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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., (© 2022 John Wiley & Sons Ltd.)

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

The prediction of vegetation responses to climate requires a knowledge of how climate-sensitive plant traits mediate not only the responses of individual plants, but also shifts in the species and functional compositions of whole communities. The emission of isoprene gas - a trait shared by one-third of tree species - is known to protect leaf biochemistry under climatic stress. Here, we test the hypothesis that isoprene emission shapes tree species compositions in tropical forests by enhancing the tolerance of emitting trees to heat and drought. Using forest inventory data, we estimated the proportional abundance of isoprene-emitting trees (pIE) at 103 lowland tropical sites. We also quantified the temporal composition shifts in three tropical forests - two natural and one artificial - subjected to either anomalous warming or drought. Across the landscape, pIE increased with site mean annual temperature, but decreased with dry season length. Through time, pIE strongly increased under high temperatures, and moderately increased following drought. Our analysis shows that isoprene emission is a key plant trait determining species responses to climate. For species adapted to seasonal dry periods, isoprene emission may tradeoff with alternative strategies, such as leaf deciduousness. Community selection for isoprene-emitting species is a potential mechanism for enhanced forest resilience to climatic change., (© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.)

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25 ha), all stems ≥ 1 cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 °S-61 °N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 °C), changes in precipitation (up to ± 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8 g N m(-2) yr(-1) and 3.1 g S m(-2) yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5 km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change., (© 2014 John Wiley & Sons Ltd.)

Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models., (Published by Elsevier Ltd.)

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.

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]

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A better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long‐term climate averages (mean climate) drive spatial variations in species' baseline growth rates, whereas deviations from these averages over time (anomalies) can create growth variation around the local baseline. However, the rarity of long‐term tree census data spanning climatic gradients has so far limited our understanding of their respective role, especially in tropical systems. Furthermore, tree growth sensitivity to climate is likely to vary widely among species, and the ecological strategies underlying these differences remain poorly understood. Here, we utilize an exceptional dataset of 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how multiannual tree growth responds to both climate means and anomalies, and how species' functional traits mediate these growth responses to climate. We show that anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast‐growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both climate means and anomalies. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests and that species traits can provide insights into understanding these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories. [ABSTRACT FROM AUTHOR]

Summary: The relative importance of tree mortality risk factors remains unknown, especially in diverse tropical forests where species may vary widely in their responses to particular conditions.We present a new framework for quantifying the importance of mortality risk factors and apply it to compare 19 risks on 31 203 trees (1977 species) in 14 one‐year periods in six tropical forests. We defined a condition as a risk factor for a species if it was associated with at least a doubling of mortality rate in univariate analyses. For each risk, we estimated prevalence (frequency), lethality (difference in mortality between trees with and without the risk) and impact ('excess mortality' associated with the risk, relative to stand‐level mortality).The most impactful risk factors were light limitation and crown/trunk loss; the most prevalent were light limitation and small size; the most lethal were leaf damage and wounds. Modes of death (standing, broken and uprooted) had limited links with previous conditions and mortality risk factors.We provide the first ranking of importance of tree‐level mortality risk factors in tropical forests. Future research should focus on the links between these risks, their climatic drivers and the physiological processes to enable mechanistic predictions of future tree mortality. [ABSTRACT FROM AUTHOR]

Plant phenology—the timing of cyclic or recurrent biological events in plants—offers insight into the ecology, evolution, and seasonality of plant‐mediated ecosystem processes. Traditionally studied phenologies are readily apparent, such as flowering events, germination timing, and season‐initiating budbreak. However, a broad range of phenologies that are fundamental to the ecology and evolution of plants, and to global biogeochemical cycles and climate change predictions, have been neglected because they are "cryptic"—that is, hidden from view (e.g., root production) or difficult to distinguish and interpret based on common measurements at typical scales of examination (e.g., leaf turnover in evergreen forests). We illustrate how capturing cryptic phenology can advance scientific understanding with two case studies: wood phenology in a deciduous forest of the northeastern USA and leaf phenology in tropical evergreen forests of Amazonia. Drawing on these case studies and other literature, we argue that conceptualizing and characterizing cryptic plant phenology is needed for understanding and accurate prediction at many scales from organisms to ecosystems. We recommend avenues of empirical and modeling research to accelerate discovery of cryptic phenological patterns, to understand their causes and consequences, and to represent these processes in terrestrial biosphere models. [ABSTRACT FROM AUTHOR]

