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Whether sources or sinks control wood growth remains debated with a paucity of evidence from mature trees in natural settings. Here, we altered carbon supply rate in stems of mature red maples (Acer rubrum) within the growing season by restricting phloem transport using stem chilling; thereby increasing carbon supply above and decreasing carbon supply below the restrictions, respectively. Chilling successfully altered nonstructural carbon (NSC) concentrations in the phloem without detectable repercussions on bulk NSC in stems and roots. Ring width responded strongly to local variations in carbon supply with up to seven-fold differences along the stem of chilled trees; however, concurrent changes in the structural carbon were inconclusive at high carbon supply due to large local variability of wood growth. Above chilling-induced bottlenecks, we also observed higher leaf NSC concentrations, reduced photosynthetic capacity, and earlier leaf coloration and fall. Our results indicate that the cambial sink is affected by carbon supply, but within-tree feedbacks can downregulate source activity, when carbon supply exceeds demand. Such feedbacks have only been hypothesized in mature trees. Consequently, these findings constitute an important advance in understanding source-sink dynamics, suggesting that mature red maples operate close to both source- and sink-limitation in the early growing season.

Wildfire is a global scale ecosystem phenomenon with substantial impact on the carbon cycle, climate warming, and ecosystem resilience. Fire and the hydrological cycle are strongly interlinked, with water availability determining the amount and combustibility of fuel, and fire influencing infiltration, runoff rates and evapotranspiration. Consequently, understanding soil moisture (SM) and vegetation water content (VWC) dynamics pre- and post-fire is fundamental for predicting fire occurrence, fire severity, and ecosystem recovery. Fire can modulate SM and VWC dynamics by influencing interception of rainfall, soil porosity, plant water uptake, and runoff; however, much evidence for fire effects on the hydrological cycle is obtained at the field- to watershed-scale. Therefore, we ask the following research question: What are the effects of large-scale fire events on SM and VWC dynamics across biomes globally?Here we use over six years of global SM, VWC and vapor pressure deficit (VPD) derived from different remote sensing datasets to investigate the effects of large-scale fires on SM and VWC dynamics. We apply a dry down framework, only analyzing consecutive observations of decreasing soil moisture, to describe post-fire response rates for SM, VWC and VPD relative to a pre-fire reference state.We find large scale evidence that the post-fire rate of change of SM over time is more negative, indicating faster water loss. Vegetation recovery, indicated by a positive change in VWC over time, exceeds the pre-fire reference state, which suggests that post-fire recovery is predominantly faster than undisturbed seasonal vegetation growth, likely due to succession of fast-growing plant species. Furthermore, fire affects ecosystem hydrology on shorter timescales as well, reducing diurnal VWC variation over a wide range of SM and VWC conditions. Our findings confirm several trends previously only observed at smaller scales and suggest global remote sensing of SM and VWC can substantially contribute to understanding the dynamics of post-fire plant and soil water status.

There have been vociferous calls for 'tree-centered' vegetation models to refine predictions of forest carbon (C) cycling. Unfortunately, our global survey at flux-tower sites indicates insufficient empirical data support for this much-needed model development. We urge for a new generation of studies across large environmental gradients that strategically pair long-term ecosystem monitoring with manipulative experiments on mature trees. For this, we outline a versatile experimental framework to build cross-scale data archives of C uptake and allocation to structural, non-structural, and respiratory sinks. Community-wide efforts and discussions are needed to implement this framework, especially in hitherto underrepresented tropical forests. Global coordination and realistic priorities for data collection will thereby be key to achieve and maintain adequate empirical support for tree-centered vegetation modeling.

The data requirements of vegetation models are changing. For more than a decade, the community has been developing “next-generation” models that should be globally applicable and at the same time incorporate great process detail. The individual tree emerges from this development as the finest scale at which carbon, water, and nutrient dynamics can be realistically simulated. As such, precise tree-level observations of the relevant processes would ideally be available from across all forested biomes to inform and evaluate tree-centered vegetation models. This is not the case. Instead, we note a growing discrepancy between the demand for and the availability of highly-resolved measurements of carbon allocation in trees and forests.To exemplify this discrepancy, we conducted a survey at 90 flux-tower sites from around the world that revealed priorities and deficiencies in existing data collections. We found that forest structure and aboveground carbon stocks have been ubiquitously inventoried, and that tree growth and foliage turnover have also been measured at many sites. By contrast, detailed information on water cycling, volume increment, and wood formation processes (especially belowground) are less common, as are records of tree mortality or terrestrial and airborne LiDAR that could help scale local observations. In addition, we found that the temporal resolution and length of existing time-series vary substantially across the current flux-tower network. Weighing the strengths and limitations of this and many other ecological monitoring networks, we conclude that the present data basis is insufficient to support accelerating vegetation model development.Looking forward, we anticipate that not only the amount of tree-level observations needs to be increased – especially in tropical and boreal systems – but that the consistency, scalability, and predictability of forest carbon cycle observations needs to be improved. We also propose that intensive long-term monitoring sites be strategically paired with manipulative experiments at comparable sites to better connect past, present, and expected future dynamics. For this, we propose a versatile experimental framework and call for a community-wide discussion on the “yield on cost” of various field observations. We also list a number of key questions on how to best build and maintain cross-scale data archives in support of tree-centered vegetation modelling.

Wood formation determines major long-term carbon (C) accumulation in trees and therefore provides a crucial ecosystem service in mitigating climate change. Nevertheless, we lack understanding of how species with contrasting wood anatomical types differ with respect to phenology and environmental controls on wood formation. In this study, we investigated the seasonality and rates of radial growth and their relationships with climatic factors, and the seasonal variations of stem nonstructural carbohydrates (NSC) in three species with contrasting wood anatomical types (red oak: ring-porous; red maple: diffuse-porous; white pine: coniferous) in a temperate mixed forest during 2017-2019. We found that the high ring width variability observed in both red oak and red maple was caused more by changes in growth duration than growth rate. Seasonal radial growth patterns did not vary following transient environmental factors for all three species. Both angiosperm species showed higher concentrations and lower inter-annual fluctuations of NSC than the coniferous species. Inter-annual variability of ring width varied by species with contrasting wood anatomical types. Due to the high dependence of annual ring width on growth duration, our study highlights the critical importance of xylem formation phenology for understanding and modelling the dynamics of wood formation.

During the Last Glacial Maximum (LGM), atmospheric CO2 was around 90 ppmv lower than during the pre-industrial period. The reasons for this decrease are most often elucidated through factorial experiments testing the impact of individual mechanisms. Due to uncertainty in our understanding of the real system, however, the different models used to conduct the experiments inevitably take on different parameter values and different structures. In this paper, the objective is therefore to take an uncertainty-based approach to investigating the LGM CO2 drop by simulating it with a large ensemble of parameter sets, designed to allow for a wide range of large-scale feedback response strengths. Our aim is not to definitely explain the causes of the CO2 drop but rather explore the range of possible responses. We find that the LGM CO2 decrease tends to predominantly be associated with decreasing sea surface temperatures (SSTs), increasing sea ice area, a weakening of the Atlantic Meridional Overturning Circulation (AMOC), a strengthening of the Antarctic Bottom Water (AABW) cell in the Atlantic Ocean, a decreasing ocean biological productivity, an increasing CaCO3 weathering flux and an increasing deep-sea CaCO3 burial flux. The majority of our simulations also predict an increase in terrestrial carbon, coupled with a decrease in ocean and increase in lithospheric carbon. We attribute the increase in terrestrial carbon to a slower soil respiration rate, as well as the preservation rather than destruction of carbon by the LGM ice sheets. An initial comparison of these dominant changes with observations and paleoproxies other than carbon isotope and oxygen data (not evaluated directly in this study) suggests broad agreement. However, we advise more detailed comparisons in the future, and also note that, conceptually at least, our results can only be reconciled with carbon isotope and oxygen data if additional processes not included in our model are brought into play.

