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.

Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites.

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC-based T estimates show higher correlation to sap flow-based T than EC-based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high-quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data-based estimates of ecosystem T permitting a data-driven perspective on the role of plants' water use for global water and carbon cycling in a changing climate.

Late-spring frost risk between 1959 and 2017 decreased in North America but increased in Europe and Asia.

Late-spring frosts (LSFs) affect the performance of plants and animals across the world's temperate and boreal zones, but despite their ecological and economic impact on agriculture and forestry, the geographic distribution and evolutionary impact of these frost events are poorly understood. Here, we analyze LSFs between 1959 and 2017 and the resistance strategies of Northern Hemisphere woody species to infer trees' adaptations for minimizing frost damage to their leaves and to forecast forest vulnerability under the ongoing changes in frost frequencies. Trait values on leaf-out and leaf-freezing resistance come from up to 1,500 temperate and boreal woody species cultivated in common gardens. We find that areas in which LSFs are common, such as eastern North America, harbor tree species with cautious (late-leafing) leaf-out strategies. Areas in which LSFs used to be unlikely, such as broad-leaved forests and shrublands in Europe and Asia, instead harbor opportunistic tree species (quickly reacting to warming air temperatures). LSFs in the latter regions are currently increasing, and given species' innate resistance strategies, we estimate that ∼35% of the European and ∼26% of the Asian temperate forest area, but only ∼10% of the North American, will experience increasing late-frost damage in the future. Our findings reveal region-specific changes in the spring-frost risk that can inform decision-making in land management, forestry, agriculture, and insurance policy.

Effect of Feeding Adaptation of Italian Simmental Cows before Summer Grazing on Animal Behavior and Milk Characteristics.

According to the alpine transhumance system, dairy cows are moved from indoor feeding with conserved forage to fresh herbage feeding on pasture. The aim of this study was to assess, as a feeding adaptation technique, the effect of a gradual inclusion of fresh herbage in the diet of Italian Simmental dairy cows before their transfer to alpine pasture on performance, behavior, and milk characteristics. Eighteen cows were assigned to three groups: animals transferred to alpine pasture with a 10-d feeding adaptation period consisting in gradual access to a pasture close to the valley farm (GT), animals transferred to alpine pasture without a feeding adaptation period (AT), and animals kept in the valley farm (IND). During the first two weeks of summer grazing, GT and AT showed higher rumination time and different concentrations of ketones, hydrocarbons, organic acids, toluene, alcohols, phenols, and dimethyl sulfone in milk as compared to IND, whereas no differences were found in milk yield, composition, or coagulation properties. No differences between GT and AT were evident for the studied variables. The feeding adaptation technique used in this study did not influence the performance and milk characteristics of Italian Simmental dairy cows grazing on alpine pasture.

Refining the role of phenology in regulating gross ecosystem productivity across European peatlands.

The role of plant phenology as a regulator for gross ecosystem productivity (GEP) in peatlands is empirically not well constrained. This is because proxies to track vegetation development with daily coverage at the ecosystem scale have only recently become available and the lack of such data has hampered the disentangling of biotic and abiotic effects. This study aimed at unraveling the mechanisms that regulate the seasonal variation in GEP across a network of eight European peatlands. Therefore, we described phenology with canopy greenness derived from digital repeat photography and disentangled the effects of radiation, temperature and phenology on GEP with commonality analysis and structural equation modeling. The resulting relational network could not only delineate direct effects but also accounted for possible effect combinations such as interdependencies (mediation) and interactions (moderation). We found that peatland GEP was controlled by the same mechanisms across all sites: phenology constituted a key predictor for the seasonal variation in GEP and further acted as a distinct mediator for temperature and radiation effects on GEP. In particular, the effect of air temperature on GEP was fully mediated through phenology, implying that direct temperature effects representing the thermoregulation of photosynthesis were negligible. The tight coupling between temperature, phenology and GEP applied especially to high latitude and high altitude peatlands and during phenological transition phases. Our study highlights the importance of phenological effects when evaluating the future response of peatland GEP to climate change. Climate change will affect peatland GEP especially through changing temperature patterns during plant phenologically sensitive phases in high latitude and high altitude regions.

