Recent decline in tropical temperature sensitivity of atmospheric CO2 growth rate variability

A two-fold enhancement in the sensitivity of atmospheric CO2 growth rate (CGR) to tropical temperature interannual variability (Γ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ ) till early 2000s has been reported, which suggests a drought-induced shift in terrestrial carbon cycle responding temperature fluctuations, thereby accelerating global warming. However, using six decades long atmospheric CO2 observations, we show thatΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ has significantly declined in the last two decades, to the level during the 1960s. TheΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline begs the question of whether the sensitivity of ecosystem carbon cycle to temperature variations at local scale has largely decreased. With state-of-the-art dynamic global vegetation models, we further find that the recentΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline is barely attributed to ecosystem carbon cycle response to temperature fluctuations at local scale, which instead results from a decrease in spatial coherence in tropical temperature variability and land use change. Our results suggest that the recently reported loss of rainforest resilience has not shown marked influence on the temperature sensitivity of ecosystem carbon cycle. Nevertheless, the increasing extent of land use change as well as more frequent and intensive drought events are likely to modulate the responses of ecosystem carbon cycle to temperature variations in the future. Therefore, our study highlights the priority to continuously monitor the temperature sensitivity of CGR variability and improve Earth system model representation on land use change, in order to predict the carbon-climate feedback.

Temperature dependence of spring carbon uptake in northern high latitudes during the past four decades

In the northern high latitudes, warmer spring temperatures generally lead to earlier leaf onsets, higher vegetation production, and enhanced spring carbon uptake. Yet, whether this positive linkage has diminished under climate change remains debated. Here, we used atmospheric CO2 measurements at Barrow (Alaska) during 1979-2020 to investigate the strength of temperature dependence of spring carbon uptake reflected by two indicators, spring zero-crossing date (SZC) and CO2 drawdown (SCC). We found a fall and rise in the interannual correlation of temperature with SZC and SCC (RSZC-T and RSCC-T ), showing a recent reversal of the previously reported weakening trend of RSZC-T and RSCC-T . We used a terrestrial biosphere model coupled with an atmospheric transport model to reproduce this fall and rise phenomenon and conducted factorial simulations to explore its potential causes. We found that a strong-weak-strong spatial synchrony of spring temperature anomalies per se has contributed to the fall and rise trend in RSZC-T and RSCC-T , despite an overall unbroken temperature control on net ecosystem CO2 fluxes at local scale. Our results provide an alternative explanation for the apparent drop of RSZC-T and RSCC-T during the late 1990s and 2000s, and suggest a continued positive linkage between spring carbon uptake and temperature during the past four decades. We thus caution the interpretation of apparent climate sensitivities of carbon cycle retrieved from spatially aggregated signals.

Interannual variability of air-water CO2 flux in a large eutrophic estuary

Air-water CO2 fluxes in estuarine environments are characterized by high interannual variability, in part due to hydrological variability that alters estuarine carbonate chemistry through multiple physical and biogeochemical processes. To understand the relative contributions of these varied controls on interannual air-water CO2 fluxes in the mainstem Chesapeake Bay, we implemented both hindcast and scenario simulations using a coupled physical-biogeochemical model. Significant spatiotemporal variability in bay-wide fluxes was found over a 10-year period (1996-2005), where the mainstem Bay was primarily a net CO2 sink, except in drought periods. Sensitivity scenario results suggested substantial effects of riverine nutrient and organic matter (OM) inputs to CO2 flux variations. The high correlations between riverine inputs and upper-Bay fluxes were due to elevated respiration under increased OM inputs. The interannual flux variations in the lower Bay was mostly regulated by the nutrient inputs. Both nutrient and OM inputs contributed to the flux variability in the mid Bay. It is found that the interannual CO2 flux of the mainstem was most sensitive to riverine nutrient inputs associated with the hydrological changes. For each hindcast simulation we computed the ratio of organic carbon turnover time to water residence time (λ), a proxy for CO2 efflux potential, and found that the wetter periods had a relatively lower λ. The variability of mainstem CO2 fluxes can be well represented using a generic function of λ. The model results showed that higher river flows would lead to enhanced CO2 sinks into a large eutrophic estuary by promoting net autotrophy.

Disorder or a new order: How climate change affects phenological variability

Advancing spring phenology is a well documented consequence of anthropogenic climate change, but it is not well understood how climate change will affect the variability of phenology year to year. Species' phenological timings reflect the adaptation to a broad suite of abiotic needs (e.g., thermal energy) and biotic interactions (e.g., predation and pollination), and changes in patterns of variability may disrupt those adaptations and interactions. Here, we present a geographically and taxonomically broad analysis of phenological shifts, temperature sensitivity, and changes in interannual variability encompassing nearly 10,000 long-term phenology time series representing more than 1000 species across much of the Northern Hemisphere. We show that the timings of leaf-out, flowering, insect first-occurrence, and bird arrival were the most sensitive to temperature variation and have advanced at the fastest pace for early-season species in colder and less seasonal regions. We did not find evidence for changing variability in warmer years in any phenophase groups, although leaf-out and flower phenology have become moderately but significantly less variable over time. Our findings suggest that climate change has not to this point fundamentally altered the patterns of interannual phenological variability.