How variations in carbon supply affect wood formation remains poorly understood in particular in mature forest trees. To elucidate how carbon supply affects carbon allocation and wood formation, we attempted to manipulate carbon supply to the cambial region by phloem girdling and compression during the mid- and late-growing season and measured effects on structural development, CO efflux, and nonstructural carbon reserves in stems of mature white pines. Wood formation and stem CO efflux varied with location relative to treatment (i.e., above or below the restriction). We observed up to twice as many tracheids formed above versus below the treatment after the phloem transport manipulation, whereas cell-wall area decreased only slightly below the treatments, and cell size did not change relative to the control. Nonstructural carbon reserves in the xylem, needles, and roots were largely unaffected by the treatments. Our results suggest that low and high carbon supply affects wood formation, primarily through a strong effect on cell proliferation, and respiration, but local nonstructural carbon concentrations appear to be maintained homeostatically. This contrasts with reports of a decoupling of source activity and wood formation at the whole-tree or ecosystem level, highlighting the need to better understand organ-specific responses, within-tree feedbacks, as well as phenological and ontological effects on sink-source dynamics.

Wood formation is a crucial process for carbon sequestration, yet how variations in carbon supply affect wood formation and carbon dynamics in trees more generally remains poorly understood.To better understand the role of carbon supply in wood formation, we restricted phloem transport using girdling and compression around the stem of mature white pines and monitored the effects on local wood formation and stem CO2efflux, as well as nonstructural carbon concentrations in needles, stems, and roots.Growth and stem CO2efflux varied with location relative to treatment (i.e., above or below on the stem). We observed up to a two-fold difference in the number of tracheids formed above versus below the manipulations over the remaining growing season. In contrast, the treatments did not affect mean cell size noticeably and mean cell-wall area decreased only slightly below them. Surprisingly, nonstructural carbon pools and concentrations in the xylem, needles, and roots remained largely unchanged, although starch reserves declined and increased marginally below and above the girdle, respectively.Our results suggest that phloem transport strongly affects cell proliferation and respiration in the cambial zone of mature white pine, but has little impact on nonstructural carbon concentrations. These findings contribute to our understanding of how wood formation is controlled.HighlightRestrictions in phloem transport designed to affect carbon supply, lead to changes in wood formation and stem respiration of mature white pines without substantially changing local nonstructural carbon concentrations.

Wood is a remarkable material. It is responsible for the sequestration of significant anthropogenic CO21, aids understanding of past climates2, has unique acoustic, thermal, and strength properties, and is an endlessly renewable source of energy3. However, we lack a general integrated understanding of how its structure is created. A theoretical framework of wood formation is presented here that explains a diverse range of poorly understood observations, including: (i) the anatomy of growth rings, with a transition from low-density earlywood to high-density latewood; (ii) the high sensitivity of latewood density to temperature; (iii) cell-size regulation; and (iv) relationships between growth and temperature. These features arise from interactions in time and space between the production of cells, the dynamics of developmental zones, and the supply of carbohydrates. Carbohydrate distribution is critical for the final density profile, challenging current theory which emphasises compensation between the rates and durations of cell enlargement and wall thickening. These findings have implications for our understanding of how growth responds to environmental variability and the interpretation of tree rings as proxies of past climates. In addition, they provide a framework for the incorporation of explicit growth processes into models, such as those used to predict the role of vegetation in the future global carbon cycle. Finally, divergent responses in volume and mass with increasing temperature suggest caution in interpreting observations based on volume alone.

Despite its importance for the study of past climates, as well as its significance for carbon sequestration, we lack a mechanistic explanation for how temperature controls wood anatomy. A model of xylogenesis is presented and used to analyse observed tree ring anatomy-temperature relationships in Scots pine (Pinus sylvestris). The model treats the daily proliferation of new cells in the cambium and their subequent differentiation through expansion and secondary wall thickening phases. Control on size at division in the cambium follows recent work on the Arabidopsis shoot apical meristem, and cell enlargement rates in the cambium and enlargement zone are controlled by temperature. The duration of post-cambial enlargement is partially controlled by the rate at which cells pass through the enlargement zone, and partially by the size of this zone, which is controlled by daylength. This set of assumptions is sufficient to generate observed profiles of cell sizes across radial files, with characteristic transitions from earlywood to latewood. After they leave the enlarging zone, cells enter the wall thickening zone, the width of which is also dependent on daylength. A temperature-dependent rate of wall material deposition is insufficient to reproduce the observed gradient in mass density across the radial file, and fails to fully capture the observed seasonality of the correlation between maximum latewood density and temperature. Inclusion of a control on the rate of wall deposition from substrate (sugar) supply, diffusing from the phloem across the radial file, corrects these deficiencies. The resulting model provides a mechanistic explanation of temperature-tree ring relationships, and has the potential to underpin understanding of how climate and CO2 interact in determining the amount of carbon sequestered in trees.

AHP received funding from the Department of Geography, University of Cambridge and Clare College, Cambridge.

Carbon dynamics within trees are intrinsically important for physiological functioning, in particular growth and survival, as well as ecological interactions on multiple timescales. Thus, these internal dynamics play a key role in the global carbon cycle by determining the residence time of carbon in forests via allocation to different tissues and pools, such as leaves, wood, storage, and exudates. Despite the importance of tree internal carbon dynamics, our understanding of how carbon is used in trees, once assimilated, has major gaps. The primary tissue that transports carbon from sources to sinks within a tree is the phloem. Therefore, direct phloem transport manipulation techniques have the potential to improve understanding of numerous aspects of internal carbon dynamics. These include relationships between carbon assimilation, nonstructural carbon availability, respiration for growth and tissue maintenance, allocation to, and remobilization from, storage reserves, and long-term sequestration in lignified structural tissues. This review aims to: (1) introduce the topic of direct phloem transport manipulations, (2) describe the three most common methods of direct phloem transport manipulation and review their mechanisms, namely (i) girdling, (ii) compression and (iii) chilling; (3) summarize the known impacts of these manipulations on carbon dynamics and use in forest trees; (4) discuss potential collateral effects and compare the methods; and finally (5) highlight outstanding key questions that relate to tree carbon dynamics and use, and propose ways to address them using direct phloem transport manipulation.

