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Processes that describe the distribution of vegetation and ecosystem succession after disturbance are an important component of dynamic global vegetation models (DGVMs). The vegetation dynamics module (ORC-VD) within the process-based ecosystem model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) has not been updated and evaluated since many years and is known to produce unrealistic results. This study presents a new parameterization of ORC-VD for mid- to high-latitude regions in the Northern Hemisphere, including processes that influence the existence, mortality and competition between tree functional types. A new set of metrics is also proposed to quantify the performance of ORC-VD, using up to five different data sets of satellite land cover, forest biomass from remote sensing and inventories, a data-driven estimate of gross primary productivity (GPP) and two gridded data sets of soil organic carbon content. The scoring of ORC-VD derived from these metrics integrates uncertainties in the observational data sets. This multi-data set evaluation framework is a generic method that could be applied to the evaluation of other DGVM models. The results of the original ORC-VD published in 2005 for mid- to high-latitudes and of the new parameterization are evaluated against the above-described data sets. Significant improvements were found in the modeling of the distribution of tree functional types north of 40° N. Three additional sensitivity runs were carried out to separate the impact of different processes or drivers on simulated vegetation vegetation distribution, including soil freezing which limits net primary production through soil moisture availability in the root zone, elevated CO2 concentration since 1850, and the effects of frequency and severity of extreme cold events during the spin-up phase of the model. [ABSTRACT FROM AUTHOR]

Agro-Land Surface Models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, a particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of Agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS' phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte-Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used to quantify the sensitivity of harvested biomass to input parameters on a continental scale across the large regions of intensive sugar cane cultivation in Australia and Brazil. Ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting climate-mediated different sensitivities of modeled sugar cane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models. [ABSTRACT FROM AUTHOR]

Abstract: A mechanistic model of grassland dynamics is used to simulate fluxes of carbon dioxide (CO2) and nitrous oxide (N2O) in European grasslands. The simulations refer to five sites belonging to a monitoring network setup within the framework of the European Union project GREENGRASS. Simulated gross primary productivity ranges from 0.4 to 1.9kgCm−2 year−1 depending on environmental conditions and management. Ecosystem respiration is calculated in the order of 0.7–1.5kgCm−2 year−1, resulting in a net CO2 uptake of about 0.3kgCm−2 year−1, in reasonable agreement with observations. Linear relationships between ecosystem respiration and gross primary productivity, as well as between net primary productivity and annual precipitation are indicated by the simulations. Annual emissions of N2O are predicted in the range of 1–5kgNha−1 year−1, a factor of 2–10 higher than observed. This is caused by an overestimation of the background fluxes. On the other hand, the model fails to faithfully reproduce timing, duration and magnitude of peak emissions triggered by the application of mineral and organic fertilizers and by rain events. [Copyright &y& Elsevier]

Objectives: This study aimed to investigate gaps in the delivery of two-spirit, lesbian, gay, bisexual, transgender, queer, and other sexual and gender identity (2SLGBTQ+) curricula and identify curricular challenges within Canadian dental schools., Methods: A 21-item closed-ended questionnaire was distributed to curriculum experts across 10 dental schools in Canada. The survey questions were organized into three sections: institution characteristics, current 2SLGBTQ+ content and delivery, and opinions on the improvement of the 2SLGBTQ+ curriculum. Microsoft Excel (2020) was used to perform a descriptive analysis of the survey responses., Results: Nine dental schools participated in the survey. All participating schools reported the offering of undergraduate, graduate, and degree completion programs. The most reported methods of teaching 2SLGBTQ+ content were 'lecture-based teaching' (n = 5), 'small-group teaching' (n = 4), and 'case-based discussions' (n = 4). The most common topics taught were 'gender identity' (n = 7) and '2SLGBTQ+ discrimination in healthcare care settings' (n = 7). The topics of 'sex reassignment surgery,' 'alcohol, tobacco, or other substance use by 2SLGBTQ+ people,' '2SLGBTQ+ pediatric and adolescent oral health issues,' 'coming out,' and 'sex reassignment surgery' were not included or were unknown by the majority of dental schools (n = 8). Overall, participants were unsatisfied with the level of 2SLGBTQ+-specific content covered at their institution and reported a 'lack of space within the curriculum and time constraints' as a barrier to implementation (n = 8)., Conclusion: Community-based research is needed to identify the unmet oral health needs of the 2SLGBTQ+ population, which can be translated into the development of a risk-based oral health curriculum within Canada and beyond., (© 2024 The Authors. Journal of Dental Education published by Wiley Periodicals LLC on behalf of American Dental Education Association.)

