Vegetation demographics in Earth System Models: A review of progress and priorities

Tree crown damage and its effects on forest carbon cycling in a tropical forest

Crown damage can account for over 23% of canopy biomass turnover in tropical forests and is a strong predictor of tree mortality; yet, it is not typically represented in vegetation models. We incorporate crown damage into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to evaluate how lags between damage and tree recovery or death alter demographic rates and patterns of carbon turnover. We represent crown damage as a reduction in a tree's crown area and leaf and branch biomass, and allow associated variation in the ratio of aboveground to belowground plant tissue. We compare simulations with crown damage to simulations with equivalent instant increases in mortality and benchmark results against data from Barro Colorado Island (BCI), Panama. In FATES, crown damage causes decreases in growth rates that match observations from BCI. Crown damage leads to increases in carbon starvation mortality in FATES, but only in configurations with high root respiration and decreases in carbon storage following damage. Crown damage also alters competitive dynamics, as plant functional types that can recover from crown damage outcompete those that cannot. This is a first exploration of the trade-off between the additional complexity of the novel crown damage module and improved predictive capabilities. At BCI, a tropical forest that does not experience high levels of disturbance, both the crown damage simulations and simulations with equivalent increases in mortality does a reasonable job of capturing observations. The crown damage module provides functionality for exploring dynamics in forests with more extreme disturbances such as cyclones and for capturing the synergistic effects of disturbances that overlap in space and time.

A Conceptual Framework to Integrate Biodiversity, Ecosystem Function, and Ecosystem Service Models

Global biodiversity and ecosystem service models typically operate independently. Ecosystem service projections may therefore be overly optimistic because they do not always account for the role of biodiversity in maintaining ecological functions. We review models used in recent global model intercomparison projects and develop a novel model integration framework to more fully account for the role of biodiversity in ecosystem function, a key gap for linking biodiversity changes to ecosystem services. We propose two integration pathways. The first uses empirical data on biodiversity-ecosystem function relationships to bridge biodiversity and ecosystem function models and could currently be implemented globally for systems and taxa with sufficient data. We also propose a trait-based approach involving greater incorporation of biodiversity into ecosystem function models. Pursuing both approaches will provide greater insight into biodiversity and ecosystem services projections. Integrating biodiversity, ecosystem function, and ecosystem service modeling will enhance policy development to meet global sustainability goals.

Summer temperature—but not growing season length—influences radial growth of Salix arctica in coastal Arctic tundra

Arctic climate change is leading to an advance of plant phenology (the timing of life history events) with uncertain impacts on tundra ecosystems. Although the lengthening of the growing season is thought to lead to increased plant growth, we have few studies of how plant phenology change is altering tundra plant productivity. Here, we test the correspondence between 14 years of Salix arctica phenology data and radial growth on Qikiqtaruk–Herschel Island, Yukon Territory, Canada. We analysed stems from 28 individuals using dendroecology and linear mixed-effect models to test the statistical power of growing season length and climate variables to individually predict radial growth. We found that summer temperature best explained annual variation in radial growth. We found no strong evidence that leaf emergence date, earlier leaf senescence date, or total growing season length had any direct or lagged effects on radial growth. Radial growth was also not explained by interannual variation in precipitation, MODIS surface greenness (NDVI), or sea ice concentration. Our results demonstrate that at this site, for the widely distributed species S. arctica, temperature—but not growing season length—influences radial growth. These findings challenge the assumption that advancing phenology and longer growing seasons will increase the productivity of all plant species in Arctic tundra ecosystems.

Forest regeneration within Earth system models: current process representations and ways forward

Earth system models must predict forest responses to global change in order to simulate future global climate, hydrology, and ecosystem dynamics. These models are increasingly adopting vegetation demographic approaches that explicitly represent tree growth, mortality, and recruitment, enabling advances in the projection of forest vulnerability and resilience, as well as evaluation with field data. To date, simulation of regeneration processes has received far less attention than simulation of processes that affect growth and mortality, in spite of their critical role maintaining forest structure, facilitating turnover in forest composition over space and time, enabling recovery from disturbance, and regulating climate-driven range shifts. Our critical review of regeneration process representations within current Earth system vegetation demographic models reveals the need to improve parameter values and algorithms for reproductive allocation, dispersal, seed survival and germination, environmental filtering in the seedling layer, and tree regeneration strategies adapted to wind, fire, and anthropogenic disturbance regimes. These improvements require synthesis of existing data, specific field data-collection protocols, and novel model algorithms compatible with global-scale simulations. Vegetation demographic models offer the opportunity to more fully integrate ecological understanding into Earth system prediction; regeneration processes need to be a critical part of the effort.

