Water availability predicts forest canopy height at the global scale

Disentangling linkages between satellite-derived indicators of forest structure and productivity for ecosystem monitoring

The essential biodiversity variables (EBV) framework has been proposed as a monitoring system of standardized, comparable variables that represents a minimum set of biological information to monitor biodiversity change at large spatial extents. Six classes of EBVs (genetic composition, species populations, species traits, community composition, ecosystem structure and ecosystem function) are defined, a number of which are ideally suited to observation and monitoring by remote sensing systems. We used moderate-resolution remotely sensed indicators representing two ecosystem-level EBV classes (ecosystem structure and function) to assess their complementarity and redundancy across a range of ecosystems encompassing significant environmental gradients. Redundancy analyses found that remote sensing indicators of forest structure were not strongly related to indicators of ecosystem productivity (represented by the Dynamic Habitat Indices; DHIs), with the structural information only explaining 15.7% of the variation in the DHIs. Complex metrics of forest structure, such as aboveground biomass, did not contribute additional information over simpler height-based attributes that can be directly estimated with light detection and ranging (LIDAR) observations. With respect to ecosystem conditions, we found that forest types and ecosystems dominated by coniferous trees had less redundancy between the remote sensing indicators when compared to broadleaf or mixed forest types. Likewise, higher productivity environments exhibited the least redundancy between indicators, in contrast to more environmentally stressed regions. We suggest that biodiversity researchers continue to exploit multiple dimensions of remote sensing data given the complementary information they provide on structure and function focused EBVs, which makes them jointly suitable for monitoring forest ecosystems.

Vertical structural complexity of plant communities represents the combined effects of resource acquisition and environmental stress on the Tibetan Plateau

The vertical structural complexity (VSC) of plant communities reflects the occupancy of spatial niches and is closely related to resource utilization and environmental adaptation. However, understanding the large-scale spatial pattern of VSC and its underlying mechanisms remains limited. Here, we systematically investigate 2013 plant communities through grid sampling on the Tibetan Plateau. VSC is quantified as the maximum plant height within a plot (Height-max), coefficient of variation of plant height (Height-var), and Shannon evenness of plant height (Height-even). Precipitation dominates the spatial variation in VSC in forests and shrublands, supporting the classic physiological tolerance hypothesis. In contrast, for alpine meadows, steppes, and desert grasslands in extreme environments, non-resource limiting factors (e.g., wide diurnal temperature ranges and strong winds) dominate VSC variation. Generally, with the shifting of climate from favorable to extreme, the effect of resource availability gradually decreases, but the effect of non-resource limiting factors gradually increases, and that the physiological tolerance hypothesis only applicable in favorable conditions. With the help of machine learning models, maps of VSC at 1-km resolution are produced for the Tibetan Plateau. Our findings and maps of VSC provide insights into macroecological studies, especially for adaptation mechanisms and model optimization.

Density affects plant size in the Gobi Desert

Plant size is a crucial functional trait with substantial implications in agronomy and forestry. Understanding the factors influencing plant size is essential for ecosystem management and restoration efforts. Various environmental factors and plant density play significant roles in plant size. However, how plant size responds to mean annual precipitation (MAP), mean annual temperature (MAT), and density in the arid areas remains incomplete. To address this knowledge gap, we conducted comprehensive vegetation surveys in the Gobi Desert in northwestern China with a MAP below 250 mm. We also collected climate data to disentangle the respective influences of climate and density on the community-weighted plant height, crown length, and crown width. Our observations revealed that the community-weighted mean plant height, crown length, and width demonstrated a positive association with MAT but negative relationships with both MAP and density. These patterns can be attributed to the predominance of shrubs over herbs in arid regions, as shrubs tend to be larger in size. The proportion of shrubs increases with MAT, while it decreases with MAP and density, resulting in higher plant height and larger crown dimensions. Although both MAP and MAT affect plant size in the Gobi Desert, our findings highlight the stronger role of plant density in regulating plant size, indicating that the surrounding plant community and competition among individuals are crucial drivers of plant size patterns. Our findings provide valuable guidance for nature-based solutions for vegetation restoration and ecosystem management, highlighting the importance of considering plant density as a key factor when designing and implementing restoration strategies in arid areas.

Temperature and Turgor "Limitation" and Environmental "Control" in Xylem Biology and Dendrochronology

Trees and other woody plants are immensely ecologically important, making it essential to understand the causes of relationships between tree structure and function. To help these efforts, we highlight persistent traditions in plant biology of appealing to environmental factors "limiting" or "controlling" woody plant features. Examples include the idea that inevitable drops in cell turgor with plant height limit cell expansion and thus leaf size and tree height; that low temperatures prohibit lignification of cells and thus the growth of woody plants at high elevation; and notions from dendrochronology and related fields that climate factors such as rainfall and temperature "control" growth ring features. We show that notions of "control," "limitation," and the like imply that selection would favor a given trait value, but that these would-be favored values are developmentally impossible to produce. Such "limitation" scenarios predict trait frequency distributions that are very narrow and are abruptly curtailed at the upper limit of developmental possibility (the right-hand side of the distribution). Such distributions have, to our knowledge, never been observed, so we see little empirical support for "limitation" hypotheses. We suggest that, as a more productive starting point, plant biologists should examine adaptation hypotheses, in which developmental possibility is wide (congruent with the wide ranges of trait variation that really are observed), but only some of the possible variants are favored. We suggest that (1) the traditional the proximate/ultimate causation distinction, (2) purging scenarios of teleology/anthropomorphism, and (3) stating hypotheses in terms of developmental potential and natural selection are three simple ways of making "limitation" hypotheses clearer with regard to biological process and thus empirically testable.

