Drought alters aboveground biomass production efficiency: Insights from two European beech forests.

The fraction of photosynthetically assimilated carbon that trees allocate to long-lasting woody biomass pools (biomass production efficiency - BPE), is a key metric of the forest carbon balance. Its apparent simplicity belies the complex interplay between underlying processes of photosynthesis, respiration, litter and fruit production, and tree growth that respond differently to climate variability. Whereas the magnitude of BPE has been routinely quantified in ecological studies, its temporal dynamics and responses to extreme events such as drought remain less well understood. Here, we combine long-term records of aboveground carbon increment (ACI) obtained from tree rings with stand-level gross primary productivity (GPP) from eddy covariance (EC) records to empirically quantify aboveground BPE (= ACI/GPP) and its interannual variability in two European beech forests (Hainich, DE-Hai, Germany; Sorø, DK-Sor, Denmark). We found significant negative correlations between BPE and a daily-resolved drought index at both sites, indicating that woody growth is de-prioritized under water limitation. During identified extreme years, early-season drought reduced same-year BPE by 29 % (Hainich, 2011), 31 % (Sorø, 2006), and 14 % (Sorø, 2013). By contrast, the 2003 late-summer drought resulted in a 17 % reduction of post-drought year BPE at Hainich. Across the entire EC period, the daily-to-seasonal drought response of BPE resembled that of ACI, rather than that of GPP. This indicates that BPE follows sink dynamics more closely than source dynamics, which appear to be decoupled given the distinctive climate response patterns of GPP and ACI. Based on our observations, we caution against estimating the magnitude and variability of the carbon sink in European beech (and likely other temperate forests) based on carbon fluxes alone. We also encourage comparable studies at other long-term EC measurement sites from different ecosystems to further constrain the BPE response to rare climatic events.

Detection and attribution of an anomaly in terrestrial photosynthesis in Europe during the COVID-19 lockdown.

Carbon dioxide (CO2) uptake by plant photosynthesis, referred to as gross primary production (GPP) at the ecosystem level, is sensitive to environmental factors, including pollutant exposure, pollutant uptake, and changes in the scattering of solar shortwave irradiance (SWin) - the energy source for photosynthesis. The 2020 spring lockdown due to COVID-19 resulted in improved air quality and atmospheric transparency, providing a unique opportunity to assess the impact of air pollutants on terrestrial ecosystem functioning. However, detecting these effects can be challenging as GPP is influenced by other meteorological drivers and management practices. Based on data collected from 44 European ecosystem-scale CO2 flux monitoring stations, we observed significant changes in spring GPP at 34 sites during 2020 compared to 2015-2019. Among these, 14 sites showed an increase in GPP associated with higher SWin, 10 sites had lower GPP linked to atmospheric and soil dryness, and seven sites were subjected to management practices. The remaining three sites exhibited varying dynamics, with one experiencing colder and rainier weather resulting in lower GPP, and two showing higher GPP associated with earlier spring melts. Analysis using the regional atmospheric chemical transport model (LOTOS-EUROS) indicated that the ozone (O3) concentration remained relatively unchanged at the research sites, making it unlikely that O3 exposure was the dominant factor driving the primary production anomaly. In contrast, SWin increased by 9.4 % at 36 sites, suggesting enhanced GPP possibly due to reduced aerosol optical depth and cloudiness. Our findings indicate that air pollution and cloudiness may weaken the terrestrial carbon sink by up to 16 %. Accurate and continuous ground-based observations are crucial for detecting and attributing subtle changes in terrestrial ecosystem functioning in response to environmental and anthropogenic drivers.

Leaf-level coordination principles propagate to the ecosystem scale.

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Accuracy, realism and general applicability of European forest models.

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

Contribution from a eutrophic temperate estuary to the landscape flux of nitrous oxide.