Intra-Decadal (2012-2021) Dynamics of Spatial Ichthyoplankton Distribution in Sevastopol Bay (Black Sea) Affected by Hydrometeorological Factors

High mortality of fish in the early stages of ontogenesis requires the detection of factors affecting it and is an extremely important problem. For this reason, we tried to consider the influence of some hydrometeorological factors on the intra-decadal dynamics and spatial distribution of ichthyoplankton abundance in Sevastopol Bay. To this end, we analyzed ichthyoplankton samples collected in 2012−2021 in Sevastopol Bay, and the four districts were identified. The ichthyoplankton distribution by areas was associated with the peculiarities of the pollution distribution. The maximum numbers in eggs (34.7 ± 7.5 ind. m−2) and larvae (10.0 ± 2.4 ind. m−2) were recorded in July−August. For the first time, a positive effect of temperature and repeatability of north and northeast winds on the ichthyoplankton number during the summer spawning in all identified areas of Sevastopol Bay using principal component analysis (PCA) was reported. In the southern region, positive influence of temperature and northerly winds on the ichthyoplankton abundance was confirmed by ANOVA (p = 0.02), and Pearson’s correlation analysis revealed significant correlations between these parameters on inter-annual scale (r > 0.5). In the eastern area, the discharge of rivers is an additional factor affecting the abundance of ichthyoplankton, while in the western and central areas, these factors were the wind characteristics caused by the orography peculiarities. The pollution spread in Sevastopol Bay is also largely due to the wind regime. The importance of comprehensive monitoring studies using intra-decadal data on ichthyoplankton is emphasized.

Global trends in grassland carrying capacity and relative stocking density of livestock

Although the role of livestock in future food systems is debated, animal proteins are unlikely to completely disappear from our diet. Grasslands are a key source of primary productivity for livestock, and feed-food competition is often limited on such land. Previous research on the potential for sustainable grazing has focused on restricted geographical areas or does not consider inter-annual changes in grazing opportunities. Here, we developed a robust method to estimate trends and interannual variability (IV) in global livestock carrying capacity (number of grazing animals a piece of land can support) over 2001-2015, as well as relative stocking density (the reported livestock distribution relative to the estimated carrying capacity [CC]) in 2010. We first estimated the aboveground biomass that is available for grazers on global grasslands based on the MODIS Net Primary Production product. This was then used to calculate livestock carrying capacities using slopes, forest cover, and animal forage requirements as restrictions. We found that globally, CC decreased on 27% of total grasslands area, mostly in Europe and southeastern Brazil, while it increased on 15% of grasslands, particularly in Sudano-Sahel and some parts of South America. In 2010, livestock forage requirements exceeded forage availability in northwestern Europe, and southern and eastern Asia. Although our findings imply some opportunities to increase grazing pressures in cold regions, Central Africa, and Australia, the high IV or low biomass supply might prevent considerable increases in stocking densities. The approach and derived open access data sets can feed into global food system modelling, support conservation efforts to reduce land degradation associated with overgrazing, and help identify undergrazed areas for targeted sustainable intensification efforts or rewilding purposes.

Successive extreme climatic events lead to immediate, large-scale, and diverse responses from fish in the Arctic

The warming trend of the Arctic is punctuated by several record-breaking warm years with very low sea ice concentrations. The nature and reversibility of marine ecosystem responses to these multiple extreme climatic events (ECEs) are poorly understood. Here, we investigate the ecological signatures of three successive bottom temperature maxima concomitant with surface ECEs between 2004 and 2017 in the Barents Sea across spatial and organizational scales. We observed community-level redistributions of fish concurrent with ECEs at the scale of the whole Barents Sea. Three groups, characterized by different sets of traits describing their capacity to cope with short-term perturbations, reacted with different timing and intensity to each ECE. Arctic species co-occurred more frequently with large predators and incoming boreal taxa during ECEs, potentially affecting food web structures and functional diversity, accelerating the impacts of long-term climate change. On the species level, responses were highly diversified, with different ECEs impacting different species, and species responses (expansion, geographical shift) varying from one ECE to another, despite the environmental perturbations being similar. Past ECEs impacts, with potential legacy effects, lagged responses, thresholds, and interactions with the underlying warming pressure, could constantly set up new initial conditions that drive the unique ecological signature of each ECE. These results highlight the complexity of ecological reactions to multiple ECEs and give prominence to several sources of process uncertainty in the predictions of climate change impact and risk for ecosystem management. Long-term monitoring and studies to characterize the vertical extent of each ECE are necessary to statistically link demersal species and environmental spatial-temporal patterns. In the future, regular monitoring will be crucial to detect early signals of change and understand the determinism of ECEs, but we need to adapt our models and management to better integrate risk and stochasticity from the complex impacts of global change.