Climate is of fundamental importance to the ecology and evolution of all organisms. However, studies of climate–organism interactions usually rely on climate variables interpolated from widely spaced measurements or modelled at coarse resolution, whereas the conditions experienced by many organisms vary over scales from millimetres to metres.To help bridge this mismatch in scale, we present models of the mechanistic processes that govern fine‐scale variation in near‐ground air temperature. The models are flexible (enabling application to a wide variety of locations and contexts), can be run using freely available data and are provided as an R package.We apply a mesoclimate model to the Lizard Peninsula in Cornwall to provide hourly estimates of air temperature at resolution of 100 m for the period Jan‐Dec 2010. A microclimate model is then applied to a 1 km2 region of the Lizard Peninsula, Caerthillean Valley (49.969°N, 5.215°W), to provide hourly estimates of near‐ground air temperature at resolution of 1 m2 during May 2010.Our models reveal substantial spatial variation in near‐ground temperatures, driven principally by variation in topography and, at the microscale, by vegetation structure. At the meso‐scale, hours of exposure to air temperatures at 1 m height in excess of 25°C ranged from 23 to 158 hr, despite this temperature never being recorded by the weather station within the study area during the study period. At the micro‐scale, steep south‐facing slopes with minimal vegetation cover experienced temperatures in excess of 40°C.The microclima package is flexible and efficient and provides an accurate means of modelling fine‐scale variation in temperature. We also provide functions that facilitate users to obtain and process a variety of freely available datasets needed to drive the model. [ABSTRACT FROM AUTHOR]

Tree mortality rates determine forest health, community dynamics, and terrestrial carbon stocks. Climate change is predicted to increase global forest mortality, and some studies have observed recent changes in mortality rates. Assessing shifts in mortality and identifying their causes is challenged by the low mortality rates of trees and the limited scale at which tree mortality is typically assessed. Detecting changes in mortality and assigning mechanisms to those changes may not be feasible unless there are exceptionally large and persistent shifts in forest mortality rates. Here, we combine simulations and lifehistory theory to explore how a doubling in mortality might result in population decline, mean life expectancy, and carbon carrying capacity of forests. Using a simulated forest, we also identify that the sampling strategy and effort required to detect a doubling in stem mortality is extensive. We recommend increased efforts at monitoring mortality and a better incorporation of life-history theory, community composition, and application of changepoint detection statistics in mortality analyses. [ABSTRACT FROM AUTHOR]

Abstract: Drought‐induced tree mortality is expected to increase globally due to climate change, with profound implications for forest composition, function and global climate feedbacks. How drought is experienced by different species is thought to depend fundamentally on where they access water vertically below‐ground, but this remains untracked so far due to the difficulty of measuring water availability at depths at which plants access water (few to several tens of metres), the broad temporal scales at which droughts at those depths unfold (seasonal to decadal), and the difficulty in linking these patterns to forest‐wide species‐specific demographic responses. We address this problem through a new eco‐hydrological framework: we used a hydrological model to estimate below‐ground water availability by depth over a period of two decades that included a multi‐year drought. Given this water availability scenario and 20 year long‐records of species‐specific growth patterns, we inversely estimated the relative depths at which 12 common species in the forest accessed water via a model of water stress. Finally, we tested whether our estimates of species relative uptake depths predicted mortality in the multi‐year drought. The hydrological model revealed clear below‐ground niches as precipitation was decoupled from water availability by depth at multi‐annual scale. Species partitioned the hydrological niche by diverging in their uptake depths and so in the same forest stand, different species experienced very different drought patterns, resulting in clear differences in species‐specific growth. Finally, species relative water uptake depths predicted species mortality patterns after the multi‐year drought. Species that our method ranked as relying on deeper water were the ones that had suffered from greater mortality, as the zone from which they access water took longer to recharge after depletion. Synthesis. This research changes our understanding of how hydrological niches operate for trees, with a trade‐off between realized growth potential and survival under drought with decadal scale return time. The eco‐hydrological framework highlights the importance of species‐specific below‐ground strategies in predicting forest response to drought. Applying this framework more broadly may help us better understand species coexistence in diverse forest communities and improve mechanistic predictions of forests productivity and compositional change under future climate. [ABSTRACT FROM AUTHOR]

1. Many morphological, physiological and ecological traits of trees scale with diameter, shaping the structure and function of forest ecosystems. Understanding the mechanistic basis for such scaling relationships is key to understanding forests globally and their role in Earth's changing climate system. 2. Here, we evaluate theoretical predictions for the scaling of nine variables in a mixed-age temperate deciduous forest (CTFS-ForestGEO forest dynamics plot at the Smithsonian Conservation Biology Institute, Virginia, USA) and compare observed scaling parameters to those from other forests world-wide. We examine fifteen species and various environmental conditions. 3. Structural, physiological and ecological traits of trees scaled with stem diameter in a manner that was sometimes consistent with existing theoretical predictions-more commonly with those predicting a range of scaling values than a single universal scaling value. 4. Scaling relationships were variable among species, reflecting substantive ecological differences. 5. Scaling relationships varied considerably with environmental conditions. For instance, the scaling of sap flux density varied with atmospheric moisture demand, and herbivore browsing dramatically influenced stem abundance scaling. 6. Thus, stand-level, time-averaged scaling relationships (e.g., the scaling of diameter growth) are underlain by a diversity of species-level scaling relationships that can vary substantially with fluctuating environmental conditions. In order to use scaling theory to accurately characterize forest ecosystems and predict their responses to global change, it will be critical to develop a more nuanced understanding of both the forces that constrain stand-level scaling and the complexity of scaling variation across species and environmental cond [ABSTRACT FROM AUTHOR]