Simulating environmentally-sensitive tree recruitment in vegetation demographic models

Vegetation demographic models (VDMs) endeavor to predict how global forests will respond to climate change. This requires simulating which trees, if any, are able to recruit under changing environmental conditions. We present a new recruitment scheme for VDMs in which functional-type-specific recruitment rates are sensitive to light, soil moisture and the productivity of reproductive trees. We evaluate the scheme by predicting tree recruitment for four tropical tree functional types under varying meteorology and canopy structure at Barro Colorado Island, Panama. We compare predictions to those of a current VDM, quantitative observations and ecological expectations. We find that the scheme improves the magnitude and rank order of recruitment rates among functional types and captures recruitment limitations in response to variable understory light, soil moisture and precipitation regimes. Our results indicate that adopting this framework will improve VDM capacity to predict functional-type-specific tree recruitment in response to climate change, thereby improving predictions of future forest distribution, composition and function.

Informing Nature-based Climate Solutions for the United States with the best-available science

Nature-based Climate Solutions (NbCS) are managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions. While they have growing public and private support, the realizable benefits and unintended consequences of NbCS are not well understood. At regional scales where policy decisions are often made, NbCS benefits are estimated from soil and tree survey data that can miss important carbon sources and sinks within an ecosystem, and do not reveal the biophysical impacts of NbCS for local water and energy cycles. The only direct observations of ecosystem-scale carbon fluxes, for example, by eddy covariance flux towers, have not yet been systematically assessed for what they can tell us about NbCS potentials, and state-of-the-art remote sensing products and land-surface models are not yet being widely used to inform NbCS policymaking or implementation. As a result, there is a critical mismatch between the point- and tree-scale data most often used to assess NbCS benefits and impacts, the ecosystem and landscape scales where NbCS projects are implemented, and the regional to continental scales most relevant to policymaking. Here, we propose a research agenda to confront these gaps using data and tools that have long been used to understand the mechanisms driving ecosystem carbon and energy cycling, but have not yet been widely applied to NbCS. We outline steps for creating robust NbCS assessments at both local to regional scales that are informed by ecosystem-scale observations, and which consider concurrent biophysical impacts, future climate feedbacks, and the need for equitable and inclusive NbCS implementation strategies. We contend that these research goals can largely be accomplished by shifting the scales at which pre-existing tools are applied and blended together, although we also highlight some opportunities for more radical shifts in approach.

Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning: Average climate versus extremes

The global distribution of vegetation is largely determined by climatic conditions and feeds back into the climate system. To predict future vegetation changes in response to climate change, it is crucial to identify and understand key patterns and processes that couple vegetation and climate. Dynamic global vegetation models (DGVMs) have been widely applied to describe the distribution of vegetation types and their future dynamics in response to climate change. As a process-based approach, it partly relies on hard-coded climate thresholds to constrain the distribution of vegetation. What thresholds to implement in DGVMs and how to replace them with more process-based descriptions remain among the major challenges. In this study, we employ machine learning using decision trees to extract large-scale relationships between the global distribution of vegetation and climatic characteristics from remotely sensed vegetation and climate data. We analyse how the dominant vegetation types are linked to climate extremes as compared to seasonally or annually averaged climatic conditions. The results show that climate extremes allow us to describe the distribution and eco-climatological space of the vegetation types more accurately than the averaged climate variables, especially those types which occupy small territories in a relatively homogeneous ecological space. Future predicted vegetation changes using both climate extremes and averaged climate variables are less prominent than that predicted by averaged climate variables and are in better agreement with those of DGVMs, further indicating the importance of climate extremes in determining geographic distributions of different vegetation types. We found that the temperature thresholds for vegetation types (e.g. grass and open shrubland) in cold environments vary with moisture conditions. The coldest daily maximum temperature (extreme cold day) is particularly important for separating many different vegetation types. These findings highlight the need for a more explicit representation of the impacts of climate extremes on vegetation in DGVMs.

Distribution of biomass dynamics in relation to tree size in forests across the world

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.

Future climate risks from stress, insects and fire across US forests

Forests are currently a substantial carbon sink globally. Many climate change mitigation strategies leverage forest preservation and expansion, but rely on forests storing carbon for decades to centuries. Yet climate‐driven disturbances pose critical risks to the long‐term stability of forest carbon. We quantify the climate drivers that influence wildfire and climate stress‐driven tree mortality, including a separate insect‐driven tree mortality, for the contiguous United States for current (1984–2018) and project these future disturbance risks over the 21st century. We find that current risks are widespread and projected to increase across different emissions scenarios by a factor of >4 for fire and >1.3 for climate‐stress mortality. These forest disturbance risks highlight pervasive climate‐sensitive disturbance impacts on US forests and raise questions about the risk management approach taken by forest carbon offset policies. Our results provide US‐wide risk maps of key climate‐sensitive disturbances for improving carbon cycle modeling, conservation and climate policy.