Multiscale Temporal Variations of Atmospheric Mercury Distinguished by the Hilbert-Huang Transform Analysis Reveals Multiple El Niño-Southern Oscillation Links

Atmospheric mercury (Hg) cycling is sensitive to climate-driven changes, but links with various teleconnections remain unestablished. Here, we revealed the El Niño-Southern Oscillation (ENSO) influence on gaseous elemental mercury (GEM) concentrations recorded at a background station in East Asia using the Hilbert-Huang transform (HHT). The timing and magnitude of GEM intrinsic variations were clearly distinguished by ensemble empirical mode decomposition (EEMD), revealing the amplitude of the GEM concentration interannual variability (IAV) is greater than that for diurnal and seasonal variability. We show that changes in the annual cycle of GEM were modulated by significant IAVs at time scales of 2-7 years, highlighted by a robust GEM IAV-ENSO relationship of the associated intrinsic mode functions. With confirmation that ENSO modulates the GEM annual cycle, we then found that weaker GEM annual cycles may have resulted from El Niño-accelerated Hg evasion from the ocean. Furthermore, the relationship between ENSO and GEM is sensitive to extreme events (i.e., 2015-2016 El Niño), resulting in perturbation of the long-term trend and atmospheric Hg cycling. Future climate change will likely increase the number of extreme El Niño events and, hence, could alter atmospheric Hg cycling and influence the effectiveness evaluation of the Minamata Convention on Mercury.

Spatial distribution and interannual variability of cyanobacteria blooms on the North-Western shelf of the Black Sea in 1985-2019 from satellite data

Long-term high and medium resolution satellite data are used to study spatial, seasonal and interannual variability of the cyanobacteria blooms (CB) in the North-Western Shelf (NWS) of the Black Sea. High-resolution Landsat data demonstrate that CB were regularly observed in the study area on satellite images in 1985-2020. Comparison of quasi-synchronous Landsat and MODIS images was used to study the characteristic features of CB spectra, which are: a "step" formed by MODIS 3 (469) and 4 (488) channel, probably related to the absorption by photoprotective carotenoids; increased reflectance in near-infrared; maximum at 547-555 nm. On the base of these features, we develop the automated algorithm of CB identification and reconstruct the daily dataset of CB over 2003-2019. The main advantage of the developed algorithm is its ability to filter out non-bloom areas in all seasons and meteorological conditions and during blooms of other algae in the deep part of the sea. Analysis of this dataset, complemented by Landsat data, allows to identify two primary sources of the CB in the NWS: the Dnieper-Bug estuary and the Danube mouth, and study the evolution of CB in these areas in detail. CB can penetrate on more than 150 km from the sources reaching in rare cases the Crimean coast. Such offshore propagation is mainly wind-driven and was often related to the upwelling frontal currents. The climatic seasonal peak of CB near the Danube is observed in May-June following the peak of river discharge in April-May. It precedes the peak of CB near the Dnieper-Bug estuary observed during maximum surface heating in August. At the same time, the case study of bloom evolution in 2009 shows that CB can be observed in these areas several times in a season, triggered mainly by periods of low winds. The strongest bloom of CB in 2003-2019 was observed in 2004-2006 and 2008-2010 following by the sharp decrease after 2011. This decrease is related to the observed reduction of the river discharge and, more important, the rise of the wind intensity in summers of the recent period.

Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2)

Earth system models are intended to make long-term projections, but they can be evaluated at interannual and seasonal time scales. Although the Community Earth System Model (CESM2) showed improvements in a number of terrestrial carbon cycle benchmarks, relative to its predecessor, our analysis suggests that the interannual variability (IAV) in net terrestrial carbon fluxes did not show similar improvements. The model simulated low IAV of net ecosystem production (NEP), resulting in a weaker than observed sensitivity of the carbon cycle to climate variability. Low IAV in net fluxes likely resulted from low variability in gross primary productivity (GPP)-especially in the tropics-and a high covariation between GPP and ecosystem respiration. Although lower than observed, the IAV of NEP had significant climate sensitivities, with positive NEP anomalies associated with warmer and drier conditions in high latitudes, and with wetter and cooler conditions in mid and low latitudes. We identified two dominant modes of seasonal variability in carbon cycle flux anomalies in our fully coupled CESM2 simulations that are characterized by seasonal amplification and redistribution of ecosystem fluxes. Seasonal amplification of net and gross carbon fluxes showed climate sensitivities mirroring those of annual fluxes. Seasonal redistribution of carbon fluxes is initiated by springtime temperature anomalies, but subsequently negative feedbacks in soil moisture during the summer and fall result in net annual carbon losses from land. These modes of variability are also seen in satellite proxies of GPP, suggesting that CESM2 appropriately represents regional sensitivities of photosynthesis to climate variability on seasonal time scales.

Reproductive traits and population dynamics of benthic invertebrates indicate episodic recruitment patterns across an Arctic polar front

Climate-induced changes in the ocean and sea ice environment of the Arctic are beginning to generate major and rapid changes in Arctic ecosystems, but the effects of directional forcing on the persistence and distribution of species remain poorly understood. Here, we examine the reproductive traits and population dynamics of the bivalve Astarte crenata and sea star Ctenodiscus crispatus across a north-south transect that intersects the polar front in the Barents Sea. Both species present large oocytes indicative of short pelagic or direct development that do not differ in size-frequency between 74.5 and 81.3º latitude. However, despite gametogenic maturity, we found low frequencies of certain size classes within populations that may indicate periodic recruitment failure. We suggest that recruitment of A. crenata could occur periodically when conditions are favorable, while populations of C. crispatus are characterized by episodic recruitment failures. Pyloric caeca indices in C. crispatus show that food uptake is greatest at, and north of, the polar front, providing credence to the view that interannual variations in the quantity and quality of primary production and its flux to the seafloor, linked to the variable extent and thickness of sea ice, are likely to be strong determinants of physiological fitness. Our findings provide evidence that the distribution and long-term survival of species is not only a simple function of adaptive capacity to specific environmental changes, but will also be contingent on the frequency and occurrence of years where environmental conditions support reproduction and settlement.