During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θ crit ). Better quantification of θ crit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θ crit . We find an average global θ crit of 0.19 m 3 /m 3 , varying from 0.12 m 3 /m 3 in arid ecosystems to 0.26 m 3 /m 3 in humid ecosystems. θ crit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θ crit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θ crit , has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points., (© 2024. The Author(s).)

During the last two decades, inventory data show that droughts have reduced biomass carbon sink of the Amazon forest by causing mortality to exceed growth. However, process-based models have struggled to include drought-induced responses of growth and mortality and have not been evaluated against plot data. A process-based model, ORCHIDEE-CAN-NHA, including forest demography with tree cohorts, plant hydraulic architecture and drought-induced tree mortality, was applied over Amazonia rainforests forced by gridded climate fields and rising CO 2 from 1901 to 2019. The model reproduced the decelerating signal of net carbon sink and drought sensitivity of aboveground biomass (AGB) growth and mortality observed at forest plots across selected Amazon intact forests for 2005 and 2010. We predicted a larger mortality rate and a more negative sensitivity of the net carbon sink during the 2015/16 El Niño compared with the former droughts. 2015/16 was indeed the most severe drought since 1901 regarding both AGB loss and area experiencing a severe carbon loss. We found that even if climate change did increase mortality, elevated CO 2 contributed to balance the biomass mortality, since CO 2 -induced stomatal closure reduces transpiration, thus, offsets increased transpiration from CO 2 -induced higher foliage area., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Synthetic Nitrogen (N) usage in agriculture has greatly increased food supply over the past century. However, the intensive use of N fertilizer is nevertheless the source of numerous environmental issues and remains a major challenge for policymakers to understand, measure, and quantify the interactions and trade-offs between ecosystem carbon and terrestrial biodiversity loss. In this study, we investigate the impacts of a public policy scenario that aims to halve N fertilizer application across European Union (EU) agriculture on both carbon (C) sequestration and biodiversity changes. We quantify the impacts by integrating two economic models with an agricultural land surface model and a terrestrial biodiversity model (that uses data from a range of taxonomic groups, including plants, fungi, vertebrates and invertebrates). Here, we show that the two economic scenarios lead to different outcomes in terms of C sequestration potential and biodiversity. Land abandonment associated with increased fertilizer price scenario facilitates higher C sequestration in soils (+ 1014 MtC) and similar species richness levels (+ 1.9%) at the EU scale. On the other hand, the more extensive crop production scenario is associated with lower C sequestration potential in soils (- 97 MtC) and similar species richness levels (- 0.4%) because of a lower area of grazing land. Our results therefore highlight the complexity of the environmental consequences of a nitrogen reduction policy, which will depend fundamentally on how the economic models used to project consequences., (© 2022. The Author(s).)