Limits to reproduction and seed size-number trade-offs that shape forest dominance and future recovery

The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential.

MASTREE+: Time-series of plant reproductive effort from six continents

Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics.

Globally, tree fecundity exceeds productivity gradients

Lack of tree fecundity data across climatic gradients precludes the analysis of how seed supply contributes to global variation in forest regeneration and biotic interactions responsible for biodiversity. A global synthesis of raw seedproduction data shows a 250-fold increase in seed abundance from cold-dry to warm-wet climates, driven primarily by a 100-fold increase in seed production for a given tree size. The modest (threefold) increase in forest productivity across the same climate gradient cannot explain the magnitudes of these trends. The increase in seeds per tree can arise from adaptive evolution driven by intense species interactions or from the direct effects of a warm, moist climate on tree fecundity. Either way, the massive differences in seed supply ramify through food webs potentially explaining a disproportionate role for species interactions in the wet tropics.

Field-based tree mortality constraint reduces estimates of model-projected forest carbon sinks

Considerable uncertainty and debate exist in projecting the future capacity of forests to sequester atmospheric CO₂. Here we estimate spatially explicit patterns of biomass loss by tree mortality (LOSS) from largely unmanaged forest plots to constrain projected (2015–2099) net primary productivity (NPP), heterotrophic respiration (HR) and net carbon sink in six dynamic global vegetation models (DGVMs) across continents. This approach relies on a strong relationship among LOSS, NPP, and HR at continental or biome scales. The DGVMs overestimated historical LOSS, particularly in tropical regions and eastern North America by as much as 5 Mg ha⁻¹ y⁻¹. The modeled spread of DGVM-projected NPP and HR uncertainties was substantially reduced in tropical regions after incorporating the field-based mortality constraint. The observation-constrained models show a decrease in the tropical forest carbon sink by the end of the century, particularly across South America (from 2 to 1.4 PgC y⁻¹), and an increase in the sink in North America (from 0.8 to 1.1 PgC y⁻¹). These results highlight the feasibility of using forest demographic data to empirically constrain forest carbon sink projections and the potential overestimation of projected tropical forest carbon sinks.

Here the authors use broad-scale tree mortality data to estimate biomass loss, constraining uncertainty of projected forest net primary productivity in 6 models, finding weaker tropical forest carbon sinks with climate change.

Global field observations of tree die-off reveal hotter-drought fingerprint for Earth's forests

Earth's forests face grave challenges in the Anthropocene, including hotter droughts increasingly associated with widespread forest die-off events. But despite the vital importance of forests to global ecosystem services, their fates in a warming world remain highly uncertain. Lacking is quantitative determination of commonality in climate anomalies associated with pulses of tree mortality-from published, field-documented mortality events-required for understanding the role of extreme climate events in overall global tree die-off patterns. Here we established a geo-referenced global database documenting climate-induced mortality events spanning all tree-supporting biomes and continents, from 154 peer-reviewed studies since 1970. Our analysis quantifies a global "hotter-drought fingerprint" from these tree-mortality sites-effectively a hotter and drier climate signal for tree mortality-across 675 locations encompassing 1,303 plots. Frequency of these observed mortality-year climate conditions strongly increases nonlinearly under projected warming. Our database also provides initial footing for further community-developed, quantitative, ground-based monitoring of global tree mortality.

Representing plant diversity in land models: An evolutionary approach to make "Functional Types" more functional

Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet, Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of "Plant Functional Types" (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, that is, to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution-based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages ("Lineage Functional Types") will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next-generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system.

Forest stand and canopy development unaltered by 12 years of CO2 enrichment

Canopy structure-the size and distribution of tree crowns and the spatial and temporal distribution of leaves within them-exerts dominant control over primary productivity, transpiration and energy exchange. Stand structure-the spatial arrangement of trees in the forest (height, basal area and spacing)-has a strong influence on forest growth, allocation and resource use. Forest response to elevated atmospheric CO2 is likely to be dependent on the canopy and stand structure. Here, we investigated elevated CO2 effects on the forest structure of a Liquidambar styraciflua L. stand in a free-air CO2 enrichment experiment, considering leaves, tree crowns, forest canopy and stand structure. During the 12-year experiment, the trees increased in height by 5 m and basal area increased by 37%. Basal area distribution among trees shifted from a relatively narrow distribution to a much broader one, but there was little evidence of a CO2 effect on height growth or basal area distribution. The differentiation into crown classes over time led to an increase in the number of unproductive intermediate and suppressed trees and to a greater concentration of stand basal area in the largest trees. A whole-tree harvest at the end of the experiment permitted detailed analysis of canopy structure. There was little effect of CO2 enrichment on the relative leaf area distribution within tree crowns and there was little change from 1998 to 2009. Leaf characteristics (leaf mass per unit area and nitrogen content) varied with crown depth; any effects of elevated CO2 were much smaller than the variation within the crown and were consistent throughout the crown. In this young, even-aged, monoculture plantation forest, there was little evidence that elevated CO2 accelerated tree and stand development, and there were remarkably small changes in canopy structure. Questions remain as to whether a more diverse, mixed species forest would respond similarly.

