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Comments on the paper "Does Temperature Sensitivity of Decomposition Vary with Soil Organic Matter (SOM) Quality?," by M. Reichstein and colleagues. Significance of the sensitivity of SOM to temperature to the debate of possible effects of climatic change on terrestrial ecosystems; Concerns raised about the analysis of soil incubation data; Criteria for the selection of data for the statistical analysis of soil incubation data.

While there is agreement that global warming over the 21st century is likely to influence the biological pump, Earth system models (ESMs) display significant divergence in their projections of future new production. This paper quantifies and interprets the sensitivity of projected changes in new production in an idealized global ocean biogeochemistry model. The model includes two tracers that explicitly represent nutrient transport, light- and nutrient-limited nutrient uptake by the ecosystem (new production), and export via sinking organic particles. Globally, new production declines with warming due to reduced surface nutrient availability, as expected. However, the magnitude, seasonality, and underlying dynamics of the nutrient uptake are sensitive to the light and nutrient dependencies of uptake, which we summarize in terms of a single biological timescale that is a linear combination of the partial derivatives of production with respect to light and nutrients. Although the relationships are nonlinear, this biological timescale is correlated with several measures of biogeochemical function: shorter timescales are associated with greater global annual new production and higher nutrient utilization. Shorter timescales are also associated with greater declines in global new production in a warmer climate and greater sensitivity to changes in nutrients than light. Future work is needed to characterize more complex ocean biogeochemical models in terms of similar timescale generalities to examine their climate change implications. [ABSTRACT FROM AUTHOR]

The overall goal of OUTPACE (Oligotrophy to UlTra-oligotrophy PACific Experiment) was to obtain a successful representation of the interactions between planktonic organisms and the cycle of biogenic elements in the western tropical South Pacific Ocean across trophic and N2 fixation gradients. Within the context of climate change, it is necessary to better quantify the ability of the oligotrophic ocean to sequester carbon through biological processes. OUTPACE was organized around three main objectives, which were (1) to perform a zonal characterization of the biogeochemistry and biological diversity of the western tropical South Pacific during austral summer conditions, (2) to study the production and fate of organic matter (including carbon export) in three contrasting trophic regimes (increasing oligotrophy) with a particular emphasis on the role of dinitrogen fixation, and (3) to obtain a representation of the main biogeochemical fluxes and dynamics of the planktonic trophic network. The international OUTPACE cruise took place between 18 February and 3 April 2015 aboard the RV L'Atalante and involved 60 scientists (30 onboard). The west--east transect covered _4000 km from the western part of the Melanesian archipelago (New Caledonia) to the western boundary of the South Pacific gyre (French Polynesia). Following an adaptive strategy, the transect initially designed along the 19_ S parallel was adapted along-route to incorporate information coming from satellite measurements of sea surface temperature, chlorophyll a concentration, currents, and diazotroph quantification. After providing a general context and describing previous work done in this area, this introductory paper elucidates the objectives of OUTPACE, the implementation plan of the cruise and water mass and climatological characteristics and concludes with a general overview of the other papers that will be published in this special issue. [ABSTRACT FROM AUTHOR]

OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national research facility to monitor and assess trends, and improve predictions, of Australia's terrestrial biosphere and climate. This paper describes the evolution, design, and current status of OzFlux as well as provides an overview of data processing. We analyse measurements from all sites within the Australian portion of the OzFlux network and two sites from New Zealand. The response of the Australian biomes to climate was largely consistent with global studies except that Australian systems had a lower ecosystem water-use efficiency. Australian semi-arid/arid ecosystems are important because of their huge extent (70%) and they have evolved with common moisture limitations. We also found that Australian ecosystems had a similar radiationuse efficiency per unit leaf area compared to global values that indicates a convergence toward a similar biochemical efficiency. The two New Zealand sites represented extremes in productivity for a moist temperate climate zone, with the grazed dairy farm site having the highest GPP of any OzFlux site (2620 gCm-2 yr-1/ and the natural raised peat bog site having a very low GPP (820 gCm-2 yr-1). The paper discusses the utility of the flux data and the synergies between flux, remote sensing, and modelling. Lastly, the paper looks ahead at the future direction of the network and concludes that there has been a substantial contribution by OzFlux, and considerable opportunities remain to further advance our understanding of ecosystem response to disturbances, including drought, fire, land-use and land-cover change, land management, and climate change, which are relevant both nationally and internationally. It is suggested that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing the delicately balanced ecosystems in Australasia. [ABSTRACT FROM AUTHOR]

A range of applications analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, make use of land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from that account for land processes in different ways and this may introduce predictive uncertainty when LSM outputs are used as inputs to inform a given application. For useful predictions for a specific application, one must therefore understand the inherent uncertainties in the LSMs and the variations between them, as well as uncertainties arising from variation in the climate data driving the LSMs. This requires methods to analyse multivariate spatio-temporal variations and differences. A methodology is proposed based on multiway data analysis, which extends singular value decomposition (SVD) to multidimensional tables and provides spatio-temporal descriptions of agreements and disagreements between LSMs for both historical simulations and future predictions. The application underlying this paper is prediction of how climate change will affect the spread of CSIs in the Fennoscandian and north-west Russian regions, and the approach is explored by comparing net primary production (NPP) estimates over the period 1998–2013 from versions of leading LSMs (JULES, CLM5 and two versions of ORCHIDEE) that are adapted to high-latitude processes, as well as variations in JULES up to 2100 when driven by 34 global circulation models (GCMs). A single optimal spatio-temporal pattern, with slightly different weights for the four LSMs (up to 14 % maximum difference), provides a good approximation to all their estimates of NPP, capturing between 87 % and 93 % of the variability in the individual models, as well as around 90 % of the variability in the combined LSM dataset. The next best adjustment to this pattern, capturing an extra 4 % of the overall variability, is essentially a spatial correction applied to ORCHIDEE-HLveg that significantly improves the fit to this LSM, with only small improvements for the other LSMs. Subsequent correction terms gradually improve the overall and individual LSM fits but capture at most 1.7 % of the overall variability. Analysis of differences between LSMs provides information on the times and places where the LSMs differ and by how much, but in this case no single spatio-temporal pattern strongly dominates the variability. Hence interpretation of the analysis requires the summation of several such patterns. Nonetheless, the three best principal tensors capture around 76 % of the variability in the LSM differences and to a first approximation successively indicate the times and places where ORCHIDEE-HLveg, CLM5 and ORCHIDEE-MICT differ from the other LSMs. Differences between the climate forcing GCMs had a marginal effect up to 6 % on NPP predictions out to 2100 without specific spatio-temporal GCM interaction. [ABSTRACT FROM AUTHOR]

In early 2006, Keppler et al. (Nature, 439:187-191) reported a novel finding that plant leaves, and even simple organic materials, can release methane under aerobic conditions. We investigated here whether the reported methane release might simply arise from methane desorption from sample surfaces after prior exposure to higher methane concentrations. We exposed standard cellulose filter papers (i.e. organic material with a high surface area) to atmospheric methane concentration and then transferred them to a low-methane atmosphere. Our results suggest that any desorption flux was extremely small (-0.0001±0.0019 ngCH4 kgDW-1 s-1) and would play no quantitatively significant role in modifying any measured methane fluxes. We also incubated fresh detached leaves of several species and intact Zea mays seedlings under aerobic and low-light conditions. After correcting for a small measured methane influx into empty chambers, measured rates of methane emission by plant materials were zero or, at most, very small, ranging from -0.25±1.1 ngCH4 kgDW-1 s-1 for Zea mays seedlings to 0.10±0.08 ngCH4 kgDW-1 s-1 for a mixture of freshly detached grasses. These rates were much smaller than the rates originally reported by Keppler et al. (2006). [ABSTRACT FROM AUTHOR]

Presents comments on the paper "DMS Cycle in the Marine Ocean-Atmosphere System--A Global Model Study," by S. Kloster et al, which appeared in the 2005 issue of "Biogeosciences Discussions." Gaps in the understanding of key processes that regulate the DMS seawater concentration; Response of the DMS emission to climate change.