Surface ozone (O 3 ) is a threat to forests by decreasing photosynthesis and, consequently, influencing the strength of land carbon sink. However, due to the lack of continuous surface O 3 measurements, observational-based assessments of O 3 impacts on forests are largely missing at hemispheric to global scales. Currently, some metrics are used for regulatory purposes by governments or national agencies to protect forests against the negative impacts of ozone: in particular, both Europe and United States (US) makes use of two different exposure-based metrics, i.e. AOT40 and W126, respectively. However, because of some limitations in these metrics, a new standard is under consideration by the European Union (EU) to replace the current exposure metric. We analyse here the different air quality standards set or proposed for use in Europe and in the US to protect forests from O 3 and to evaluate their spatial and temporal consistency while assessing their effectiveness in protecting northern-hemisphere forests. Then, we compare their results with the information obtained from a complex land surface model (ORCHIDEE). We find that present O 3 uptake decreases gross primary production (GPP) in 37.7% of the NH forested area of northern hemisphere with a mean loss of 2.4% year -1 . We show how the proposed US (W126) and the currently used European (AOT40) air quality standards substantially overestimate the extension of potential vulnerable regions, predicting that 46% and 61% of the Northern Hemisphere (NH) forested area are at risk of O 3 pollution. Conversely, the new proposed European standard (POD1) identifies lower extension of vulnerability regions (39.6%)., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Recent studies suggest increasing sensitivity to orbital variations across the Eocene-Oligocene greenhouse to icehouse climate transition. However, climate simulations and paleoenvironmental studies mostly provide snapshots of the past climate, therefore overlooking the role of this short-term variability in driving major environmental changes and possibly biasing model-data comparisons. We address this problem by performing numerical simulations describing the end-members of eccentricity, obliquity, and precession. The orbitally induced biome variability obtained in our simulations allows to reconcile previous apparent mismatch between models and paleobotanical compilations. We show that precession-driven intermittent monsoon-like climate may have taken place during the Eocene, resulting in biomes shifting from shrubland to tropical forest in the intertropical convergence zone migration region. Our Oligocene simulations suggest that, along with decreased p CO 2 , orbital variations crucially modulated major faunal dispersal events around the EOT such as the Grande Coupure by creating and fragmenting the biome corridors along several key land bridges.

Aerosols have a dimming and cooling effect and change hydrological regimes, thus affecting carbon fluxes, which are sensitive to climate. Aerosols also scatter sunlight, which increases the fraction of diffuse radiation, increasing photosynthesis. There remains no clear conclusion whether the impact of aerosols on land carbon fluxes is larger through diffuse radiation change than through changes in other climate variables. In this study, we quantified the overall physical impacts of anthropogenic aerosols on land C fluxes and explored the contribution from each factor using a set of factorial simulations driven by climate and aerosol data from the IPSL-CM6A-LR experiments during 1850-2014. A newly developed land surface model which distinguishes diffuse and direct radiation in canopy radiation transmission, ORCHIDEE_DF, was used. Specifically, a subgrid scheme was developed to distinguish the cloudy and clear sky conditions. We found that anthropogenic aerosol emissions since 1850 cumulatively enhanced the land C sink by 22.6 PgC. Seventy-eight percent of this C sink enhancement is contributed by aerosol-induced increase in the diffuse radiation fraction, much larger than the effect of the aerosol-induced dimming. The cooling of anthropogenic aerosols has different impacts in different latitudes but overall increases the global land C sink. The dominant role of diffuse radiation changes found in this study implies that future aerosol emissions may have a much stronger impacts on the C cycle through changing radiation quality than through changing climate alone. Earth system models need to consider the diffuse radiation fertilization effect to better evaluate the impacts of climate change mitigation scenarios., (© 2021. The Authors.)