Publisher Correction: Stand age and species richness dampen interannual variation of ecosystem-level photosynthetic capacity.

In the version of this Article originally published, the wrong Supplementary Information pdf was uploaded, in which the figures did not correspond with those mentioned in the main text and the R code was not presented properly. This has now been replaced.

Individual tree crown delineation and tree species classification with hyperspectral and LiDAR data.

An international data science challenge, called National Ecological Observatory Network-National Institute of Standards and Technology data science evaluation, was set up in autumn 2017 with the goal to improve the use of remote sensing data in ecological applications. The competition was divided into three tasks: (1) individual tree crown (ITC) delineation, for identifying the location and size of individual trees; (2) alignment between field surveyed trees and ITCs delineated on remote sensing data; and (3) tree species classification. In this paper, the methods and results of team Fondazione Edmund Mach (FEM) are presented. The ITC delineation (Task 1 of the challenge) was done using a region growing method applied to a near-infrared band of the hyperspectral images. The optimization of the parameters of the delineation algorithm was done in a supervised way on the basis of the Jaccard score using the training set provided by the organizers. The alignment (Task 2) between the delineated ITCs and the field surveyed trees was done using the Euclidean distance among the position, the height, and the crown radius of the ITCs and the field surveyed trees. The classification (Task 3) was performed using a support vector machine classifier applied to a selection of the hyperspectral bands and the canopy height model. The selection of the bands was done using the sequential forward floating selection method and the Jeffries Matusita distance. The results of the three tasks were very promising: team FEM ranked first in the data science competition in Task 1 and 2, and second in Task 3. The Jaccard score of the delineated crowns was 0.3402, and the results showed that the proposed approach delineated both small and large crowns. The alignment was correctly done for all the test samples. The classification results were good (overall accuracy of 88.1%, kappa accuracy of 75.7%, and mean class accuracy of 61.5%), although the accuracy was biased toward the most represented species.

High Resolution Assessment of Spatio-Temporal Changes in O2 Concentration in Root-Pathogen Interaction.

Fusarium wilt, caused by the fungus Fusarium oxysporum f. sp. lycopersici (Fol), is one of the most destructive soil-borne diseases of tomatoes. Infection takes place on the roots and the process starts with contact between the fungus and the roots hairs. To date, no detailed studies are available on metabolic activity in the early stages of the Fol and tomato root interaction. Spatial and temporal patterns of oxygen consumption could provide new insights into the dynamics of early colonization. Here, we combined planar optodes and spatial analysis to assess how tomato roots influence the metabolic activity and growth patterns of Fol. The results shows that the fungal metabolism, measured as oxygen consumption, increases within a few hours after the inoculation. Statistical analysis revealed that the fungus tends to growth toward the root, whereas, when the root is not present, the single elements of the fungus move with a Brownian motion (random). The combination of planar optodes and spatial analysis is a powerful new tool for assessing temporal and spatial dynamics in the early stages of root-pathogen interaction.

How to map forest structure from aircraft, one tree at a time.

Forest structure is strongly related to forest ecology, and it is a key parameter to understand ecosystem processes and services. Airborne laser scanning (ALS) is becoming an important tool in environmental mapping. It is increasingly common to collect ALS data at high enough point density to recognize individual tree crowns (ITCs) allowing analyses to move beyond classical stand-level approaches. In this study, an effective and simple method to map ITCs, and their stem diameter and aboveground biomass (AGB) is presented. ALS data were used to delineate ITCs and to extract ITCs' height and crown diameter; then, using newly developed allometries, the ITCs' diameter at breast height (DBH) and AGB were predicted. Gini coefficient of DBHs was also predicted and mapped aggregating ITCs predictions. Two datasets from spruce dominated temperate forests were considered: one was used to develop the allometric models, while the second was used to validate the methodology. The proposed approach provides accurate predictions of individual DBH and AGB (R2 = .85 and .78, respectively) and of tree size distributions. The proposed method had a higher generalization ability compared to a standard area-based method, in particular for the prediction of the Gini coefficient of DBHs. The delineation method used detected more than 50% of the trees with DBH >10 cm. The detection rate was particularly low for trees with DBH below 10 cm, but they represent a small amount of the total biomass. The Gini coefficient of the DBH distribution was predicted at plot level with R2 = .46. The approach described in this work, easy applicable in different forested areas, is an important development of the traditional area-based remote sensing tools and can be applied for more detailed analysis of forest ecology and dynamics.

