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Tree size shapes forest carbon dynamics and determines how trees interact with their environment, including a changing climate. Here, we conduct the first global analysis of among-site differences in how aboveground biomass stocks and fluxes are distributed with tree size. We analyzed repeat tree censuses from 25 large-scale (4-52 ha) forest plots spanning a broad climatic range over five continents to characterize how aboveground biomass, woody productivity, and woody mortality vary with tree diameter. We examined how the median, dispersion, and skewness of these size-related distributions vary with mean annual temperature and precipitation. In warmer forests, aboveground biomass, woody productivity, and woody mortality were more broadly distributed with respect to tree size. In warmer and wetter forests, aboveground biomass and woody productivity were more right skewed, with a long tail towards large trees. Small trees (1-10 cm diameter) contributed more to productivity and mortality than to biomass, highlighting the importance of including these trees in analyses of forest dynamics. Our findings provide an improved characterization of climate-driven forest differences in the size structure of aboveground biomass and dynamics of that biomass, as well as refined benchmarks for capturing climate influences in vegetation demographic models.

AimGlobal forests and their structural and functional features are shaped by many mechanisms that impact tree vital rates. Although many studies have tried to quantify how specific mechanisms influence vital rates, their relative importance among forests remains unclear. We aimed to assess the patterns of variation in vital rates among species and in space and time across forests to understand and provide a baseline for expectations of the relative importance of the different mechanisms in different contexts.Location21 forest plots worldwide.Time period1981-2021Major taxa studiedWoody plantsMethodsWe developed a conceptual and statistical framework (variance partitioning of multilevel models) that attributes the variability in growth, mortality, and recruitment to variation in species, space, and time, and their interactions, which we refer to asorganising principles(OPs). We applied it to data from 21 forest plots covering more than 2.9 million trees of approximately 6,500 species.ResultsDifferences among species, thespeciesOP, were a major source of variability in tree vital rates, explaining 28-33% of demographic variance alone, and in interaction withspace14-17%, totalling 40-43%. Models with small spatial grain sizes (quadrats at 5 × 5 m) retained most of the spatial OP, but a large proportion of variance remained unexplained (31-55%). The average variability among species declined with species richness across forests, indicating that diverse forests featured smaller interspecific differences in vital rates.Main conclusionsDecomposing variance in vital rates into the proposed OPs showed that taxonomy is crucial to predictions and understanding of tree demography. Our framework has a high potential for identifying the structuring mechanisms of global forest dynamics as it highlights the most promising avenues for future research both in terms of understanding the relative contributions of mechanisms to forest demography and diversity and for improving projections of forest ecosystems.

Allometric equations for calculation of tree above-ground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across boreal and temperate regions that comprise the global extratropics. Here we present an integrated R package, allodb, containing systematically selected published allometric equations and proposed functions to compute AGB. The data component of the package is based on 701 woody species identified at 24 large Forest Global Earth Observatory (ForestGEO) forest dynamics plots representing a wide diversity of extratropical forests. A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset can be customized with built-in functions that subset the original dataset and add new equations. Although equations were curated based on a limited set of forest communities and number of species, this resource is appropriate for large portions of the global extratropics and can easily be expanded to cover novel forest types.

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.

Transcriptomics, the quantification of gene expression, provides a versatile tool for ecological monitoring. Here, we show that through genome-guided profiling of transcripts mapping to 33,042 loci, gene expression differences can be discerned among multi-year and seasonal leaf samples collected from American beech trees at two latitudinally separated sites. Despite a bottleneck imposed due to large-scale post-Columbian deforestation, the SNP-based population genetic background analysis has yielded sufficient variation to account for differences between populations and among individuals. Our time series of expression analyses during spring-summer and summer-fall transitions for two consecutive years involved 4197 differentially expressed protein coding genes. A global comparison of 12 seasons has revealed that spring gene expression sets the pace for the rest of the growing season. UsingPopulusorthologs of the differentially expressed genes, we reconstructed a protein-protein interactome as a representation of the leaf physiological states of trees during the seasonal transitions. Gene set enrichment analysis revealed GO terms that highlight molecular functions and biological processes possibly influenced by abiotic forcings such as recovery from drought and response to excess precipitation. Further, based on 324 co-regulated transcripts, we focused on a subset of terms that could be putatively attributed to phenological shifts due to late spring. Our conservative results indicate that extended transcriptome-based monitoring of forests can capture ranges of responses arising from other factors including air quality, chronic disease as well as herbivore outbreaks that require activation and/or downregulation of genes collectively tuning reaction norms needed for the survival of long living trees such as the American beech.