• Key message Dynamic global vegetation models are key tools for interpreting and forecasting the responses of terrestrial ecosystems to climatic variation and other drivers. They estimate plant growth as the outcome of the supply of carbon through photosynthesis. However, growth is itself under direct control, and not simply controlled by the amount of available carbon. Therefore predictions by current photosynthesis-driven models of large increases in future vegetation biomass due to increasing concentrations of atmospheric CO2may be significant over-estimations. We describe how current understanding of wood formation can be used to reformulate global vegetation models, with potentially major implications for their behaviour.

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.

All recent climatic projections for the next century suggest that we are heading towards a warmer climate than today (Intergovernmental Panel on Climate Change; Fifth Assessment Report), driven by increasing atmospheric burdens of anthropogenic greenhouse gases. In particular, the volume mixing ratio of methane, the second-most important anthropogenic greenhouse gas, has increased by a factor of ∼2.5 from the beginning of the European Industrial Revolution. Due to their complex responses to climatic factors, understanding of the dynamics of future global methane emissions and sinks is crucial for the next generation of climate projections. Of relevance to this problem, the Earth likely experienced warmer average temperatures than today during the Last Interglacial (LIG) period (130–115 kaBP). Interestingly, ice cores do not indicate a different methane mixing ratio from the Pre-Industrial Holocene (PIH), in other words the current interglacial period prior to anthropogenic influence. This is surprising as warmer temperatures might be expected to increase methane emissions. The present study aims to improve our understanding of the changes in the global methane budget through quantifying the relative importance of sources and sinks of methane during the last full glacial–interglacial cycle. A fairly limited number of studies have investigated this cycle at the millenium time scale with most of them examining the doubling in CH 4 from the Last Glacial Maximum (LGM) to the PIH. Though it is still a matter of debate, a general consensus suggests a predominant role to the change in methane emissions from wetlands and only a limited change in the oxidising capacity of the atmosphere. In the present study we provide an estimate of the relative importance of sources and sinks during the LIG period, using a complex climate–chemistry model to quantify the sinks, and a methane emissions model included in a global land surface model, for the sources. We are not aware of any previous studies that have explicitly tackled sources and sinks of methane in the previous interglacial. Our results suggest that both emissions and sinks of methane were higher during the LIG period, relative to the PIH, resulting in similar atmospheric concentrations of methane. Our simulated change in methane lifetime is primarily driven by climate (i.e. air temperature and humidity). However, a significant part of the reduced methane lifetime is also attributable to the impact of changes in NO x emissions from lightning. An increase in biogenic emissions of non-methane volatile organic compounds during the LIG seems unlikely to have compensated for the impact of temperature and humidity. Surface methane emissions from wetlands were higher in northern latitudes due to an increase of summer temperature, whilst the change in the tropics is less certain. Simulated methane emissions are strongly sensitive to the atmospheric forcing, with most of this sensitivity related to changes in wetland extent.

During the Last Glacial Maximum (LGM), atmospheric CO2 was around 90 ppmv lower than during the preindustrial period. Despite years of research, however, the exact mechanisms leading to the glacial atmospheric CO2 drop are still not entirely understood. Here, a large (471-member) ensemble of GENIE-1 simulations is used to simulate the equilibrium LGM minus preindustrial atmospheric CO2 concentration difference (ΔCO2). The ensemble has previously been weakly constrained with modern observations and was designed to allow for a wide range of large-scale feedback response strengths. Out of the 471 simulations, 315 complete without evidence of numerical instability, and with a ΔCO2 that centres around −20 ppmv. Roughly a quarter of the 315 runs predict a more significant atmospheric CO2 drop, between ~ 30 and 90 ppmv. This range captures the error in the model's process representations and the impact of processes which may be important for ΔCO2 but are not included in the model. These runs jointly constitute what we refer to as the plausible glacial atmospheric CO2 change-filtered (PGACF) ensemble. Our analyses suggest that decreasing LGM atmospheric CO2 tends to be associated with decreasing SSTs, increasing sea ice area, a weakening of the Atlantic Meridional Overturning Circulation (AMOC), a strengthening of the Antarctic Bottom Water (AABW) cell in the Atlantic Ocean, a decreasing ocean biological productivity, an increasing CaCO3 weathering flux, an increasing terrestrial biosphere carbon inventory and an increasing deep-sea CaCO3 burial flux. The increases in terrestrial biosphere carbon are predominantly due to our choice to preserve rather than destroy carbon in ice sheet areas. However, the ensemble soil respiration also tends to decrease significantly more than net photosynthesis, resulting in relatively large increases in non-burial carbon. In a majority of simulations, the terrestrial biosphere carbon increases are also accompanied by decreases in ocean carbon and increases in lithospheric carbon. In total, however, we find there are 5 different ways of achieving a plausible ΔCO2 in terms of the sign of individual carbon reservoir changes. The PGACF ensemble members also predict both positive and negative changes in global particulate organic carbon (POC) flux, AMOC and AABW cell strengths, and global CaCO3 burial flux. Comparison of the PGACF ensemble results against observations suggests that the simulated LGM physical climate and biogeochemical changes are mostly of the right sign and magnitude or within the range of observational error, except for the change in global deep-sea CaCO3 burial flux – which tends to be overestimated. We note that changing CaCO3 weathering flux is a variable parameter (included to account for variation in both the CaCO3 weathering rate and the un-modelled CaCO3 shallow water deposition flux), and this parameter is strongly associated with changes in global CaCO3 burial rate. The increasing terrestrial carbon inventory is also likely to have contributed to the LGM increase in deep-sea CaCO3 burial flux via the process of carbonate compensation. However, we do not yet rule out either of these processes as causes of ΔCO2 since missing processes such as Si fertilisation, Si leakage and the effect of decreasing SSTs on CaCO3 production may have introduced a high LGM global CaCO3 burial rate bias. Including these processes would, all else held constant, lower the rain ratio seen by the sediments and result in a decrease in atmospheric CO2 and increase in ocean carbon. Despite not modelling Δ14C(atm (DIC)) and δ13C(atm (DIC)), we also highlight some ways in which our results may potentially be reconciled with these records.

Typhoon is the most frequent natural disturbance in northwest Pacific Ocean, and it is an important factor to affect the structure and function of forest ecosystem in East Asia [1, 2]. Recent observations revealed that climate change may alter the intensity or frequency of typhoons in the past decade [3, 4]. Assessing the potential impacts of extreme typhoon events on ecosystem structure and carbon cycle is critical, especially in frequently perturbed regions such as Taiwan (3.7 typhoons/year) [1].

Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 °C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so.