Mapping small mammal optimal habitats using satellite-derived proxy variables and species distribution models

Small mammal species play an important role influencing vegetation primary productivity and plant species composition, seed dispersal, soil structure, and as predator and/or prey species. Species which experience population dynamics cycles can, at high population phases, heavily impact agricultural sectors and promote rodent-borne disease transmission. To better understand the drivers behind small mammal distributions and abundances, and how these differ for individual species, it is necessary to characterise landscape variables important for the life cycles of the species in question. In this study, a suite of Earth observation derived metrics quantifying landscape characteristics and dynamics, and in-situ small mammal trapline and transect survey data, are used to generate random forest species distribution models for nine small mammal species for study sites in Narati, China and Sary Mogul, Kyrgyzstan. These species distribution models identify the important landscape proxy variables driving species abundance and distributions, in turn identifying the optimal conditions for each species. The observed relationships differed between species, with the number of landscape proxy variables identified as important for each species ranging from 3 for Microtus gregalis at Sary Mogul, to 26 for Ellobius tancrei at Narati. Results indicate that grasslands were predicted to hold higher abundances of Microtus obscurus, E. tancrei and Marmota baibacina, forest areas hold higher abundances of Myodes centralis and Sorex asper, with mixed forest-grassland boundary areas and areas close to watercourses predicted to hold higher abundances of Apodemus uralensis and Sicista tianshanica. Localised variability in vegetation and wetness conditions, as well as presence of certain habitat types, are also shown to influence these small mammal species abundances. Predictive application of the Random Forest (RF) models identified spatial hot-spots of high abundance, with model validation producing R2 values between 0.670 for M. gregalis transect data at Sary Mogul to 0.939 for E. tancrei transect data at Narati. This enhances previous work whereby optimal habitat was defined simply as presence of a given land cover type, and instead defines optimal habitat via a combination of important landscape dynamic variables, moving from a human-defined to species-defined perspective of optimal habitat. The species distribution models demonstrate differing distributions and abundances of host species across the study areas, utilising the strengths of Earth observation data to improve our understanding of landscape and ecological linkages to small mammal distributions and abundances.

A Comparison of Different Stomatal Density Phenotypes of Hordeum vulgare under Varied Watering Regimes Reveals Superior Genotypes with Enhanced Drought Tolerance

Enhancing the water-use efficiency (WUE) of barley cultivars may safeguard yield deficits during periods of low rainfall. Reduced stomatal density is linked to enhanced WUE, leading to improved drought resistance across plant genera. In this study, 10 barley varieties exhibiting a range of stomatal density phenotypes were grown under differing soil water contents to determine whether stomatal density influences the capacity of genotypes to resist low water availability. The low-stomatal-density genotype Hindmarsh showed the least impact on biomass production during early development, with a 37.13% decrease in dry biomass during drought treatment. Low-stomatal-density genotypes additionally outcompeted high-stomatal-density genotypes under water-deprivation conditions during the reproductive phase of development, exhibiting 19.35% greater wilting resistance and generating 54.62% more heads relative to high-stomatal-density genotypes (p < 0.05). Finally, a correlation analysis revealed a strong negative linear relationship between stomatal density and the traits of head number (r = -0.71) and the number of days until wilting symptoms (r = -0.67) (p < 0.05). The combined results indicate that low-stomatal-density genotypes show promising attributes for high WUE, revealing novel barley varieties that may be useful to future breed improvement for drought tolerance.

Responses of two Acacia species to drought suggest different water-use strategies, reflecting their topographic distribution

Introduction

Soil water availability is a key factor in the growth of trees. In arid deserts, tree growth is limited by very dry soil and atmosphere conditions. Acacia tree species are distributed in the most arid deserts of the globe, therefore they are well adapted to heat and long droughts. Understanding why some plants do better than others in some environments is a key question in plant science.

Methods

Here we conducted a greenhouse experiment to continuously and simultaneously track the whole-plant water-balance of two desert Acacia species, in order to unravel their physiological responses to low water availability.

Results

We found that even under volumetric water content (VWC) of 5-9% in the soil, both species maintained 25% of the control plants, with a peak of canopy activity at noon. Moreover, plants exposed to the low water availability treatment continued growing in this period. A. tortilis applied a more opportunistic strategy than A. raddiana, and showed stomatal responses at a lower VWC (9.8% vs. 13.1%, t₄= -4.23, p = 0.006), 2.2-fold higher growth, and faster recovery from drought stress.

Discussion

Although the experiment was done in milder VPD (~3 kPa) compared to the natural conditions in the field (~5 kPa), the different physiological responses to drought between the two species might explain their different topographic distributions. A. tortilis is more abundant in elevated locations with larger fluctuations in water availability while A. raddiana is more abundant in the main channels with higher and less fluctuating water availability. This work shows a unique and non-trivial water-spending strategy in two Acacia species adapted to hyper-arid conditions.

Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR

Canopy height is a fundamental parameter for determining forest ecosystem functions such as biodiversity and above-ground biomass. Previous studies examining the underlying patterns of the complex relationship between canopy height and its environmental and climatic determinants suffered from the scarcity of accurate canopy height measurements at large scales. NASA’s mission, the Global Ecosystem Dynamic Investigation (GEDI), has provided sampled observations of the forest vertical structure at near global scale since late 2018. The availability of such unprecedented measurements allows for examining the vertical structure of vegetation spatially and temporally. Herein, we explore the most influential climatic and environmental drivers of the canopy height in tropical forests. We examined different resampling resolutions of GEDI-based canopy height to approximate maximum canopy height over tropical forests across all of Malaysia. Moreover, we attempted to interpret the dynamics underlining the bivariate and multivariate relationships between canopy height and its climatic and topographic predictors including world climate data and topographic data. The approaches to analyzing these interactions included machine learning algorithms, namely, generalized linear regression, random forest and extreme gradient boosting with tree and Dart implementations. Water availability, represented as the difference between precipitation and potential evapotranspiration, annual mean temperature and elevation gradients were found to be the most influential determinants of canopy height in Malaysia’s tropical forest landscape. The patterns observed are in line with the reported global patterns and support the hydraulic limitation hypothesis and the previously reported negative trend for excessive water supply. Nevertheless, different breaking points for excessive water supply and elevation were identified in this study, and the canopy height relationship with water availability observed to be less significant for the mountainous forest on altitudes higher than 1000 m. This study provides insights into the influential factors of tree height and helps with better comprehending the variation in canopy height in tropical forests based on GEDI measurements, thereby supporting the development and interpretation of ecosystem modeling, forest management practices and monitoring forest response to climatic changes in montane forests.

Paired analysis of tree ring width and carbon isotopes indicates when controls on tropical tree growth change from light to water limitations

Light and water availability are likely to vary over the lifespan of closed-canopy forest trees, with understory trees experiencing greater limitations to growth by light and canopy trees greater limitation due to drought. As drought and shade have opposing effects on isotope discrimination (Δ13C), paired measurement of ring width and Δ13C can potentially be used to differentiate between water and light limitations on tree growth. We tested this approach for Cedrela trees from three tropical forests in Bolivia and Mexico that differ in rainfall and canopy structure. Using lifetime ring width and Δ13C data for trees of up to and over 200 years old, we assessed how controls on tree growth changed from understory to the canopy. Growth and Δ13C are mostly anti-correlated in the understory, but this anti-correlation disappeared or weakened when trees reached the canopy, especially at the wettest site. This indicates that understory growth variation is controlled by photosynthetic carbon assimilation due to variation in light levels. Once trees reached the canopy, inter-annual variation in growth and Δ13C at one of the dry sites showed positive correlations, indicating that inter-annual variation in growth is driven by variation in water stress affecting stomatal conductance. Paired analysis of ring widths and carbon isotopes provides significant insight in what environmental factors control growth over a tree's life; strong light limitations for understory trees in closed-canopy moist forests switched to drought stress for (sub)canopy trees in dry forests. We show that combined isotope and ring width measurements can significantly improve our insights in tree functioning and be used to disentangle limitations due to shade from those due to drought.

Global relationships in tree functional traits

Due to massive energetic investments in woody support structures, trees are subject to unique physiological, mechanical, and ecological pressures not experienced by herbaceous plants. Despite a wealth of studies exploring trait relationships across the entire plant kingdom, the dominant traits underpinning these unique aspects of tree form and function remain unclear. Here, by considering 18 functional traits, encompassing leaf, seed, bark, wood, crown, and root characteristics, we quantify the multidimensional relationships in tree trait expression. We find that nearly half of trait variation is captured by two axes: one reflecting leaf economics, the other reflecting tree size and competition for light. Yet these orthogonal axes reveal strong environmental convergence, exhibiting correlated responses to temperature, moisture, and elevation. By subsequently exploring multidimensional trait relationships, we show that the full dimensionality of trait space is captured by eight distinct clusters, each reflecting a unique aspect of tree form and function. Collectively, this work identifies a core set of traits needed to quantify global patterns in functional biodiversity, and it contributes to our fundamental understanding of the functioning of forests worldwide.

Understanding patterns in woody plant trait relationships and trade-offs is challenging. Here, by applying machine learning and data imputation methods to a global database of georeferenced trait measurements, the authors unravel key relationships in tree functional traits at the global scale.