A comprehensive characterization of drought's impact on biogenic volatile organic compound (BVOC) emissions is essential for understanding atmospheric chemistry under global climate change, with implications for both air quality and climate model simulation. Currently, the effects of drought on BVOC emissions are not well characterized. Our study aims to test (i) whether instantaneous changes in meteorological conditions can serve as a better proxy for drought-related changes in BVOC emissions compared to the absolute values of the meteorological parameters, as indicated by previous BVOC mixing-ratio measurements and (ii) the impact of a plant under drought stress receiving a small amount of precipitation on BVOC emission rate, and on the manner in which the emission rate is influenced by meteorological parameters. To address these objectives, we conducted our study during the warm and dry summer conditions of the eastern Mediterranean region, focusing on the impact of drought on BVOC emissions from natural vegetation. Specifically, we conducted branch-enclosure sampling measurements in Ramat Hanadiv Nature Park, under natural drought and after irrigation (equivalent to 5.5–7 mm precipitation) for six selected branches of Phillyrea latifolia, the highest BVOC emitter in this park, in September–October 2020. The samplings were followed by gas chromatography–mass spectrometry analysis for BVOC identification and flux quantification. The results corroborate the finding that instantaneous changes in meteorological parameters, particularly relative humidity (RH), offer the most accurate proxy for BVOC emission rates under drought compared to the absolute values of either temperature (T) or RH. However, after irrigation, the correlation of the detected BVOC emission rate with the instantaneous changes in RH became significantly more moderate or even reversed. Our findings highlight that under drought, the instantaneous changes in RH and to a lesser extent in T are the best proxy for the emission rate of monoterpenes (MTs) and sesquiterpenes (SQTs), whereas under moderate drought conditions, T or RH serves as the best proxy for MT and SQT emission rate, respectively. In addition, the detected emission rates of MTs and SQTs increased by 150 % and 545 %, respectively, after a small amount of irrigation. [ABSTRACT FROM AUTHOR]

Large-scale reforestation, afforestation, and forest restoration schemes have gained global support as climate change mitigation strategies due to their significant carbon dioxide removal (CDR) potential. However, there has been limited research into the unintended consequences of forestation from a biophysical perspective. In the Community Earth System Model version 2 (CESM2), we apply a global forestation scenario, within a Paris Agreement-compatible warming scenario, to investigate the land surface and hydroclimate response. Compared to a control scenario where land use is fixed to present-day levels, the forestation scenario is up to 2 °C cooler at low latitudes by 2100, driven by a 10 % increase in evaporative cooling in forested areas. However, afforested areas where grassland or shrubland are replaced lead to a doubling of plant water demand in some tropical regions, causing significant decreases in soil moisture (∼ 5 % globally, 5 %–10 % regionally) and water availability (∼ 10 % globally, 10 %–15 % regionally) in regions with increased forest cover. While there are some increases in low cloud and seasonal precipitation over the expanded tropical forests, with enhanced negative cloud radiative forcing, the impacts on large-scale precipitation and atmospheric circulation are limited. This contrasts with the precipitation response to simulated large-scale deforestation found in previous studies. The forestation scenario demonstrates local cooling benefits without major disruption to global hydrodynamics beyond those already projected to result from climate change, in addition to the cooling associated with CDR. However, the water demands of extensive forestation, especially afforestation, have implications for its viability, given the uncertainty in future precipitation changes. [ABSTRACT FROM AUTHOR]

This study evaluates the ability of Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate biogeochemical variables in the southern South China Sea (SCS). The analysis focuses on key biogeochemical variables: chlorophyll, phytoplankton, nitrate, and oxygen based on their availability in the selected models at annual and seasonal scales. The models' performance is assessed against Copernicus Marine Environment Monitoring Service (CMEMS) data using statistical metrics such as the Taylor diagram and Taylor skill score. The results show that the models generally capture the observed spatial patterns of surface biogeochemical variables. However, they exhibit varying degrees of overestimation or underestimation in their quantitative measures. Specifically, their mean bias error ranges from -0.02 to +2.5 mg m -3 for chlorophyll, -0.5 to +1 mmol m -3 for phytoplankton, -0.1 to +1.3 mmol m -3 for nitrate, and -2 to +2.5 mmol m -3 for oxygen. The performance of the models is also influenced by the season, with some models showing better performance during June, July, and August than December, January, and February. Overall, the top five best-performing models for biogeochemical variables are MIROC-ES2H, GFDL-ESM4, CanESM5-CanOE, MPI-ESM1-2-LR, and NorESM2-LM. The findings of this study have implications for researchers and end users of the datasets, providing guidance for model improvement and understanding the impacts of climate change on the southern SCS ecosystem. [ABSTRACT FROM AUTHOR]

Subalpine forests are a crucial component of the carbon cycling system in the Qinghai–Tibet Plateau (QTP). However, there are currently significant data gaps in the QTP, and it is essential to enhance continuous monitoring of forest carbon absorption processes in the future. This study investigates 2 years' carbon exchange dynamics of a subalpine forest on the QTP using an eddy covariance method. We first characterized the seasonal carbon dynamics of the subalpine forest, revealing the higher carbon dioxide (CO 2) exchange rates in summer and autumn and lower rates in winter and spring, and found that autumn is the peak period for carbon sequestration in this subalpine forest, with the maximum measured value of CO 2 absorption reaching 10.70 µ mol m -2 s -1. Subsequently, we examined the environmental factors influencing the carbon sequestration function. Principal component analysis (PCA) shows that photosynthetically active radiation (PAR) was the major environmental factor driving the net ecosystem exchange (NEE) of CO 2 , significantly influencing forest carbon absorption, and the increase in relative humidity decreases the rate of carbon fixation. In addition, we explored NEE and its influencing factors at the regional scale and found that air temperature promotes carbon dioxide absorption (negative NEE values), while the average annual precipitation shows a minor effect on NEE. At the annual scale, the subalpine forest functions as a strong carbon sink, with an average NEE of -332 to -351 g C m -2 (from November 2020 to October 2022). Despite the challenges of climate change, forests remain robust carbon sinks with the highest carbon sequestration capacity in the QTP, with an average annual CO 2 absorption rate of 368 g C m -2. This study provides valuable insights into the carbon cycling mechanism in subalpine ecosystems and the global carbon balance. [ABSTRACT FROM AUTHOR]

This study describes and implements an integrated, multimedia, process-based system-level approach to estimating nitrogen (N) fate and transport in large river basins. The modeling system includes the following components: (1) Community Multiscale Air Quality (CMAQ), (2) Weather Research and Forecasting Model (WRF), (3) Environmental Policy Integrated Climate (EPIC), and (4) Soil and Water Assessment Tool (SWAT). The previously developed Fertilizer Emission Scenario Tool for CMAQ (FEST-C), an advanced user interface, integrated EPIC with the WRF model and CMAQ. The FEST-C system, driven by process-based WRF weather simulations, includes atmospheric N additions to agricultural cropland and agricultural cropland contributions to ammonia emissions. This study focuses on integrating the watershed hydrology and water quality model with FEST-C system so that a full multimedia assessment on water quality in large river basins to address impacts of fertilization, meteorology, and atmospheric N deposition on water quality can be achieved. Objectives of this paper are to describe how to expand the previous effort by integrating the SWAT model with the FEST-C (CMAQ/WRF/EPIC) modeling system, as well as to demonstrate application of the Integrated Modeling System (IMS) to the Mississippi River basin (MRB) to simulate streamflow and dissolved N loadings to the Gulf of Mexico (GOM). IMS simulation results generally agree with US Geological Survey (USGS) observations/estimations; the annual simulated streamflow is 218.9 mm and USGS observation is 211.1 mm and the annual simulated dissolved N is 2.1 kg ha -1 and the USGS estimation is 2.8 kg ha -1. Integrating SWAT with the CMAQ/WRF/EPIC modeling system allows for its use within large river basins without losing EPIC's more detailed biogeochemistry processes, which will strengthen the assessment of impacts of future climate scenarios, regulatory and voluntary programs for N oxide air emissions, and land use and land management on N transport and transformation in large river basins. [ABSTRACT FROM AUTHOR]