[1] Large volcanic eruptions can have a significant cooling effect on climate, which is evident in both modern and palaeo data. However, due to the difficulty of disentangling volcanic and other influences in the modern atmospheric CO2 record, and uncertainties associated with palaeo reconstructions of atmospheric CO2, the magnitude of the carbon cycle response to volcanically induced climatic changes is difficult to quantify. In this study, three Earth System Models (SIMEARTH, CLIMBER‐2, and CLIMBER LPJ) are used to simulate the effects of different magnitudes of volcanic eruption, from relatively small (e.g., Mount Pelee, 1902) to very large (e.g., the 1258 ice core event), on the coupled global climate‐carbon cycle system. These models each use different, but justifiable, parameterizations to simulate the global carbon cycle and climate. Key differences include how soil respiration and net primary productivity respond to temperature and atmospheric CO2. All models simulate global surface cooling in response to volcanic events. In response to a Mount Pinatubo‐equivalent eruption, the modelled temperature decrease is 0.3°C to 0.4°C and atmospheric CO2 decreases by 1.1 ppm to 3.4 ppm. The initial response time of climate to volcanic forcing and subsequent recovery time vary little with changes in the size of the forcing. Response times for vegetation and soil carbon are relatively consistent across forcings for each model. However, results indicate that there is significant uncertainty concerning the response of the carbon cycle to volcanic eruptions. Suggestions for future research directed at reducing this uncertainty are given.

Turnover concepts in state‐of‐the‐art global vegetation models (GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate (k) derived from a combination of remote sensing based products of biomass and net primary production (NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation‐based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation‐based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation‐based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large‐scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models.

Increasing CO2 concentrations are strongly controlled by the behavior of established forests, which are believed to be a major current sink of atmospheric CO2. There are many models which predict forest responses to environmental changes but they are almost exclusively carbon source (i.e., photosynthesis) driven. Here we present a model for an individual tree that takes into account the intrinsic limits of meristems and cellular growth rates, as well as control mechanisms within the tree that influence its diameter and height growth over time. This new framework is built on process-based understanding combined with differential equations solved by numerical method. Our aim is to construct a model framework of tree growth for replacing current formulations in Dynamic Global Vegetation Models, and so address the issue of the terrestrial carbon sink. Our approach was successfully tested for stands of beech trees in two different sites representing part of a long-term forest yield experiment in Germany. This model provides new insights into tree growth and limits to tree height, and addresses limitations of previous models with respect to sink-limited growth.

Increasing CO2 concentrations are strongly controlled by the behaviour of undisturbed forests, which are believed to be a major current sink of atmospheric CO2. There are many models which predict forest responses to environmental changes but they are almost exclusively carbon source (i.e. photosynthesis) driven. Here we present a model for an individual tree that takes into account also the intrinsic limits of meristems and cellular growth rates, as well as control mechanisms within the tree that influence its diameter and height growth over time. This new framework is built on process-based understanding combined with differential equations solved by the Runge-Kutta-Fehlberg (RKF45) numerical method. It was successfully tested for stands of beech trees in two different sites representing part of a long-term forest yield experiment in Germany. This model provides new insights into tree growth and limits to tree height, and addresses limitations of previous models with respect to sink-limited growth.Author SummaryGreenhouse gas emissions, in particular of CO2, have emerged as one of the most important global concerns, and it is therefore important to understand the behaviour of forests as they absorb and store a very large quantity of carbon. Most models treat forests as boxes with growth only driven by photosynthesis, while their actual growth depends also on many other important processes such as the maximal rate at which individual cells can grow, the influences of temperature and soil moisture on these cells, and the control that the tree has on itself through endogenous signalling pathways. Therefore, and with inspiration from process-based understanding of the biological functioning of trees, we have developed a model which takes into account these different factors. We first use this knowledge and additional basic assumptions to derive a system of several equations which, when solved, enable us to predict the height and the radius of an individual tree at a given time, provided that we have enough information about its initial state and its surroundings. We use the Runge-Kutta-Fehlberg mathematical method to obtain a numerical solution and thus predict the development of the height and radius of an individual tree over time under specified conditions.

A better understanding of the mechanisms controlling the magnitude and sign of carbon components in tropical forest ecosystems is important for reliable estimation of this important regional component of the global carbon cycle. We used the JULES vegetation model to simulate all components of the carbon balance at six sites along an Andes-Amazon transect across Peru and Brazil and compared the results to published field measurements. In the upper montane zone the model predicted a lack of forest vegetation, indicating a need for better parameterization of the responses of cloud forest vegetation within the model. In the lower montane and lowland zones simulated ecosystem productivity and respiration were predicted with reasonable accuracy, although not always within the error bounds of the observations. Model-predicted carbon use efficiency in this transect surprisingly did not increase with elevation, but remained close to the 'temperate' value 0.5. Upper montane forests were predicted to allocate ~50% of carbon fixation to biomass maintenance and growth, despite available measurements showing that they only allocate ~33%. This may be explained by elevational changes in the balance between growth and maintenance respiration within the forest canopy, as controlled by both temperature- and pressure-mediated processes, which is not yet well represented in current vegetation models. © 2012 Blackwell Publishing Ltd.

This paper introduces a surface model with two soil-layers for use in a high-resolution circulation model that has been modified with an extrapolated surface temperature, to be used for the calculation of turbulent fluxes. A quadratic temperature profile based on the layer mean and base temperature is assumed in each layer and extended to the surface. The model is tested at two sites on the Tibetan Plateau near Nam Co Lake during four days during the 2009 Monsoon season. In comparison to a two-layer model without explicit surface temperature estimate, there is a greatly reduced delay in diurnal flux cycles and the modelled surface temperature is much closer to observations. Comparison with a SVAT model and eddy covariance measurements shows an overall reasonable model performance based on RMSD and cross correlation comparisons between the modified and original model. A potential limitation of the model is the need for careful initialisation of the initial soil temperature profile, that requires field measurements. We show that the modified model is capable of reproducing fluxes of similar magnitudes and dynamics when compared to more complex methods chosen as a reference.

On average, about 45 per cent of global annual anthropogenic carbon dioxide (CO 2 ) emissions remain in the atmosphere, while the remainder are taken up by carbon reservoirs on land and in the oceans—the CO 2 ‘sinks’. As sink size and dynamics are highly variable in space and time, cross-verification of reported anthropogenic CO 2 emissions with atmospheric CO 2 measurements is challenging. Highly variable CO 2 sinks also limit the capability to detect anomolous changes in natural carbon reservoirs. This paper argues that significant uncertainty reduction in annual estimates of the global carbon balance could be achieved rapidly through coordinated up-scaling of existing methods, and that this uncertainty reduction would provide incentive for accurate reporting of CO 2 emissions at the country level. We estimate that if 5 per cent of global CO 2 emissions go unreported and undetected, the associated marginal economic impacts could reach approximately US$20 billion each year by 2050. The net present day value of these impacts aggregated until 2200, and discounted back to the present would have a mean value exceeding US$10 trillion. The costs of potential impacts of unreported emissions far outweigh the costs of enhancement of measurement infrastructure to reduce uncertainty in the global carbon balance.