Leaf and canopy photosynthesis of a chlorophyll deficient soybean mutant.

The photosynthetic, optical, and morphological characteristics of a chlorophyll-deficient (Chl-deficient) "yellow" soybean mutant (MinnGold) were examined in comparison with 2 green varieties (MN0095 and Eiko). Despite the large difference in Chl content, similar leaf photosynthesis rates were maintained in the Chl-deficient mutant by offsetting the reduced absorption of red photons by a small increase in photochemical efficiency and lower non-photochemical quenching. When grown in the field, at full canopy cover, the mutants reflected a significantly larger proportion of incoming shortwave radiation, but the total canopy light absorption was only slightly reduced, most likely due to a deeper penetration of light into the canopy space. As a consequence, canopy-scale gross primary production and ecosystem respiration were comparable between the Chl-deficient mutant and the green variety. However, total biomass production was lower in the mutant, which indicates that processes other than steady state photosynthesis caused a reduction in biomass accumulation over time. Analysis of non-photochemical quenching relaxation and gas exchange in Chl-deficient and green leaves after transitions from high to low light conditions suggested that dynamic photosynthesis might be responsible for the reduced biomass production in the Chl-deficient mutant under field conditions.

Stand age and species richness dampen interannual variation of ecosystem-level photosynthetic capacity.

The total uptake of carbon dioxide by ecosystems via photosynthesis (gross primary productivity, GPP) is the largest flux in the global carbon cycle. A key ecosystem functional property determining GPP is the photosynthetic capacity at light saturation (GPPsat), and its interannual variability (IAV) is propagated to the net land-atmosphere exchange of CO2. Given the importance of understanding the IAV in CO2 fluxes for improving the predictability of the global carbon cycle, we have tested a range of alternative hypotheses to identify potential drivers of the magnitude of IAV in GPPsat in forest ecosystems. Our results show that while the IAV in GPPsat within sites is closely related to air temperature and soil water availability fluctuations, the magnitude of IAV in GPPsat is related to stand age and biodiversity (R2 = 0.55, P < 0.0001). We find that the IAV of GPPsat is greatly reduced in older and more diverse forests, and is higher in younger forests with few dominant species. Older and more diverse forests seem to dampen the effect of climate variability on the carbon cycle irrespective of forest type. Preserving old forests and their diversity would therefore be beneficial in reducing the effect of climate variability on Earth's forest ecosystems.

Stand age and species richness dampen interannual variation of ecosystem-level photosynthetic capacity.

The total uptake of carbon dioxide by ecosystems via photosynthesis (gross primary productivity, GPP) is the largest flux in the global carbon cycle. A key ecosystem functional property determining GPP is the photosynthetic capacity at light saturation (GPPsat), and its interannual variability (IAV) is propagated to the net land-atmosphere exchange of CO2. Given the importance of understanding the IAV in CO2 fluxes for improving the predictability of the global carbon cycle, we have tested a range of alternative hypotheses to identify potential drivers of the magnitude of IAV in GPPsat in forest ecosystems. Our results show that while the IAV in GPPsat within sites is closely related to air temperature and soil water availability fluctuations, the magnitude of IAV in GPPsat is related to stand age and biodiversity (R2 = 0.55, P < 0.0001). We find that the IAV of GPPsat is greatly reduced in older and more diverse forests, and is higher in younger forests with few dominant species. Older and more diverse forests seem to dampen the effect of climate variability on the carbon cycle irrespective of forest type. Preserving old forests and their diversity would therefore be beneficial in reducing the effect of climate variability on Earth's forest ecosystems.

Positive biodiversity-productivity relationship predominant in global forests.

The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone-US$166 billion to 490 billion per year according to our estimation-is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities.

Maximum Growth Potential and Periods of Resource Limitation in Apple Tree.