Long-term environmental research networks are one approach to advancing local, regional, and global environmental science and education. A remarkable number and wide variety of environmental research networks operate around the world today. These are diverse in funding, infrastructure, motivating questions, scientific strengths, and the sciences that birthed and maintain the networks. Some networks have individual sites that were selected because they had produced invaluable long-term data, while other networks have new sites selected to span ecological gradients. However, all long-term environmental networks share two challenges. Networks must keep pace with scientific advances and interact with both the scientific community and society at large. If networks fall short of successfully addressing these challenges, they risk becoming irrelevant. The objective of this paper is to assert that the biogeosciences offer environmental research networks a number of opportunities to expand scientific impact and public engagement. We explore some of these opportunities with four networks: the International Long-Term Ecological Research Network programs (ILTERs), critical zone observatories (CZOs), Earth and ecological observatory networks (EONs), and the FLUXNET program of eddy flux sites. While these networks were founded and expanded by interdisciplinary scientists, the preponderance of expertise and funding has gravitated activities of ILTERs and EONs toward ecology and biology, CZOs toward the Earth sciences and geology, and FLUXNET toward ecophysiology and micrometeorology. Our point is not to homogenize networks, nor to diminish disciplinary science. Rather, we argue that by more fully incorporating the integration of biology and geology in long-term environmental research networks, scientists can better leverage network assets, keep pace with the ever-changing science of the environment, and engage with larger scientific and public audiences. [ABSTRACT FROM AUTHOR]

Atmospheric tracers are often used to interpret the local CO 2 budget, where measurements at a single height are assumed to represent local flux signatures. Alternatively, these signatures can be derived from direct flux measurements or by using fluxes derived from measurements at multiple heights. In this study, we contrast interpretation of surface CO 2 exchange from tracer measurements at a single height to measurements at multiple heights. Specifically, we analyse the ratio between atmospheric O 2 and CO 2 (exchange ratio, ER) above a forest. We consider the following two alternative approaches: the exchange ratio of the forest (ER forest) obtained from the ratio of the surface fluxes of O 2 and CO 2 derived from measurements at multiple heights, and the exchange ratio of the atmosphere (ER atmos) obtained from changes in the O 2 and CO 2 mole fractions over time measured at a single height. We investigate the diurnal cycle of both ER signals to better understand the biophysical meaning of the ER atmos signal. We have combined CO 2 and O 2 measurements from Hyytiälä, Finland, during spring and summer of 2018 and 2019 with a conceptual land–atmosphere model to investigate the behaviour of ER atmos and ER forest. We show that the CO 2 and O 2 signals as well as their resulting ERs are influenced by climate conditions such as variations in soil moisture and temperature, for example during the 2018 heatwave. We furthermore show that the ER atmos signal obtained from single-height measurements rarely represents the forest exchange directly, mainly because it is influenced by entrainment of air from the free troposphere into the atmospheric boundary layer. The influence of these larger-scale processes can lead to very high ER atmos values (even larger than 2), especially in the early morning. These high values do not directly represent carbon cycle processes, but are rather a mixture of different signals. We conclude that the ER atmos signal provides only a weak constraint on local-scale surface CO 2 exchange, and that ER forest above the canopy should be used instead. Single-height measurements always require careful selection of the time of day and should be combined with atmospheric modelling to yield a meaningful representation of forest carbon exchange. More generally, we recommend always measuring at multiple heights when using multi-tracer measurements to study surface CO 2 exchange. [ABSTRACT FROM AUTHOR]

Afforestation has been considered a critical nature-based solution to mitigate global warming. China has announced an ambitious afforestation plan covering an area of 73.78×104 km2 for the period 2020–2050. However, it is unclear which areas will be suitable for afforestation under future climate change. Here, we carried out a finer-resolution (25×25 km) dynamical downscaling of climate change for China using the Weather Research and Forecast (WRF) model nested with the bias-corrected MPI-ESM1-2-HR model. Then, using the Holdridge life zone model forced by the WRF model output, we mapped the climatological suitability for forests in China. The results showed that the potential forestation domain (PFD) at present (1995–2014) approximated 500.75×104 km2 , and it would increase by about 3.49 % to 518.25×104 km2 in the period 2041–2060 under the Shared Socioeconomic Pathway (SSP) scenario (SSP2-4.5). Considering the expansion of the future PFD due to climate change, the afforestation area for each province was allocated to grid cells following the climatological suitability for forests. The new afforestation grid cells would be located around and to the east of the Hu Line (a geographical division stretching from Heihe to Tengchong). Due to afforestation, the land cover would be modified. The conversion from grasslands to deciduous broadleaf forests in northern China took up the most area, accounting for 40 % of the new afforestation area. The grid-cell-resolved afforestation dataset was consistent with the provincial afforestation plan and the future climatological forest suitability. The dataset would be valuable for investigating the impacts of future afforestation on various aspects, including the carbon budget, ecosystem services, water resources, and surface hydroclimate regime. [ABSTRACT FROM AUTHOR]

Modeling terrestrial gross primary productivity (GPP) is central to predicting the global carbon cycle. Much interest has been focused on the environmentally induced dynamics of photosystem energy partitioning and how improvements in the description of such dynamics assist the prediction of light reactions of photosynthesis and therefore GPP. The maximum quantum yield of photosystem II (ΦPSIImax) is a key parameter of the light reactions that influence the electron transport rate needed for supporting the biochemical reactions of photosynthesis. ΦPSIImax is generally treated as a constant in biochemical photosynthetic models even though a constant ΦPSIImax is expected only for non-stressed plants. We synthesized reported ΦPSIImax values from pulse-amplitude-modulated fluorometry measurements in response to variable temperatures across the globe. We found that ΦPSIImax is strongly affected by prevailing temperature regimes with declined values in both hot and cold conditions. To understand the spatiotemporal variability in ΦPSIImax , we analyzed the temperature effect on ΦPSIImax across plant functional type (PFT) and habitat climatology. The analysis showed that temperature's impact on ΦPSIImax is shaped more by climate than by PFT for plants with broad latitudinal distributions or in regions with extreme temperature variability. There is a trade-off between the temperature range within which ΦPSIImax remains maximal and the overall rate of decline of ΦPSIImax outside the temperature range such that species cannot be simultaneously tolerant and resilient to extreme temperatures. Our study points to a quantitative approach for improving electron transport and photosynthetic productivity modeling under changing climates at regional and global scales. [ABSTRACT FROM AUTHOR]

The overall goal of the BOUM (Biogeochemistry from the Oligotrophic to the Ultraoligotrophic Mediterranean) experiment was to obtain a better representation of the interactions between planktonic organisms and the cycle of biogenic elements in the Mediterranean Sea (MS), in the context of global climate change and, more particularly, on the role of the ocean in carbon sequestration through biological processes. The BOUM experiment was organized around three main objectives: (1) to give a longitudinal description of the biogeochemistry and the biological diversity of the MS during the strongest stratified period, (2) to study processes at the centre of three anticyclonic eddies, and (3) to obtain a representation of the main biogeochemical fluxes and the dynamics of the planktonic trophic network. The international BOUM cruise took place between 16 June and 20 July 2008, involved 32 scientists on board, and covered around 3000 km in the MS from the south of Cyprus to Marseilles (France). This paper describes in detail the objectives of the BOUM experiment, the implementation plan of the cruise before giving an introduction of the 25 other papers published in this special issue. [ABSTRACT FROM AUTHOR]

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests. [ABSTRACT FROM AUTHOR]

We present an analysis of the evolution of near-bed oxygen in the next century in the northwest European continental shelf in a three-member ensemble of coupled physics–biogeochemistry models. The comparison between model results helps highlight the biogeochemical mechanisms responsible for the observed deoxygenation trends and their response to climate drivers. While all models predict a decrease in near-bed oxygen proportional to climate change intensity, the response is spatially heterogeneous, with hotspots of oxygen decline (up to - 1 mg L -1) developing along the Norwegian trench in the members with the most intense change, as well as areas where compensating mechanisms mitigate change. We separate the components of oxygen change associated with the warming effect on oxygen solubility from those due to the effects of changes in transport and biological processes. We find that while warming is responsible for a mostly uniform decline throughout the shelf (- 0.30 mg L -1 averaged across ensemble members), changes in transport and biological processes account for the detected heterogeneity. Hotspots of deoxygenation are associated with enhanced stratification that greatly reduces vertical transport. A major change in circulation in the North Sea is responsible for the onset of one such hotspot that develops along the Norwegian trench and adjacent areas in the members characterised by intense climate change. Conversely, relatively shallow and well-mixed coastal areas like the southern North Sea, Irish Sea and English Channel experience an increase in net primary production that partially mitigates oxygen decline in all members. This work represents the first multi-model comparison addressing deoxygenation in the northwest European shelf and contributes to characterising the possible trajectories of near-bed oxygen and the processes that drive deoxygenation in this region. As our downscaled members factor in riverine inputs and small- and medium-scale circulation, which are not usually well represented in earth system models, results are relevant for the understanding of deoxygenation in coastal and shelf systems. [ABSTRACT FROM AUTHOR]