The likely future increase in atmospheric CO(2) and associated changes in climate will affect global patterns of plant production. Models integrate understanding of the influence of the environment on plant physiological processes and so enable estimates of future changes to be made. Moreover, they allow us to assess the consequences of different assumptions for predictions and so stimulate further research. This paper is a review of the sensitivities of one such model, Hybrid6.5, a detailed mechanistic model of terrestrial primary production. This model is typical of its type, and the sensitivities of the global distribution of predicted production to model assumptions and possible future CO(2) levels and climate are assessed. Sensitivity tests show that leaf phenology has large effects on mean C(3) crop and needleleaved cold deciduous tree production, reducing potential net primary production (NPP) from that obtained using constant maximum annual leaf area index by 32.9% and 41.6%, respectively. Generalized Plant Type (GPT) specific parameterizations, particularly photosynthetic capacity per unit leaf N, affect mean predicted NPP of higher C(3) plants by -22.3% to 27.9%, depending on the GPT, compared to NPP predictions obtained using mean parameter values. An increase in atmospheric CO(2) concentrations from current values to 720 ppm by the end of this century, with associated effects on climate from a typical climate model, is predicted to increase global NPP by 37.3%. Mean increases range from 43.9-52.9% across different C(3) GPTs, whereas the mean NPP of C(4) grass and crop increases by 5.9%. Significant uncertainties concern the extent to which acclimative processes may reduce any potential future increase in primary production and the degree to which any gains are transferred to durable, and especially edible, biomass. Experimentalists and modellers need to work closely together to reduce these uncertainties. A number of research priorities are suggested. 'The green leaf or, to be more precise, the microscopic green grain of chlorophyll, is the focus, the point in the world to which solar energy flows on one side while all the manifestations of life on earth take their source on the other side.' Kliment Arkadievich Timiryazev The conclusions of a century of plant physiology, speech at Moscow University, 12 January 1901.

Water stress is a defining characteristic of Mediterranean ecosystems, and is likely to become more severe in the coming decades. Simulation models are key tools for making predictions, but our current understanding of how soil moisture controls ecosystem functioning is not sufficient to adequately constrain parameterisations. Canopy-scale flux data from four forest ecosystems with Mediterranean-type climates were used in order to analyse the physiological controls on carbon and water flues through the year. Significant non-stomatal limitations on photosynthesis were detected, along with lesser changes in the conductance-assimilation relationship. New model parameterisations were derived and implemented in two contrasting modelling approaches. The effectiveness of two models, one a dynamic global vegetation model ("ORCHIDEE"), and the other a forest growth model particularly developed for Mediterranean simulations ("GOTILWA+"), was assessed and modelled canopy responses to seasonal changes in soil moisture were analysed in comparison with in situ flux measurements. In contrast to commonly held assumptions, we find that changing the ratio of conductance to assimilation under natural, seasonally-developing, soil moisture stress is not sufficient to reproduce forest canopy CO2 and water fluxes. However, accurate predictions of both CO2 and water fluxes under all soil moisture levels encountered in the field are obtained if photosynthetic capacity is assumed to vary with soil moisture. This new parameterisation has important consequences for simulated responses of carbon and water fluxes to seasonal soil moisture stress, and should greatly improve our ability to anticipate future impacts of climate changes on the functioning of ecosystems in Mediterranean-type climates.

© 2016 The Author(s)The aim of our study was to determine variation in the response of radial growth in $\textit{Fagus sylvatica}$ L (European Beech) to climate across the species full geographical distribution and climatic tolerance. We combined new and existing data to build a database of 140 tree-ring chronologies to investigate patterns in growth–climate relationships. Our novel meta-analysis approach has allowed the first investigation of the effect of climate on tree growth across the entire geographical distribution of the species. We identified key climate signals in tree-ring chronologies and then investigated how these varied geographically and according to mean local climate, and by tree age and size. We found that the most important climate variables significantly correlated with growth did not show strong geographical patterns. Growth of trees in the core and at the southern edge of the distribution was reduced by high temperature and low precipitation during the growing season, and by high temperatures in the previous summer. However, growth of trees growing in warmer and drier locations was more frequently significantly correlated with summer precipitation than other populations. Additionally, the growth of older and larger trees was more frequently significantly correlated with previous summer temperature than younger and smaller trees. Trees growing at the south of the species geographical distributions are often considered most at risk from climate change, but our results indicate that radial growth of populations in other areas of the distribution is equally likely to be significantly correlated with summer climate and may also be vulnerable. Additionally, tree-rings from older trees contain particular growth–climate relationships that are rarely found in younger trees. These results have important implications for predicting forest carbon balance, resource use and likely future changes to forest composition across the continent.

[EN] Large portions of Earth's terrestrial surface are arid or semiarid. As in these regions, the hydrological cycle and the vegetation dynamics are tightly interconnected, a coupled modelling of these two systems is needed to fully reproduce the ecosystem behaviour. In this paper, the performance of two parsimonious dynamic vegetation models, suitable for the inclusion in operational ecohydrological models and based on well-established but different approaches, is compared in a semiarid Aleppo Pine region. The first model [water use efficiency (WUE) model] links growth to transpiration through WUE; the second model [light use efficiency (LUE) model] simulates biomass increase in relation to absorbed photosynthetically active radiation and LUE. Furthermore, an analysis of the information contained in MODIS products is presented to indicate the best vegetation indices to be used as observational verification for the models. Enhanced Vegetation Index is reported in literature to be highly correlated with leaf area index, so it is compared with modelled LAI(mod) (rWUE model = 0.45; rLUE model = 0.57). In contrast, Normalized Difference Vegetation Index appears highly linked to soil moisture, through the control exerted by this variable on chlorophyll production, and is therefore used to analyze LAI*(mod), models' output corrected by plant water stress (rWUE model = 0.62; rLUE model = 0.59). Moderate-resolution imaging spectroradiometer Leaf Area Index and evapotranspiration are found to be unrealistic in the studied area. The performance of both models in this semiarid region is found to be reasonable. However, the LUE model presents the advantages of a better performance, the possibility to be used in a wider range of climates and to have been extensively tested in literature. (C) Copyright 2014 John Wiley & Sons, Ltd., The research leading to these results has received funding from the Spanish Ministry of Economy and Competitiveness through the research projects FLOOD-MED (ref. CGL2008-06474-C02-02), SCARCE-CONSOLIDER (ref. CSD2009-00065) and ECO-TETIS (ref. CGL2011-28776-C02-01), and from the European Community's Seventh Framework Programme (FP7 2007-2013) under grant agreement no. 238366. The MODIS data were obtained through the online Data Pool at the NASA Land Processes Distributed Active Archive Centre (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Centre, Sioux Falls, South Dakota (https://lpdaac.usgs.gov/get_data). The meteorological data were provided by the Spanish National Weather Agency (AEMET). The authors thank Antonio Del Campo Garcia and Maria Gonzalez Sanchis at the Universitat Politecnica de Valencia for their support and valuable comments.

Tree growth is frequently linked to weather conditions prior to the growing season but our understanding of these lagged climate signatures is still poorly developed. We investigated the influence of masting behaviour on the relationship between growth and climate in European Beech (Fagus sylvatica L.) using a rare long-term dataset of seed production and a new regional tree ring chronology. Fagus sylvatica is a masting species with synchronous variations in seed production which are strongly linked to the temperature in the previous two summers. We noted that the weather conditions associated with years of heavy seed production (mast years) were the same as commonly reported correlations between growth and climate for this species. We tested the hypothesis that a trade-off between growth and reproduction in mast years could be responsible for the observed lagged correlations between growth and previous summers' temperatures. We developed statistical models of growth based on monthly climate variables, and show that summer drought (negative correlation), temperature of the previous summer (negative) and temperature of the summer 2 years previous (positive) are significant predictors of growth. Replacing previous summers' tem perature in the model with annual seed production resulted in a model with the same predictive power, explaining the same variance in growth. Masting is a common behaviour in many tree species and these findings therefore have important implications for the interpretation of general climate–growth relationships. Lagged correlations can be the result of processes occurring in the year of growth (that are determined by conditions in previous years), obviating or reducing the need for ‘carry-over’ processes such as carbohydrate depletion to be invoked to explain this climate signature in tree rings. Masting occurs in many tree species and these findings therefore have important implications for the interpretation of general climate–growth relationships.