Grasslands absorb and release carbon dioxide (CO 2 ), emit methane (CH 4 ) from grazing livestock, and emit nitrous oxide (N 2 O) from soils. Little is known about how the fluxes of these three greenhouse gases, from managed and natural grasslands worldwide, have contributed to past climate change, or the roles of managed pastures versus natural grasslands. Here, global trends and regional patterns of the full greenhouse gas balance of grasslands are estimated for the period 1750 to 2012. A new spatially explicit land surface model is applied, to separate the direct effects of human activities from land management and the indirect effects from climate change, increasing CO 2 and regional changes in nitrogen deposition. Direct human management activities are simulated to have caused grasslands to switch from a sink to a source of greenhouse gas, because of increased livestock numbers and accelerated conversion of natural lands to pasture. However, climate change drivers contributed a net carbon sink in soil organic matter, mainly from the increased productivity of grasslands due to increased CO 2 and nitrogen deposition. The net radiative forcing of all grasslands is currently close to neutral, but has been increasing since the 1960s. Here, we show that the net global climate warming caused by managed grassland cancels the net climate cooling from carbon sinks in sparsely grazed and natural grasslands. In the face of future climate change and increased demand for livestock products, these findings highlight the need to use sustainable management to preserve and enhance soil carbon storage in grasslands and to reduce greenhouse gas emissions from managed grasslands.

In Europe, three widespread extreme summer drought and heat (DH) events have occurred in 2003, 2010 and 2018. These events were comparable in magnitude but varied in their geographical distribution and biomes affected. In this study, we perform a comparative analysis of the impact of the DH events on ecosystem CO 2 fluxes over Europe based on an ensemble of 11 dynamic global vegetation models (DGVMs), and the observation-based FLUXCOM product. We find that all DH events were associated with decreases in net ecosystem productivity (NEP), but the gross summer flux anomalies differ between DGVMs and FLUXCOM. At the annual scale, FLUXCOM and DGVMs indicate close to neutral or above-average land CO 2 uptake in DH2003 and DH2018, due to increased productivity in spring and reduced respiration in autumn and winter compensating for less photosynthetic uptake in summer. Most DGVMs estimate lower gross primary production (GPP) sensitivity to soil moisture during extreme summers than FLUXCOM. Finally, we show that the different impacts of the DH events at continental-scale GPP are in part related to differences in vegetation composition of the regions affected and to regional compensating or offsetting effects from climate anomalies beyond the DH centres. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

In summer 2018, central and northern Europe were stricken by extreme drought and heat (DH2018). The DH2018 differed from previous events in being preceded by extreme spring warming and brightening, but moderate rainfall deficits, yet registering the fastest transition between wet winter conditions and extreme summer drought. Using 11 vegetation models, we show that spring conditions promoted increased vegetation growth, which, in turn, contributed to fast soil moisture depletion, amplifying the summer drought. We find regional asymmetries in summer ecosystem carbon fluxes: increased (reduced) sink in the northern (southern) areas affected by drought. These asymmetries can be explained by distinct legacy effects of spring growth and of water-use efficiency dynamics mediated by vegetation composition, rather than by distinct ecosystem responses to summer heat/drought. The asymmetries in carbon and water exchanges during spring and summer 2018 suggest that future land-management strategies could influence patterns of summer heat waves and droughts under long-term warming., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models., (© 2020 John Wiley & Sons Ltd.)

Satellite observations show that leaf area index (LAI) has increased globally since 1981, but the impact of this vegetation structural change on the global terrestrial carbon cycle has not been systematically evaluated. Through process-based diagnostic ecosystem modeling, we find that the increase in LAI alone was responsible for 12.4% of the accumulated terrestrial carbon sink (95 ± 5 Pg C) from 1981 to 2016, whereas other drivers of CO 2 fertilization, nitrogen deposition, and climate change (temperature, radiation, and precipitation) contributed to 47.0%, 1.1%, and -28.6% of the sink, respectively. The legacy effects of past changes in these drivers prior to 1981 are responsible for the remaining 65.5% of the accumulated sink from 1981 to 2016. These results refine the attribution of the land sink to the various drivers and would help constrain prognostic models that often have large uncertainties in simulating changes in vegetation and their impacts on the global carbon cycle.

Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land-atmosphere CO 2 fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4-0.7 PgC yr -1 (inversions) and by 1.0 PgC yr -1 (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'., (© 2018 The Authors.)