Forest system hydraulic conductance: partitioning tree and soil components

Soil-leaf hydraulic conductance determines canopy-atmosphere coupling in vegetation models, but it is typically derived from ex-situ measurements of stem segments and soil samples. Using a novel approach, we derive robust in-situ estimates for whole-tree conductance (k_tree ), 'functional' soil conductance (k_soil ), and 'system' conductance (k_system , water table to canopy), at two climatically different tropical rainforest sites. Hydraulic 'functional rooting depth', determined for each tree using profiles of soil water potential (Ψ_soil ) and sap flux data, enabled a robust determination of k_tree and k_soil . k_tree was compared across species, size classes, seasons, height above nearest drainage (HAND), two field sites, and to alternative representations of k_tree ; k_soil was analysed with respect to variations in site, season and HAND. k_tree was lower and changed seasonally at the site with higher vapour pressure deficit (VPD) and rainfall; k_tree differed little across species but scaled with tree circumference; r_soil (1/k_soil ) ranged from 0 in the wet season to 10× less than r_tree (1/k_tree ) in the dry season. VPD and not rainfall may influence plot-level k; leaf water potentials and sap flux can be used to determine k_tree , k_soil and k_system ; Ψ_soil profiles can provide mechanistic insights into ecosystem-level water fluxes.

Reducing model uncertainty of climate change impacts on high latitude carbon assimilation

The Arctic-Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO₂ . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Here we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology, and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.

Limitations to Propagule Dispersal Will Constrain Postfire Recovery of Plants and Fungi in Western Coniferous Forests

Many forest species are adapted to long-interval, high-severity fires, but the intervals between severe fires are decreasing with changes in climate, land use, and biological invasions. Although the effects of changing fire regimes on some important recovery processes have previously been considered, the consequences for the dispersal of propagules (plant seeds and fungal spores) in forest communities have not. We characterize three mechanisms by which changing fire regimes disrupt propagule dispersal in mesic temperate, boreal, and high-elevation forests: reduced abundance and altered spatial distributions of propagule source populations, less effective dispersal of propagules by wind, and altered behavior of animal dispersers and propagule predators. We consider how disruptions to propagule dispersal may interact with other factors that are also influenced by fire regime change, potentially increasing risk of forest conversion. Finally, we highlight urgent research topics regarding how dispersal limitation may shape twenty-first century forest recovery after stand-replacing fire.

JA, Sanchez‐Azofeifa GA, De Deurwaerder HPT, Krishna Moorthy SM, Schnitzer SA, Marvin DC, Longo M, Liu C, Broadbent EN, Almeyda Zambrano AM, Muller‐Landau HC, Detto M, Verbeeck H. Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (-30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (-19%) and ecosystem (-7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

Long-term leaf C:N ratio change under elevated CO2 and nitrogen deposition in China: Evidence from observations and process-based modeling

Climate change, elevating atmosphere CO₂ (eCO₂) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon‑nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO₂ and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO₂ and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO₂ and ΔMAT rather than ΔMAP and ecosystem types. Process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO₂ led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.

Assessing and predicting soil carbon density in China using CMIP5 earth system models

Soil carbon (SC) is a key component of the carbon cycle and plays an important role in climate change; however, quantitatively assessing SC dynamics at the regional scale remains challenging. Earth system model (ESM) that considers multiple environmental factors and spatial heterogeneity has become a powerful tool to explore carbon cycle-climate feedbacks, although the performance of the ESM is diverse and highly uncertain. Thus, identifying reliable ESMs is a prerequisite for better understanding the response of SC dynamics to human activity and climate change. The 16 ESMs that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) were employed to evaluate the skill performance of SC density simulation by comparison with reference data from the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS). Although ESMs generally reflect spatial patterns with lower SC in northwest China and higher SC in southeast China, 11 of 16 ESMs underestimated the SC in China, and 5 of 16 ESMs overestimated the SC density as most ESMs had large discrepancies in capturing the SC density in the northern high latitudes of China and the Qinghai-Tibet Plateau. According to a series of model performance statistics, SC simulated by Institute Pierre Simon Laplace (IPSL) Coupled Model had a close spatial pattern with IGBP-DIS and showed higher skills for SC predictions in China relative to other CMIP5 ESMs. The multimodel ensemble average obtained by IPSL family ESMs showed that SC density exhibited increasing trends under both the RCP4.5 scenario and RCP8.5 scenario. The SC density increased slowly under RCP8.5 compared with that under RCP4.5 and even displayed a decreasing trend in the late 21st century. The findings of this study can provide a reference for identifying the shortcomings of SC predictions in China and guide SC parameterization improvement in ESMs.