Globally, forests provide important ecosystem services, but anthropogenic change may shift the boundaries of forested biomes, because small-scale environmental changes govern biome transitions. This is especially true in semi-arid forests, where minor topographic and microclimatic changes influence forest functioning and transitions to open biomes such as grasslands. However, we lack quantitative descriptions of topographically driven microclimate variation and how it shapes forest structure, diversity, and composition in these transition zones.Leveraging a 20.2-ha forest inventory plot (Niobrara plot) at a semi-arid forest-grassland transition zone in the Niobrara River valley (Nebraska, USA), we paired data on abundances and distributions of seedlings, saplings, and adults of woody species with topographic and microclimate data to test the hypothesis that if topographic variation causes variation in microclimate that affects forest function, then forest structure, diversity, and composition should vary significantly with topography and microclimate.Microclimatic variation within the Niobrara plot strongly corresponded with topography, creating a sharp water availability and exposure gradient from the river floodplain to the forest-grassland transition zone. The magnitude of microclimate variation corresponded to that of regional macroclimate variation. Mean soil moisture was 10.2% lower along the higher-elevation transition zone than in the canyon bottoms, corresponding to variation across approximately 2.5 degrees of longitude. Mean air temperature increased by 2.2 °C from the canyon bottoms to upper canyon, corresponding to variation across approximately 3 degrees of latitude.Forest structure, diversity, and composition correlated strongly with topographic and microclimatic gradients. More complex forest structure and higher species richness of adults and saplings occurred in moister, less exposed habitats with steeper slopes and lower elevations, whereas seedling stem density and richness were higher in higher-light, moister habitats at lower elevations. Species occupied well-defined topographic niches, promoting high beta diversity along topographic and microclimatic gradients and high species turnover from the floodplain to the transition zone.Synthesis: Microclimatic and topographic variation drive patterns of structure, diversity, and composition in the forests at this forest-grassland transition zone. As the macroclimate becomes warmer and drier, topographically mediated microclimatic refuges supporting diverse, structurally complex forested ecosystems may shrink in semi-arid regions.

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 35years (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.

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 effects of climate change on tropical forests will depend on how diverse tropical tree species respond to drought. Current distributions of evergreen and deciduous tree species across local and regional moisture gradients reflect their ability to tolerate drought stress, and might be explained by functional traits. We measured leaf water potential at turgor loss (i.e. ‘wilting point’; πtlp), wood density (WD) and leaf mass per area (LMA) on 50 of the most abundant tree species in central Panama. We then tested their ability to explain distributions of evergreen and deciduous species within a 50 ha plot on Barro Colorado Island and across a 70 km rainfall gradient spanning the Isthmus of Panama. Among evergreen trees, species with lower πtlp were associated with drier habitats, with πtlp explaining 28% and 32% of habitat association on local and regional scales, respectively, greatly exceeding the predictive power of WD and LMA. In contrast, πtlp did not predict habitat associations among deciduous species. Across spatial scales, πtlp is a useful indicator of habitat preference for tropical tree species that retain their leaves during periods of water stress, and holds the potential to predict vegetation responses to climate change.

Evidence exists that tree mortality is accelerating in some regions of the tropics1,2, with profound consequences for the future of the tropical carbon sink and the global anthropogenic carbon budget left to limit peak global warming below 2 °C. However, the mechanisms that may be driving such mortality changes and whether particular species are especially vulnerable remain unclear3,4,5,6,7,8. Here we analyse a 49-year record of tree dynamics from 24 old-growth forest plots encompassing a broad climatic gradient across the Australian moist tropics and find that annual tree mortality risk has, on average, doubled across all plots and species over the last 35 years, indicating a potential halving in life expectancy and carbon residence time. Associated losses in biomass were not offset by gains from growth and recruitment. Plots in less moist local climates presented higher average mortality risk, but local mean climate did not predict the pace of temporal increase in mortality risk. Species varied in the trajectories of their mortality risk, with the highest average risk found nearer to the upper end of the atmospheric vapour pressure deficit niches of species. A long-term increase in vapour pressure deficit was evident across the region, suggesting that thresholds involving atmospheric water stress, driven by global warming, may be a primary cause of increasing tree mortality in moist tropical forests.