The Shift from Energy to Water Limitation in Local Canopy Height from Temperate to Tropical Forests in China

Canopy height greatly affects the biomass stock, carbon dynamics, and maintenance of biodiversity in forests. Previous research reported that the maximum forest canopy height (Hmax) at global and regional scales could be explained by variations in water or energy availability, that is, the water- or energy-related hypothesis. However, fundamental gaps remain in our understanding of how different drivers (i.e., water and energy) contribute to the Hmax at the local scale. In this study, we selected eight dynamic forest plots (20–30 ha) across a latitudinal gradient (from 21.6° N to 48.1° N) in China and measured the canopy structure using airborne light detection and ranging (LiDAR) data. Based on the LiDAR point cloud data, we extracted the maximum tree height (Hmax) in a 20 × 20 m quadrat as a proxy for canopy height, and the topographic wetness index (TWI) and digital terrain model-derived insolation (DTMI) were calculated as proxies for water and energy conditions. We used a linear mixed model and spatial simultaneous autoregressive error model to quantify how TWI and DTMI contributed to variations in Hmax at the local scale. We found that the positive effect of TWI was stronger in subtropical and tropical forests, highlighting that water was the main factor that drives the canopy height pattern in these regions. In contrast, although the effects of DTMI can be both positive and negative, its relative contribution was higher in temperate forest plots than in other forest types, supporting the idea that energy input is more critical for Hmax in temperate forests. Overall, our study revealed the directional change from energy to water limitation from temperate to subtropical and tropical forests. Our findings can offer important insights into forest management, especially under global climate change in the Anthropocene.

Small and slow is safe: On the drought tolerance of tropical tree species

Understanding how evolutionary history and the coordination between trait trade-off axes shape the drought tolerance of trees is crucial to predict forest dynamics under climate change. Here, we compiled traits related to drought tolerance and the fast-slow and stature-recruitment trade-off axes in 601 tropical woody species to explore their covariations and phylogenetic signals. We found that xylem resistance to embolism (P50) determines the risk of hydraulic failure, while the functional significance of leaf turgor loss point (TLP) relies on its coordination with water use strategies. P50 and TLP exhibit weak phylogenetic signals and substantial variation within genera. TLP is closely associated with the fast-slow trait axis: slow species maintain leaf functioning under higher water stress. P50 is associated with both the fast-slow and stature-recruitment trait axes: slow and small species exhibit more resistant xylem. Lower leaf phosphorus concentration is associated with more resistant xylem, which suggests a (nutrient and drought) stress-tolerance syndrome in the tropics. Overall, our results imply that (1) drought tolerance is under strong selective pressure in tropical forests, and TLP and P50 result from the repeated evolutionary adaptation of closely related taxa, and (2) drought tolerance is coordinated with the ecological strategies governing tropical forest demography. These findings provide a physiological basis to interpret the drought-induced shift toward slow-growing, smaller, denser-wooded trees observed in the tropics, with implications for forest restoration programmes.

Integrating Multi-Source Remote Sensing to Assess Forest Aboveground Biomass in the Khingan Mountains of North-Eastern China Using Machine-Learning Algorithms

Forest aboveground biomass (AGB) is of great significance since it represents large carbon storage and may reduce global climate change. However, there are still considerable uncertainties in forest AGB estimates, especially in rugged regions, due to the lack of effective algorithms to remove the effects of topography and the lack of comprehensive comparisons of methods used for estimation. Here, we systematically compare the performance of three sources of remote sensing data used in forest AGB estimation, along with three machine-learning algorithms using extensive field measurements (N = 1058) made in the Khingan Mountains of north-eastern China in 2008. The datasets used were obtained from the LiDAR-based Geoscience Laser Altimeter System onboard the Ice, Cloud, and land Elevation satellite (ICESat/GLAS), the optical-based Moderate Resolution Imaging Spectroradiometer (MODIS), and the SAR-based Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR). We show that terrain correction is effective for this mountainous study region and that the combination of terrain-corrected GLAS and PALSAR features with Random Forest regression produces the best results at the plot scale. Including further MODIS-based features added little power for prediction. Based upon the parsimonious data source combination, we created a map of AGB circa 2008 and its uncertainty, which yields a coefficient of determination (R2) of 0.82 and a root mean squared error of 16.84 Mg ha−1 when validated with field data. Forest AGB values in our study area were within the range 79.81 ± 16.00 Mg ha−1, ~25% larger than a previous, SAR-based, analysis. Our result provides a historic benchmark for regional carbon budget estimation.

Herbaceous perennial plants with short generation time have stronger responses to climate anomalies than those with longer generation time

There is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesize time series of structured population models from 162 populations of 62 plants, mostly herbaceous species from temperate biomes, to link plant population growth rates (λ) to precipitation and temperature drivers. We expect: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; and (2) a higher climate sensitivity in short-lived rather than long-lived species. We find that precipitation anomalies have a nearly three-fold larger effect on λ than temperature. Species with shorter generation time have much stronger absolute responses to climate anomalies. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning.

Where do leaf water leaks come from? Trade-offs underlying the variability in minimum conductance across tropical savanna species with contrasting growth strategies

Plants continue to lose water from their leaves even after complete stomatal closure. Although this minimum conductance (g_leaf-res ) has substantial impacts on strategies of water use and conservation, little is known about the potential drivers underlying the variability of this trait across species. We thus untangled the relative contribution of water leaks from the cuticle and stomata in order to investigate how the variability in leaf morphological and anatomical traits is related to the variation in g_leaf-res and carbon assimilation capacity across 30 diverse species from the Brazilian Cerrado. In addition to cuticle permeance, water leaks from stomata had a significant impact on g_leaf-res . The differential pattern of stomata distribution in the epidermis was a key factor driving this variation, suggesting the existence of a trade-off between carbon assimilation and water loss through g_leaf-res . For instance, higher g_leaf-res , observed in fast-growing species, was associated with the investment in small and numerous stomata, which allowed higher carbon assimilation rates but also increased water leaks, with negative impacts on leaf survival under drought. Variation in cuticle structural properties was not linked to g_leaf-res . Our results therefore suggest the existence of a trade-off between carbon assimilation efficiency and dehydration tolerance at foliar level.