Large herbivores are a major agent in ecosystems, influencing vegetation structure, and carbon and nutrient flows. During the last glacial period, a mammoth steppe ecosystem prevailed in the unglaciated northern lands, supporting a high diversity and density of megafaunal herbivores. The apparent discrepancy between abundant megafauna and the expected low vegetation productivity under a generally harsher climate with a lower CO 2 concentration, termed the productivity paradox, requires large-scale quantitative analysis using process-based ecosystem models. However, most of the current global dynamic vegetation models (DGVMs) lack explicit representation of large herbivores. Here we incorporated a grazing module in a DGVM based on physiological and demographic equations for wild large grazers, taking into account feedbacks of large grazers on vegetation. The model was applied globally for present-day and the Last Glacial Maximum (LGM). The present-day results of potential grazer biomass, combined with an empirical land-use map, infer a reduction in wild grazer biomass by 79-93% owing to anthropogenic land replacement of natural grasslands. For the LGM, we find that the larger mean body size of mammalian herbivores than today is the crucial clue to explain the productivity paradox, due to a more efficient exploitation of grass production by grazers with a large body size.

Background: Europe has warmed more than the global average (land and ocean) since pre-industrial times, and is also projected to continue to warm faster than the global average in the twenty-first century. According to the climate models ensemble projections for various climate scenarios, annual mean temperature of Europe for 2071-2100 is predicted to be 1-5.5 °C higher than that for 1971-2000. Climate change and elevated CO 2 concentration are anticipated to affect grassland management and livestock production in Europe. However, there has been little work done to quantify the European-wide response of grassland to future climate change. Here we applied ORCHIDEE-GM v2.2, a grid-based model for managed grassland, over European grassland to estimate the impacts of future global change., Results: Increases in grassland productivity are simulated in response to future global change, which are mainly attributed to the simulated fertilization effect of rising CO 2 . The results show significant phenology shifts, in particular an earlier winter-spring onset of grass growth over Europe. A longer growing season is projected over southern and southeastern Europe. In other regions, summer drought causes an earlier end to the growing season, overall reducing growing season length. Future global change allows an increase of management intensity with higher than current potential annual grass forage yield, grazing capacity and livestock density, and a shift in seasonal grazing capacity. We found a continual grassland soil carbon sink in Mediterranean, Alpine, North eastern, South eastern and Eastern regions under specific warming level (SWL) of 1.5 and 2 °C relative to pre-industrial climate. However, this carbon sink is found to saturate, and gradually turn to a carbon source at warming level reaching 3.5 °C., Conclusions: This study provides a European-wide assessment of the future changes in productivity and phenology of grassland, and their consequences for the management intensity and the carbon balance. The simulated productivity increase in response to future global change enables an intensification of grassland management over Europe. However, the simulated increase in the interannual variability of grassland productivity over some regions may reduce the farmers' ability to take advantage of the increased long-term mean productivity in the face of more frequent, and more severe drops of productivity in the future.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO 2 ) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.

Several lines of evidence point to European managed grassland ecosystems being a sink of carbon. In this study, we apply ORCHIDEE-GM a process-based carbon cycle model that describes specific management practices of pastures and the dynamics of carbon cycling in response to changes in climatic and biogeochemical drivers. The model is used to simulate changes in the carbon balance [i.e., net biome production (NBP)] of European grasslands over 1991-2010 on a 25 km × 25 km grid. The modeled average trend in NBP is 1.8-2.0 g C m(-2)  yr(-2) during the past two decades. Attribution of this trend suggests management intensity as the dominant driver explaining NBP trends in the model (36-43% of the trend due to all drivers). A major change in grassland management intensity has occurred across Europe resulting from reduced livestock numbers. This change has 'inadvertently' enhanced soil C sequestration and reduced N2 O and CH4 emissions by 1.2-1.5 Gt CO2 -equivalent, offsetting more than 7% of greenhouse gas emissions in the whole European agricultural sector during the period 1991-2010. Land-cover change, climate change and rising CO2 also make positive and moderate contributions to the NBP trend (between 24% and 31% of the trend due to all drivers). Changes in nitrogen addition (including fertilization and atmospheric deposition) are found to have only marginal net effect on NBP trends. However, this may not reflect reality because our model has only a very simple parameterization of nitrogen effects on photosynthesis. The sum of NBP trends from each driver is larger than the trend obtained when all drivers are varied together, leaving a residual - nonattributed - term (22-26% of the trend due to all drivers) indicating negative interactions between drivers., (© 2015 John Wiley & Sons Ltd.)