Interannual Variability of Air-Sea Exchange of Mercury in the Global Ocean: The "Seesaw Effect" in the Equatorial Pacific and Contributions to the Atmosphere

Air-sea exchange of gaseous elemental mercury (Hg(0)) is influenced by different meteorological factors and the availability of Hg in seawater. Here, we use the MITgcm ocean model to explore the interannual variability of this flux and the influence of oceanographic and atmospheric dynamics. We apply the GEOS-Chem model to further simulate the potential impact of the evasion variability on the atmospheric Hg levels. We find a latitudinal pattern in Hg(0) evasion with a relatively small variability in mid-latitudes (3.1-6.7%) and a large one in the high latitudes and Equator (>10%). Different factors dominate the patterns in the equatorial (wind speed), mid- (oceanic flow and temperature), and high-latitudinal (sea-ice, temperature, and dynamic processes) oceans. A seesaw pattern of Hg(0) evasion anomaly (±5-20%) in the equatorial Pacific is found from November to next January between El Niño and La Niña years, owing to the anomalies in wind speed, temperature, and vertical mixing. Higher atmospheric Hg level (2%-5%) are simulated for Hg(0) evasion fluxes with three-month lag, associated with the suppression of upwelling in the beginning of the El Niño event. Despite of the uncertainties, this study elucidates the spatial patterns of the interannual variability of the ocean Hg(0) evasion flux and its potential impact on atmospheric Hg levels.

Wind and Solar Resource Droughts in California Highlight the Benefits of Long-Term Storage and Integration with the Western Interconnect

As reliance on wind and solar power for electricity generation increases, so does the importance of understanding how variability in these resources affects the feasible, cost-effective ways of supplying energy services. We use hourly weather data over multiple decades and historical electricity demand data to analyze the gaps between wind and solar supply and electricity demand for California (CA) and the Western Interconnect (WECC). We quantify the occurrence of resource droughts when the daily power from each resource was less than half of the 39-year daily mean for that day of the year. Averaged over 39 years, CA experienced 6.6 days of solar and 48 days of wind drought per year, compared to 0.41 and 19 for WECC. Using a macro-scale electricity model, we evaluate the potential for both long-term storage and more geographically diverse generation resources to minimize system costs. For wind-solar-battery electricity systems, meeting California demand with WECC generation resources reduces the cost by 9% compared to constraining resources entirely to California. Adding long-duration storage lowers system costs by 21% when treating California as an island. This data-driven analysis quantifies rare weather-related events and provides an understanding that can be used to inform stakeholders in future electricity systems.

Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness

●Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (Ψ_L ). However, how iso/anisohydry changes over time in response to year-to-year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. ●We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem-level analysis was further complemented with published field observations of species-level Ψ_L . ●We found different behaviors in the directionality and sensitivity of isohydricity (σ) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, σ decreases in drier years with a higher sensitivity to dryness; in xeric ecosystems, σ increases in drier years with a lower sensitivity to dryness. These results were supported by the species-level synthesis. ●Our study suggests that how plants adjust their water use across years - as revealed by their interannual variability in isohydricity - depends on the dryness of plants' living environment. This finding advances our understanding of plant responses to drought at regional scales.

Climate-Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products

Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation-based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS-LUE), and from a suite of terrestrial biosphere models (TRENDYv6). At local scales, we find high correlations in annual GPP among the products, with exceptions in tropical and high northern latitudes. On longer time scales, the products agree on the direction of trends over 58% of the land, with large increases across northern latitudes driven by warming trends. Further, tropical regions exhibit the largest interannual variability in GPP, with both rainforests and savannas contributing substantially. Variability in savanna GPP is likely predominantly driven by water availability, although temperature could play a role via soil moisture-atmosphere feedbacks. There is, however, no consensus on the magnitude and driver of variability of tropical forests, which suggest uncertainties in process representations and underlying observations remain. These results emphasize the need for more direct long-term observations of GPP along with an extension of in situ networks in underrepresented regions (e.g., tropical forests). Such capabilities would support efforts to better validate relevant processes in models, to more accurately estimate GPP.

Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East-West Divide of Temperate North America

Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010-2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.

The European carbon cycle response to heat and drought as seen from atmospheric CO2 data for 1999-2018

In 2018, central and northern parts of Europe experienced heat and drought conditions over many months from spring to autumn, strongly affecting both natural ecosystems and crops. Besides their impact on nature and society, events like this can be used to study the impact of climate variations on the terrestrial carbon cycle, which is an important determinant of the future climate trajectory. Here, variations in the regional net ecosystem exchange (NEE) of CO₂ between terrestrial ecosystems and the atmosphere were quantified from measurements of atmospheric CO₂ mole fractions. Over Europe, several observational records have been maintained since at least 1999, giving us the opportunity to assess the 2018 anomaly in the context of at least two decades of variations, including the strong climate anomaly in 2003. In addition to an atmospheric inversion with temporally explicitly estimated anomalies, we use an inversion based on empirical statistical relations between anomalies in the local NEE and anomalies in local climate conditions. For our analysis period 1999–2018, we find that higher-than-usual NEE in hot and dry summers may tend to arise in Central Europe from enhanced ecosystem respiration due to the elevated temperatures, and in Southern Europe from reduced photosynthesis due to the reduced water availability. Despite concerns in the literature, the level of agreement between regression-based NEE anomalies and temporally explicitly estimated anomalies indicates that the atmospheric CO₂ measurements from the relatively dense European station network do provide information about the year-to-year variations of Europe’s carbon sources and sinks, at least in summer.