Global patterns and climatic controls of forest structural complexity

The complexity of forest structures plays a crucial role in regulating forest ecosystem functions and strongly influences biodiversity. Yet, knowledge of the global patterns and determinants of forest structural complexity remains scarce. Using a stand structural complexity index based on terrestrial laser scanning, we quantify the structural complexity of boreal, temperate, subtropical and tropical primary forests. We find that the global variation of forest structural complexity is largely explained by annual precipitation and precipitation seasonality (R² = 0.89). Using the structural complexity of primary forests as benchmark, we model the potential structural complexity across biomes and present a global map of the potential structural complexity of the earth´s forest ecoregions. Our analyses reveal distinct latitudinal patterns of forest structure and show that hotspots of high structural complexity coincide with hotspots of plant diversity. Considering the mechanistic underpinnings of forest structural complexity, our results suggest spatially contrasting changes of forest structure with climate change within and across biomes.

Resource availability and disturbance shape maximum tree height across the Amazon

Tall trees are key drivers of ecosystem processes in tropical forest, but the controls on the distribution of the very tallest trees remain poorly understood. The recent discovery of grove of giant trees over 80 meters tall in the Amazon forest requires a reevaluation of current thinking. We used high-resolution airborne laser surveys to measure canopy height across 282,750 ha of old-growth and second-growth forests randomly sampling the entire Brazilian Amazon. We investigated how resources and disturbances shape the maximum height distribution across the Brazilian Amazon through the relations between the occurrence of giant trees and environmental factors. Common drivers of height development are fundamentally different from those influencing the occurrence of giant trees. We found that changes in wind and light availability drive giant tree distribution as much as precipitation and temperature, together shaping the forest structure of the Brazilian Amazon. The location of giant trees should be carefully considered by policymakers when identifying important hot spots for the conservation of biodiversity in the Amazon.

The InVEST Habitat Quality Model Associated with Land Use/Cover Changes: A Qualitative Case Study of the Winike Watershed in the Omo-Gibe Basin, Southwest Ethiopia

The contribution of biodiversity to the global economy, human survival, and welfare has been increasing significantly, but the anthropogenic pressure as a threat to the pristine habitat has followed. This study aims to identify habitat suitability, analyze the change in habitat quality from 1988 to 2018, and to investigate the correlation between impact factors and habitat quality. The InVEST habitat quality model was used to analyze the spatiotemporal change in habitat quality in individual land-use types in the Winike watershed. Remote sensing data were used to analyze the land use/land cover changes. Nine threat sources, their maximum distance of impact, mode of decay, and sensitivity to threats were also estimated for each land-use cover type. The analysis illustrates that habitat degradation in the watershed was continuously increasing over the last three decades (1988 to 2018). Each threat impact factor and habitat sensitivity have increased for the last 30 years. The most contributing factor of habitat degradation was the 25.41% agricultural expansion in 2018. Population density, land-use intensity, elevation, and slope were significantly correlated with the distribution of habitat quality. Habitat quality degradation in the watershed during the past three decades suggested that the conservation strategies applied in the watershed ecosystem were not effective. Therefore, this study helps decision makers, particularly regarding the lack of data on biodiversity. It further looks into the conflict between economic development and conservation of biodiversity.

Limited capacity of tree growth to mitigate the global greenhouse effect under predicted warming

It is generally accepted that animal heartbeat and lifespan are often inversely correlated, however, the relationship between productivity and longevity has not yet been described for trees growing under industrial and pre-industrial climates. Using 1768 annually resolved and absolutely dated ring width measurement series from living and dead conifers that grew in undisturbed, high-elevation sites in the Spanish Pyrenees and the Russian Altai over the past 2000 years, we test the hypothesis of grow fast-die young. We find maximum tree ages are significantly correlated with slow juvenile growth rates. We conclude, the interdependence between higher stem productivity, faster tree turnover, and shorter carbon residence time, reduces the capacity of forest ecosystems to store carbon under a climate warming-induced stimulation of tree growth at policy-relevant timescales.

Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes

We consider alternate formulations of recently proposed hierarchical Nearest Neighbor Gaussian Process (NNGP) models (Datta et al., 2016a) for improved convergence, faster computing time, and more robust and reproducible Bayesian inference. Algorithms are defined that improve CPU memory management and exploit existing high-performance numerical linear algebra libraries. Computational and inferential benefits are assessed for alternate NNGP specifications using simulated datasets and remotely sensed light detection and ranging (LiDAR) data collected over the US Forest Service Tanana Inventory Unit (TIU) in a remote portion of Interior Alaska. The resulting data product is the first statistically robust map of forest canopy for the TIU.