The response of the global climate–carbon-cycle system to anthropogenic perturbations happens differently at different timescales. The unravelling of the memory structure underlying this timescale dependence is a major challenge in climate research. Recently the widely applied α – β – γ framework proposed by to quantify climate–carbon-cycle feedbacks has been generalized to account also for such internal memory. By means of this generalized framework, we investigate the timescale dependence of the airborne fraction for a set of Earth system models that participated in CMIP5 (Coupled Model Intercomparison Project Phase 5). The analysis is based on published simulation data from C 4 MIP-type (Coupled Climate–Carbon Cycle Model Intercomparison) experiments with these models. Independently of the considered scenario, the proposed generalization describes at global scale the reaction of the climate–carbon system to sufficiently weak perturbations. One prediction from this theory is how the timescale-resolved airborne fraction depends on the underlying feedbacks between climate and the carbon cycle. These feedbacks are expressed as timescale-resolved functions depending solely on analogues of the α , β , and γ sensitivities, introduced in the generalized framework as linear response functions. In this way a feedback-dependent quantity (airborne fraction) is predicted from feedback-independent quantities (the sensitivities). This is the key relation underlying our study. As a preparatory step, we demonstrate the predictive power of the generalized framework exemplarily for simulations with the Max Planck Institute (MPI) Earth System Model. The whole approach turns out to be valid for perturbations of up to an about 100 ppm CO 2 rise above the pre-industrial level; beyond this value the response becomes non-linear. By means of the generalized framework we then derive the timescale dependence of the airborne fraction from the underlying climate–carbon-cycle feedbacks for an ensemble of CMIP5 models. Our analysis reveals that for all studied CMIP5 models (1) the total climate–carbon-cycle feedback is negative at all investigated timescales, (2) the airborne fraction generally decreases for increasing timescales, and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all these timescales. Qualitatively similar results were previously found by employing the original α – β – γ framework to particular perturbation scenarios, but our study demonstrates that, although obtained from particular scenario simulations, they are characteristics of the coupled climate–carbon-cycle system as such, valid at all considered timescales. These more general conclusions are obtained by accounting for the internal memory of the system as encoded in the generalized sensitivities, which in contrast to the original α , β , and γ are scenario-independent. [ABSTRACT FROM AUTHOR]

The French coast facing the Bay of Biscay (North-East Atlantic) is characterised by the presence of small macrotidal and turbid estuaries, including the Charente, which is geographically located between the two large estuaries of the Gironde and the Loire (south-west France). Multi-year, multi-site and high-frequency water quality surveys have shown that the Loire and, to a lesser extent, the Gironde suffer from summer hypoxia. These observations raised the question of the possible occurrence of hypoxia, particularly in one of these small estuaries, the Charente, which flows into the Bay of Marennes-Oléron, the first oyster-farming area in France. Unlike its two large neighbours, the Charente estuary is not continuously monitored, although it is subject to similar climatic changes and anthropogenic pressures, making it impossible to assess potential risks to the ecosystem. Here we present a first study of dissolved oxygen in the Charente estuary based on a combination of longitudinal studies along the estuary axis and instrumented sites to determine the intensity and spatial extent of deoxygenation. Temperature, dissolved oxygen and conductivity sensors were deployed at several sites during the summers of 2018, 2019 and 2020 to record temperature, salinity and dissolved oxygen every 15 min. The high-frequency dataset is compared with a long-term low-frequency dataset (1975–2022; 8–12 measurements per year) to determine whether or not there is a deterioration in the oxygenation of the Charente estuary. The high-frequency dataset shows a high variability in dissolved oxygen (DO) with a clear influence of the tidal cycle. During summer, DO concentrations are often below 5 mgL-1 and sometimes even below 2 mgL-1 , indicating the presence of a summer estuarine oxygen minimum zone with an extension along the estuarine axis of about 20–25 km. Temperature is the main factor controlling DO in the Charente estuary, which limits preventive management strategies and, in the context of global warming, raises questions about the long-term suitability of estuarine conditions for the needs of the biological communities, particularly migratory fish. [ABSTRACT FROM AUTHOR]

Four adjacent lakes (Arco, Budd, Deming, and Josephine) within Itasca State Park in Minnesota, USA, are reported to be meromictic in the scientific literature. However, seasonally persistent chemoclines have never been documented. We collected seasonal profiles of temperature and specific conductance and placed temperature sensor chains in two lakes for ∼1 year to explore whether these lakes remain stratified through seasonal mixing events and what factors contribute to their stability. The results indicate that all lakes are predominantly thermally stratified and are prone to mixing in isothermal periods during spring and fall. Despite brief, semi-annual erosion of thermal stratification, Deming Lake showed no signs of complete mixing from 2006–2009 and 2019–2022 and is likely meromictic. However, the other lakes are not convincingly meromictic. Geochemical data indicate that water in Budd Lake, which contains the most water, is predominantly sourced from precipitation. The water in the other three lakes is of the calcium–magnesium–bicarbonate type, reflecting a source of water that has interacted with the deglaciated landscape. δ18OH2O and δ2HH2O measurements indicate the lakes are supplied by precipitation modified by evaporation. Josephine, Arco, and Deming lakes sit in a valley with likely permeable sediments and may be hydrologically connected through wetlands and recharged with shallow groundwater, as no streams are present. The water residence time in meromictic Deming Lake is short (100 d), yet it maintains a large reservoir of dissolved iron, indicating that shallow groundwater may be an additional source of water and dissolved ions. All four lakes develop subsurface chlorophyll maxima layers during the summer. All lakes also develop subsurface oxygen maxima that may result from oxygen trapping in the spring by rapidly developed summer thermoclines. Documenting the mixing status and general chemistry of these lakes enhances their utility and accessibility for future biogeochemical studies, which is important as lake stratification and anoxia are becoming more prevalent due to changes in climate and land use. [ABSTRACT FROM AUTHOR]

Afforestation affects the earth's climate system by changing the biogeochemical and biogeophysical characteristics of the land surface. While the regional effects of afforestation are well understood in the tropics and the high latitudes, its climate impact on the midlatitudes is still the subject of scientific discussions. The general impact of afforestation on the regional climate conditions in Europe during the last decades is investigated in this study. For this purpose, regional climate simulations are performed with different forest cover fractions over Europe. In a first simulation, afforestation in Europe is considered, while this is not the case for a second simulation. We focus on the years 1986–2015, a period in which the forest cover in Europe increased comparatively strongly, accompanied by a strong general warming over the continent. Results show that afforestation has both local and non-local effects on the regional climate system in Europe. Due to an increased transport of turbulent heat (latent + sensible) into the atmosphere, afforestation leads to a significant reduction of the mean local surface temperatures in summer. In northern Europe, mean local surface temperatures were reduced about - 0.3 K with afforestation, in central Europe about - 0.5 K, and in southern Europe about - 0.8 K. During heat periods, this local cooling effect can reach - 1.9 K. In winter, afforestation results in a slight local warming in both northern and southern Europe because of the albedo effect of forests. However, this effect is rather small and the mean temperature changes are not significant. In the downwind direction, locally increased evapotranspiration rates with afforestation increase the general cloud cover, which results in a slight non-local warming in winter in several regions of Europe, particularly during cold spells. Thus, afforestation had a discernible impact on the climate change signal in Europe during the period 1986–2015, which may have mitigated the general warming trend in Europe, especially on the local scale in summer. [ABSTRACT FROM AUTHOR]