As the climate changes, warmer spring temperatures are causing earlier leaf-out

Maples (the genus Acer) represent important and beloved forest, urban, and ornamental trees distributed throughout the Northern hemisphere. They exist in a diverse array of native ranges and distributions, across spectrums of tolerance or decline, and have varying levels of susceptibility to biotic and abiotic stress. Among Acer species, several stand out in their importance to economic interest. Here we report the first two chromosome-scale genomes for North American species, Acer negundo and Acer saccharum. Both assembled genomes contain scaffolds corresponding to 13 chromosomes, with A. negundo at a length of 442 Mb, an N50 of 32 Mb, and 30 491 genes, and A. saccharum at a length of 626 Mb, an N50 of 46 Mb, and 40 074 genes. No recent whole genome duplications were detected, though A. saccharum has local gene duplication and more recent bursts of transposable elements, as well as a large-scale translocation between two chromosomes. Genomic comparison revealed that A. negundo has a smaller genome with recent gene family evolution that is predominantly contracted and expansions that are potentially related to invasive tendencies and tolerance to abiotic stress. Examination of RNA sequencing data obtained from A. saccharum given long-term aluminum and calcium soil treatments at the Hubbard Brook Experimental Forest provided insights into genes involved in the aluminum stress response at the systemic level, as well as signs of compromised processes upon calcium deficiency, a condition contributing to maple decline.

Maples (the genus Acer) represent important and beloved forest, urban, and ornamental trees distributed throughout the Northern hemisphere. They exist in a diverse array of native ranges and distributions, across spectrums of tolerance or decline, and have varying levels of susceptibility to biotic and abiotic stress. Among Acer species, several stand out in their importance to economic interest. Here we report the first two chromosome-scale genomes for North American species, Acer negundo and Acer saccharum. Both assembled genomes contain scaffolds corresponding to 13 chromosomes, with A. negundo at a length of 442 Mb, N50 of 32 Mb and 30,491 genes, and A. saccharum at 626 Mb, N50 of 46 Mb, and 40,074 genes. No recent whole genome duplications were detected, though A. saccharum has local gene duplication and more recent bursts of transposable elements, as well as a large-scale translocation between two chromosomes. Genomic comparison revealed that A. negundo has a smaller genome with recent gene family evolution that is predominantly contracted and expansions that are potentially related to invasive tendencies and tolerance to abiotic stress. Examination of expression from RNA-Seq obtained from A. saccharum grown in long-term aluminum and calcium soil treatments at the Hubbard Brook Experimental Forest, provided insights into genes involved in aluminum stress response at the systemic level, as well as signs of compromised processes upon calcium deficiency, a condition contributing to maple decline.Significance statementThe first chromosome-scale assemblies for North American members of the Acer genus, sugar maple (Acer saccharum) and boxelder (Acer negundo), as well as transcriptomic evaluation of abiotic stress response in A. saccharum. This integrated study describes in-depth aspects contributing to each species’ approach to tolerance and applies current knowledge in many areas of plant genome biology with Acer physiology to help convey the genomic complexities underlying tolerance in broadleaf tree species.

Evidence exists that tree mortality is accelerating in some regions of the tropics

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) and short-term deviations from these averages (anomalies) both influence tree growth, but the rarity of long-term data integrating climatic gradients with tree censuses has so far limited our understanding of their respective role, especially in tropical systems. Here, we combined 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how tree growth responds to both climate means and anomalies, and how species functional traits mediate these tree growth responses to climate. We showed that short-term, 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 long-term and short-term climate variations. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests, and that species traits can be leveraged to understand these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.

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., The relationship of mycorrhizal associations with latitudinal gradients in tree beta-diversity is unexplored. Using a global dataset approach, this study examines how trees with arbuscular mycorrhizal and ectomycorrhizal associations contribute to latitudinal beta-diversity patterns and the environmental controls of these patterns.

Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process-explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process-explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs - regulatory planning, extinction risk, climate refugia and invasive species - we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process-explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised.