For mitigation of climate change, all sources and sinks of greenhouse gases from the environment must be quantified and their driving factors identified. Nitrous oxide (N2O) is a strong greenhouse gas, and the contribution of aquatic systems to the global N2O budget remains poorly constrained. In this study, we measured N2O concentrations in a eutrophic coastal system, Roskilde Fjord (Denmark), and combined measurements with statistical modeling to quantify the N2O fluxes and budget in the system over a period of six months. To do so, we collected water at 15 sampling points and measured N2O concentrations along with physico-chemical water quality parameters, e.g. temperature, salinity, dissolved inorganic nitrogen and phosphorus, and silicon. We used mixed-effect regression models to predict N2O concentrations in the water from water quality parameters. We then derived N2O fluxes using well-established equations of N2O solubility and water-atmosphere exchanges. These fluxes were then put in perspective with those measured at the landscape scale by eddy-covariance at a 96 m nearby tall tower, and to those estimated from the agricultural land next to the fjord using Intergovernmental Panel on Climate Change (IPCC) guidelines. N2O concentrations in the Roskilde Fjord ranged between 2.40 and 8.05 nmol l-1. The best fitting model between water parameters and N2O concentrations in water included phosphorus and temperature. We estimated that (i) Roskilde Fjord was a sink of N2O, with a median inward flux of -0.04 nmol m-2 s-1, (ii) while the surrounding median agricultural flux was 0.13-0.18 nmol m-2 s-1, and (iii) the median landscape flux was 0.07 nmol m-2 s-1. All estimates of N2O fluxes were of the same magnitude and consistent with each other. These preliminary results need to be consolidated by further research.

Uncovering the critical soil moisture thresholds of plant water stress for European ecosystems.

Understanding the critical soil moisture (SM) threshold (θcrit ) of plant water stress and land surface energy partitioning is a basis to evaluate drought impacts and improve models for predicting future ecosystem condition and climate. Quantifying the θcrit across biomes and climates is challenging because observations of surface energy fluxes and SM remain sparse. Here, we used the latest database of eddy covariance measurements to estimate θcrit across Europe by evaluating evaporative fraction (EF)-SM relationships and investigating the covariance between vapor pressure deficit (VPD) and gross primary production (GPP) during SM dry-down periods. We found that the θcrit and soil matric potential threshold in Europe are 16.5% and -0.7 MPa, respectively. Surface energy partitioning characteristics varied among different vegetation types; EF in savannas had the highest sensitivities to SM in water-limited stage, and the lowest in forests. The sign of the covariance between daily VPD and GPP consistently changed from positive to negative during dry-down across all sites when EF shifted from relatively high to low values. This sign of the covariance changed after longer period of SM decline in forests than in grasslands and savannas. Estimated θcrit from the VPD-GPP covariance method match well with the EF-SM method, showing this covariance method can be used to detect the θcrit . We further found that soil texture dominates the spatial variability of θcrit while shortwave radiation and VPD are the major drivers in determining the spatial pattern of EF sensitivities. Our results highlight for the first time that the sign change of the covariance between daily VPD and GPP can be used as an indicator of how ecosystems transition from energy to SM limitation. We also characterized the corresponding θcrit and its drivers across diverse ecosystems in Europe, an essential variable to improve the representation of water stress in land surface models.

The three major axes of terrestrial ecosystem function.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Non-stomatal processes reduce gross primary productivity in temperate forest ecosystems during severe edaphic drought.

Severe drought events are known to cause important reductions of gross primary productivity (GPP) in forest ecosystems. However, it is still unclear whether this reduction originates from stomatal closure (Stomatal Origin Limitation) and/or non-stomatal limitations (Non-SOL). In this study, we investigated the impact of edaphic drought in 2018 on GPP and its origin (SOL, NSOL) using a dataset of 10 European forest ecosystem flux towers. In all stations where GPP reductions were observed during the drought, these were largely explained by declines in the maximum apparent canopy scale carboxylation rate VCMAX,APP (NSOL) when the soil relative extractable water content dropped below around 0.4. Concurrently, we found that the stomatal slope parameter (G1, related to SOL) of the Medlyn et al. unified optimization model linking vegetation conductance and GPP remained relatively constant. These results strengthen the increasing evidence that NSOL should be included in stomatal conductance/photosynthesis models to faithfully simulate both GPP and water fluxes in forest ecosystems during severe drought. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Effects of drought and meteorological forcing on carbon and water fluxes in Nordic forests during the dry summer of 2018.

