Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change

Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new quasi‐equilibrium suitable habitats (~2100) after accounting for the lag in colonization. However, it is an open question if and when these newly suitable habitats will be colonized under current fragmented landscapes and realistic migration rates. To evaluate this, we used a spatially explicit cell‐based model (SHIFT) that estimates colonization potentials under current fragmented habitats and several estimates of historical migration rates at a 1 km resolution. Computation time, which was previously the biggest constraint, was overcome by a novel application of convolution and Fast Fourier Transforms. SHIFT outputs, when intersected with future suitable habitats predicted by DISTRIB, allow assessment of colonization potential under future climates. In this article, we show how our approach can be used to screen multiple tree species for their colonization potentials under climate change. In particular, we use the DISTRIB and SHIFT models in combination to assess if the future dominant forest types in the north will really be dominated by oaks, as modelled via DISTRIB. Even under optimistic scenarios, we conclude that only a small fraction of the suitable habitats of oaks predicted by DISTRIB is likely to be occupied within 100 years, and this will be concentrated in the first 10–20 km from the current boundary. We also show how DISTRIB and SHIFT can be used to evaluate the potential for assisted migration of vulnerable tree species, and discuss the dynamics of colonization at range limits.     

Potential Changes in Tree Species Richness and Forest Community Types following Climate Change

Potential changes in tree species richness and forest community types were evaluated for the eastern United States according to five scenarios of future climate change resulting from a doubling of atmospheric carbon dioxide (CO₂). DISTRIB, an empirical model that uses a regression tree analysis approach, was used to generate suitable habitat, or potential future distributions, of 80 common tree species for each scenario. The model assumes that the vegetation and climate are in equilibrium with no barriers to species migration. Combinations of the individual species model outcomes allowed estimates of species richness (from among the 80 species) and forest type (from simple rules) for each of 2100 counties in the eastern United States. Average species richness across all counties may increase slightly with climatic change. This increase tends to be larger as the average temperature of the climate change scenario increases. Dramatic changes in the distribution of potential forest types were modeled. All five scenarios project the extirpation of the spruce–fir forest types from New England. Outputs from only the two least severe scenarios retain aspen–birch, and they are largely reduced. Maple–beech–birch also shows a large reduction in area under all scenarios. By contrast, oak–hickory and oak–pine types were modeled to increase by 34% and 290%, respectively, averaged over the five scenarios. Although many assumptions are made, these modeled outcomes substantially agree with a limited number of predictions from researchers using paleoecological data or other models. Received 12 May 2000; accepted 20 October 2000.     

Influence of Disturbance on Temperate Forest Productivity

Climate, tree species traits, and soil fertility are key controls on forest productivity. However, in most forest ecosystems, natural and human disturbances, such as wind throw, fire, and harvest, can also exert important and lasting direct and indirect influence over productivity. We used an ecosystem model, PnET-CN, to examine how disturbance type, intensity, and frequency influence net primary production (NPP) across a range of forest types from Minnesota and Wisconsin, USA. We assessed the importance of past disturbances on NPP, net N mineralization, foliar N, and leaf area index at 107 forest stands of differing types (aspen, jack pine, northern hardwood, black spruce) and disturbance history (fire, harvest) by comparing model simulations with observations. The model reasonably predicted differences among forest types in productivity, foliar N, leaf area index, and net N mineralization. Model simulations that included past disturbances minimally improved predictions compared to simulations without disturbance, suggesting the legacy of past disturbances played a minor role in influencing current forest productivity rates. Modeled NPP was more sensitive to the intensity of soil removal during a disturbance than the fraction of stand mortality or wood removal. Increasing crown fire frequency resulted in lower NPP, particularly for conifer forest types with longer leaf life spans and longer recovery times. These findings suggest that, over long time periods, moderate frequency disturbances are a relatively less important control on productivity than climate, soil, and species traits.     