Environmental signals are important triggers in the life-cycle transitions and play a crucial role in the life-history evolution. Yet very little is known about the leading ecological factors contributing to the variations of life-history traits in perennial plants. This paper explores both the causes and consequences for the evolution of life-history traits (i.e., seed dormancy and size) in lodgepole pine (Pinus contorta Dougl.) across British Columbia (B.C.), Canada. We selected 83 logepole pine populations covering 22 ecosystem zones of B.C. and through their geographic coordinate, 197 climatic variables were generated accordingly for the reference (1961-1990) and future (2041-2070) periods. We found that dynamic climatic variables rather than constant geographic variables are the true environmental driving forces in seed dormancy and size variations and thus provide reliable predictors in response to global climate change. Evapotranspiration and precipitation in the plant-to-seed chronology are the most critical climate variables for seed dormancy and size variations, respectively. Hence, we predicted that levels of seed dormancy in lodgepole pine would increase across large tracts of B.C. in 2050s. Winter-chilling is able to increase the magnitude of life-history plasticity and lower the bet-hedge strategy in the seed-to-plant transition; however, winter-chilling is likely to be insufficient in the north of 49° N in 2050s, which may delay germination while unfavorable conditions during dry summers may result in adverse consequences in the survival of seedlings owing to extended germination span. These findings provide useful information to studies related to assessments of seed transfer and tree adaptation. [ABSTRACT FROM AUTHOR]

Fossil invertebrates from cave sediments have been recently described as a potential new proxy for paleoenvironment and used in cross-correlations with alternate proxy records from cave deposits. Here we present the results of a fossil invertebrates study in four caves from two climatically different regions of the Romanian Carpathians, to complement paleoenvironmental data previously reported. Oribatid mites and ostracods are the most common invertebrates in the studied cave sediments. Some of the identified taxa are new to science, and most of them are indicative for either warm and/or cold stages or dry and/or wetter oscillations. In two caves the fossil invertebrates records indicate rapid climate oscillations during times known for a relatively stable climate. By corroborating the fossil invertebrates' record with the information given by magnetic properties and sediment structures, complementary data on past vegetation, temperatures and hydraulic regimes could be gathered. This paper analyzes the potential of fossil invertebrate records as a paleoenvironmental proxy, potential problems and pitfalls. [ABSTRACT FROM AUTHOR]

Coccolithophores are sensitive recorders of environmental change. The size of their coccosphere varies in the ocean along gradients of environmental conditions and provides a key for understanding the fate of this important phytoplankton group in the future ocean. But interpreting field changes in coccosphere size in terms of laboratory observations is hard, mainly because the marine signal reflects the response of multiple morphotypes to changes in a combination of environmental variables. In this paper I examine the large corpus of published laboratory experiments with coccolithophores looking for relations between environmental conditions, metabolic rates and cell size (a proxy for coccosphere size). I show that growth, photosynthesis and, to a lesser extent, calcification covary with cell size when pCO2, irradiance, temperature, nitrate, phosphate and iron conditions change. With the exception of phosphate and temperature, a change from limiting to non-limiting conditions always results in an increase in cell size. An increase in phosphate or temperature (below the optimum temperature for growth) produces the opposite effect. The magnitude of the coccosphere-size changes observed in the laboratory is comparable to that observed in the ocean. If the biological reasons behind the environment-metabolism-size link are understood, it will be possible to use coccosphere-size changes in the modern ocean and in marine sediments to investigate the fate of coccolithophores in the future ocean. This reasoning can be extended to the size of coccoliths if, as recent experiments are starting to show, coccolith size reacts to environmental change proportionally to coccosphere size. The coccolithophore database is strongly biased in favour of experiments with the coccolithophore Emiliania huxleyi (E. huxleyi; 82% of database entries), and more experiments with other species are needed to understand whether these observations can be extended to coccolithophores in general. I introduce a simple model that simulates the growth rate and the size of cells forced by nitrate and phosphate concentrations. By considering a simple rule that allocates the energy flow from nutrient acquisition to cell structure (biomass) and cell maturity (biological complexity, eventually leading to cell division), the model is able to reproduce the covariation of growth rate and cell size observed in laboratory experiments with E. huxleyi when these nutrients become limiting. These results support ongoing efforts to interpret coccosphere and coccolith size measurements in the context of climate change. [ABSTRACT FROM AUTHOR]

A new generation of an Earth System Model now includes a number of land surface processes directly relevant to analyzing potential impacts of climate change. This model, HadGEM2-ES, allows us to assess the impacts of climate change, multiple interactions, and feedbacks as the model is run. This paper discusses the results of century-scale HadGEM2-ES simulations from an impacts perspective--specifically, terrestrial ecosystems and water resources--for four different scenarios following the Representative Concentration Pathways (RCPs), being used for next assessment report of the Intergovernmental Panel on Climate Change (IPCC). Over the 21st Century, simulated changes in global and continential-scale terrestrial ecosystems due to climate change appear to be very similar in all 4 RCPs, even though the level of global warming by the end of the 21st Century ranges from 2 °C in the lowest scenario to 5.5° in the highest. A warming climate generally favours broadleaf trees over needleleaf, needleleaf trees over shrubs, and shrubs over herbaceous vegetation, resulting in a poleward shift of temperate and boreal forests and woody tundra in all scenarios. Although climate related changes are slightly larger in scenarios of greater warming, the largest differences between scenarios arise at regional scales as a consequence of different patterns of anthropogenic land cover change. In the model, the scenario with the lowest global warming results in the most extensive decline in tropical forest cover due to a large expansion of agriculture. Under all four RCPs, fire potential could increase across extensive land areas, particularly tropical and sub-tropical latitudes. River outflows are simulated to increase with higher levels of CO2 and global warming in all projections, with outflow increasing with mean temperature at the end of the 21st Century at the global scale and in North America, Asia, and Africa. In South America, Europe, and Australia, the relationship with climate warming and CO2 rise is less clear, probably as a result of land cover change exerting a dominant effect in those regions. [ABSTRACT FROM AUTHOR]

The Hengduan Mountains, with their strong altitudinal vegetation zonation, form a biodiversity hotspot which offers the potential for comparison between sites in order to understand how this zonation arose and how it has responded to climate change and human impacts through time. This paper presents a 22 570-year pollen record of vegetational and climatic change based on a core 320 cm in depth collected from Wenhai Lake on Jade Dragon Snow Mountain, one of the highest peaks in the Hengduan Mountains region of Yunnan, Southwest China. From 22 570 to 21 140 cal yr BP, the vegetation was dominated by broad-leaved forest (comprising mainly Quercus, Betula and Castanopsis), accompanied by needle-leaved forest (mainly Pinus and Abies), indicating a rather cold and dry climate relative to the present followed by cold and wet conditions. In the period between 21 140 and 19 350 cal yr BP, the vegetation was still dominated by broad-leaved forest and needle-leaved forest as before but with a notable increase in Betula pollen and a sharp decrease in Quercus pollen, implying a relatively cold and dry climate with several fluctuations in humidity. The period 19 350 to 17 930 cal yr BP was a transition stage from broad-leaved forest to needle-leaved forest, with a dramatic decrease in Quercus pollen and a maximum reading for Abies pollen, reflecting the coldest and driest climate since 22 570 cal yr BP. The expansion in needle-leaved forest dominated by Pinus and Abies (22 570-17 930 cal yr BP) along with an increase of Betula might correspond to the Last Glacial Maximum (LGM; the start of the LGM perhaps occurred prior to the basal age of the core). Between 17 930 and 9250 cal yr BP, needle-leaved forest declined and broad-leaved forest began to increase at first, suggesting increases in temperature and humidity, while towards the end of the period, needle-leaved forest expanded and broad-leaved forest shrank, indicating a colder and drier climate, possibly corresponding to the Younger Dryas. From 9250 cal yr BP to the present, the vegetation has been dominated by needle-leaved forest (comprising mainly Pinus, Abies and Tsuga), interspersed with broad-leaved Quercus and Betula, reflecting a significant decline in humidity from the early to late Holocene. During this period, human activity likely increased in this region, with impacts on the vegetation such as a distinct decrease in Pinus and Quercus pollen and an increase in Polygonaceae pollen in the upper 30 cm of the core. The marked decline in Quercus pollen compared with the early stage of this period, in particular, in the Wenhai core can be correlated with that observed in the Haligu core (situated about 2 km away) between 2400 cal yr BP and the present. [ABSTRACT FROM AUTHOR]