The Nordic region was subjected to severe drought in 2018 with a particularly long-lasting and large soil water deficit in Denmark, Southern Sweden and Estonia. Here, we analyse the impact of the drought on carbon and water fluxes in 11 forest ecosystems of different composition: spruce, pine, mixed and deciduous. We assess the impact of drought on fluxes by estimating the difference (anomaly) between year 2018 and a reference year without drought. Unexpectedly, the evaporation was only slightly reduced during 2018 compared to the reference year at two sites while it increased or was nearly unchanged at all other sites. This occurred under a 40 to 60% reduction in mean surface conductance and the concurrent increase in evaporative demand due to the warm and dry weather. The anomaly in the net ecosystem productivity (NEP) was 93% explained by a multilinear regression with the anomaly in heterotrophic respiration and the relative precipitation deficit as independent variables. Most of the variation (77%) was explained by the heterotrophic component. Six out of 11 forests reduced their annual NEP with more than 50 g C m-2 yr-1 during 2018 as compared to the reference year. The NEP anomaly ranged between -389 and +74 g C m-2 yr-1 with a median value of -59 g C m-2 yr-1. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Altered energy partitioning across terrestrial ecosystems in the European drought year 2018.

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004-2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Axial changes in wood functional traits have limited net effects on stem biomass increment in European beech (Fagus sylvatica).

During the growing season, trees allocate photoassimilates to increase their aboveground woody biomass in the stem (ABIstem). This 'carbon allocation' to structural growth is a dynamic process influenced by internal and external (e.g., climatic) drivers. While radial variability in wood formation and its resulting structure have been intensively studied, their variability along tree stems and subsequent impacts on ABIstem remain poorly understood. We collected wood cores from mature trees within a fixed plot in a well-studied temperate Fagus sylvatica L. forest. For a subset of trees, we performed regular interval sampling along the stem to elucidate axial variability in ring width (RW) and wood density (ρ), and the resulting effects on tree- and plot-level ABIstem. Moreover, we measured wood anatomical traits to understand the anatomical basis of ρ and the coupling between changes in RW and ρ during drought. We found no significant axial variability in ρ because an increase in the vessel-to-fiber ratio with smaller RW compensated for vessel tapering towards the apex. By contrast, temporal variability in RW varied significantly along the stem axis, depending on the growing conditions. Drought caused a more severe growth decrease, and wetter summers caused a disproportionate growth increase at the stem base compared with the top. Discarding this axial variability resulted in a significant overestimation of tree-level ABIstem in wetter and cooler summers, but this bias was reduced to ~2% when scaling ABIstem to the plot level. These results suggest that F. sylvatica prioritizes structural carbon sinks close to the canopy when conditions are unfavorable. The different axial variability in RW and ρ thereby indicates some independence of the processes that drive volume growth and wood structure along the stem. This refines our knowledge of carbon allocation dynamics in temperate diffuse-porous species and contributes to reducing uncertainties in determining forest carbon fixation.

Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate.

Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here we assess the potential impact of thinning on projected carbon cycle dynamics and implications for forest CUE and its components (i.e., gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process-based forest ecosystem model forced by climate outputs of five Earth System Models under four representative climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO2 concentration, and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development, and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations lead the forests to grow faster, mature earlier, and also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody pools, and reduce physiological-climate-induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest-based mitigation strategies and should be carefully considered within a portfolio of mitigation options.

Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts.

Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon-climate feedbacks.

Above-ground woody carbon sequestration measured from tree rings is coherent with net ecosystem productivity at five eddy-covariance sites.

• Attempts to combine biometric and eddy-covariance (EC) quantifications of carbon allocation to different storage pools in forests have been inconsistent and variably successful in the past. • We assessed above-ground biomass changes at five long-term EC forest stations based on tree-ring width and wood density measurements, together with multiple allometric models. Measurements were validated with site-specific biomass estimates and compared with the sum of monthly CO2 fluxes between 1997 and 2009. • Biometric measurements and seasonal net ecosystem productivity (NEP) proved largely compatible and suggested that carbon sequestered between January and July is mainly used for volume increase, whereas that taken up between August and September supports a combination of cell wall thickening and storage. The inter-annual variability in above-ground woody carbon uptake was significantly linked with wood production at the sites, ranging between 110 and 370 g C m(-2) yr(-1) , thereby accounting for 10-25% of gross primary productivity (GPP), 15-32% of terrestrial ecosystem respiration (TER) and 25-80% of NEP. • The observed seasonal partitioning of carbon used to support different wood formation processes refines our knowledge on the dynamics and magnitude of carbon allocation in forests across the major European climatic zones. It may thus contribute, for example, to improved vegetation model parameterization and provides an enhanced framework to link tree-ring parameters with EC measurements.

Reduction of molecular gas diffusion through gaskets in leaf gas exchange cuvettes by leaf-mediated pores.