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

Linking drought to the timing of physiological processes governing tree growth remains one limitation in forecasting climate change effects on tropical trees. Using dendrometers, we measured fine-scale growth for 96 trees of 25 species from 2013 to 2016 in an everwet forest in Puerto Rico. Rainfall over this time span varied, including an unusual, severe El Niño drought in 2015. We assessed how growing season onset, median day, conclusion, and length varied with absolute growth rate and tree size over time. Stem growth was seasonal, beginning in February, peaking in July, and ending in November. Species growth rates varied between 0 and 8 mm/year and correlated weakly with specific leaf area, leaf phosphorus, and leaf nitrogen, and to a lesser degree with wood specific gravity and plant height. Drought and tree growth were decoupled, and drought lengthened and increased variation in growing season length. During the 2015 drought, many trees terminated growth early but did not necessarily grow less. In the year following drought, trees grew more over a shorter growing season, with many smaller trees showing a post-drought increase in growth. We attribute the increased growth of smaller trees to release from light limitation as the canopy thinned because of the drought, and less inferred hydraulic stress than larger trees during drought. Soil type accounted for interannual and interspecific differences, with the finest Zarzal clays reducing tree growth. We conclude that drought affects the phenological timing of tree growth and favors the post-drought growth of smaller, sub-canopy trees in this everwet forest.

In this repository, the trait data used for the analysis in the article "Leaf turgor loss point shapes local and regional distributions of evergreen but not deciduous tropical trees" is made available.&nbsp

Background: COVID-19 can result in a severe viral pneumonia, with high reported mortality rates in patients requiring mechanical ventilation. There is controversy as to whether established therapeutic approaches to acute respiratory distress syndrome are optimal in this condition, and numerous novel therapies have been used, often outside the context of randomised trials. In addition, longer term quality of life outcomes associated with COVID-19 are as yet unknown. The aim of this case series is to describe demographic, physiological and outcome data of patients with COVID-19 admitted to our intensive care units who were treated according to evidence-based guidelines for acute respiratory distress syndrome.Methods: We retrospectively reviewed the records of all patients admitted to intensive care units in our institution with COVID-19 between March and June, 2020. Physiological and laboratory data were recorded at baseline and daily until intensive care discharge or death. Quality of life was assessed at a virtual post-intensive care follow-up clinic around 10 weeks after ICU discharge.Results: 45 patients with COVID-19 were included, 37 (82.2%) of whom were male, with a mean age of 55 years. 42 (93.3%) of this cohort met criteria for acute respiratory distress syndrome at time of admission. Clinical management was consistent with evidence based institutional guidelines introduced for acute respiratory distress syndrome. Median length of intensive care stay was 14 days. The intensive care mortality rate was 8.9%. Functional and psychological morbidity post intensive care was significant: 45.2% of respondents had at least moderate impairment of mobility and 35.5% described at least moderate symptoms of anxiety or depression at the time of follow up.Conclusions : This case series demonstrates low mortality in a cohort of patients treated according to an established evidence-based approach for acute respiratory distress syndrome. However, COVID-19 survivors have a marked functional and psychological morbidity impacting quality of life following ICU admission. The therapeutic goal in the future will be to achieve similar survival outcomes while minimizing the significant morbidity associated with COVID-19 related critical care admission.

Atmospheric carbon dioxide concentration ([CO

© 2018, The Author(s). 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.

© 2019 John Wiley & Sons Ltd 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.