Forest structure,diversity, and primary production in relation to disturbance severity

1. Differential disturbance severity effects on forest vegetation structure, species diversity, and net primary production (NPP) have been long theorized and observed. Here, we examined these factors concurrently to explore the potential for a mechanistic pathway linking disturbance severity, changes in light environment, leaf functional response, and wood NPP in a temperate hardwood forest.
2. Using a suite of measurements spanning an experimental gradient of tree mortality, we evaluated the direction and magnitude of change in vegetation structural and diversity indexes in relation to wood NPP. Informed by prior observations, we hypothesized that forest structural and species diversity changes and wood NPP would exhibit either a linear, unimodal, or threshold response in relation to disturbance severity. We expected increasing disturbance severity would progressively shift subcanopy light availability and leaf traits, thereby coupling structural and species diversity changes with primary production.
3. Linear or unimodal changes in three of four vegetation structural indexes were observed across the gradient in disturbance severity. However, disturbance‐related changes in vegetation structure were not consistently correlated with shifts in light environment, leaf traits, and wood NPP. Species diversity indexes did not change in response to rising disturbance severity.
4. We conclude that, in our study system, the sensitivity of wood NPP to rising disturbance severity is generally tied to changing vegetation structure but not species diversity. Changes in vegetation structure are inconsistently coupled with light environment and leaf traits, resulting in mixed support for our hypothesized cascade linking disturbance severity to wood NPP.

     

An ecoregion assessment of projected tree species vulnerabilities in western North America through the 21st century

Forest ecosystems across western North America will likely see shifts in both tree species dominance and composition over the rest of this century in response to climate change. Our objective in this study was to identify which ecological regions might expect the greatest changes to occur. We used the process‐based growth model 3‐PG, to provide estimates of tree species responses to changes in environmental conditions and to evaluate the extent that species are resilient to shifts in climate over the rest of this century. We assessed the vulnerability of 20 tree species in western North America using the Canadian global circulation model under three different emission scenarios. We provided detailed projections of species shifts by including soil maps that account for the spatial variation in soil water availability and soil fertility as well as by utilizing annual climate projections of monthly changes in air temperature, precipitation, solar radiation, vapor pressure deficit and frost at a spatial resolution of one km. Projected suitable areas for tree species were compared to their current ranges based on observations at >40 000 field survey plots. Tree species were classified as vulnerable if environmental conditions projected in the future appear outside that of their current distribution ≥70% of the time. We added a migration constraint that limits species dispersal to <200 m yr^?1 to provide more realistic projections on species distributions. Based on these combinations of constraints, we predicted the greatest changes in the distribution of dominant tree species to occur within the Northwest Forested Mountains and the highest number of tree species stressed will likely be in the North American Deserts. Projected climatic changes appear especially unfavorable for species in the subalpine zone, where major shifts in composition may lead to the emergence of new forest types.     

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species‐specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model‐data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.     

Responses of Terrestrial Ecosystems’ Net Primary Productivity to Future Regional Climate Change in China

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems’ response to global climate change. China’s ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund–Potsdam–Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China’s terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.     

Circumpolar arctic tundra biomass and productivity dynamics in response to projected climate change and herbivory

Satellite remote sensing data have indicated a general ‘greening’ trend in the arctic tundra biome. However, the observed changes based on remote sensing are the result of multiple environmental drivers, and the effects of individual controls such as warming, herbivory, and other disturbances on changes in vegetation biomass, community structure, and ecosystem function remain unclear. We apply ArcVeg, an arctic tundra vegetation dynamics model, to estimate potential changes in vegetation biomass and net primary production (NPP) at the plant community and functional type levels. ArcVeg is driven by soil nitrogen output from the Terrestrial Ecosystem Model, existing densities of Rangifer populations, and projected summer temperature changes by the NCAR CCSM4.0 general circulation model across the Arctic. We quantified the changes in aboveground biomass and NPP resulting from (i) observed herbivory only; (ii) projected climate change only; and (iii) coupled effects of projected climate change and herbivory. We evaluated model outputs of the absolute and relative differences in biomass and NPP by country, bioclimate subzone, and floristic province. Estimated potential biomass increases resulting from temperature increase only are approximately 5% greater than the biomass modeled due to coupled warming and herbivory. Such potential increases are greater in areas currently occupied by large or dense Rangifer herds such as the Nenets‐occupied regions in Russia (27% greater vegetation increase without herbivores). In addition, herbivory modulates shifts in plant community structure caused by warming. Plant functional types such as shrubs and mosses were affected to a greater degree than other functional types by either warming or herbivory or coupled effects of the two.     