Adding Tree Rings to North America's National Forest Inventories: An Essential Tool to Guide Drawdown of Atmospheric CO2

Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and—ultimately—the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair.

Intermediate disturbances are a key driver of long-term tree demography across old-growth temperate forests

Disentangling the relative influence of background versus disturbance related mortality on forest demography is crucial for understanding long-term dynamics and predicting the influence of global change on forests. Quantifying the rates and drivers of tree demography requires direct observations of tree populations over multiple decades, yet such studies are rare in old-growth forest, particularly in the temperate zone of Europe. We use multi-decade (1980-2020) monitoring of permanent plots, including observations of mode of mortality and disturbance events, to quantify rates and drivers of tree demography across a network of old-growth remnants in temperate mountain forests of Slovenia. Annual rates of mortality and recruitment varied markedly among sites and over time; census intervals that captured intermediate severity canopy disturbances caused subtle peaks in annual mortality (e.g., >2%/year), while rates of background mortality in non-disturbed intervals averaged about 1%/year. Roughly half of the trees died from modes of mortality associated with disturbance (i.e., uprooting or snapped-alive). Results of a Bayesian multilevel model indicate that beech (Fagus sylvatica) had a higher likelihood of disturbance related mortality compared to fir (Abies alba), which mainly died standing, and there was a notable increase in the odds of disturbance mortality with increasing diameter for all species. Annual recruitment rates were consistently low at sites (<0.5%) that lacked evidence of disturbance, but often exceeded 3% on sites with higher levels of past canopy mortality. Recruitment was dominated by beech on sites with more diffuse background mortality, while the less shade tolerant maple (Acer pseudoplatanus) recruited following known disturbance events. Our study highlights the important role of stand-scale, partial canopy disturbance for long-term forest demography. These results suggest that subtle climate-driven changes in the regime of intermediate severity disturbances could have an important influence on future forest dynamics and warrant attention.

Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities

BACKGROUND

Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.

SCOPE

The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.

CONCLUSIONS

We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.

Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot

Community trait assembly in highly diverse tropical rainforests is still poorly understood. Based on more than a decade of field measurements in a biodiversity hotspot of southern Ecuador, we implemented plant trait variation and improved soil organic matter dynamics in a widely used dynamic vegetation model (the Lund-Potsdam-Jena General Ecosystem Simulator, LPJ-GUESS) to explore the main drivers of community assembly along an elevational gradient. In the model used here (LPJ-GUESS-NTD, where NTD stands for nutrient-trait dynamics), each plant individual can possess different trait combinations, and the community trait composition emerges via ecological sorting. Further model developments include plant growth limitation by phosphorous (P) and mycorrhizal nutrient uptake. The new model version reproduced the main observed community trait shift and related vegetation processes along the elevational gradient, but only if nutrient limitations to plant growth were activated. In turn, when traits were fixed, low productivity communities emerged due to reduced nutrient-use efficiency. Mycorrhizal nutrient uptake, when deactivated, reduced net primary production (NPP) by 61-72% along the gradient. Our results strongly suggest that the elevational temperature gradient drives community assembly and ecosystem functioning indirectly through its effect on soil nutrient dynamics and vegetation traits. This illustrates the importance of considering these processes to yield realistic model predictions.

Tree recruitment is determined by stand structure and shade tolerance with uncertain role of climate and water relations

Tree regeneration is a key process for long-term forest dynamics, determining changes in species composition and shaping successional trajectories. While tree regeneration is a highly stochastic process, tree regeneration studies often cover narrow environmental gradients only, focusing on specific forest types or species in distinct regions. Thus, the larger-scale effects of temperature, water availability, and stand structure on tree regeneration are poorly understood.We investigated these effects in respect of tree recruitment (in-growth) along wide environmental gradients using forest inventory data from Flanders (Belgium), northwestern Germany, and Switzerland covering more than 40 tree species. We employed generalized linear mixed models to capture the abundance of tree recruitment in response to basal area, stem density, shade casting ability of a forest stand as well as site-specific degree-day sum (temperature), water balance, and plant-available water holding capacity. We grouped tree species to facilitate comparisons between species with different levels of tolerance to shade and drought.Basal area and shade casting ability of the overstory had generally a negative impact on tree recruitment, but the effects differed between levels of shade tolerance of tree recruitment in all study regions. Recruitment rates of very shade-tolerant species were positively affected by shade casting ability. Stem density and summer warmth (degree-day sum) had similar effects on all tree species and successional strategies. Water-related variables revealed a high degree of uncertainty and did not allow for general conclusions. All variables had similar effects independent of the varying diameter thresholds for tree recruitment in the different data sets.Synthesis: Shade tolerance and stand structure are the main drivers of tree recruitment along wide environmental gradients in temperate forests. Higher temperature generally increases tree recruitment rates, but the role of water relations and drought tolerance remains uncertain for tree recruitment on cross-regional scales.