The effect of biodiversity on ecosystem functioning has been widely acknowledged, and the importance of the functional roles of species, as well as their diversity, in the control of ecosystem processes has been emphasised recently. However, bridging biodiversity and ecosystem science to address issues at a biogeographic scale is still in its infancy. Bridging this gap is the primary goal of the emerging field of functional biogeography. While the rise of Big Data has catalysed functional biogeography studies in recent years, comprehensive evidence remains scarce. Here, we present the rationale and the first results of a country-wide initiative focused on the C3 permanent grasslands. We aimed to collate, integrate and process large databases of vegetation relevés, plant traits and environmental layers to provide a country-wide assessment of ecosystem properties and services which can be used to improve regional models of climate and land use changes. We outline the theoretical background, data availability, and ecoinformatics challenges associated with the approach and its feasibility. We provide a case study of upscaling of leaf dry matter content averaged at ecosystem level and country-wide predictions of forage digestibility. Our framework sets milestones for further hypothesis testing in functional biogeography and earth system modelling., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The greenhouse gas (GHG) balance of European grasslands (EU-28 plus Norway and Switzerland), including CO2 , CH4 and N2 O, is estimated using the new process-based biogeochemical model ORCHIDEE-GM over the period 1961-2010. The model includes the following: (1) a mechanistic representation of the spatial distribution of management practice; (2) management intensity, going from intensively to extensively managed; (3) gridded simulation of the carbon balance at ecosystem and farm scale; and (4) gridded simulation of N2 O and CH4 emissions by fertilized grassland soils and livestock. The external drivers of the model are changing animal numbers, nitrogen fertilization and deposition, land-use change, and variable CO2 and climate. The carbon balance of European grassland (NBP) is estimated to be a net sink of 15 ± 7 g C m(-2 ) year(-1) during 1961-2010, equivalent to a 50-year continental cumulative soil carbon sequestration of 1.0 ± 0.4 Pg C. At the farm scale, which includes both ecosystem CO2 fluxes and CO2 emissions from the digestion of harvested forage, the net C balance is roughly halved, down to a small sink, or nearly neutral flux of 8 g C m(-2 ) year(-1) . Adding CH4 and N2 O emissions to net ecosystem exchange to define the ecosystem-scale GHG balance, we found that grasslands remain a net GHG sink of 19 ± 10 g C-CO2 equiv. m(-2 ) year(-1) , because the CO2 sink offsets N2 O and grazing animal CH4 emissions. However, when considering the farm scale, the GHG balance (NGB) becomes a net GHG source of -50 g C-CO2 equiv. m(-2 ) year(-1) . ORCHIDEE-GM simulated an increase in European grassland NBP during the last five decades. This enhanced NBP reflects the combination of a positive trend of net primary production due to CO2 , climate and nitrogen fertilization and the diminishing requirement for grass forage due to the Europe-wide reduction in livestock numbers., (© 2015 John Wiley & Sons Ltd.)