Free-ocean CO2 enrichment (FOCE) systems are designed to assess the impact of ocean acidification on biological communities in situ for extended periods of time (weeks to months). They overcome some of the drawbacks of laboratory experiments and field observations by enabling (1) precise control of CO2 enrichment by monitoring pH as an offset of ambient pH, (2) consideration of indirect effects such as those mediated through interspecific relationships and food webs, and (3) relatively long experiments with intact communities. Bringing perturbation experiments from the laboratory to the field is, however, extremely challenging. The main goal of this paper is to provide guidelines on the general design, engineering, and sensor options required to conduct FOCE experiments. Another goal is to introduce xFOCE, a community-led initiative to promote awareness, provide resources for in situ perturbation experiments, and build a user community. Present and existing FOCE systems are briefly described and examples of data collected presented. Future developments are also addressed as it is anticipated that the next generation of FOCE systems will include, in addition to pH, options for oxygen and/or temperature control. FOCE systems should become an important experimental approach for projecting the future response of marine ecosystems to environmental change. [ABSTRACT FROM AUTHOR]

Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate change impacts on biodiversity and ecosystem functioning. Here we combine a network of microclimate temperature measurements across different habitats and vertical heights with a novel radiative transfer model to map daily temperatures during the vegetation period at 10 m spatial resolution across Switzerland. Our results reveal strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 ∘ C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 ∘ C, respectively. We also found that, in open grasslands, maximum temperatures at 5 cm above ground are, on average, 3.4 ∘ C warmer than those of the macroclimate, suggesting that, in such habitats, heat exposure close to the ground is often underestimated when using macroclimatic data. Spatial interpolation was achieved by using a hybrid approach based on linear mixed-effect models with input from detailed radiation estimates from radiative transfer models that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography, and vegetation height. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by root mean squared errors ranging from 1.18 to 3.43 ∘ C, with minimum temperatures being predicted more accurately overall than maximum temperatures. The microclimate-mapping methodology presented here enables a biologically relevant perspective when analysing climate–species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change. [ABSTRACT FROM AUTHOR]

The global ocean's coastal areas are rapidly experiencing the effects of climate change. These regions are highly dynamic, with relatively small-scale circulation features like shelf break currents playing an important role. Projections can produce widely diverging estimates of future regional circulation structures. Here, we use the northwestern North Atlantic, a hotspot of ocean warming, as a case study to illustrate how the uncertainty in future estimates of regional circulation manifests itself and affects projections of shelf-wide biogeochemistry. Two diverging climate model projections are considered and downscaled using a high-resolution regional model with intermediate biogeochemical complexity. The two resulting future scenarios exhibit qualitatively different circulation structures by 2075 where along-shelf volume transport is reduced by 70 % in one of them and while remaining largely unchanged in the other. The reduction in along-shelf transport creates localized areas with either amplified warming (+3 ∘ C) and salinification (+0.25 units) or increased acidification (-0.25 units) in shelf bottom waters. Our results suggest that a wide range of outcomes is possible for continental margins and suggest a need for accurate projections of small-scale circulation features like shelf break currents in order to improve the reliability of biogeochemical projections. [ABSTRACT FROM AUTHOR]

The impacts of climate change on marine organisms have been increasingly documented in laboratory and experimental studies. However, the use of different taxonomic groupings and the assessment of a range of processes make identifying overall trends challenging. Meta-analysis has been used to determine general trends, but coarse taxonomic granularity may mask phylogenetically specific responses. Bivalve molluscs are a data-rich clade of ecologically and economically important calcifying marine taxa that allow for the assessment of species-specific vulnerability across developmental stages. Drawing on the large body of available literature, we conduct a meta-analysis of 203 unique experimental set-ups in order to examine how bivalve growth responds to increased water temperature, acidity, deoxygenation, and changes in salinity in 10 climate change stressor combinations. This is the most complete examination of bivalve responses to date and shows that anthropogenic climate change will disproportionally affect particular families, suggesting taxonomic differentiation in climate change response. Specifically, Mytilidae, Ostreidae, and Pectinidae (67 % of experiments) respond with negative effect sizes for all individual stressors, whereas responses in Pinnidae, Tellinidae, and Veneridae are more complex. Our analysis shows that earlier studies reporting negative impacts on bivalves are driven by only three or four well-studied, commercially important families. Despite the taxonomic differentiation, almost all drivers and their combinations have significant negative effects on growth. The synergistic impacts of deoxygenation, acidification, and temperature result in the largest negative effect size. Infaunal taxa, including Tellinidae and Veneridae, appear more resistant to warming and oxygen reduction than epifaunal or motile taxa, but this difference between the two taxa is also based on a small number of data points. The current focus of experimental set-ups on commercially important taxa and families within a small geographic range creates gaps in the understanding of global impacts on these economically important foundation organisms. [ABSTRACT FROM AUTHOR]

The pH of coastal seawater varies based on several local forcings, such as water circulation, terrestrial inputs, and biological processes, and these forcings are changing along with global climate change. Understanding the mechanism of pH variation in each coastal area is thus important for a realistic future projection that considers changes in these forcings. From 2020 to 2021, we performed parallel year-round observations of pH and related ocean parameters at five stations around the Japanese coast (Miyako Bay, Shizugawa Bay, Kashiwazaki Coast, Hinase Archipelago, and Ohno Strait) to understand the characteristics of short-term pH variations and their forcings. Annual variability (∼ 1 standard deviation) of pH and aragonite saturation state (Ωar) were 0.05–0.09 and 0.25–0.29, respectively, for three areas with low anthropogenic pressures (Miyako Bay, Kashiwazaki Coast, and Shizugawa Bay), while it increased to 0.16–0.21 and 0.52–0.58, respectively, in two areas with medium anthropogenic pressures (Hinase Archipelago and Ohno Strait in Seto Inland Sea). Statistical assessment of temporal variability at various timescales revealed that most of the annual variabilities in both pH and Ωar were derived by short-term variation at a timescale of <10 d, rather than seasonal-scale variation. Our analyses further illustrated that most of the short-term pH variation was caused by biological processes, while both thermodynamic and biological processes equally contributed to the temporal variation in Ωar. The observed results showed that short-term acidification with Ωar < 1.5 occurred occasionally in Miyako and Shizugawa bays, while it occurred frequently in the Hinase Archipelago and Ohno Strait. Most of such short-term acidified events were related to short-term low-salinity events. Our analyses showed that the amplitude of short-term pH variation was linearly correlated with that of short-term salinity variation, and its regression coefficient at the time of high freshwater input was positively correlated with the nutrient concentration of the main river that flows into the coastal area. [ABSTRACT FROM AUTHOR]

Leaf stoichiometric traits are central to ecosystem function and biogeochemical cycling, yet no accepted theory predicts their variation along environmental gradients. Using data in the China Plant Trait Database version 2, we aimed to characterize variation in leaf carbon and nitrogen per unit mass (Cmass , Nmass) and their ratio and to test an eco-evolutionary optimality model for Nmass. Community-mean trait values were related to climate variables by multiple linear regression. Climatic optima and tolerances of major genera were estimated; Pagel's λ was used to quantify phylogenetic controls, and Bayesian phylogenetic linear mixed models to assess the contributions of climate, species identity, and phylogeny. Optimality-based predictions of community-mean Nmass were compared to observed values. All traits showed strong phylogenetic signals. Climate explained only 18 % of C:N ratio variation among species but 45 % among communities, highlighting the role of taxonomic replacement in mediating community-level responses. Geographic distributions of deciduous taxa were separated primarily by moisture and evergreens by temperature. Cmass increased with irradiance but decreased with moisture and temperature. Nmass declined with all three variables. C:N ratio variations were dominated by Nmass. The coefficients relating Nmass to the ratio of maximum carboxylation capacity at 25 ∘ C (Vcmax25) and leaf mass per area (Ma) were influenced by leaf area index. The optimality model captured 68 % and 53 % of variation between communities for Vcmax25 and Ma , respectively, and 21 % for Nmass. We conclude that stoichiometric variations along climate gradients are achieved largely by environmental selection among species and clades with different intraspecific trait values. Variations in leaf C:N ratio are mainly determined by Nmass , and optimality-based modelling shows useful predictive ability for community-mean Nmass. These findings should help to improve the representation of C:N coupling in ecosystem models. [ABSTRACT FROM AUTHOR]