Abstract: Buildings represent long-term, capital-intensive investments designed to perform for decades into the future. Consequently, the potential for changes in climate across the design lifetime of built environments represents an immediate challenge for planning, design, and construction. In this study, we consider the opportunities to assess Climate Sensitivity and adaptive opportunities associated with green building practice. We developed a pair of complementary indicators called the Climate Sensitivity Index (CSI) and Climate Adaptation Opportunity Index (CAOI). These indicators are applied to evaluate individual strategies (“credits”) within the Leadership in Energy and Environmental Design (LEED™) for New Construction rating system. The indices provide two complementary scores for each strategy. The CSI reflects potential sensitivity to changing conditions (i.e., risks to performance outcomes), and the CAOI indicates potential adaptive opportunities (i.e., plausible strategies to adapt to changing conditions). We apply the indices to retrospectively examine the prevalence of potentially sensitive and adaptive practices among a global set of 2440 LEED-certified projects. Adaptive opportunities were more prevalent than sensitivities in the LEED-NC rating system. The CSI and CAOI indices illustrate how information can be derived by interpreting patterns of LEED credit achievement. The indices will be available within a suite of analytical tools in the Green Building Information Gateway (www.gbig.org). [Copyright &y& Elsevier]

Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system. [ABSTRACT FROM AUTHOR]

The flora of California, a global biodiversity hotspot, includes 2387 endemic plant taxa. With anticipated climate change, we project that up to 66% will experience .80% reductions in range size within a century. These results are comparable with other studies of fewer species or just samples of a region's endemics. Projected reductions depend on the magnitude of future emissions and on the ability of species to disperse from their current locations. California's varied terrain could cause species to move in very different directions, breaking up present-day floras. However, our projections also identify regions where species undergoing severe range reductions may persist. Protecting these potential future refugia and facilitating species dispersal will be essential to maintain biodiversity in the face of climate change. [ABSTRACT FROM AUTHOR]

Potential biosignatures that offer the promise of extraterrestrial life (past or present) are to be expected in the coming years and decades, whether from within our own solar system, from an exoplanet atmosphere, or otherwise. With each such potential biosignature, the degree of our uncertainty will be the first question asked. Have we really identified extraterrestrial life? How sure are we? This paper considers the problem of unconceived alternative explanations. We stress that articulating our uncertainty requires an assessment of the extent to which we have explored the relevant possibility space. It is argued that, for most conceivable potential biosignatures, we currently have not explored the relevant possibility space very thoroughly at all. Not only does this severely limit the circumstances in which we could reasonably be confident in our detection of extraterrestrial life, it also poses a significant challenge to any attempt to quantify our degree of uncertainty. The discussion leads us to the following recommendation: when it comes specifically to an extraterrestrial life-detection claim, the astrobiology community should follow the uncertainty assessment approach adopted by the Intergovernmental Panel on Climate Change (IPCC). [ABSTRACT FROM AUTHOR]

Rigorous monitoring of Earth's terrestrial surface requires mapping estimates of land cover and of their errors in space and time. Estimation of error in land-cover change detection currently relies heavily on external, post hoc validation—i.e., comparison of estimated cover to independent values that are assumed to be true. However, reference data are themselves uncertain, and acquiring observations coincident with historical data is often impossible. Complementarily, modeling the transmission, or propagation, of error through the processes of classification and change detection provides an internal means to estimate classification and change-detection error at the scale of pixels. Modeling uncertainty around the estimate of fractional, “continuous-field” cover as a standard Normal distribution in each pixel at each of two times, we derive a method for propagating this uncertainty to categorical land cover-classification and change detection. We demonstrate the approach for mapping forest-cover change and its uncertainty based on bi-temporal estimates of percent-tree cover and their associated root-mean-square errors (RMSE). The method described here propagates only the imprecision component of error and not bias, so neither the resulting categorical estimates of cover nor the detection of change (e.g., forest loss) are affected by the transmission of uncertainty. However, propagating the RMSE of input estimates into probabilities of forest cover and change enables mapping and visualization of the spatial distribution of the imprecision resulting from model-based estimation of tree cover and from selection of the threshold of tree cover to define “forest”. When compared to reference data with a fixed definition of forest (e.g., ≥ 30% tree cover) the threshold effect is an importance source of apparent error in forest-cover and -change estimates. The approach described here provides a useful description of classification and change-detection certainty and can accommodate any definition of forest based on tree cover—an especially important consideration given the variety of institutional definitions of forest cover based on remotely sensible structural characteristics. [ABSTRACT FROM AUTHOR]