Hydraulic traits are coordinated with maximum plant height at the global scale

Water must be transported long distances in tall plants, resulting in increasing hydraulic resistance, which may place limitations on the maximum plant height (H _max) in a given habitat. However, the coordination of hydraulic traits with H _max and habitat aridity remains poorly understood. To explore whether H _max modifies the trade-off between hydraulic efficiency and safety or how water availability might influence the relationship between H _max and other hydraulic traits, we compiled a dataset including H _max and 11 hydraulic traits for 1281 woody species from 369 sites worldwide. We found that taller species from wet habitats exhibited greater xylem efficiency and lower hydraulic safety, wider conduits, lower conduit density, and lower sapwood density, which were all associated with habitat water availability. Plant height and hydraulic functioning appear to represent a single, coordinated axis of variation, aligned primarily with water availability, thus suggesting an important role for this axis in species sorting processes.

Hydraulic Constraints to Whole-Tree Water Use and Respiration in Young Cryptomeria Trees under Competition

Although extensive studies have focused on carbon and water balance from aboveground measurements, the link between the belowground and aboveground processes deserves greater attention. In this context, the aim of this work was to assess the bi-directional feedback between whole-plant respiration and transpiration. The study was performed on 25 saplings of Sugi (Japanese cedar, Cryptomeria japonica D. Don), including dominant and suppressed individuals (total fresh weight ranging between 0.2 and 8.0 kg). During one week, the integrated water use (WU) was determined using the Deuterium dilution method. After this, the trees were uprooted and the root, stem, and leaf respiration were measured using incubation chambers and CO2 infrared sensors. The stem and root respiration followed a power response to mass (power exponent b < 1), implying a decline in mass-specific respiration with size. Conversely, the leaf respiration followed a near-linear increase with size (power exponent b ≈ 1), but was negatively affected by the stem density, indicating the hydraulic limitations of the leaf metabolism. The water use followed a power response with the tree size (b < 1), showing a decline in the transpiration per leaf mass with the tree size, but was also negatively correlated with the stem density. Our results indicate that dominant trees are more efficient in the use of water, and highlight the role of hydraulic limitations to leaf metabolism in suppressed trees.

Plant height and hydraulic vulnerability to drought and cold

Understanding how plants survive drought and cold is increasingly important as plants worldwide experience dieback with drought in moist places and grow taller with warming in cold ones. Crucial in plant climate adaptation are the diameters of water-transporting conduits. Sampling 537 species across climate zones dominated by angiosperms, we find that plant size is unambiguously the main driver of conduit diameter variation. And because taller plants have wider conduits, and wider conduits within species are more vulnerable to conduction-blocking embolisms, taller conspecifics should be more vulnerable than shorter ones, a prediction we confirm with a plantation experiment. As a result, maximum plant size should be short under drought and cold, which cause embolism, or increase if these pressures relax. That conduit diameter and embolism vulnerability are inseparably related to plant size helps explain why factors that interact with conduit diameter, such as drought or warming, are altering plant heights worldwide.

A global climate niche for giant trees

Rainforests are among the most charismatic as well as the most endangered ecosystems of the world. However, although the effects of climate change on tropical forests resilience is a focus of intense research, the conditions for their equally impressive temperate counterparts remain poorly understood, and it remains unclear whether tropical and temperate rainforests have fundamental similarities or not. Here we use new global data from high precision laser altimetry equipment on satellites to reveal for the first time that across climate zones 'giant forests' are a distinct and universal phenomenon, reflected in a separate mode of canopy height (~40 m) worldwide. Occurrence of these giant forests (cutoff height > 25 m) is negatively correlated with variability in rainfall and temperature. We also demonstrate that their distribution is sharply limited to situations with a mean annual precipitation above a threshold of 1,500 mm that is surprisingly universal across tropical and temperate climates. The total area with such precipitation levels is projected to increase by ~4 million km² globally. Our results thus imply that strategic management could in principle facilitate the expansion of giant forests, securing critically endangered biodiversity as well as carbon storage in selected regions.

Divergent trait and environment relationships among parallel radiations in Pelargonium (Geraniaceae): a role for evolutionary legacy?

Functional traits in closely related lineages are expected to vary similarly along common environmental gradients as a result of shared evolutionary and biogeographic history, or legacy effects, and as a result of biophysical tradeoffs in construction. We test these predictions in Pelargonium, a relatively recent evolutionary radiation. Bayesian phylogenetic mixed effects models assessed, at the subclade level, associations between plant height, leaf area, leaf nitrogen content and leaf mass per area (LMA), and five environmental variables capturing temperature and rainfall gradients across the Greater Cape Floristic Region of South Africa. Trait-trait integration was assessed via pairwise correlations within subclades. Of 20 trait-environment associations, 17 differed among subclades. Signs of regression coefficients diverged for height, leaf area and leaf nitrogen content, but not for LMA. Subclades also differed in trait-trait relationships and these differences were modulated by rainfall seasonality. Leave-one-out cross-validation revealed that whether trait variation was better predicted by environmental predictors or trait-trait integration depended on the clade and trait in question. Legacy signals in trait-environment and trait-trait relationships were apparently lost during the earliest diversification of Pelargonium, but then retained during subsequent subclade evolution. Overall, we demonstrate that global-scale patterns are poor predictors of patterns of trait variation at finer geographic and taxonomic scales.