Earth system models suggest that anthropogenic climate change will influence marine phytoplankton over the coming century with light-limited regions becoming more productive and nutrient-limited regions less productive. Anthropogenic climate change can influence not only the mean state but also the internal variability around the mean state, yet little is known about how internal variability in marine phytoplankton will change with time. Here, we quantify the influence of anthropogenic climate change on internal variability in marine phytoplankton biomass from 1920 to 2100 using the Community Earth System Model 1 Large Ensemble (CESM1-LE). We find a significant decrease in the internal variability of global phytoplankton carbon biomass under a high emission (RCP8.5) scenario and heterogeneous regional trends. Decreasing internal variability in biomass is most apparent in the subpolar North Atlantic and North Pacific. In these high-latitude regions, bottom-up controls (e.g., nutrient supply, temperature) influence changes in biomass internal variability. In the biogeochemically critical regions of the Southern Ocean and the equatorial Pacific, bottom-up controls (e.g., light, nutrients) and top-down controls (e.g., grazer biomass) affect changes in phytoplankton carbon internal variability, respectively. Our results suggest that climate mitigation and adaptation efforts that account for marine phytoplankton changes (e.g., fisheries, marine carbon cycling) should also consider changes in phytoplankton internal variability driven by anthropogenic warming, particularly on regional scales. [ABSTRACT FROM AUTHOR]

Understanding the response of forest net ecosystem productivity (NEP) to environmental drivers under climate change is highly relevant for predictions of annual forest carbon (C) flux budgets. Modeling annual forest NEP with soil-vegetation-atmosphere transfer models (SVATs), however, remains challenging due to unknown delayed responses to weather of the previous year. In this study, we addressed the influence of previous year's weather on the interannual variability of NEP for a subalpine spruce forest in Switzerland. Analysis of long-term (1997-2011) eddy co-variance measurements showed that the Norway spruce forest Davos Seehornwald was a consistent sink for atmospheric CO2, sequestering 210 ± 88 g C m-2 yr-1 on average. Previous year's weather strongly affected interannual variability of NEP, increasing the explained variance in linear models to 53 % compared to 20 % without accounting for previous year's weather. Thus, our results highlight the need to consider previous year's weather in modeling annual C budgets of forests. Furthermore, soil temperature in the current year's spring played a major role controlling annual NEP, mainly by influencing gross primary productivity early in the year, with spring NEP accounting for 56 % of annual NEP. Consequently, we expect an increase in net CO2 uptake with future climate warming, as long as no other resources become limiting. [ABSTRACT FROM AUTHOR]

Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multi-decadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), which failed in December 2010. The Moderate Resolution Imaging Spec-troradiometer (MODIS) ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS) instrument, or successful launch of the Ocean and Land Colour Instrument (OLCI) expected in 2014 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation) especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies. [ABSTRACT FROM AUTHOR]

This paper reports a study of the full carbon (C- CO2) budget of the Australian continent, focussing on 1990-2011 in the context of estimates over two centuries. The work is a contribution to the RECCAP (REgional Carbon Cycle Assessment and Processes) project, as one of numerous regional studies. In constructing the budget, we estimate the following component carbon fluxes: net primary production (NPP); net ecosystem production (NEP); fire; land use change (LUC); riverine export; dust export; harvest (wood, crop and livestock) and fossil fuel emissions (both territorial and non-territorial). Major biospheric fluxes were derived using BIOS2 (Haverd et al., 2012), a fine-spatial-resolution (0.05°) offline modelling environment in which predictions of CABLE (Wang et al., 2011), a sophisticated land surface model with carbon cycle, are constrained by multiple observation types. The mean NEP reveals that climate variability and rising CO2 contributed 12±24 (1σ error on mean) and 68±15 TgC yr-1, respectively. However these gains were partially offset by fire and LUC (along with other minor fluxes), which caused net losses of 26±4 TgC yr -1 and 18±7 TgC yr-1, respectively. The resultant net biome production (NBP) is 36±29 TgC yr-1, in which the largest contributions to uncertainty are NEP, fire and LUC. This NBP offset fossil fuel emissions (95±6 TgC yr-1) by 38±30%. The interannual variability (IAV) in the Australian carbon budget exceeds Australia's total carbon emissions by fossil fuel combustion and is dominated by IAV in NEP. Territorial fossil fuel emissions are significantly smaller than the rapidly growing fossil fuel exports: in 2009-2010, Australia exported 2.5 times more carbon in fossil fuels than it emitted by burning fossil fuels. [ABSTRACT FROM AUTHOR]

Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202±28, 179±63 and 178±20 kg N ha-1 yr-1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31±10 kg N ha-1 yr-1, but was similar to the N surplus of PL and DK (122±20 and 146±55 kg N ha-1 yr-1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007-2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998-2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N- efficient farms, it was concluded that additional N-surplus reductions of 25-50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling. [ABSTRACT FROM AUTHOR]

Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data--model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills. [ABSTRACT FROM AUTHOR]

Improving systematic observations of land cover, as an Essential Climate Variable, should contribute to a better understanding of the global climate system and thus improve our ability to predict climatic change. The aim of this paper is to bring global land cover observations closer to meeting the needs of climate science. First, consultation mechanisms were established with the climate modeling community to identify its specific requirements in terms of satellite-based global land cover products. This assessment highlighted specific needs in terms of land cover characterization, accuracy of products, as well as stability and consistency needs that are currently not met or even addressed. The current land cover representation and mapping techniques were then called into question to specifically focus on the critical need of stable products expressed by climate users. Decoupling the stable and dynamic components of the land cover characterization and using a multi-year dataset were proposed as two key approaches to allow generating consistent suites of global land cover products over time. [ABSTRACT FROM AUTHOR]

Time series of vegetation indices (VI) derived from satellite imagery provide a consistent monitoring system for terrestrial plant productivity. They enable detection and quantification of gradual changes within the time frame covered, which are of crucial importance in global change studies, for example. However, VI time series typically contain a strong seasonal signal which complicates change detection. Commonly, trends are quantified using linear regression methods, while the effect of serial autocorrelation is remediated by temporal aggregation over bins having a fixed width. Aggregating the data in this way produces temporal units which are modifiable. Analogous to the well-known Modifiable Area Unit Problem (MAUP), the way in which these temporal units are defined may influence the fitted model parameters and therefore the amount of change detected. This paper illustrates the effect of this Modifiable Temporal Unit Problem (MTUP) on a synthetic data set and a real VI data set. Large variation in detected changes was found for aggregation over bins that mismatched full lengths of vegetative cycles, which demonstrates that aperiodicity in the data may influence model results. Using 26 yr of VI data and aggregation over full-length periods, deviations in VI gains of less than 1% were found for annual periods (with respect to seasonally adjusted data), while deviations increased up to 24% for aggregation windows of 5 yr. This demonstrates that temporal aggregation needs to be carried out with care in order to avoid spurious model results. [ABSTRACT FROM AUTHOR]

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE <0.08; r² > 0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons. [ABSTRACT FROM AUTHOR]

Climate warming is amplified in the land-sea system of the East Siberian Arctic, which also holds large pools of vulnerable carbon in permafrost. This coastal area is strongly influenced by sediment and carbon transport from both its large rivers and extensive erosion of Pleistocene permafrost along its coastline. This study is investigating the coastal fate of the sediment and organic carbon delivered to the Buor-Khaya Gulf, which is the first recipient of the over-whelming fluvial discharge from the Lena River and is additionally receiving large input from extensive erosion of the coastal ice-complex (permafrost a.k.a. Yedoma; loess soil with high organic carbon content). Both water column suspended particulate matter (SPM) and surface sediments were sampled at about 250 oceanographic stations in the Gulf in this multi-year effort, including one winter campaign, and analyzed for the distribution and sorting of sediment size, organic carbon content, and stable carbon isotope signals. The composition of the surface sediment suggests an overwhelmingly terrestrial contribution from both river and coastal erosion. The objective of this paper is to improve our understanding of the seasonal (i.e., winter vs summer) and interannual variability of these coastal sedimentation processes and the dynamics of organic carbon (OC) distribution in both the water column SPM and the surface sediments of the Buor-Khaya Gulf. Based on data collected during several years in the period 2000--2008, two different sedimentation regimes were revealed for the Buor-Khaya Gulf, the relative importance of each at a given time depend on hydrometeorological conditions, the Lena River water discharge and sea-ice regime: Type 1 erosion-accumulation and Type 2 accumulation. The Type 1 erosion-accumulation sedimentation regime is typical (2000--2006) for the ice-free period of the year (here considered in detail for August 2005). Under such conditions terrigenous sources of SPM and particulate organic carbon (POC) stem predominantly from river discharge, thermal erosion of coastal ice-complex and remobilized bottom sediments. The Type 2 accumulation sedimentation regime develops under ice-covered conditions, and only occasionally during the ice-free period (August 2008). In Type 2 winter, combined terrigenous and marine-biogenic SPM and POC sources are dominating due to relatively low overall terrigenous input (April 2007). In Type 2 summer, river alluvium becomes the major SPM and POC source (August 2008). The water column SPM and POC loadings vary by more than a factor of two between the two regimes. This study underscores the necessity of multi-year investigations to better understand the functioning of the primary recipient of terrestrially expulsed matter in the East Siberian Arctic. [ABSTRACT FROM AUTHOR]