About 25% of European livestock intake is based on permanent and sown grasslands. To fulfill rising demand for animal products, an intensification of livestock production may lead to an increased consumption of crop and compound feeds. In order to preserve an economically and environmentally sustainable agriculture, a more forage based livestock alimentation may be an advantage. However, besides management, grassland productivity is highly vulnerable to climate (i.e., temperature, precipitation, CO2 concentration), and spatial information about European grassland productivity in response to climate change is scarce. The process-based vegetation model ORCHIDEE-GM, containing an explicit representation of grassland management (i.e., herbage mowing and grazing), is used here to estimate changes in potential productivity and potential grass-fed ruminant livestock density across European grasslands over the period 1961-2010. Here "potential grass-fed ruminant livestock density" denotes the maximum density of livestock that can be supported by grassland productivity in each 25 km × 25 km grid cell. In reality, livestock density could be higher than potential (e.g., if additional feed is supplied to animals) or lower (e.g., in response to economic factors, pedo-climatic and biotic conditions ignored by the model, or policy decisions that can for instance reduce livestock numbers). When compared to agricultural statistics (Eurostat and FAOstat), ORCHIDEE-GM gave a good reproduction of the regional gradients of annual grassland productivity and ruminant livestock density. The model however tends to systematically overestimate the absolute values of productivity in most regions, suggesting that most grid cells remain below their potential grassland productivity due to possible nutrient and biotic limitations on plant growth. When ORCHIDEE-GM was run for the period 1961-2010 with variable climate and rising CO2, an increase of potential annual production (over 3%) per decade was found: 97% of this increase was attributed to the rise in CO2, -3% to climate trends and 15% to trends in nitrogen fertilization and deposition. When compared with statistical data, ORCHIDEE-GM captures well the observed phase of climate-driven interannual variability in grassland production well, whereas the magnitude of the interannual variability in modeled productivity is larger than the statistical data. Regional grass-fed livestock numbers can be reproduced by ORCHIDEE-GM based on its simple assumptions and parameterization about productivity being the only limiting factor to define the sustainable number of animals per unit area. Causes for regional model-data misfits are discussed, including uncertainties in farming practices (e.g., nitrogen fertilizer application, and mowing and grazing intensity) and in ruminant diet composition, as well as uncertainties in the statistical data and in model parameter values.

The growth rate of atmospheric carbon dioxide (CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature., (Copyright © 2015, American Association for the Advancement of Science.)

Satellite-derived Normalized Difference Vegetation Index (NDVI), a proxy of vegetation productivity, is known to be correlated with temperature in northern ecosystems. This relationship, however, may change over time following alternations in other environmental factors. Here we show that above 30°N, the strength of the relationship between the interannual variability of growing season NDVI and temperature (partial correlation coefficient RNDVI-GT) declined substantially between 1982 and 2011. This decrease in RNDVI-GT is mainly observed in temperate and arctic ecosystems, and is also partly reproduced by process-based ecosystem model results. In the temperate ecosystem, the decrease in RNDVI-GT coincides with an increase in drought. In the arctic ecosystem, it may be related to a nonlinear response of photosynthesis to temperature, increase of hot extreme days and shrub expansion over grass-dominated tundra. Our results caution the use of results from interannual time scales to constrain the decadal response of plants to ongoing warming.

The African humid tropical biome constitutes the second largest rainforest region, significantly impacts global carbon cycling and climate, and has undergone major changes in functioning owing to climate and land-use change over the past century. We assess changes and trends in CO₂ fluxes from 1901 to 2010 using nine land surface models forced with common driving data, and depict the inter-model variability as the uncertainty in fluxes. The biome is estimated to be a natural (no disturbance) net carbon sink (-0.02 kg C m⁻² yr⁻¹ or -0.04 Pg C yr⁻¹, p < 0.05) with increasing strength fourfold in the second half of the century. The models were in close agreement on net CO₂ flux at the beginning of the century (σ1901 = 0.02 kg C m⁻² yr⁻¹), but diverged exponentially throughout the century (σ2010 = 0.03 kg C m⁻² yr⁻¹). The increasing uncertainty is due to differences in sensitivity to increasing atmospheric CO₂, but not increasing water stress, despite a decrease in precipitation and increase in air temperature. However, the largest uncertainties were associated with the most extreme drought events of the century. These results highlight the need to constrain modelled CO₂ fluxes with increasing atmospheric CO₂ concentrations and extreme climatic events, as the uncertainties will only amplify in the next century.