This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.

Changes in the Arctic Ocean Carbon Cycle With Diminishing Ice Cover

Less than three decades ago only a small fraction of the Arctic Ocean (AO) was ice free and then only for short periods. The ice cover kept sea surface pCO2 at levels lower relative to other ocean basins that have been exposed year round to ever increasing atmospheric levels. In this study, we evaluate sea surface pCO2 measurements collected over a 6-year period along a fixed cruise track in the Canada Basin. The measurements show that mean pCO2 levels are significantly higher during low ice years. The pCO2 increase is likely driven by ocean surface heating and uptake of atmospheric CO2 with large interannual variability in the contributions of these processes. These findings suggest that increased ice-free periods will further increase sea surface pCO2, reducing the Canada Basin's current role as a net sink of atmospheric CO2.

Interannual variation of terrestrial carbon cycle: Issues and perspectives

With accumulation of carbon cycle observations and model developments over the past decades, exploring interannual variation (IAV) of terrestrial carbon cycle offers the opportunity to better understand climate-carbon cycle relationships. However, despite growing research interest, uncertainties remain on some fundamental issues, such as the contributions of different regions, constituent fluxes and climatic factors to carbon cycle IAV. Here we overviewed the literature on carbon cycle IAV about current understanding of these issues. Observations and models of the carbon cycle unanimously show the dominance of tropical land ecosystems to the signal of global carbon cycle IAV, where tropical semiarid ecosystems contribute as much as the combination of all other tropical ecosystems. Vegetation photosynthesis contributes more than ecosystem respiration to IAV of the global net land carbon flux, but large uncertainties remain on the contribution of fires and other disturbance fluxes. Climatic variations are the major drivers to the IAV of net land carbon flux. Although debate remains on whether the dominant driver is temperature or moisture variability, their interaction,that is, the dependence of carbon cycle sensitivity to temperature on moisture conditions, is emerging as key regulators of the carbon cycle IAV. On timescales from the interannual to the centennial, global carbon cycle variability will be increasingly contributed by northern land ecosystems and oceans. Therefore, both improving Earth system models (ESMs) with the progressive understanding on the fast processes manifested at interannual timescale and expanding carbon cycle observations at broader spatial and longer temporal scales are critical to better prediction on evolution of the carbon-climate system.

Solar-wind-magnetosphere energy influences the interannual variability of the northern-hemispheric winter climate

Solar irradiance has been universally acknowledged to be dominant by quasi-decadal variability, which has been adopted frequently to investigate its effect on climate decadal variability. As one major terrestrial energy source, solar-wind energy flux into Earth's magnetosphere (E_in) exhibits dramatic interannual variation, the effect of which on Earth's climate, however, has not drawn much attention. Based on the E_in estimated by 3D magnetohydrodynamic simulations, we demonstrate a novelty that the annual mean E_in can explain up to 25% total interannual variance of the northern-hemispheric temperature in the subsequent boreal winter. The concurrent anomalous atmospheric circulation resembles the positive phase of Arctic Oscillation/North Atlantic Oscillation. The warm anomalies in the tropic stratopause and tropopause induced by increased solar-wind-magnetosphere energy persist into the subsequent winter. Due to the dominant change in the polar vortex and mid-latitude westerly in boreal winter, a 'top-down' propagation of the stationary planetary wave emerges in the Northern Hemisphere and further influences the atmospheric circulation and climate.

Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO₂ ) concentrations, but processes driving the IAV of net ecosystem CO₂ exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long-term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water-limited ecosystems versus temperature- and radiation-limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water-limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature- and radiation-limited ecosystems. The Lund-Potsdam-Jena (LPJ) model and the Multi-scale Synthesis and Terrestrial Model Inter-comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.

Effect of interannual precipitation variability on dryland productivity: A global synthesis

Climate-change assessments project increasing precipitation variability through increased frequency of extreme events. However, the effects of interannual precipitation variance per se on ecosystem functioning have been largely understudied. Here, we report on the effects of interannual precipitation variability on the primary production of global drylands, which include deserts, steppes, shrublands, grasslands, and prairies and cover about 40% of the terrestrial earth surface. We used a global database that has 43 datasets, which are uniformly distributed in parameter space and each has at least 10 years of data. We found (a) that at the global scale, precipitation variability has a negative effect on aboveground net primary production. (b) Expected increases in interannual precipitation variability for the year 2,100 may result in a decrease of up to 12% of the global terrestrial carbon sink. (c) The effect of precipitation interannual variability on dryland productivity changes from positive to negative along a precipitation gradient. Arid sites with mean precipitation under 300 mm/year responded positively to increases in precipitation variability, whereas sites with mean precipitation over 300 mm/year responded negatively. We propose three complementary mechanisms to explain this result: (a) concave-up and concave-down precipitation-production relationships in arid vs. humid systems, (b) shift in the distribution of water in the soil profile, and (c) altered frequency of positive and negative legacies. Our results demonstrated that enhanced precipitation variability will have direct impacts on global drylands that can potentially affect the future terrestrial carbon sink.