A biogenic emissions scheme is incorporated in the global dynamic vegetation model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic EcosystEms) in order to calculate global biogenic emissions of isoprene, monoterpenes, methanol, acetone, acetaldehyde, formaldehyde and formic and acetic acids. Important parameters such as the leaf area index are fully determined by the global vegetation model and the influences of light extinction (for isoprene emissions) and leaf age (for isoprene and methanol emissions) are also taken into account. We study the interannual variability of biogenic emissions using the satellite-based climate forcing ISLSCP-II as well as relevant CO2 atmospheric levels, for the 1983–1995 period. Mean global emissions of 460 TgC/year for isoprene, 117 TgC/year for monoterpenes, 106 TgC/year for methanol and 42 TgC/year for acetone are predicted. The mean global emission of all biogenic compounds is 752±16 TgC/yr with extremes ranging from 717 TgC/yr in 1986 to 778 TgC/yr in 1995, that is a 8.5% increase between both. This variability differs significantly from one region to another and among the regions studied, biogenic emissions anomalies were the most variable in Europe and the least variable in Indonesia (isoprene and monoterpenes) and North America (methanol). Year-to-year variability also reveals a strong correlation of emissions in tropical regions with El Niño events, particularly for isoprene, for which the tropical regions are a major source. Two scenarios of land use changes are considered using the 1983 climate and atmospheric CO2 conditions, to study the sensitivity of biogenic emissions to vegetation alteration, namely tropical deforestation and European afforestation. Global biogenic emissions are highly affected by tropical deforestation, with a 29% decrease in isoprene emission and a 22% increase in methanol emission. Global emissions are not significantly affected by European afforestation, but on a European scale, total biogenic VOCs emissions increase by 54%.

A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

We used a global vegetation model, ‘HyLand’, to simulate the effects of changes in climate, CO 2 concentration and land use on natural ecosystems. Changes were prescribed by four SRES scenarios: A1f, A2, B1 and B2. Under all SRES scenarios simulated, the terrestrial biosphere is predicted to be a net sink for carbon over practically all of the 21st century. This sink peaks around 2050 and then diminishes rapidly towards the end of the century as a result of climate change. Averaged over the period 1990–2100, the net sink varies between scenarios, from ∼2 to 6 Pg C yr −1 . Differences are largely the result of differences in CO 2 concentrations. Effects of climate change are substantially less, and counteract the effect of elevated CO 2 . Land use change results in a loss of carbon to the atmosphere in the B2B scenario, in which the increase in cropland area continues. In the other scenarios, there is a decrease in croplands and grassland, with a corresponding increase in natural vegetation, resulting in a net sink to the biosphere. The credibility of these results depends on the accuracy of the predictions of land use change in the SRES scenarios, and these are highly uncertain. As CO 2 is the dominating influence on the vegetation, the scenarios with high fossil fuel emissions, and thus the highest CO 2 concentrations (A1F & A2) generate the largest net terrestrial sink for carbon. This conclusion would change if these scenarios assumed continued deforestation and cropland expansion. Without the beneficial effects of elevated CO 2 , the effects of climate change are much more severe. This is of concern, as the long-term and large-scale effects of elevated CO 2 are still open to question. Differences between scenarios in the predicted global spatial pattern of net biome productivity and vegetation type are relatively small, and there are not major shifts in the dominant types. The regions predicted to be at greatest risk from global environmental change are Amazonia, the Sahel, South Central USA and Central Australia.

We examined the changes to global net primary production (NPP), vegetation biomass carbon (VegC), and soil organic carbon (SOC) estimated by six global vegetation models (GVMs) obtained from the Inter-Sectoral Impact Model Intercomparison Project. Simulation results were obtained using five global climate models (GCMs) forced with four representative concentration pathway (RCP) scenarios. To clarify which component (i.e., emission scenarios, climate projections, or global vegetation models) contributes the most to uncertainties in projected global terrestrial C cycling by 2100, analysis of variance (ANOVA) and wavelet clustering were applied to 70 projected simulation sets. At the end of the simulation period, changes from the year 2000 in all three variables varied considerably from net negative to positive values. ANOVA revealed that the main sources of uncertainty are different among variables and depend on the projection period. We determined that in the global VegC and SOC projections, GVMs are the main influence on uncertainties (60 % and 90 %, respectively) rather than climate-driving scenarios (RCPs and GCMs). Moreover, the divergence of changes in vegetation carbon residence times is dominated by GVM uncertainty, particularly in the latter half of the 21st century. In addition, we found that the contribution of each uncertainty source is spatiotemporally heterogeneous and it differs among the GVM variables. The dominant uncertainty source for changes in NPP and VegC varies along the climatic gradient. The contribution of GVM to the uncertainty decreases as the climate division becomes cooler (from ca. 80 % in the equatorial division to 40 % in the snow division). Our results suggest that to assess climate change impacts on global ecosystem C cycling among each RCP scenario, the long-term C dynamics within the ecosystems (i.e., vegetation turnover and soil decomposition) are more critical factors than photosynthetic processes. The different trends in the contribution of uncertainty sources in each variable among climate divisions indicate that improvement of GVMs based on climate division or biome type will be effective. On the other hand, in dry regions, GCMs are the dominant uncertainty source in climate impact assessments of vegetation and soil C dynamics.

How and when the Americas were populated remains contentious. Using ancient and modern genome-wide data, we find that the ancestors of all present-day Native Americans, including Athabascans and Amerindians, entered the Americas as a single migration wave from Siberia no earlier than 23 thousand years ago (KYA), and after no more than 8,000-year isolation period in Beringia. Following their arrival to the Americas, ancestral Native Americans diversified into two basal genetic branches around 13 KYA, one that is now dispersed across North and South America and the other is restricted to North America. Subsequent gene flow resulted in some Native Americans sharing ancestry with present-day East Asians (including Siberians) and, more distantly, Australo-Melanesians. Putative ‘Paleoamerican’ relict populations, including the historical Mexican Pericúes and South American Fuego-Patagonians, are not directly related to modern Australo-Melanesians as suggested by the Paleoamerican Model.

In order to achieve climate change mitigation, long-term decisions are required that must be reconciled with other societal goals that draw on the same resources. For example, ensuring food security for a growing population may require an expansion of crop land, thereby reducing natural carbon sinks or the area available for bio-energy production. Here, we show that current impact-model uncertainties pose an important challenge to long-term mitigation planning and propose a new risk-assessment and decision framework that accounts for competing interests. Based on cross-sectorally consistent simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) we discuss potential gains and limitations of additional irrigation and trade-offs of the expansion of agricultural land as two possible response measures to climate change and growing food demand. We describe an illustrative example in which the combination of both measures may close the supply demand gap while leading to a loss of approximately half of all natural carbon sinks. We highlight current limitations of available simulations and additional steps required for a comprehensive risk assessment.