Competitive and demographic leverage points of community shifts under climate warming

Accelerating rates of climate change and a paucity of whole-community studies of climate impacts limit our ability to forecast shifts in ecosystem structure and dynamics, particularly because climate change can lead to idiosyncratic responses via both demographic effects and altered species interactions. We used a multispecies model to predict which processes and species'' responses are likely to drive shifts in the composition of a space-limited benthic marine community. Our model was parametrized from experimental manipulations of the community. Model simulations indicated shifts in species dominance patterns as temperatures increase, with projected shifts in composition primarily owing to the temperature dependence of growth, mortality and competition for three critical species. By contrast, warming impacts on two other species (rendering them weaker competitors for space) and recruitment rates of all species were of lesser importance in determining projected community changes. Our analysis reveals the importance of temperature-dependent competitive interactions for predicting effects of changing climate on such communities. Furthermore, by identifying processes and species that could disproportionately leverage shifts in community composition, our results contribute to a mechanistic understanding of climate change impacts, thereby allowing more insightful predictions of future biodiversity patterns.     

What is the role of disturbance in catalyzing spatial shifts in forest composition and tree species biomass under climate change?

Mounting evidence suggests that climate change will cause shifts of tree species range and abundance (biomass). Abundance changes under climate change are likely to occur prior to a detectable range shift. Disturbances are expected to directly affect tree species abundance and composition, and could profoundly influence tree species spatial distribution within a geographical region. However, how multiple disturbance regimes will interact with changing climate to alter the spatial distribution of species abundance remains unclear. We simulated such forest demographic processes using a forest landscape succession and disturbance model (LANDIS-II) parameterized with forest inventory data in the northeastern United States. Our study incorporated climate change under a high-emission future and disturbance regimes varying with gradients of intensities and spatial extents. The results suggest that disturbances catalyze changes in tree species abundance and composition under a changing climate, but the effects of disturbances differ by intensity and extent. Moderate disturbances and large extent disturbances have limited effects, while high-intensity disturbances accelerate changes by removing cohorts of mid- and late-successional species, creating opportunities for early-successional species. High-intensity disturbances result in the northern movement of early-successional species and the southern movement of late-successional species abundances. Our study is among the first to systematically investigate how disturbance extent and intensity interact to determine the spatial distribution of changes in species abundance and forest composition.     

Predicted Effects of Gypsy Moth Defoliation and Climate Change on Forest Carbon Dynamics in the New Jersey Pine Barrens

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years.     

Modeling Forest Mortality Caused by Drought Stress: Implications for Climate Change

Climate change is expected to affect forest landscape dynamics in many ways, but it is possible that the most important direct impact of climate change will be drought stress. We combined data from weather stations and forest inventory plots (FIA) across the upper Great Lakes region (USA) to study the relationship between measures of drought stress and mortality for four drought sensitivity species groups using a weight-of-evidence approach. For all groups, the model that predicted mortality as a function of mean drought length had the greatest plausibility. Model tests confirmed that the models for all groups except the most drought tolerant had predictive value. We assumed that no relationship exists between drought and mortality for the drought-tolerant group. We used these empirical models to develop a drought extension for the forest landscape disturbance and succession model LANDIS-II, and applied the model in Oconto county, Wisconsin (USA) to assess the influence of drought on forest dynamics relative to other factors such as stand-replacing disturbance and site characteristics. The simulations showed that drought stress does affect species composition and total biomass, but effects on age classes, spatial pattern, and productivity were insignificant. We conclude that (for the upper Midwest) (1) a drought-induced tree mortality signal can be detected using FIA data, (2) tree species respond primarily to the length of drought events rather than their severity, (3) the differences in drought tolerance of tree species can be quantified, (4) future increases in drought can potentially change forest composition, and (5) drought is a potentially important factor to include in forest dynamics simulations because it affects forest composition and carbon storage.     