Influence of winter precipitation on spring phenology in boreal forests

Understanding the variations in spring vegetation phenology associated with preseason climate conditions can significantly improve our knowledge on ecosystem dynamics and biosphere-atmosphere interactions. Recent studies have shown that wet winters can delay the start date of the vegetation growing season (SOS) in the high latitudes. However, associated underlying mechanisms remain unclear due to the lack of observation sites as well as complex interactions between various climate and ecosystem variables. In this study, the impact of winter precipitation on year-to-year variations of the SOS in boreal forests from 1982 to 2005 was investigated. Two experiments were performed using the Community Land Model version 4.5. In the control experiment, observed precipitation was used; in the sensitivity experiment, precipitation in the year 1982 was repeated throughout the period. The SOS in the control experiment shows high temporal correlations with the SOS estimated from the satellite-retrieved leaf area index, indicating that the land model is capable of simulating realistic response of vegetation to interannual climate variability. The effects of winter precipitation on the SOS are examined by comparing the two model experiments for wet- and dry winters. After wet winters, the SOS was delayed by 2.7 days over 70.1% of the boreal forests than after dry winters; this accounts for 42.5% of the interannual variation in the SOS. The SOS delay is related to the decrease in the growing degree-days (GDD) based on soil temperatures, suggesting that the effects of heat exposure on vegetation growth is strongly modulated by winter precipitation. The GDD decrease is related to both the increase in snowmelt heat flux and reduced absorption of solar radiation, which are proportional to the amount of winter precipitation and the ratio of short plants to tall trees, respectively. Our results provide a physical basis for the winter precipitation-SOS relationship, suggesting that an increase in winter precipitation can alleviate strong advancing trends in spring vegetation growth in conjunction with global warming even for temperature-limited ecosystems.

Environmental Variability and Cyanobacterial Blooms in a Subtropical Coastal Lagoon: Searching for a Sign of Climate Change Effects

Cyanobacterial blooms in marine and freshwater environments may be favored by shifts in physical water column parameters due to warming under climate change. The Patos Lagoon (PL), a subtropical coastal environment in southern Brazil, is known for recurrent blooms of Microcystis aeruginosa complex (MAC). Here, we analyze the variability of these blooms and their relation to changes in wind direction and speed, rainfall and freshwater run-off from 2000 to 2017. Also, we discuss both longer time-series of air temperature and rainfall and a review of local studies with microcystins produced by these noxious species. Since the 1980s, MAC blooms were associated to negative anomalies in annual precipitation that occur during La Niña periods and, in the last years (2001-2014), accompanied by a trend in low river discharge. MAC blooms were conspicuous from December to March, i.e., austral summer, with massive patches seen in satellite images as for 2017. We suggest that low rainfall and run-off years under NE wind-driven hydrodynamics might accumulate MAC biomass in the west margin of the PL system. In contrast, a positive, long-term trend in precipitation (from 1950 to 2016; slope = 3.9868 mm/yr, p < 0.05) should imply in high river discharge and, consequently, advection of this biomass to the adjacent coastal region. Due to the proximity to urban areas, the blooms can represent recreational and economic hazards to the region.

[Analysis of Aerosol Optical Depth Variation Characteristics for 10 years in Urumqi Based on MODIS_C006]

Based on the MYD04_L2_C006 dataset gained from Moderate resolution imaging spectroradiometer MODIS Level 2 at 10 km resolution of NASA's EOS (Earth Observing System) from 2006 to 2015, the aerosol optical depths (AODs) for 10 years under the condition of mild above atmospheric pollution (including mild) were analyzed for Urumqi City. The results showed that the average AODs in Urumqi were unimodally distribution over the 10 years. From January to April, the AODs gradually increased. During a year, the annual peak of 0.37±0.19 was in April, and the lowest value of 0.22±0.20 was in October. Owing to the frequent occurrence of dust weather conditions in spring, the largest seasonal variation of AOD was in spring, as the air pollution in the entire area was very serious, followed by summer and winter, with the smallest in autumn. In addition, the urban area was the high AOD value area in Urumqi, as its air pollution was more severe than that in the suburbs. The average value of AOD during the 10 years was 0.293. The highest value of AOD was 0.33 in 2006, and the lowest value of 0.24 was in 2008, which declined to 23.3% of that in 2007. The annual change in AOD in Urumqi over the 10 years rose steadily. Compared with previous studies, the lowest and highest values were both higher to different degrees. Despite the deduction trend in 2015, air pollution in Urumqi was serious in the studied decade, and thus control of such needs to be strengthened.

Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.

Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years

The uncertainties of China's gross primary productivity (GPP) estimates by global data-oriented products and ecosystem models justify a development of high-resolution data-oriented GPP dataset over China. We applied a machine learning algorithm developing a new GPP dataset for China with 0.1° spatial resolution and monthly temporal frequency based on eddy flux measurements from 40 sites in China and surrounding countries, most of which have not been explored in previous global GPP datasets. According to our estimates, mean annual GPP over China is 6.62 ± 0.23 PgC/year during 1982-2015 with a clear gradient from southeast to northwest. The trend of GPP estimated by this study (0.020 ± 0.002 PgC/year² from 1982 to 2015) is almost two times of that estimated by the previous global dataset. The GPP increment is widely spread with 60% area showing significant increasing trend (p < .05), except for Inner Mongolia. Most ecosystem models overestimated the GPP magnitudes but underestimated the temporal trend of GPP. The monsoon affected eastern China, in particular the area surrounding Qinling Mountain, seems having larger contribution to interannual variability (IAV) of China's GPP than the semiarid northwestern China and Tibetan Plateau. At country scale, temperature is the dominant climatic driver for IAV of GPP. The area where IAV of GPP dominated by temperature is about 42%, while precipitation and solar radiation dominate 31% and 27% respectively over semiarid area and cold-wet area. Such spatial pattern was generally consistent with global GPP dataset, except over the Tibetan Plateau and northeastern forests, but not captured by most ecosystem models, highlighting future research needs to improve the modeling of ecosystem response to climate variations.

Sensitivity of marine protected area network connectivity to atmospheric variability

International efforts are underway to establish well-connected systems of marine protected areas (MPAs) covering at least 10% of the ocean by 2020. But the nature and dynamics of ocean ecosystem connectivity are poorly understood, with unresolved effects of climate variability. We used 40-year runs of a particle tracking model to examine the sensitivity of an MPA network for habitat-forming cold-water corals in the northeast Atlantic to changes in larval dispersal driven by atmospheric cycles and larval behaviour. Trajectories of Lophelia pertusa larvae were strongly correlated to the North Atlantic Oscillation (NAO), the dominant pattern of interannual atmospheric circulation variability over the northeast Atlantic. Variability in trajectories significantly altered network connectivity and source-sink dynamics, with positive phase NAO conditions producing a well-connected but asymmetrical network connected from west to east. Negative phase NAO produced reduced connectivity, but notably some larvae tracked westward-flowing currents towards coral populations on the mid-Atlantic ridge. Graph theoretical metrics demonstrate critical roles played by seamounts and offshore banks in larval supply and maintaining connectivity across the network. Larval longevity and behaviour mediated dispersal and connectivity, with shorter lived and passive larvae associated with reduced connectivity. We conclude that the existing MPA network is vulnerable to atmospheric-driven changes in ocean circulation.

Sensitivity of marine protected area network connectivity to atmospheric variability

International efforts are underway to establish well-connected systems of marine protected areas (MPAs) covering at least 10% of the ocean by 2020. But the nature and dynamics of ocean ecosystem connectivity are poorly understood, with unresolved effects of climate variability. We used 40-year runs of a particle tracking model to examine the sensitivity of an MPA network for habitat-forming cold-water corals in the northeast Atlantic to changes in larval dispersal driven by atmospheric cycles and larval behaviour. Trajectories of Lophelia pertusa larvae were strongly correlated to the North Atlantic Oscillation (NAO), the dominant pattern of interannual atmospheric circulation variability over the northeast Atlantic. Variability in trajectories significantly altered network connectivity and source-sink dynamics, with positive phase NAO conditions producing a well-connected but asymmetrical network connected from west to east. Negative phase NAO produced reduced connectivity, but notably some larvae tracked westward-flowing currents towards coral populations on the mid-Atlantic ridge. Graph theoretical metrics demonstrate critical roles played by seamounts and offshore banks in larval supply and maintaining connectivity across the network. Larval longevity and behaviour mediated dispersal and connectivity, with shorter lived and passive larvae associated with reduced connectivity. We conclude that the existing MPA network is vulnerable to atmospheric-driven changes in ocean circulation.

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra- and interspecific trait variation on ecosystem functioning.

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence of favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the "most active hours/days" (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.

Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest

Although the analysis of flux data has increased our understanding of the interannual variability of carbon inputs into forest ecosystems, we still know little about the determinants of wood growth. Here, we aimed to identify which drivers control the interannual variability of wood growth in a mesic temperate deciduous forest. We analysed a 9-yr time series of carbon fluxes and aboveground wood growth (AWG), reconstructed at a weekly time-scale through the combination of dendrometer and wood density data. Carbon inputs and AWG anomalies appeared to be uncorrelated from the seasonal to interannual scales. More than 90% of the interannual variability of AWG was explained by a combination of the growth intensity during a first 'critical period' of the wood growing season, occurring close to the seasonal maximum, and the timing of the first summer growth halt. Both atmospheric and soil water stress exerted a strong control on the interannual variability of AWG at the study site, despite its mesic conditions, whilst not affecting carbon inputs. Carbon sink activity, not carbon inputs, determined the interannual variations in wood growth at the study site. Our results provide a functional understanding of the dependence of radial growth on precipitation observed in dendrological studies.