The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr(-1) ) than JU11 (118 ± 6 Pg C yr(-1) ). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr(-1) is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr(-1) ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 ± 1.5 Pg C yr(-1) °C(-1) , within the uncertainty of what derived from RLS (-3.9 ± 1.1 Pg C yr(-1) °C(-1) ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models., (© 2013 Blackwell Publishing Ltd.)

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land−a key diagnostic criterion of the effects of climate change and variability−remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

Background: If biofuels are to be a viable substitute for fossil fuels, it is essential that they retain their potential to mitigate climate change under future atmospheric conditions. Elevated atmospheric CO2 concentration [CO2] stimulates plant biomass production; however, the beneficial effects of increased production may be offset by higher energy costs in crop management., Methodology/main Findings: We maintained full size poplar short rotation coppice (SRC) systems under both current ambient and future elevated [CO2] (550 ppm) and estimated their net energy and greenhouse gas balance. We show that a poplar SRC system is energy efficient and produces more energy than required for coppice management. Even more, elevated [CO2] will increase the net energy production and greenhouse gas balance of a SRC system with 18%. Managing the trees in shorter rotation cycles (i.e., 2 year cycles instead of 3 year cycles) will further enhance the benefits from elevated [CO2] on both the net energy and greenhouse gas balance., Conclusions/significance: Adapting coppice management to the future atmospheric [CO2] is necessary to fully benefit from the climate mitigation potential of bio-energy systems. Further, a future increase in potential biomass production due to elevated [CO2] outweighs the increased production costs resulting in a northward extension of the area where SRC is greenhouse gas neutral. Currently, the main part of the European terrestrial carbon sink is found in forest biomass and attributed to harvesting less than the annual growth in wood. Because SRC is intensively managed, with a higher turnover in wood production than conventional forest, northward expansion of SRC is likely to erode the European terrestrial carbon sink.

Process-based models can be classified into: (a) terrestrial biogeochemical models (TBMs), which simulate fluxes of carbon, water and nitrogen coupled within terrestrial ecosystems, and (b) dynamic global vegetation models (DGVMs), which further couple these processes interactively with changes in slow ecosystem processes depending on resource competition, establishment, growth and mortality of different vegetation types. In this study, four models - RHESSys, GOTILWA+, LPJ-GUESS and ORCHIDEE - representing both modelling approaches were compared and evaluated against benchmarks provided by eddy-covariance measurements of carbon and water fluxes at 15 forest sites within the EUROFLUX project. Overall, model-measurement agreement varied greatly among sites. Both modelling approaches have somewhat different strengths, but there was no model among those tested that universally performed well on the two variables evaluated. Small biases and errors suggest that ORCHIDEE and GOTILWA+ performed better in simulating carbon fluxes while LPJ-GUESS and RHESSys did a better job in simulating water fluxes. In general, the models can be considered as useful tools for studies of climate change impacts on carbon and water cycling in forests. However, the various sources of variation among models simulations and between models simulations and observed data described in this study place some constraints on the results and to some extent reduce their reliability. For example, at most sites in the Mediterranean region all models generally performed poorly most likely because of problems in the representation of water stress effects on both carbon uptake by photosynthesis and carbon release by heterotrophic respiration (R h ). The use of flux data as a means of assessing key processes in models of this type is an important approach to improving model performance. Our results show that the models have value but that further model development is necessary with regard to the representation of the some of the key ecosystem processes.

French records of grape-harvest dates in Burgundy were used to reconstruct spring-summer temperatures from 1370 to 2003 using a process-based phenology model developed for the Pinot Noir grape. Our results reveal that temperatures as high as those reached in the 1990s have occurred several times in Burgundy since 1370. However, the summer of 2003 appears to have been extraordinary, with temperatures that were probably higher than in any other year since 1370.