长白山红松年轮碳同位素与净初级生产力的关系

解析树木年轮碳同位素变化是揭示气候与环境变化的有效途径,然而少有研究分析年轮碳同位素对森林净初级生产力(NPP)的指示效应.基于生长季气象因子,分析了长白山红松年轮δ¹³C记录序列与阔叶红松林红松种群NPP变化趋势以及两者之间的相关关系.结果表明: 1970年以前,研究区红松年轮δ¹³C与红松种群NPP变化同步,且两者间呈极显著线性正相关关系,年轮δ¹³C记录了气候变化对红松种群NPP的影响;1970年以后,红松年轮δ¹³C与红松种群NPP变化出现分异,两者呈负相关关系但相关性不显著,表明干旱等其他环境因子的影响使年轮δ¹³C对气候变化的敏感性和对NPP指示性降低.这一相关关系在红松年轮δ¹³C与当年和下一年红松种群NPP之间都存在,表明当年环境状况对来年红松生长的重要意义.说明长白山红松年轮δ¹³C对红松种群NPP有良好的指示性,树木年轮δ¹³C有重建森林历史NPP长期变化的潜力.     

Modelling the recent historical impacts of atmospheric CO2 and climate change on Mediterranean vegetation

During the past century, annual mean temperature has increased by 0.75°C and precipitation has shown marked variation throughout the Mediterranean basin. These historical climate changes may have had significant, but presently undefined, impacts on the productivity and structure of sclerophyllous shrubland, an important vegetation type in the region. We used a vegetation model for this functional type to examine climate change impacts, and their interaction with the concurrent historical rise in atmospheric CO₂. Using only climate and soil texture as data inputs, model predictions showed good agreement with observations of seasonal and regional variation in leaf and canopy physiology, net primary productivity (NPP), leaf area index (LAI) and soil water. Model simulations for shrubland sites indicated that potential NPP has risen by 25% and LAI by 7% during the past century, although the absolute increase in LAI was small. Sensitivity analysis suggested that the increase in atmospheric CO₂ since 1900 was the primary cause of these changes, and that simulated climate change alone had negative impacts on both NPP and LAI. Effects of rising CO₂ were mediated by significant increases in the efficiency of water‐use in NPP throughout the region, as a consequence of the direct effect of CO₂ on leaf gas exchange. This increase in efficiency compensated for limitation of NPP by drought, except in areas where drought was most severe. However, while water was used more efficiently, total canopy water loss rose slightly or remained unaffected in model simulations, because increases in LAI with CO₂ counteracted the effects of reduced stomatal conductance on transpiration. Model simulations for the Mediterranean region indicate that the recent rise in atmospheric CO₂ may already have had significant impacts on productivity, structure and water relations of sclerophyllous shrub vegetation, which tended to offset the detrimental effects of climate change in the region.     

Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees

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Forest composition in Mediterranean mountains is projected to shift along the entire elevational gradient under climate change