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

Fagus sylvatica (European beech) populations in Central Europe are currently expanding their dominance in many forest types. In this study we focused on the spatio-temporal dynamics of beech recruitment as a mechanism for successful expansion. Specifically we investigated: (1) the developmental trend of the tree community composition and spatial pattern in an unmanaged Picea abies-F. sylvatica forest over 37 years, (2) the pattern of decrease in clustering along increasing tree size gradient of beech, and (3) the spatial patterns of beech regeneration in relation to gap-makers. The study was conducted in the Žofin Forest Dynamics Plot, which is part to the Smithsonian Institution’s Forest Global Earth Observatory (ForestGEO) as the research plot representing European natural mixed temperate forests. To quantify these dynamics, we used the stem map of trees with DBH ⩾ 10 cm carried out in 1975, 1997, 2008 and a census of trees with DBH ⩾ 1 cm from 2012 to calculate recruitment, growth, mortality and, from those vital rates, population change. Various types of the pair correlation function were applied to the data to describe the tree density variability over time. Our analyses revealed a trend of increasing F. sylvatica representation at the expense of P. abies and Abies alba over the 37 years. Increased clustering of F. sylvatica trees with DBH ⩾ 10 cm correlated with new recruits at plots where F. sylvatica replaced declining P. abies . On the other hand, the decrease in F. sylvatica clustering at some plots was likely due to strong intra-specific competition. The analysis of the spatial patterns of F. sylvatica individuals along DBH gradient 1–9 cm showed a trend of increasing clustering up to 5 m distance. F. sylvatica saplings to 4 cm of DBH were positively spatially correlated with other conspecific individuals, although at larger sizes (DBH 7–9 cm), this relationship reversed to a negative correlation. Analysis of relationships between saplings and gap-makers did not reveal a clear pattern. We concluded that without a coarse-scale disturbance capable of restructuring the community, F. sylvatica will become the only dominant tree species in this forest type. F. sylvatica gradually replaces P. abies through its space occupation strategy because its recruits are already present before a canopy disturbance. Our results indicate that F. sylvatica saplings can grow up to 4 cm DBH under a closed canopy, but require a canopy disturbance to advance to a larger size class.

Conceptual models that describe temperate forest dynamics differ substantially between Europe and America. In Europe, the concept of the forest cycle describes a sequentially shifting fine-scale mosaic of patches in different phases of forest development. In North America, the descriptive concept is largely based on severe coarse-scale disturbances that repeat in a cyclic fashion and restart the succession of the whole forest stand from initiation through to ‘old-growth,’ neglecting the within-stand dynamics on the patch level. Here, we investigate fine-scale stand structures across European and North American forests by applying the European concept of forest developmental phases to all stands. The patches of four major forest developmental stages were recognized and delineated by the spatially explicit rule-based classification system implemented in GIS, which employs stem position maps of live and dead trees for analysis. The basic quantitative characteristics of identified patch structures in the N. American stands, as the Mean Patch Size of the mosaic (between 760 and 890 m2), were comparable with European old-growth stands, although mosaic complexity was higher in the latter. We demonstrated that in addition to the large-scale forest cycle assumed by N. American conceptual models there simultaneously exist finer-scale patch dynamics described by the European conceptual model. We also demonstrated that the occurrence of the Steady State stage was promoted by higher local tree species richness, which may explain the abundant occurrence of this stage in N. American secondary stands. The Steady State stage of the European model might represent an important commonality across both paradigms.

Population ecology, the discipline that studies the dynamics of species' populations and how they interact with the environment, has been one of the most prolific fields of ecology and evolution. Demographic research is central to quantifying population-level processes and their underlying mechanisms and has provided critical contributions to a diversity of research fields. Examples include the spread of infectious diseases, eco-evolutionary dynamics and rapid evolution, mechanisms underlying invasions and extinctions, and forest productivity. As the fates of individual organisms are influenced by, and subsequently underlie, many other patterns and processes, we suggest that connecting demography beyond the population level offers promising avenues of innovation in ecology and evolution. Under the premise that population-level processes are an ideal common currency within ecology and evolution, we organized the British Ecological Society Symposium, Demography Beyond the Population. This event attracted international researchers who are applying demographic theory and approaches to a broad range of questions. This special feature builds off of the symposium and illustrates the ability of demography to connect across diverse research areas in ecology and evolution, including functional traits, transient dynamics, quantitative genetics, environmental drivers and feedbacks, land management and other topics. In addition to highlighting the contributed manuscripts, this editorial provides a brief background on the development of the discipline and suggests how demographic tools may be used in novel ways to study more than just populations. Synthesis. This special feature integrates novel lines of research in the vast field of demography that directly interact with other ecological and evolutionary disciplines. The cross-disciplinary potential of demography is further emphasized by the fact that its 20 manuscripts are spread across all six journals of the British Ecological Society. Together, these articles highlight that there is much to be gained by linking demography to other disciplines and scales in ecology and evolution. This special feature integrates novel lines of research in the vast field of demography that directly interact with other ecological and evolutionary disciplines. The cross-disciplinary potential of demography is further emphasized by the fact that its 20 manuscripts are spread across all six journals of the British Ecological Society. Together, these articles highlight that there is much to be gained by linking demography to other disciplines and scales in ecology and evolution.

