individual-based model (IBM) that is applied with stochastic simulations. We calculated longevities, passage times to, and occupancy time in, different life cycle stages, important metrics for understanding how demographic rates translate into patterns of forest turnover and carbon residence times. Here, we illustrate the methods for three tropical forest species with varying life-forms. Population dynamics from IPMs and IBMs matched a 34 year time series of data (albeit a snapshot of the life cycle for canopy trees) and highlight differences in life-history strategies between species. Specifically, the greater variation in growth rates within the two canopy species suggests an ability to respond to available resources, which in turn manifests as faster passage times and greater occupancy times in larger size classes. The framework presented here offers a novel and accessible approach to modelling the population dynamics of forest trees.

Macroclimate drives vegetation distributions, but fine‐scale topographic variation can generate microclimate refugia for plant persistence in unsuitable areas. However, we lack quantitative descriptions of topography‐driven microclimatic variation and how it shapes forest structure, diversity, and composition. We hypothesized that topographic variation and the presence of the forest overstory cause spatiotemporal microclimate variation affecting tree performance, causing forest structure, diversity, and composition to vary with topography and microclimate, and topography and the overstory to buffer microclimate. In a 20.2‐ha inventory plot in the North American Great Plains, we censused woody stems ≥1 cm in diameter and collected detailed topographic and microclimatic data. Across 59‐m of elevation, microclimate covaried with topography to create a sharp desiccation gradient, and topography and the overstory buffered understory microclimate. The magnitude of microclimatic variation mirrored that of regional‐scale variation: with increasing elevation, there was a decrease in soil moisture corresponding to the difference across ~2.1° of longitude along the east‐to‐west aridity gradient and an increase in air temperature corresponding to the difference across ~2.7° of latitude along the north‐to‐south gradient. More complex forest structure and higher diversity occurred in moister, less‐exposed habitats, and species occupied distinct topographic niches. Our study demonstrates how topographic and microclimatic gradients structure forests in putative climate‐change refugia, by revealing ecological processes enabling populations to be maintained during periods of unfavorable macroclimate. [ABSTRACT FROM AUTHOR]

Haiti is still recovering from the effects of the massive 2010 earthquake that destroyed much of its infrastructure. While a large international humanitarian response was mounted to save lives and rebuild the country, international nongovernmental organizations have failed to meet many of their most important and relevant objectives in the last four years. Nongovernmental organizations operate within a precise set of legal, economic and political restrictions that have variously been described as too lenient and too obstructive. This paper seeks to examine the governing aid framework in order to describe how a specific combination of limitations and liberties have resulted in organizational imperatives that obfuscate the economic origins of humanitarian financiers, limit aid transparency, reduces NGO accountability to both donors and recipients and lead to poor overall development outcomes. To demonstrate these outcomes this paper uses detailed case studies of three large nonprofit organizations operating in Haiti: Partners in Health, Save the Children and CARE. The objective is not to assume that these are perfectly representative outcomes of aid, but rather to show a variety of development outcomes that the aid apparatus either allowed for or failed to prevent.

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Emerging satellite radar and lidar platforms are being developed to produce gridded aboveground biomass (AGB) predictions that are poised to expand our understanding of global carbon stocks and changes. However, the spatial resolution of AGB map products from these platforms is often larger than the available field plot data underpinning model calibration and validation efforts. Intermediate-resolution/extent remotely sensed data, like airborne lidar, can serve as a bridge between small plots and map resolution, but methods are needed to estimate and propagate uncertainties with multiple layers of data. Here, we introduce a workflow to estimate the pixel-level mean and variance in AGB maps by propagating uncertainty from a lidar-based model using small plots, taking into account prediction uncertainty, residual uncertainty, and residual spatial autocorrelation. We apply this workflow to estimate AGB uncertainty at a 100 m map resolution (1 ha pixels) using 0.04 ha field plots from 11 sites across four ecoregions. We compare uncertainty estimates using site-specific models, ecoregion-specific models, and a general model using all sites. The estimated AGB uncertainty for 1 ha pixels increased with mean AGB, reaching 7.8–33.3 Mg ha−1 for site-specific models (one standard deviation), 11.1–28.2 Mg ha−1 for ecoregion-specific models, and 21.1–22.1 Mg ha−1 for the general model for pixels in the AGB range of 80–100 Mg ha−1. Only 3 of 11 site-specific models had a total uncertainty of <15 Mg ha−1 in this biomass range, suitable for the calibration or validation of AGB map products. Using two additional sites with larger field plots, we show that lidar-based models calibrated with larger field plots can substantially reduce 1 ha pixel AGB uncertainty for the same range from 18.2 Mg ha−1 using 0.04 ha plots to 10.9 Mg ha−1 using 0.25 ha plots and 10.1 Mg ha−1 using 1 ha plots. We conclude that the estimated AGB uncertainty from models estimated from small field plots may be unacceptably large, and we recommend coordinated efforts to measure larger field plots as reference data for the calibration or validation of satellite-based map products at landscape scales (≥0.25 ha). [ABSTRACT FROM AUTHOR]