Topography shapes the structure, composition and function of tropical forest landscapes

Topography is a key driver of tropical forest structure and composition, as it constrains local nutrient and hydraulic conditions within which trees grow. Yet, we do not fully understand how changes in forest physiognomy driven by topography impact other emergent properties of forests, such as their aboveground carbon density (ACD). Working in Borneo – at a site where 70‐m‐tall forests in alluvial valleys rapidly transition to stunted heath forests on nutrient‐depleted dip slopes – we combined field data with airborne laser scanning and hyperspectral imaging to characterise how topography shapes the vertical structure, wood density, diversity and ACD of nearly 15 km² of old‐growth forest. We found that subtle differences in elevation – which control soil chemistry and hydrology – profoundly influenced the structure, composition and diversity of the canopy. Capturing these processes was critical to explaining landscape‐scale heterogeneity in ACD, highlighting how emerging remote sensing technologies can provide new insights into long‐standing ecological questions.

Future global productivity will be affected by plant trait response to climate

Plant traits are both responsive to local climate and strong predictors of primary productivity. We hypothesized that future climate change might promote a shift in global plant traits resulting in changes in Gross Primary Productivity (GPP). We characterized the relationship between key plant traits, namely Specific Leaf Area (SLA), height, and seed mass, and local climate and primary productivity. We found that by 2070, tropical and arid ecosystems will be more suitable for plants with relatively lower canopy height, SLA and seed mass, while far northern latitudes will favor woody and taller plants than at present. Using a network of tower eddy covariance CO2 flux measurements and the extrapolated plant trait maps, we estimated the global distribution of annual GPP under current and projected future plant community distribution. We predict that annual GPP in northern biomes (≥45 °N) will increase by 31% (+8.1 ± 0.5 Pg C), but this will be offset by a 17.9% GPP decline in the tropics (-11.8 ± 0.84 Pg C). These findings suggest that regional climate changes will affect plant trait distributions, which may in turn affect global productivity patterns.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Optimal climate for large trees at high elevations drives patterns of biomass in remote forests of Papua New Guinea

Our ability to model global carbon fluxes depends on understanding how terrestrial carbon stocks respond to varying environmental conditions. Tropical forests contain the bulk of the biosphere's carbon. However, there is a lack of consensus as to how gradients in environmental conditions affect tropical forest carbon. Papua New Guinea (PNG) lies within one of the largest areas of contiguous tropical forest and is characterized by environmental gradients driven by altitude; yet, the region has been grossly understudied. Here, we present the first field assessment of aboveground biomass (AGB) across three main forest types of PNG using 193 plots stratified across 3,100-m elevation gradient. Unexpectedly, AGB had no direct relationship to rainfall, temperature, soil, or topography. Instead, natural disturbances explained most variation in AGB. While large trees (diameter at breast height > 50 cm) drove altitudinal patterns of AGB, resulting in a major peak in AGB (2,200-3,100 m) and some of the most carbon-rich forests at these altitudes anywhere. Large trees were correlated to a set of climatic variables following a hump-shaped curve. The set of "optimal" climatic conditions found in montane cloud forests is similar to that of maritime temperate areas that harbor the largest trees in the world: high ratio of precipitation to evapotranspiration (2.8), moderate mean annual temperature (13.7°C), and low intra-annual temperature range (7.5°C). At extreme altitudes (2,800-3,100 m), where tree diversity elsewhere is usually low and large trees are generally rare or absent, specimens from 18 families had girths >70 cm diameter and maximum heights 20-41 m. These findings indicate that simple AGB-climate-edaphic models may not be suitable for estimating carbon storage in forests where optimal climate niches exist. Our study, conducted in a very remote area, suggests that tropical montane forests may contain greater AGB than previously thought and the importance of securing their future under a changing climate is therefore enhanced.

Global patterns and determinants of forest canopy height

Forest canopy height is an important indicator of forest biomass, species diversity, and other ecosystem functions; however, the climatic determinants that underlie its global patterns have not been fully explored. Using satellite LiDAR-derived forest canopy heights and field measurements of the world's giant trees, combined with climate indices, we evaluated the global patterns and determinants of forest canopy height. The mean canopy height was highest in tropical regions, but tall forests (>50 m) occur at various latitudes. Water availability, quantified by the difference between annual precipitation and annual potential evapotranspiration (P-PET), was the best predictor of global forest canopy height, which supports the hydraulic limitation hypothesis. However, in striking contrast with previous studies, the canopy height exhibited a hump-shaped curve along a gradient of P-PET: it initially increased, then peaked at approximately 680 mm of P-PET, and finally declined, which suggests that excessive water supply negatively affects the canopy height. This trend held true across continents and forest types, and it was also validated using forest inventory data from China and the United States. Our findings provide new insights into the climatic controls of the world's giant trees and have important implications for forest management and improvement of forest growth models.

Tree diversity in relation to maximum tree height: evidence for the harshness hypothesis of species diversity gradients

Marks et al. (Ecology Letters, 19, 2016, 743) showed tree species richness correlates with maximum tree height, and interpret this as evidence that the environmental stressors that limit tree height also act as ecological filters on species richness. Here, we strengthen these arguments by further addressing the roles of environmental covariates and beta diversity.

Tree diversity in relation to tree height: alternative perspectives

Marks et al. (Ecol. Lett., 19, 2016, 743-751) show that tree diversity increases with tree height in North America and argue it reflects habitat 'suitability'. This finding conflicts with classical results, lacks controls for covariates of tree height, and can be explained alternatively using the modified Janzen-Connell effect and regional variance in habitats.