Large-scale mortality events in forests are increasing in frequency and intensity and can lead to both intermediate- and long-term changes in these systems. Specialist pests and pathogens are unique disturbances, as they commonly target individual species that are relatively prevalent in the community. Understanding the consequences of pathogen-caused mortality requires using sometimes limited available data to create statistical models that can forecast future community states. In the last two decades, ash dieback disease has swept through Europe causing widespread mortality of Fraxinus excelsior L. (European ash) across much of its distribution. In the UK, F. excelsior is an abundant and ecologically important species. Using demographic data from an 18 ha plot in Wytham Woods, Oxfordshire, we built models that forecast the response of this forest plot to the loss of F. excelsior. We combine integral projection models and individual-based models to link models of growth, survival and fecundity to population dynamics. We demonstrate likely responses in Wytham by comparing projections under different levels of F. excelsior mortality. To extrapolate results to other systems, we test hypotheses regarding the role of abundance, spatial structure and demographic differences between species in determining community response to disease disturbance. We show that the outcome of succession is determined largely by the differing demographic strategies and starting abundances of competing species. Spatial associations between species were shown to have little effect on community dynamics at the spatial scale of this plot. Synthesis. Host-specific pests and pathogens are an increasingly important type of disturbance. We have developed a framework that makes use of forest inventory data to forecast changes in the population dynamics of remaining species and the consequences for community structure. We use our framework to predict how a typical British woodland will respond to ash dieback disease and show how vital rates, spatial structure and abundance impact the community response to the loss of a key species. Host-specific pests and pathogens are an increasingly important type of disturbance. We have developed a framework that makes use of forest inventory data to forecast changes in the population dynamics of remaining species and the consequences for community structure. We use our framework to predict how a typical British woodland will respond to ash dieback disease and show how vital rates, spatial structure and abundance impact the community response to the loss of a key species.

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 Nino 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.

This article focuses on the use of Bayesian methods in assessing the probability of rare climate events, and more specifically the potential collapse of the meridional overturning circulation (MOC) in the Atlantic Ocean. It first provides an overview of climate models and their use to perform climate simulations, drawing attention to uncertainty in climate simulators and the role of data in climate prediction, before describing an experiment that simulates the evolution of the MOC through the twenty-first century. MOC collapse is predicted by the GENIE-1 (Grid Enabled Integrated Earth system model) for some values of the model inputs, and Bayesian emulation is used for collapse probability analysis. Data comprising a sparse time series of five measurements of the MOC from 1957 to 2004 are analysed. The results demonstrate the utility of Bayesian analysis in dealing with uncertainty in complex models, and in particular in quantifying the risk of extreme outcomes.

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

Interspecific variation in the secondary metabolites of plants constrains host specificity of insect herbivores and microbial pathogens. The intensity and specificity of these plant-pest interactions is widely believed to increase towards the Equator, leading to the prediction that secondary metabolites should differ more among co-occurring plant species in tropical communities than in temperate communities. To evaluate this prediction, we quantified metabolomic similarity for 203 tree species that represent >89% of all individuals in large forest plots in Maryland and Panama. We constructed molecular networks based on mass spectrometry of all 203 species, quantified metabolomic similarity for all pairwise combinations of species, and evaluated how pairwise metabolomic similarity varies phylogenetically. Leaf metabolomes exhibited clear phylogenetic signal for the temperate plot, with high similarity among congeneric species. In contrast, leaf metabolomes lacked phylogenetic signal for the tropical plot, with low similarity among congeners. Our results suggest that species differences in secondary chemistry comprise important axes of niche differentiation among tropical trees, especially within species-rich genera, and that the contribution of species differences in secondary chemistry to niche differences increases towards the equator in forest tree communities.