The global geographic distribution of biodiversity and biomes is determined by species-specific physiological tolerances to climatic constraints. Current vegetation models employ empirical bioclimatic relationships to predict present-day vegetation patterns and to forecast biodiversity changes and biome shifts under climatic change. In this paper, we consider trade-offs in plant functioning and their responses under climatic changes to forecast and explain changes in plant functional richness and shifts in biome geographic distributions. The Jena Diversity model (JeDi) simulates plant survival according to essential plant functional trade-offs, including ecophysiological processes such as water uptake, photosynthesis, allocation, reproduction and phenology. We use JeDi to quantify changes in plant functional richness and biome shifts between present-day and a range of possible future climates from two SRES emission scenarios (A2 and B1) and seven global climate models using metrics of plant functional richness and functional identity. Our results show (i) a significant loss of plant functional richness in the tropics, (ii) an increase in plant functional richness at mid and high latitudes, and (iii) a pole-ward shift of biomes. While these results are consistent with the findings of empirical approaches, we are able to explain them in terms of the plant functional trade-offs involved in the allocation, metabolic and reproduction strategies of plants. We conclude that general aspects of plant physiological tolerances can be derived from functional trade-offs, which may provide a useful process- and trait-based alternative to bioclimatic relationships. Such a mechanistic approach may be particularly relevant when addressing vegetation responses to climatic changes that encounter novel combinations of climate parameters that do not exist under contemporary climate. [ABSTRACT FROM AUTHOR]

The Peru Chile Current ecosystem is characterized by high biological productivity and important fisheries. Although this system is likely to be severely affected by climate change, its response to current global warming is still uncertain. In this paper, we analyze 10-166 year-old sediments in two cores collected from Mejillones Bay, an anoxic sedimentary setting favorable for the preservation of proxies. Based on a 166-year chronology, we used proxies of bottom-water oxygenation (Mo, V, S, and the (lycopane+n-C35)/n-C31 ratio) and surface water productivity (biogenic opal, counts of diatom valves, biogenic Ba, organic carbon, and chlorins) to reconstruct environmental variations in Mejillones Bay. During the last two centuries, a shift took place in the coastal marine ecosystem of Bahia Mejillones at decadal scales. This shift was characterized by intense ENSO-like activity, large-scale fluctuations in biological export productivity and bottom water oxygenation, and increased eolian activity (inferred from Ti/Al and Zr/Al). This short-term variability was accompanied by a gradual increase of sulfidic conditions that has intensified since the early 1960s. [ABSTRACT FROM AUTHOR]

Forested tropical peatlands in Southeast Asia store at least 42 000 Million metric tonnes (Mt) of soil carbon. Human activity and climate change threatens the stability of this large pool, which has been decreasing rapidly over the last few decades owing to deforestation, drainage and fire. In this paper we estimate the carbon dioxide (CO2) emissions resulting from drainage of lowland tropical peatland for agricultural and forestry development which dominates the perturbation of the carbon balance in the region. Present and future emissions from drained peatlands are quantified using data on peatland extent and peat thickness, present and projected land use, water management practices and decomposition rates. Of the 27.1 Million hectares (Mha) of peatland in Southeast Asia, 12.9 Mha had been deforested and mostly drained by 2006. This latter area is increasing rapidly because of increasing land development pressures. Carbon dioxide (CO2) emission caused by decomposition of drained peatlands was between 355 Mt y-1 and 855 Mt y-1 in 2006 of which 82% came from Indonesia, largely Sumatra and Kalimantan. At a global scale, CO2 emission from peatland drainage in Southeast Asia is contributing the equivalent of 1.3% to 3.1% of current global CO2 emissions from the combustion of fossil fuel. If current peatland development and management practices continue, these emissions are predicted to continue for decades. This warrants inclusion of tropical peatland CO2 emissions in global greenhouse gas emission calculations and climate mitigation policies. Uncertainties in emission calculations are discussed and research needs for improved estimates are identified. [ABSTRACT FROM AUTHOR]

Estimating carbon exchange at regional scales is paramount to understanding feedbacks between climate and the carbon cycle, but also to verifying climate change mitigation such as emission reductions and strategies compensating for emissions such as carbon sequestration. This paper discusses evidence for a number of important shortcomings of current generation modelling frameworks designed to provide regional scale budgets from atmospheric observations. Current top-down and bottom-up approaches targeted at deriving consistent regional scale carbon exchange estimates for biospheric and anthropogenic sources and sinks are hampered by a number of issues: we show that top-down constraints using point measurements made from tall towers, although sensitive to larger spatial scales, are however influenced by local areas much more strongly than previously thought. On the other hand, classical bottom-up approaches using process information collected at the local scale, such as from eddy covariance data, need up-scaling and validation on larger scales. We therefore argue for a combination of both approaches, implicitly providing the important local scale information for the top-down constraint, and providing the atmospheric constraint for up-scaling of flux measurements. Combining these data streams necessitates quantifying their respective representation errors, which are discussed. The impact of these findings on future network design is highlighted, and some recommendations are given. [ABSTRACT FROM AUTHOR]

Africa is the single largest continental source of biomass burning emissions. Here we conduct the first analysis of one full year of geostationary active fire detections and fire radiative power data recorded over Africa at 15-mm temporal interval and a 3 km sub-satellite spatial resolution by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) imaging radiometer onboard the Meteosat-8 satellite. We use these data to provide new insights into the rates and totals of open biomass burning over Africa, particularly into the extremely strong seasonal and diurnal cycles that exist across the continent. We estimate peak daily biomass combustion totals to be 9 and 6 million tonnes of fuel per day in the northern and southern hemispheres respectively, and total fuel consumption between February 2004 and January 2005 is estimated to be at least 855 million tonnes. Analysis is carried out with regard to fire pixel temporal persistence, and we note that the majority of African fires are detected only once in consecutive 15 mm imaging slots. An investigation of the variability of the diurnal fire cycle is carried out with respect to 20 different land cover types, and whilst differences are noted between land covers, the fire diurnal cycle characteristics for most land cover type are very similar in both African hemispheres. We compare the Fire Radiative Power (FRP) derived biomass combustion estimates to burned-areas, both at the scale of individual fires and over the entire continent at a 1-degree scale. Fuel consumption estimates are found to be less than 2 kg/m² for all land cover types noted to be subject to significant fire activity, and for savanna grasslands where literature values are commonly reported the FRP-derived median fuel consumption estimate of 300 g/m² is well within commonly quoted values. Meteosat-derived FRP data of the type presented here is now available freely to interested users continuously and in near real-time for Africa, Europe and parts of South America via the EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) Land Surface Analysis Satellite Applications Facility (http://landsaf.meteo.ptl). Continuous generation of these products will allow the types of analysis presented in this paper to be improved and extended, and such multi-year records should allow relationships between climate, fire and fuel to be further examined. [ABSTRACT FROM AUTHOR]

The interest in bioaerosols has traditionally been linked to health hazards for humans, animals and plants. However, several components of bioaerosols exhibit physical properties of great significance for cloud processes, such as ice nucleation and cloud condensation. To gain a better understanding of their influence on climate, it is therefore important to determine the composition, concentration, seasonal fluctuation, regional diversity and evolution of bioaerosols. In this paper, we will review briefly the existing techniques for detection, quantification, physical and chemical analysis of biological particles, attempting to bridge physical, chemical and biological methods for analysis of biological particles and integrate them with aerosol sampling techniques. We will also explore some emerging spectroscopy techniques for bulk and single-particle analysis that have potential for in-situ physical and chemical analysis. Lastly, we will outline open questions and further desired capabilities (e.g.. in-situ, sensitive, both broad and selective, on-line, time-resolved, rapid, versatile, cost-effective techniques) required prior to comprehensive understanding of chemical and physical characterization of bioaerosols. [ABSTRACT FROM AUTHOR]