Plant functional types broadly describe water use strategies in the Caatinga, a seasonally dry tropical forest in northeast Brazil

In seasonally dry tropical forests, plant functional type can be classified as deciduous low wood density, deciduous high wood density, or evergreen high wood density species. While deciduousness is often associated with drought-avoidance and low wood density is often associated with tissue water storage, the degree to which these functional types may correspond to diverging and unique water use strategies has not been extensively tested.We examined (a) tolerance to water stress, measured by predawn and mid-day leaf water potential; (b) water use efficiency, measured via foliar δ13C; and (c) access to soil water, measured via stem water δ18O.We found that deciduous low wood density species maintain high leaf water potential and low water use efficiency. Deciduous high wood density species have lower leaf water potential and variable water use efficiency. Both groups rely on shallow soil water. Evergreen high wood density species have low leaf water potential, higher water use efficiency, and access alternative water sources. These findings indicate that deciduous low wood density species are drought avoiders, with a specialized strategy for storing root and stem water. Deciduous high wood density species are moderately drought tolerant, and evergreen high wood density species are the most drought tolerant group.Synthesis. Our results broadly support the plant functional type framework as a way to understand water use strategies, but also highlight species-level differences.

Annual precipitation explains variability in dryland vegetation greenness globally but not locally

Dryland vegetation productivity is strongly modulated by water availability. As precipitation patterns and variability are altered by climate change, there is a pressing need to better understand vegetation responses to precipitation variability in these ecologically fragile regions. Here we present a global analysis of dryland sensitivity to annual precipitation variations using long-term records of normalized difference vegetation index (NDVI). We show that while precipitation explains 66% of spatial gradients in NDVI across dryland regions, precipitation only accounts for <26% of temporal NDVI variability over most (>75%) dryland regions. We observed this weaker temporal relative to spatial relationship between NDVI and precipitation across all global drylands. We confirmed this result using three alternative water availability metrics that account for water loss to evaporation, and growing season and precipitation timing. This suggests that predicting vegetation responses to future rainfall using space-for-time substitution will strongly overestimate precipitation control on interannual variability in aboveground growth. We explore multiple mechanisms to explain the discrepancy between spatial and temporal responses and find contributions from multiple factors including local-scale vegetation characteristics, climate and soil properties. Earth system models (ESMs) from the latest Coupled Model Intercomparison Project overestimate the observed vegetation sensitivity to precipitation variability up to threefold, particularly during dry years. Given projections of increasing meteorological drought, ESMs are likely to overestimate the impacts of future drought on dryland vegetation with observations suggesting that dryland vegetation is more resistant to annual precipitation variations than ESMs project.

Is there tree senescence? The fecundity evidence

Despite its importance for forest regeneration, food webs, and human economies, changes in tree fecundity with tree size and age remain largely unknown. The allometric increase with tree diameter assumed in ecological models would substantially overestimate seed contributions from large trees if fecundity eventually declines with size. Current estimates are dominated by overrepresentation of small trees in regression models. We combined global fecundity data, including a substantial representation of large trees. We compared size-fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture. All allometric models fail to describe the declining rate of increase in fecundity with diameter found for 80% of 597 species in our analysis. The strong evidence of declining fecundity, beyond what can be explained by crown architectural change, is consistent with physiological decline. A downward revision of projected fecundity of large trees can improve the next generation of forest dynamic models.

Living on the edge: A continental-scale assessment of forest vulnerability to drought

Globally, forests are facing an increasing risk of mass tree mortality events associated with extreme droughts and higher temperatures. Hydraulic dysfunction is considered a key mechanism of drought-triggered dieback. By leveraging the climate breadth of the Australian landscape and a national network of research sites (Terrestrial Ecosystem Research Network), we conducted a continental-scale study of physiological and hydraulic traits of 33 native tree species from contrasting environments to disentangle the complexities of plant response to drought across communities. We found strong relationships between key plant hydraulic traits and site aridity. Leaf turgor loss point and xylem embolism resistance were correlated with minimum water potential experienced by each species. Across the data set, there was a strong coordination between hydraulic traits, including those linked to hydraulic safety, stomatal regulation and the cost of carbon investment into woody tissue. These results illustrate that aridity has acted as a strong selective pressure, shaping hydraulic traits of tree species across the Australian landscape. Hydraulic safety margins were constrained across sites, with species from wetter sites tending to have smaller safety margin compared with species at drier sites, suggesting trees are operating close to their hydraulic thresholds and forest biomes across the spectrum may be susceptible to shifts in climate that result in the intensification of drought.