Plant enemies that attack chemically similar host species are thought to mediate competitive exclusion of chemically similar plants and select for chemical divergence among closely related species. This hypothesis predicts that plant defenses should diverge rapidly, minimizing phylogenetic signal. To evaluate this prediction, we quantified metabolomic similarity for 203 tree species that represent >89% of all individuals in large forest plots in Maryland and Panama. We constructed molecular networks based on mass spectrometry of all 203 species, quantified metabolomic similarity for all pairwise combinations of species, and used phylogenetically independent contrasts to evaluate how pairwise metabolomic similarity varies phylogenetically. Leaf metabolomes exhibited clear phylogenetic signal for the temperate plot, which is inconsistent with the prediction. In contrast, leaf metabolomes lacked phylogenetic signal for the tropical plot, with particularly low metabolomic similarity among congeners. In addition, community-wide variation in metabolomes was much greater for the tropical community, with single tropical genera supporting greater metabolomic variation than the entire temperate community. Our results are consistent with the hypothesis that stronger plant-enemy interactions lead to more rapid divergence and greater metabolomic variation in tropical than temperate plants. Additional community-level foliar metabolomes will be required from tropical and temperate forests to evaluate this hypothesis.

Summary Temporal fluctuations in vital rates such as survival, growth or reproduction alter long-term population dynamics and can change the dynamics from invasion and population persistence to extinction. Projections of population dynamics made in the absence of such fluctuations may consequently be misleading. However, data for estimation of yearly fluctuations in demographic parameters are often limited. Accordingly, the current diverse range of statistical and demographic modelling strategies used for stochastic population modelling may influence predictions. We used simulations to explore the effects of different methods of parameter estimation on projections of population dynamics obtained using stochastic integral projection models (IPMs). The simulations were built from data on a monocarpic thistle, Carlina vulgaris, and an ungulate, Soay sheep, Ovis aries; these populations are subject to yearly fluctuation in vital rates facilitating the exploration of the effects of different methods of model construction on the properties of stochastic IPMs. Specifically, we looked at effects on the stochastic growth rate, log λs, and the mean and variance in the one-step population growth rate (Nt+1/Nt). Our analyses showed that none of the tested approaches resulted in large biases in the estimation of log λs. However, when realistic study durations (e.g. 12 years) were used for statistical modelling, the confidence intervals around the λs estimates remained large. Estimation of the variance in one-step population growth rates, on the other hand, was strongly sensitive to the method employed, and the overestimation and underestimation of the variance were also influenced by the life history of the organism. Our findings highlight the need to consider the influences of statistical and demographic modelling approaches when population dynamics have significant temporal stochasticity, as in population viability analyses and evolutionary predictions of bet hedging.

Summary 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. 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. 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. Scaling relationships were variable among species, reflecting substantive ecological differences. 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. 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 conditions.

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.

The structure of forest canopies correlates with stand maturity and biomass, and develops consistently over time. Remote-sensing technologies such as Light Detection and Ranging (LiDAR) have become prominent tools for measuring structural characteristics of forests.We walked a portable canopy LiDAR (PCL), an up-facing rangefinder that detects vegetation through the canopy at two kilohertz, along multiple transects at ten different forest stands in the area of Wytham Woods, Oxfordshire, UK. The stands had different species composition, were situated at forest edges and in forest core, were in fragments of different sizes and had different land-use histories. With these data we tested structural differences in vegetation across these stand types.Although none of the stands have been managed in the last 70. years, they have not converged structurally. Vertical canopy structure differed between stands that regrew naturally from open field and those with a history of coppice management. Forest stands that have developed following major fellings or through spread on to former grazing land showed some structural similarities to classic natural succession from large disturbances. Stands that were actively managed as coppice over preceding centuries, showed a similar structural pattern to mature forest, but without the tall overstorey that can develop into old growth communities.This structural divergence indicates two distinct pathways for secondary forests: with implications for the future biomass, stand structure, and species composition. The legacy of management practices can determine canopy structure decades after the forest is removed from active management, but can also be difficult to discern with remote sensing data. We recommend that "ground-truthing" remote sensing data go beyond traditional checks of height and topography, as the history and composition of secondary forests can have an important influence on the pace and compositional structure of recovery from management.