Micrometeorological measurements over 3 years reveal differences in N2 O emissions between annual and perennial crops

Perennial crops can deliver a wide range of ecosystem services compared to annual crops. Some of these benefits are achieved by lengthening the growing season, which increases the period of crop water and nutrient uptake, pointing to a potential role for perennial systems to mitigate soil nitrous oxide (N2 O) emissions. Employing a micrometeorological method, we tested this hypothesis in a 3-year field experiment with a perennial grass-legume mixture and an annual corn monoculture. Given that N2 O emissions are strongly dependent on the method of fertilizer application, two manure application options commonly used by farmers for each crop were studied: injection vs. broadcast application for the perennial; fall vs. spring application for the annual. Across the 3 years, lower N2 O emissions (P < 0.001) were measured for the perennial compared to the annual crop, even though annual N2 O emissions increased tenfold for the perennial after ploughing. The percentage of N2 O lost per unit of fertilizer applied was 3.7, 3.1 and 1.3 times higher for the annual for each consecutive year. Differences in soil organic matter due to the contrasting root systems of these crops are probably a major factor behind the N2 O reduction. We found that a specific manure management practice can lead to increases or reductions in annual N2 O emissions depending on environmental variables. The number of freeze-thaw cycles during winter and the amount of rainfall after fertilization in spring were key factors. Therefore, general manure management recommendations should be avoided because interannual weather variability has the potential to determine if a specific practice is beneficial or detrimental. The lower N2 O emissions of perennial crops deserve further research attention and must be considered in future land-use decisions. Increasing the proportion of perennial crops in agricultural landscapes may provide an overlooked opportunity to regulate N2 O emissions.

The importance of rare, high-wind events for dust uplift in northern Africa

Dust uplift is a nonlinear thresholded function of wind speed and therefore particularly sensitive to the long tails of observed wind speed probability density functions. This suggests that a few rare high-wind events can contribute substantially to annual dust emission. Here we quantify the relative roles of different wind speeds to dust-generating winds using surface synoptic observations of dust emission and wind from northern Africa. The results show that winds between 2 and 5 m s^-1 above the threshold cause the most emission. Of the dust-generating winds, 25% is produced by very rare events occurring only at 0.1 to 1.4% of the time, depending on the region. Dust-producing winds are underestimated in ERA-I, since it misses the long tail found in observations. ERA-I overpredicts (underpredicts) the frequency of emission strength winds in the southern (northern) regions. These problems cannot be solved by simple tunings. Finally, we show that rare events make the largest contribution to interannual variability in dust-generating winds and that ERA severely underestimates this interannual variability.

Enhanced precipitation variability decreases grass- and increases shrub-productivity

Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plant-functional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society.

Chesapeake Bay nitrogen fluxes derived from a land-estuarine ocean biogeochemical modeling system: Model description, evaluation, and nitrogen budgets

The Chesapeake Bay plays an important role in transforming riverine nutrients before they are exported to the adjacent continental shelf. Although the mean nitrogen budget of the Chesapeake Bay has been previously estimated from observations, uncertainties associated with interannually varying hydrological conditions remain. In this study, a land-estuarine-ocean biogeochemical modeling system is developed to quantify Chesapeake riverine nitrogen inputs, within-estuary nitrogen transformation processes and the ultimate export of nitrogen to the coastal ocean. Model skill was evaluated using extensive in situ and satellite-derived data, and a simulation using environmental conditions for 2001-2005 was conducted to quantify the Chesapeake Bay nitrogen budget. The 5 year simulation was characterized by large riverine inputs of nitrogen (154 × 10⁹ g N yr^-1) split roughly 60:40 between inorganic:organic components. Much of this was denitrified (34 × 10⁹ g N yr^-1) and buried (46 × 10⁹ g N yr^-1) within the estuarine system. A positive net annual ecosystem production for the bay further contributed to a large advective export of organic nitrogen to the shelf (91 × 10⁹ g N yr^-1) and negligible inorganic nitrogen export. Interannual variability was strong, particularly for the riverine nitrogen fluxes. In years with higher than average riverine nitrogen inputs, most of this excess nitrogen (50-60%) was exported from the bay as organic nitrogen, with the remaining split between burial, denitrification, and inorganic export to the coastal ocean. In comparison to previous simulations using generic shelf biogeochemical model formulations inside the estuary, the estuarine biogeochemical model described here produced more realistic and significantly greater exports of organic nitrogen and lower exports of inorganic nitrogen to the shelf.

In silico system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management

Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work.

Autumn warming reduces the CO2 sink of a black spruce forest in interior Alaska based on a nine-year eddy covariance measurement

Nine years (2003-2011) of carbon dioxide (CO2) flux were measured at a black spruce forest in interior Alaska using the eddy covariance method. Seasonal and interannual variations in the gross primary productivity (GPP) and ecosystem respiration (RE) were associated primarily with air temperature: warmer conditions enhanced GPP and RE. Meanwhile, interannual variation in annual CO2 balance was controlled predominantly by RE, and not GPP. During these 9 years of measurement, the annual CO2 balance shifted from a CO2 sink to a CO2 source, with a 9-year average near zero. The increase in autumn RE was associated with autumn warming and was mostly attributed to a shift in the annual CO2 balance. The increase in autumn air temperature (0.22 °C yr(-1)) during the 9 years of study was 15 times greater than the long-term warming trend between 1905 and 2011 (0.015 °C yr(-1)) due to decadal climate oscillation. This result indicates that most of the shifts in observed CO2 fluxes were associated with decadal climate variability. Because the natural climate varies in a cycle of 10-30 years, a long-term study covering at least one full cycle of decadal climate oscillation is important to quantify the CO2 balance and its interaction with the climate.