Aim Species distribution models have been used frequently to assess the effects of climate change on mountain biodiversity. However, the value and accuracy of these assessments have been hampered by the use of low‐resolution data for species distributions and climatic conditions. Herein we assess potential changes in the distribution and community composition of tree species in two mountainous regions of Spain under specific scenarios of climate change using data with a high spatial resolution. We also describe potential changes in species distributions and tree communities along the entire elevational gradient. Location Two mountain ranges in southern Europe: the Central Mountain Range (central west of the Iberian Peninsula), and the Iberian Mountain Range (central east). Methods We modelled current and future distributions of 15 tree species (Eurosiberian, sub‐Mediterranean and Mediterranean species) as functions of climate, lithology and availability of soil water using generalized linear models (logistic regression) and machine learning models (gradient boosting). Using multivariate ordination of a matrix of presence/absence of tree species obtained under two Intergovernmental Panel on Climate Change (IPCC) scenarios (A2 and B2) for two different periods in the future (2041–70 and 2071–2100), we assessed the predicted changes in the composition of tree communities. Results The models predicted an upward migration of communities of Mediterranean trees to higher elevations and an associated decline in communities of temperate or cold‐adapted trees during the 21st century. It was predicted that 80–99% of the area that shows a climate suitable for cold–wet‐optimum Eurosiberian coniferous and broad‐leaved species will be lost. The largest overall changes were predicted for Mediterranean species found currently at low elevations, such as Pinus halepensis, Pinus pinaster, Quercus ilex ssp. ballota and Juniperus oxycedrus, with sharp increases in their range of 350%. Main conclusions It is likely that areas with climatic conditions suitable for cold‐adapted species will decrease significantly under climate warming. Large changes in species ranges and forest communities might occur, not only at high elevations within Mediterranean mountains but also along the entire elevational gradient throughout this region, particularly at low and mid‐elevations. Mediterranean mountains might lose their key role as refugia for cold‐adapted species and thus an important part of their genetic heritage.     

沿水分梯度草原群落NPP动态及对气候变化响应的模拟分析

 水分条件不仅影响半干旱区群落的组成, 而且在一定程度上决定了群落的功能。处于不同水分条件生境下群落的优势物种在水分利用和同化物利用效率方面的功能特征会存在差异, 这些差异将导致群落对于气候变化产生不同的响应, 进而影响到景观和区域尺度上对于全球变化下碳动态和格局的分析。该文选取了锡林河流域典型草原区沿水分梯度的4个代表群落, 在野外实验测定并结合长期定位研究成果基础上, 利用BIOME-BGC模型对代表群落的长期净初级生产力(Net primary productivity,NPP)动态进行了模拟和模型验证。 通过分析该地区1953～2005年气候变化趋势, 推测了未来可能的气候变化情景, 进而模拟了气候变化下4个群落长期NPP动态的响应。结果表明,当前气候条件下, 羊草(Leymus chinensis)群落NPP平均值为197.76 gC·m^-2 (SE=7.11), 大针茅(Stipa grandis)群落NPP平均值为198.95 gC·m^-2 (SE=6.41), 贝加尔针茅(Stipa baicalensis)群落NPP平均值为210.41 gC·m^-2(SE=7.87), 克氏针茅(Stipa krylovii)群落NPP平均值为144.92 gC·m^{- 2} (SE=4.64), 4个群落NPP平均值为188.01 gC·m^-2 (SE=3.72); 气候变化情景下, 温度增加下(P0T1),NPP平均下降14.2%,降水增加下(P1T0), NPP平均增加13.2%,温度与降水都增加情景下(P1T1), NPP平均下降2 .7%, 但由于生境水分条件差别和优势物种功能特征差异, 4个群落表现出了增减幅度不同的趋势。对气候因子的敏感性分析及回归分析表明, 降水是该地区NPP最主要的决定因子, 而温度决定作用相对较小,主要通过影响植物的呼吸和水分蒸散等过程影响NPP。在最有可能代表未来气候 变化的温度增加的两种情景下(P0T1、P1T1), NPP均呈下降趋势。群落NPP对气候变化的响应趋势与水分胁迫系数(Water stress index, WSI)、碳胁迫系数(Carbon stress index, CSI)变化密切相关。克氏针茅群落由于所处生境水分条件差,WSI高,对降水的依赖程度最大;贝加尔针茅群落一方面处于较好的水分生境,具有较小的WSI,另一方面,由于具有高碳氮比,维持呼吸消耗的光合产物比例低,CSI远低于其它3个群落, 未来气候变化下, NPP较其它3个群落仍较高。     