Future climate change and increasing atmospheric CO 2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510–758 ppm of CO 2 ), vegetation carbon increases by 52–477 Pg C (224 Pg C mean), mainly due to CO 2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

The possible responses of ecosystem processes to rising atmospheric CO2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO2 (Wigley et al. 1991), and by climate changes resulting from effective CO2 concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2-SUL. Simulations with changing CO2 alone show a widely distributed terrestrial carbon sink of 1.4‐3.8 Pg C y ‐1 during the 1990s, rising to 3.7‐8.6 Pg C y ‐1 a century later. Simulations including climate change show a reduced sink both today (0.6‐ 3.0 Pg C y ‐1 ) and a century later (0.3‐6.6 Pg C y ‐1 ) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO2 effects at high CO2 concentrations. Four out of the six models show a further, climate-induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO2 concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO2 concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO2 and climate change. They reveal major uncertainties about the response of NEP to climate

Gap models have a rich history of being used to simulate individual tree interactions that impact species diversity and patterns of forest succession. Questions arise, however, as to whether these same models can be used to study the response of forest structure and composition under a changing climate. In contrast to many process-based models, gap models have traditionally been based on rather descriptive representations of species-specific growth processes. Opportunities now exist to expand upon these simple empirical relationships with more mechanistic descriptions of growth, the response of growth to environmental variables, and competition among species for avail- able light, water, and nutrient resources. In this paper, we focus on several areas of below-ground research with the potential to improve the utility of gap models for predicting forest composition in response to a changing climate. Specific areas for model improvement include (1) improved descriptions of the soil environment for seed germination and subsequent seedling establishment, (2) multi-layer representations of soil water and nutrient availability, (3) more accurate information on biomass allocation to roots and root distribution within the soil profile, (4) improved treatment of inter- and intra-specific competition for available soil resources, (5) increased consideration of spatial processes as related to land-surface hydrology, and (6) improved attention to above- and below-ground interactions. This list is meant to stimulate discussion and provide guidance for future field research and model development. As an example of how increased attention to below- ground processes could help address intra-specific competition for water among trees of differing size classes, the gap model LINKAGES was modified to include a sub-model of multi-layered soil hydrology. It was then used to examine the impact of root distribution within soils on the simulated drought response of seedlings, saplings, and mature trees. An annual simulation of soil water con- tent for a deciduous forest in eastern Tennessee showed that seedlings whose roots were restricted to the upper 20-cm of the soil experienced far more 'drought days' than did saplings and larger

The ability of a mechanistically based dynamic terrestrial ecosystem model, Hybrid v4.1, to predict the global distribution of vegetation, primary productivity, biomass carbon, and soil carbon under preindustrial conditions of climate, atmospheric CO2, and nitrogen deposition is evaluated. This model predicts the dynamic global distribution of eight Plant Functional Types (PFTs) by treating the interactions between individual trees, an herbaceous layer, and their physical environment at independent points on the land surface. Carbon, water, and nitrogen flows are simulated on a daily, or subdaily, basis resulting in dynamic predictions of productivity, biomass, and plant and soil carbon and nitrogen contents. Hybrid v4.1 successfully predicts the major global patterns of preindustrial vegetation, primary productivity, biomass carbon, and soil carbon. When not subject to competition, single PFTs have much broader distributions across climatic gradients than when allowed to compete with one another, demonstrating the importance of competition in determining vegetation distribution. Trade-offs between the avoidance of frost and drought damage, growing season length, and foliage nitrogen allocation determine the relative performance of tree PFTs along climatic gradients. Six areas of disagreement between prediction and reality are noted: (1) African savanna, (2) South American grassland, (3) an area of desert in Amazonia, (4) Southern Chinese evergreen forest, (5) Siberian larch forest, and (6) tundra. These discrepancies provide useful information for future model development.

Summary A nonequilibrium, dynamic, global vegetation model, Hybrid v4.1, with a subdaily timestep, was driven by increasing CO2 and transient climate output from the UK Hadley Centre GCM (HadCM2) with simulated daily and interannual variability. Three IPCC emission scenarios were used: (i) IS92a, giving 790 ppm CO2 by 2100, (ii) CO2 stabilization at 750 ppm by 2225, and (iii) CO2 stabilization at 550 ppm by 2150. Land use and future N deposition were not included. In the IS92a scenario, boreal and tropical lands warmed 4.5 °C by 2100 with rainfall decreased in parts of the tropics, where temperatures increased over 6 °C in some years and vapour pressure deficits (VPD) doubled. Stabilization at 750 ppm CO2 delayed these changes by about 100 years while stabilization at 550 ppm limited the rise in global land surface temperature to 2.5 °C and lessened the appearance of relatively hot, dry areas in the tropics. Present-day global predictions were 645 PgC in vegetation, 1190 PgC in soils, a mean carbon residence time of 40 years, NPP 47 PgC y−1 and NEP (the terrestrial sink) about 1 PgC y−1, distributed at both high and tropical latitudes. With IS92a emissions, the high latitude sink increased to the year 2100, as forest NPP accelerated and forest vegetation carbon stocks increased. The tropics became a source of CO2 as forest dieback occurred in relatively hot, dry areas in 2060–2080. High VPDs and temperatures reduced NPP in tropical forests, primarily by reducing stomatal conductance and increasing maintenance respiration. Global NEP peaked at 3–4 PgC y−1 in 2020–2050 and then decreased abruptly to near zero by 2100 as the tropical source offset the high-latitude sink. The pattern of change in NEP was similar with CO2 stabilization at 750 ppm, but was delayed by about 100 years and with a less abrupt collapse in global NEP. CO2 stabilization at 550 ppm prevented sustained tropical forest dieback and enabled recovery to occur in favourable years, while maintaining a similar time course of global NEP as occurred with 750 ppm stabilization. By lessening dieback, stabilization increased the fraction of carbon emissions taken up by the land. Comparable studies and other evidence are discussed: climate-induced tropical forest dieback is considered a plausible risk of following an unmitigated emissions scenario.