Knowledge of seasonal maximum potential growth rates are important for assessing periods of resource limitations in fruit tree species. In this study we assessed the periods of resource limitation for vegetative (current year stems, and woody biomass) and reproductive (fruit) organs of a major agricultural crop: the apple tree. This was done by comparing relative growth rates (RGRs) of individual organs in trees with reduced competition for resources to trees grown under standard field conditions. Special attention was dedicated to disentangling patterns and values of maximum potential growth for each organ type. The period of resource limitation for vegetative growth was much longer than in another fruit tree species (peach): from late May until harvest. Two periods of resource limitation were highlighted for fruit: from the beginning of the season until mid-June, and about 1 month prior to harvest. By investigating the variability in individual organs growth we identified substantial differences in RGRs among different shoot categories (proleptic and epicormic) and within each group of monitored organs. Qualitatively different and more accurate values of growth rates for vegetative organs, compared to the use of the simple compartmental means, were estimated. Detailed, source-sink based tree growth models, commonly in need of fine parameter tuning, are expected to benefit from the results produced by these analyses.

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.

WhiteRef: a new tower-based hyperspectral system for continuous reflectance measurements.

Proximal sensing is fundamental to monitor the spatial and seasonal dynamics of ecosystems and can be considered as a crucial validation tool to upscale in situ observations to the satellite level. Linking hyperspectral remote sensing with carbon fluxes and biophysical parameters is critical to allow the exploitation of spatial and temporal extensive information for validating model simulations at different scales. In this study, we present the WhiteRef, a new hyperspectral system designed as a direct result of the needs identified during the EUROSPEC ES0903 Cost Action, and developed by Fondazione Edmund Mach and the Institute of Biometeorology, CNR, Italy. The system is based on the ASD FieldSpec Pro spectroradiometer and was designed to acquire continuous radiometric measurements at the Eddy Covariance (EC) towers and to fill a gap in the scientific community: in fact, no system for continuous spectral measurements in the Short Wave Infrared was tested before at the EC sites. The paper illustrates the functioning of the WhiteRef and describes its main advantages and disadvantages. The WhiteRef system, being based on a robust and high quality commercially available instrument, has a clear potential for unattended continuous measurements aiming at the validation of satellites' vegetation products.

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence.

Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.

Convergence of potential net ecosystem production among contrasting C3 grasslands.

Metabolic theory and body size constraints on biomass production and decomposition suggest that differences in the intrinsic potential net ecosystem production (NEPPOT ) should be small among contrasting C3 grasslands and therefore unable to explain the wide range in the annual apparent net ecosystem production (NEPAPP ) reported by previous studies. We estimated NEPPOT for nine C3 grasslands under contrasting climate and management regimes using multiyear eddy covariance data. NEPPOT converged within a narrow range, suggesting little difference in the net carbon dioxide uptake capacity among C3 grasslands. Our results indicate a unique feature of C3 grasslands compared with other terrestrial ecosystems and suggest a state of stability in NEPPOT due to tightly coupled production and respiration processes. Consequently, the annual NEPAPP of C3 grasslands is primarily a function of seasonal and short-term environmental and management constraints, and therefore especially susceptible to changes in future climate patterns and associated adaptation of management practices.

Tradeoffs between global warming and day length on the start of the carbon uptake period in seasonally cold ecosystems.

It is well established that warming leads to longer growing seasons in seasonally cold ecosystems. Whether this goes along with an increase in the net ecosystem carbon dioxide (CO2) uptake is much more controversial. We studied the effects of warming on the start of the carbon uptake period (CUP) of three mountain grasslands situated along an elevational gradient in the Alps. To this end we used a simple empirical model of the net ecosystem CO2 exchange, calibrated and forced with multi-year empirical data from each site. We show that reductions in the quantity and duration of daylight associated with earlier snowmelts were responsible for diminishing returns, in terms of carbon gain, from longer growing seasons caused by reductions in daytime photosynthetic uptake and increases in nighttime losses of CO2. This effect was less pronounced at high, compared to low, elevations, where the start of the CUP occurred closer to the summer solstice when changes in day length and incident radiation are minimal.