Tree growth is an important indicator of forest health, productivity, and demography. Knowing precisely how trees' grow within a year, instead of across years, can lead to a finer understanding of the mechanisms that drive these larger patterns. The growing use of dendrometer bands in research forests has only rarely been used to measure growth at resolutions finer than yearly, but intra-annual growth patterns can be observed from dendrometer bands using precision digital calipers and weekly measurements. Here we present a workflow to help forest ecologists fit growth models to intra-annual measurements using standard optimization functions provided by the R platform. We explain our protocol, test uncertainty in parameter estimates with respect to sample sizes, extend the optimization protocol to estimate robust lower and upper annual diameter bounds, and discuss potential challenges to optimal fits. We offer R code to implement this workflow. We found that starting values and initial optimization routines are critical to fitting the best functional forms. After using a bounded, broad search method, a more focused search algorithm obtained consistent results. To estimate starting and ending annual diameters, we combined the growth function with early and late estimates of beginning and ending growth. Once we fit the functions, we present extension algorithms that estimate periodic reductions in growth, total growth, and present a method of controlling for the shifting allocation to girth during the growth season. We demonstrate that with these extensions, an analysis of growth response to weather (e.g., the water available to a tree) can be derived in a way that is comparable across trees, years, and sites. Thus, this approach, when applied across broader data sets, offers a pathway to build inference about the effects of seasonal weather on growth, size- and light-dependent patterns of growth, species-specific patterns, and phenology.

The shifting mosaic of patches in different phases of forest development is a widely used framework for describing stand dynamics, structure and biodiversity in European temperate forests. In spite of the common application of patch mapping of developmental stages/phases, an objective and quantified evaluation of patch mosaics has been missing. This approach identifies patches of forest stand according to a developmental trajectory, from Growth, through an Optimum stage to Breakdown. Here we present the first attempt to compare quantitative and qualitative characteristics of patch mosaics of stand developmental stages using three decades of extensive data in five study sites along a vegetation gradient. We do this using the same, observer independent method based on an artificial neural network classifier. We also used the historical stem position datasets to evaluate the change of mosaic characteristics in time. Resulting patch patterns were analyzed by standard mosaic metrics commonly used in landscape ecology, evaluating area, shape, aggregation and connectivity of patches. The mean patch size of the mosaic of four developmental stages showed a relatively narrow range of 570–800 m 2 in all study sites and censuses. The shape of patches in all sites and years had no significant differences, and the aggregation of patches of the same type was similar in all sites at the mosaic level. Conversely, we did find some stage-specific patterns. For example, the Growth stage was usually the most abundant (covering 25–50% of the stand), and had the highest mean patch size, ranging between 590 and 2800 m 2 . The Growth stage patches also had the most complex shapes. On the contrary, the Breakdown stage usually had the opposite values, forming constantly small (250–720 m 2 ), simple and scattered patches in the mosaic. These basic traits were found in all study sites and were stable in time. We also found some common trends in the dataset, such as increasing mean patch size of the Breakdown stage along the altitudinal vegetation gradient. The complex Steady State stage was generally more abundant than expected according to results of other studies and thus might indicate processes that have not been well described in previous, subjective, applications of the patch mosaic paradigm.

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

Knowledge of species' geographic distributions is critical for understanding and forecasting population dynamics, responses to environmental change, biodiversity patterns, and conservation planning. While many suggestive correlative occurrence models have been used to these ends, progress lies in understanding the underlying population biology that generates patterns of range dynamics. Here, we show how to use a limited quantity of demographic data to produce demographic distribution models (DDMs) using integral projection models for size-structured populations. By modeling survival, growth, and fecundity using regression, integral projection models can interpolate across missing size data and environmental conditions to compensate for limited data. To accommodate the uncertainty associated with limited data and model assumptions, we use Bayesian models to propagate uncertainty through all stages of model development to predictions. DDMs have a number of strengths: 1) DDMs allow a mechanistic understanding of spatial occurrence patterns; 2) DDMs can predict spatial and temporal variation in local population dynamics; 3) DDMs can facilitate extrapolation under altered environmental conditions because one can evaluate the consequences for individual vital rates. To illustrate these features, we construct DDMs for an overstory perennial shrub in the Proteaceae family in the Cape Floristic Region of South Africa. We find that the species' population growth rate is limited most strongly by adult survival throughout the range and by individual growth in higher rainfall regions. While the models predict higher population growth rates in the core of the range under projected climates for 2050, they also suggest that the species faces a threat along arid range margins from the interaction of more frequent fire and drying climate. The results (and uncertainties) are helpful for prioritizing additional sampling of particular demographic parameters along these gradients to iteratively refine projections. In the appendices, we provide fully functional R code to perform all analyses.