华北地区油松林生态系统对气候变化和CO2浓度升高的响应——基于BIOME-BGC模型和树木年轮的模拟

应用BIOME-BGC模型和树木年轮数据模拟1952-2008年华北地区典型油松林生态系统净初级生产力（NPP）动态,探究了树木径向生长和NPP对区域气候变暖的响应以及未来气候情景下油松林生态系统NPP动态变化.结果表明：1952-2008年,研究区油松林生态系统NPP波动于244.12～645.31 g C·m^-2·a^-1,平均值为418.6 g C·m^-2·a^-1.5-6月的平均温度和上年8月至当年7月的降水是限制该地区油松径向生长和油松林生态系统NPP的主要因子.研究期间,随着区域暖干化趋势的加强,树木径向生长和生态系统NPP均呈下降趋势.未来气候情景下,NPP对温度和降水的单独和复合变化的响应为正向.CO₂浓度升高有利于油松林生态系统NPP的增加,CO₂的施肥效应使NPP增加16.1%.在生态系统和区域水平,树木年轮是一种理想的指示生态系统动态变化的代用资料,可以检验和校正包括BIOME-BGC模型在内的各种生态系统过程模型.     

Future climate change effects on US forest composition may offset benefits of reduced atmospheric deposition of N and S

Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) are important drivers of forest demography. Here we apply previously derived growth and survival responses for 94 tree species, representing >90% of the contiguous US forest basal area, to project how changes in mean annual temperature, precipitation, and N and S deposition from 20 different future scenarios may affect forest composition to 2100. We find that under the low climate change scenario (RCP 4.5), reductions in aboveground tree biomass from higher temperatures are roughly offset by increases in aboveground tree biomass from reductions in N and S deposition. However, under the higher climate change scenario (RCP 8.5) the decreases from climate change overwhelm increases from reductions in N and S deposition. These broad trends underlie wide variation among species. We found averaged across temperature scenarios the relative abundance of 60 species were projected to decrease more than 5% and 20 species were projected to increase more than 5%; and reductions of N and S deposition led to a decrease for 13 species and an increase for 40 species. This suggests large shifts in the composition of US forests in the future. Negative climate effects were mostly from elevated temperature and were not offset by scenarios with wetter conditions. We found that by 2100 an estimated 1 billion trees under the RCP 4.5 scenario and 20 billion trees under the RCP 8.5 scenario may be pushed outside the temperature record upon which these relationships were derived. These results may not fully capture future changes in forest composition as several other factors were not included. Overall efforts to reduce atmospheric deposition of N and S will likely be insufficient to overcome climate change impacts on forest demography across much of the United States unless we adhere to the low climate change scenario.     

Regional scale patterns of fine root lifespan and turnover under current and future climate

Fine root dynamics control a dominant flux of carbon from plants and into soils and mediate potential uptake and cycling of nutrients and water in terrestrial ecosystems. Understanding of these patterns is needed to accurately describe critical processes like productivity and carbon storage from ecosystem to global scales. However, limited observations of root dynamics make it difficult to define and predict patterns of root dynamics across broad spatial scales. Here, we combine species‐specific estimates of fine root dynamics with a model that predicts current distribution and future suitable habitat of temperate tree species across the eastern United States (US). Estimates of fine root lifespan and turnover are based on empirical observations and relationships with fine root and whole‐plant traits and apply explicitly to the fine root pool that is relatively short‐lived and most active in nutrient and water uptake. Results from the combined model identified patterns of faster root turnover rates in the North Central US and slower turnover rates in the Southeastern US. Portions of Minnesota, Ohio, and Pennsylvania were also predicted to experience >10% increases in root turnover rates given potential shifts in tree species composition under future climate scenarios while root turnover rates in other portions of the eastern US were predicted to decrease. Despite potential regional changes, the average estimates of root lifespan and turnover for the entire study area remained relatively stable between the current and future climate scenarios. Our combined model provides the first empirically based, spatially explicit, and spatially extensive estimates of fine root lifespan and turnover and is a potentially powerful tool allowing researchers to identify reasonable approximations of forest fine root turnover in areas where no direct observations are available. Future efforts should focus on reducing uncertainty in estimates of root dynamics by better understanding how climate and soil factors drive variability in root dynamics of different species.