Summary A dynamic, global vegetation model, hybrid v4.1 (Friend et al. 1997), was driven by transient climate output from the UK Hadley Centre GCM (HadCM2) with the IS92a scenario of increasing atmospheric CO2 equivalent, sulphate aerosols and predicted patterns of atmospheric N deposition. Changes in areas of vegetation types and carbon storage in biomass and soils were predicted for areas north of 50°N from 1860 to 2100. Hybrid is a combined biogeochemical, biophysical and biogeographical model of natural, potential ecosystems. The effect of periodic boreal forest fires was assessed by adding a simple stochastic fire model. Hybrid represents plant physiological and soil processes regulating the carbon, water and N cycles and competition between individuals of parameterized generalized plant types. The latter were combined to represent tundra, temperate grassland, temperate/mixed forest and coniferous forest. The model simulated the current areas and estimated carbon stocks in the four vegetation types. It was predicted that land areas above 50°N (about 23% of the vegetated global land area) are currently accumulating about 0.4 PgC y−1 (about 30% of the estimated global terrestrial sink) and that this sink could grow to 0.8–1.0 PgC y−1 by the second half of the next century and persist undiminished until 2100. This sink was due mainly to an increase in forest productivity and biomass in response to increasing atmospheric CO2, temperature and N deposition, and includes an estimate of the effect of boreal forest fire, which was estimated to diminish the sink approximately by the amount of carbon emitted to the atmosphere during fires. Averaged over the region, N deposition contributed about 18% to the sink by the 2080 s. As expected, climate change (temperature, precipitation, solar radiation and saturation pressure deficit) and N deposition without increasing atmospheric CO2 produced a carbon source. Forest areas expanded both south and north, halving the current tundra area by 2100. This expansion contributed about 30% to the sink by the 2090 s. Tundra areas which were not invaded by forest fluctuated from sink to source. It was concluded that a high latitude carbon sink exists at present and, even assuming little effect of N deposition, no forest expansion and continued boreal forest fires, the sink is likely to persist at its current level for a century.

Climate output from the UK Hadley Centre’s HadCM2 and HadCM3 experiments for the period 1860 to 2100, with IS92a greenhouse gas forcing, together with predicted patterns of N deposition and increasing CO 2 , were input (o%ine) to the dynamic vegetation model, Hybrid v4.1 (Friend et al., 1997; Friend and White, 1999). This model represents biogeochemical, biophysical and biogeographical processes, coupling the carbon, nitrogen and water cycles on a sub-daily timestep, simulating potential vegetation and transient changes in annual growth and competition between eight generalized plant types in response to climate. Global vegetation carbon was predicted to rise from about 600 to 800 PgC (or to 650 PgC for HadCM3) while the soil carbon pool of about 1100 PgC decreased by about 8%. By the 2080s, climate change caused a partial loss of Amazonian rainforest, C 4 grasslands and temperate forest in areas of southern Europe and eastern USA, but an expansion in the boreal forest area. These changes were accompanied by a decrease in net primary productivity (NPP) of vegetation in many tropical areas, southern Europe and eastern USA (in response to warming and a decrease in rainfall), but an increase in NPP of boreal forests. Global NPP increased from 45 to 50 PgC y~1 in the 1990s to about 65 PgC y~1 in the 2080s (about 58 PgC y~1 for HadCM3). Global net ecosystem productivity (NEP) increased from about 1.3 PgC y~1 in the 1990s to about 3.6 PgC y~1 in the 2030s and then declined to zero by 2100 owing to a loss of carbon from declining forests in the tropics and at warm temperate latitudes * despite strengthening of the carbon sink at northern high latitudes. HadCM3 gave a more erratic temporal evolution of NEP than HadCM2, with a dramatic collapse in NEP in the 2050s. ( 1999 Elsevier Science Ltd. All rights reserved.

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedbacks with elevated atmospheric carbon dioxide (CO2) in a warmer future world. We examined the simulation results of seven terrestrial biome models when forced with climate projections from four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify calculated uncertainty in global SOC stock projections from global and regional perspectives and give insight to the improvement of SOC-relevant processes in biome models. SOC stocks among the biome models varied from 1090 to 2650 Pg C even in historical periods (ca. 2000). In a higher forcing scenario (i.e., RCP8.5), inconsistent estimates of impact on the total SOC (2099–2000) were obtained from different biome model simulations, ranging from a net sink of 347 Pg C to a net source of 122 Pg C. In all models, the increasing atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 Pg C by the end of the 21st century across biome models. Using the time-series data of total global SOC simulated by each biome model, we analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (ΔT and ΔP respectively) in each biome model using a state-space model. This analysis suggests that ΔT explained global SOC stock changes in most models with a resolution of 1–2 °C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 to 3.53 Pg C yr−1 among the biome models. However, ΔP had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the biome models, especially in boreal to arctic regions. Our study reveals considerable climate uncertainty in SOC decomposition responses to climate and CO2 change among biome models. Further research is required to improve our ability to estimate biospheric feedbacks through both SOC-relevant and vegetation-relevant processes.

A numerical process-based model of terrestrial ecosystem dynamics is described and tested. The model, Hybrid v3.0, treats the daily cycling of carbon, nitrogen, and water within the biosphere and between the biosphere and the atmosphere. It combines a mass-balance approach with the capacity to predict the relative dominance of different species or generalised plant types (such as evergreen needleleaved trees, cold deciduous broadleaved trees, and C3 grasses). The growth of individual trees is simulated on an annual timestep, and the growth of a grass layer is simulated on a daily timestep. The exchange of carbon, nitrogen, and water with the atmosphere and the soil is simulated on a daily timestep (except the flux of tree litter to the soil, which occurs annually). Individual trees and the grass layer compete with each other for light, water, and nitrogen within a ‘plot’. Larger and taller plants shade smaller ones; they also take up a greater proportion of the available water and nitrogen. The above-ground space in each plot is divided into 1 m deep layers for the purposes of calculating irradiance interception; horizontal variation in the plot environment is not treated. The soil is represented as a single layer, with a daily hydrological budget. Decomposition of soil organic matter is calculated using an empirical sub-model. The initial size of each tree seedling is stochastic. To predict the mean behaviour of the model for a particular boundary condition it is necessary to simulate a number of plots. Hybrid v3.0 has been written with three major requirements in mind: (i) the carbon, water, and nutrient cycles must be fully coupled in the soil-plant-atmosphere system; (ii) the internal constraints on the model's behaviour, and the driving forces for the model, must be the same as those which operate in nature (e.g., climate, nitrogen deposition, and the atmospheric concentrations of CO2 and O2); and (iii) the model must be constructed so that it is capable of predicting transient as well as equilibrium responses to climate change. These conditions have largely been met by constructing the model around a set of fundamental hypotheses regarding the general constraints under which plants and soils behave, independently of any particular location or time. The model is thus potentially capable of making reliable predictions of ecosystem behaviour and structure under future, new, atmospheric conditions. The model is tested for a site in eastern North America. A quasi-equilibrium is reached after approximately 250 years with 10 plots. It is found that more plots are not necessary in order to obtain a reliable estimate of mean behaviour. Predictions of productivity, leaf area index, foliage nitrogen, soil carbon, and biomass carbon are all within the range expected for this location. Mortality is shown to be a necessary model component; without it large trees reach a maximum size, and then remain in dynamic equilibrium with the climate, without dying. The model runs at a rate of 0.176 s plot−1 year−1 on a workstation (a 500 year simulation, with 10 plots, thus takes approximately 15 min). A sensitivity analysis demonstrates the importance of the parameterisation of phenology, photosynthesis, and foliage/fine root carbon and nitrogen partitioning for the overall carbon balance of the modelled ecosystem. Hybrid v3.0 has been written with the intention of using it to represent the terrestrial biosphere in a total earth system model. This would be achieved by linking it to models of other components of the earth system, such as the climate and the oceans, in a fully coupled manner. This total earth system model could then be used to answer a large range of questions concerning global environmental change.

The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980–2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.