Intra-specific association between carbon isotope composition and productivity in woody plants: A meta-analysis

The study of intra-specific variations in growth and plant physiological response to drought is crucial to understand the potential for plant adaptation to global change. Carbon isotope composition (δ(13)C) in plant tissues offers an integrated measure of intrinsic water-use efficiency (WUEi). The intra-specific association between δ(13)C and productivity has been extensively studied in herbaceous crops, but species-specific information on woody plants is still limited and has so far provided contradictory results. In this work we explored the general patterns of the relationship between δ(13)C and growth traits (height, diameter and biomass) using a meta-analysis. We compiled information from 49 articles, including 176 studies performed on 34 species from 16 genera. We found a positive global intra-specific correlation between δ(13)C and growth (Gr=0.28, P<0.0001), stronger for biomass than for height, and non-significant for diameter. The extent of this intra-specific association increased from Mediterranean to subtropical, temperate and boreal biomes, i.e. from water-limited to energy-limited environments. Conifers and shrubs, but not broadleaves, showed consistent positive intra-specific correlations. The meta-analysis also revealed that the relationship between δ(13)C and growth is better characterized at juvenile stages, under near-optimal and controlled conditions, and by analyzing δ(13)C in leaves rather than in wood.

Leaf mass per area, not total leaf area, drives differences in above-ground biomass distribution among woody plant functional types

Here, we aim to understand differences in biomass distribution between major woody plant functional types (PFTs) (deciduous vs evergreen and gymnosperm vs angiosperm) in terms of underlying traits, in particular the leaf mass per area (LMA) and leaf area per unit stem basal area. We used a large compilation of plant biomass and size observations, including observations of 21 084 individuals on 656 species. We used a combination of semiparametric methods and variance partitioning to test the influence of PFT, plant height, LMA, total leaf area, stem basal area and climate on above-ground biomass distribution. The ratio of leaf mass to above-ground woody mass (MF /MS ) varied strongly among PFTs. We found that MF /MS at a given plant height was proportional to LMA across PFTs. As a result, the PFTs did not differ in the amount of leaf area supported per unit above-ground biomass or per unit stem basal area. Climate consistently explained very little additional variation in biomass distribution at a given plant size. Combined, these results demonstrate consistent patterns in above-ground biomass distribution and leaf area relationships among major woody PFTs, which can be used to further constrain global vegetation models.

Plant hydraulics as a central hub integrating plant and ecosystem function: meeting report for 'Emerging Frontiers in Plant Hydraulics' (Washington, DC, May 2015)

Water plays a central role in plant biology and the efficiency of water transport throughout the plant affects both photosynthetic rate and growth, an influence that scales up deterministically to the productivity of terrestrial ecosystems. Moreover, hydraulic traits mediate the ways in which plants interact with their abiotic and biotic environment. At landscape to global scale, plant hydraulic traits are important in describing the function of ecological communities and ecosystems. Plant hydraulics is increasingly recognized as a central hub within a network by which plant biology is connected to palaeobiology, agronomy, climatology, forestry, community and ecosystem ecology and earth-system science. Such grand challenges as anticipating and mitigating the impacts of climate change, and improving the security and sustainability of our food supply rely on our fundamental knowledge of how water behaves in the cells, tissues, organs, bodies and diverse communities of plants. A workshop, 'Emerging Frontiers in Plant Hydraulics' supported by the National Science Foundation, was held in Washington DC, 2015 to promote open discussion of new ideas, controversies regarding measurements and analyses, and especially, the potential for expansion of up-scaled and down-scaled inter-disciplinary research, and the strengthening of connections between plant hydraulic research, allied fields and global modelling efforts.

The Impacts of Droughts in Tropical Forests

Tropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other vegetation type and, thus, form a crucial component of the global carbon cycle. However, the impacts of anthropogenic climate change on drought occurrence and intensity could weaken the tropical forest carbon sink, with resulting feedback to future climates. We urgently need a better understanding of the mechanisms and processes involved to predict future responses of tropical forest carbon sequestration to climate change. Recent progress has been made in the study of drought responses at the molecular, cellular, organ, individual, species, community, and landscape levels. Although understanding of the mechanisms is incomplete, the models used to predict drought impacts could be significantly improved by incorporating existing knowledge.

The relative influences of climate and competition on tree growth along montane ecotones in the Rocky Mountains

Distribution shifts of tree species are likely to be highly dependent upon population performance at distribution edges. Understanding the drivers of aspects of performance, such as growth, at distribution edges is thus crucial to accurately predicting responses of tree species to climate change. Here, we use a Bayesian model and sensitivity analysis to partition the effects of climate and crowding, as a metric of competition, on radial growth of three dominant conifer species along montane ecotones in the Rocky Mountains. These ecotones represent upper and lower distribution edges of two species, and span the distribution interior of the third species. Our results indicate a greater influence of climate (i.e., temperature and precipitation) than crowding on radial growth. Competition importance appears to increase towards regions of more favorable growing conditions, and precise responses to crowding and climate vary across species. Overall, our results suggest that climate will likely be the most important determinant of changes in tree growth at distribution edges of these montane conifers in the future.