Late spring freezes coupled with warming winters alter temperate tree phenology and growth

Spring phenology is advancing with warming but late spring freezes may not advance at the same rate, potentially leading to an increase in freezes after trees initiate budburst. Research suggests warming winters may delay budburst through reduced chilling, which may cause plants to leafout more slowly, thus decreasing spring freeze tolerance. Here, we assessed the effects of late spring freezes and reduced over-winter chilling on sapling phenology, growth and tissue traits, across eight temperate tree and shrub species in a laboratory experiment. We found that spring freezes delayed leafout - extending the period of greatest risk for freeze damage - increased damage to the shoot apical meristem, and decreased leaf toughness and leaf thickness. Longer chilling accelerated budburst and leafout, even under spring freeze conditions. Thus, chilling compensated for the adverse effects of late spring freezes on phenology. Despite the effects of spring freezes and chilling on phenology, we did not see any major reordering in the sequence of species leafout. Our results suggest climate change may impact forest communities not through temporal reassembly, but rather through impacts on phenology and growth from the coupled effects of late spring freezes and decreased over-winter chilling under climate change.

Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6

The main goal of this study was to assess the interannual variations and spatial patterns of projected changes in simulated evapotranspiration (ET) in the 21st century over continental Africa based on the latest Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) provided by the France Centre National de Recherches Météorologiques (CNRM-CM) model in the Sixth Phase of Coupled Model Intercomparison Project (CMIP6) framework. The projected spatial and temporal changes were computed for three time slices: 2020–2039 (near future), 2040–2069 (mid-century), and 2080–2099 (end-of-the-century), relative to the baseline period (1995–2014). The results show that the spatial pattern of the projected ET was not uniform and varied across the climate region and under the SSP-RCPs scenarios. Although the trends varied, they were statistically significant for all SSP-RCPs. The SSP5-8.5 and SSP3-7.0 projected higher ET seasonality than SSP1-2.6 and SSP2-4.5. In general, we suggest the need for modelers and forecasters to pay more attention to changes in the simulated ET and their impact on extreme events. The findings provide useful information for water resources managers to develop specific measures to mitigate extreme events in the regions most affected by possible changes in the region’s climate. However, readers are advised to treat the results with caution as they are based on a single GCM model. Further research on multi-model ensembles (as more models’ outputs become available) and possible key drivers may provide additional information on CMIP6 ET projections in the region.

Emergent Shapes of Trait-Based Competition Functions from Resource-Based Models: A Gaussian Is Not Normal in Plant Communities

AbstractIn community ecology, it is widely assumed that organisms with similar traits compete more intensely with one another for resources. This assumption is often encoded into theory and empirical tests via a unimodal competition function, which predicts that per capita competitive effect declines with separation in traits. Yet it remains unknown how well this function represents the true effect of traits on competitive outcomes, especially for long-lived plant communities, where lifetime fitness is difficult to estimate. Here, we evaluate the shape of competition functions embedded in two resource-based (RB) models, wherein plants compete for shared, essential resources. In the first RB model individuals compete for two essential nutrients, and in the second they compete for light in a size-based successional setting. We compared the shapes of the competition functions that emerged from interactions within these RB models to the unimodal function and others shapes commonly applied. In few instances did the trait-based competition function emerging from the RB model even vaguely resemble any of the shapes previously used. The mismatch between these two approaches suggests that theory derived using fixed competition functions based on trait separation may not apply well to plant systems, where individuals compete for shared resources. The more promising path will be to model depletion of resources by populations in relation to their traits, with its consequences for fitness landscapes and competitive exclusion.

Tackling unresolved questions in forest ecology: The past and future role of simulation models

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Linking plant hydraulics and the fast-slow continuum to understand resilience to drought in tropical ecosystems

Tropical ecosystems have the highest levels of biodiversity, cycle more water and absorb more carbon than any other terrestrial ecosystem on Earth. Consequently, these ecosystems are extremely important components of Earth's climatic system and biogeochemical cycles. Plant hydraulics is an essential discipline to understand and predict the dynamics of tropical vegetation in scenarios of changing water availability. Using published plant hydraulic data we show that the trade-off between drought avoidance (expressed as deep-rooting, deciduousness and capacitance) and hydraulic safety (P50 - the water potential when plants lose 50% of their maximum hydraulic conductivity) is a major axis of physiological variation across tropical ecosystems. We also propose a novel and independent axis of hydraulic trait variation linking vulnerability to hydraulic failure (expressed as the hydraulic safety margin (HSM)) and growth, where inherent fast-growing plants have lower HSM compared to slow-growing plants. We surmise that soil nutrients are fundamental drivers of tropical community assembly determining the distribution and abundance of the slow-safe/fast-risky strategies. We conclude showing that including either the growth-HSM or the resistance-avoidance trade-off in models can make simulated tropical rainforest communities substantially more vulnerable to drought than similar communities without the trade-off. These results suggest that vegetation models need to represent hydraulic trade-off axes to accurately project the functioning and distribution of tropical ecosystems.

Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia-along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%-30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%-15% of incoming solar radiation, compared to 0.15%-0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (R_n ), the key driver of water and energy fluxes (LE ~ 0.6 R_n and H ~ 0.15 R_n ), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation-atmosphere exchange and reduce uncertainty of regional and global biogeochemical models.

Intraspecific trait variation in plants: a renewed focus on its role in ecological processes

BACKGROUND

Investigating the causes and consequences of intraspecific trait variation (ITV) in plants is not novel, as it has long been recognized that such variation shapes biotic and abiotic interactions. While evolutionary and population biology have extensively investigated ITV, only in the last 10 years has interest in ITV surged within community and comparative ecology.

SCOPE

Despite this recent interest, still lacking are thorough descriptions of ITV's extent, the spatial and temporal structure of ITV, and stronger connections between ITV and community and ecosystem properties. Our primary aim in this review is to synthesize the recent literature and ask: (1) How extensive is intraspecific variation in traits across scales, and what underlying mechanisms drive this variation? (2) How does this variation impact higher-order ecological processes (e.g. population dynamics, community assembly, invasion, ecosystem productivity)? (3) What are the consequences of ignoring ITV and how can these be mitigated? and (4) What are the most pressing research questions, and how can current practices be modified to suit our research needs? Our secondary aim is to target diverse and underrepresented traits and plant organs, including anatomy, wood, roots, hydraulics, reproduction and secondary chemistry. In addressing these aims, we showcase papers from the Special Issue.

CONCLUSIONS

Plant ITV plays a key role in determining individual and population performance, species interactions, community structure and assembly, and ecosystem properties. Its extent varies widely across species, traits and environments, and it remains difficult to develop a predictive model for ITV that is broadly applicable. Systematically characterizing the sources (e.g. ontogeny, population differences) of ITV will be a vital step forward towards identifying generalities and the underlying mechanisms that shape ITV. While the use of species means to link traits to higher-order processes may be appropriate in many cases, such approaches can obscure potentially meaningful variation. We urge the reporting of individual replicates and population means in online data repositories, a greater consideration of the mechanisms that enhance and constrain ITV's extent, and studies that span sub-disciplines.

Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass

Tropical forests vary widely in biomass carbon (C) stocks and fluxes even after controlling for forest age. A mechanistic understanding of this variation is critical to accurately predicting responses to global change. We review empirical studies of spatial variation in tropical forest biomass, productivity and woody residence time, focusing on mature forests. Woody productivity and biomass decrease from wet to dry forests and with elevation. Within lowland forests, productivity and biomass increase with temperature in wet forests, but decrease with temperature where water becomes limiting. Woody productivity increases with soil fertility, whereas residence time decreases, and biomass responses are variable, consistent with an overall unimodal relationship. Areas with higher disturbance rates and intensities have lower woody residence time and biomass. These environmental gradients all involve both direct effects of changing environments on forest C fluxes and shifts in functional composition - including changing abundances of lianas - that substantially mitigate or exacerbate direct effects. Biogeographic realms differ significantly and importantly in productivity and biomass, even after controlling for climate and biogeochemistry, further demonstrating the importance of plant species composition. Capturing these patterns in global vegetation models requires better mechanistic representation of water and nutrient limitation, plant compositional shifts and tree mortality.

Continent-wide tree fecundity driven by indirect climate effects

Indirect climate effects on tree fecundity that come through variation in size and growth (climate-condition interactions) are not currently part of models used to predict future forests. Trends in species abundances predicted from meta-analyses and species distribution models will be misleading if they depend on the conditions of individuals. Here we find from a synthesis of tree species in North America that climate-condition interactions dominate responses through two pathways, i) effects of growth that depend on climate, and ii) effects of climate that depend on tree size. Because tree fecundity first increases and then declines with size, climate change that stimulates growth promotes a shift of small trees to more fecund sizes, but the opposite can be true for large sizes. Change the depresses growth also affects fecundity. We find a biogeographic divide, with these interactions reducing fecundity in the West and increasing it in the East. Continental-scale responses of these forests are thus driven largely by indirect effects, recommending management for climate change that considers multiple demographic rates.