There is an ongoing debate on how to correct leaf gas exchange measurements for the unavoidable diffusion leakage that occurs when measurements are done in non-ambient CO2 concentrations. In this study, we present a theory on how the CO2 diffusion gradient over the gasket is affected by leaf-mediated pores (LMP) and how LMP reduce diffusive exchange across the gaskets. Recent discussions have so far neglected the processes in the quasi-laminar boundary layer around the gasket. Counter intuitively, LMP reduce the leakage through gaskets, which can be explained by assuming that the boundary layer at the exterior of the cuvette is enriched with air from the inside of the cuvette. The effect can thus be reduced by reducing the boundary layer thickness. The theory clarifies conflicting results from earlier studies. We developed leaf adaptor frames that eliminate LMP during measurements on delicate plant material such as grass leaves with circular cross section, and the effectiveness is shown with respiration measurements on a harp of Deschampsia flexuosa leaves. We conclude that the best solution for measurements with portable photosynthesis systems is to avoid LMP rather than trying to correct for the effects.

Variation in photosynthetic light-use efficiency in a mountainous tropical rain forest in Indonesia.

Photosynthetically active radiation (Q)-use efficiency (epsilon) is an important parameter for deriving carbon fluxes between forest canopies and the atmosphere from meteorological ground and remote sensing data. A common approach is to assume gross primary production (P(g)) and net primary production (P(n)) are proportional to Q absorbed by vegetation (Q(abs)) by defining the proportionality constants epsilon(Pg) and epsilon(Pn) (for P(g) and P(n), respectively). Although remote sensing and climate monitoring provide Q(abs) and other meteorological data at the global scale, information on epsilon is particularly scarce in remote tropical areas. We used a 16-month continuous CO(2) flux and meteorological dataset from a mountainous tropical rain forest in central Sulawesi, Indonesia to derive values of epsilon(Pg) and to investigate the relationship between P(g) and Q(abs). Absorption was estimated with a 1D SVAT model from measured canopy structure and short wave radiation. The half-hourly P(g) data showed a saturation response to Q(abs). The amount of Q(abs) required to saturate P(g) was reduced when water vapor saturation deficit (D) was high. Light saturation of P(g) was still evident when shifting from half-hourly to daily and monthly time scales. Thus, for a majority of observations, P(g) was insensitive to changes in Q(abs). A large proportion of the observed seasonal variability in P(g) could not be attributed to changes in Q(abs) or D. Values of epsilon(Pg) varied little around the long-term mean of 0.0179 mol CO(2) (mol photon)(-1) or 0.99 g C MJ(-1) (the standard deviations were +/- 0.006 and +/- 0.0018 mol CO(2) (mol photon)(-1) for daily and monthly means, respectively). In both cases, epsilon(Pg) values were more sensitive to Q(abs) than to daytime D. These findings show that the current epsilon-approaches fail to predict P(g) at our tropical rain forest site for two reasons: (1) they neglect saturation of P(g) when Q(abs) is high; and (2) they do not include factors, other than Q(abs) and D, that determine seasonality and annual sums of P(g).

A comparative analysis of simulated and observed photosynthetic CO2 uptake in two coniferous forest canopies.

Gross canopy photosynthesis (P(g)) can be simulated with canopy models or retrieved from turbulent carbon dioxide (CO2) flux measurements above the forest canopy. We compare the two estimates and illustrate our findings with two case studies. We used the three-dimensional canopy model MAESTRA to simulate P(g) of two spruce forests differing in age and structure. Model parameter acquisition and model sensitivity to selected model parameters are described, and modeled results are compared with independent flux estimates. Despite higher photon fluxes at the site, an older German Norway spruce (Picea abies L. (Karst.)) canopy took up 25% less CO2 from the atmosphere than a young Scottish Sitka spruce (Picea sitchensis (Bong.) Carr.) plantation. The average magnitudes of P(g) and the differences between the two canopies were satisfactorily represented by the model. The main reasons for the different uptake rates were a slightly smaller quantum yield and lower absorptance of the Norway spruce stand because of a more clumped canopy structure. The model did not represent the scatter in the turbulent CO2 flux densities, which was of the same order of magnitude as the non-photosynthetically-active-radiation-induced biophysical variability in the simulated P(g). Analysis of residuals identified only small systematic differences between the modeled flux estimates and turbulent flux measurements at high vapor pressure saturation deficits. The merits and limitations of comparative analysis for quality evaluation of both methods are discussed. From this analysis, we recommend use of both parameter sets and model structure as a basis for future applications and model development.