Eddy Covariance Tower Research Articles

Carbon dioxide and evapotranspiration fluxes in an urban area of Krakow, Poland

AbstractUrban areas play an essential role in the global carbon balance, being responsible for more than 70% of anthropogenic carbon emissions, entering the atmosphere mainly in the form of carbon dioxide (CO2). Another crucial component of the carbon balance of the urban atmosphere is CO2 exchange with the biosphere, expressed in both emission and absorption fluxes. The biosphere component of the net CO2 flux is inseparably linked to the water (H2O) balance due to evapotranspiration. This article presents an estimation of CO2 and H2O net fluxes based on eddy covariance (EC) tower measurements and in‐depth analysis of its temporal and spatial variability for a typical urban site at mid‐latitude of the northern hemisphere. The source area was divided into two sectors, one representing dense urban development with sources of CO2 from traffic and households, and the second containing predominantly recreation and sports areas. Temporal variability analysis of evapotranspiration showed a clear seasonal cycle closely correlated with incoming radiation and air temperature, with the seasonal mean ranging from 0.4 mm·day−1 in winter to 1.6 mm·day−1 in summer. As a result of similar green coverage between the urban and green sectors, spatial variability was statistically insignificant. The net CO2 flux over a seasonal cycle was less pronounced for the total source area with a mean of 5.0 g C·m−2·day−1 in summer and 7.5 g C·m−2·day−1 in winter. However, significant variations between urban and green sectors were observed with the highest seasonal mean difference of 4.5 g C·m−2·day−1 in winter. The results confirm that while on the local, short time‐scale urban vegetation has a potential to mitigate the emissions, it is not able to offset them.

A Copernicus-based evapotranspiration dataset at 100 m spatial resolution over four Mediterranean basins

Abstract. Evapotranspiration (ET) is responsible for regulating the hydrological cycle, with a relevant impact on air humidity and precipitation that is particularly important in the context of acute drought events in recent years. With the intensification of rainfall deficits and extreme heat events, the Mediterranean region requires regular monitoring to enhance water resource management. Even though remote sensing provides spatially continuous information for estimating ET on large scales, existing global products with spatial resolutions ≥ 0.5 km are insufficient for capturing spatial detail at a local level. In the framework of ESA's 4DMED-Hydrology project, we generate an ET dataset at both high spatial and high temporal resolutions using the Priestley–Taylor Two-Source Energy Balance (TSEB-PT) model driven by Copernicus satellite data. We build an automatic workflow to generate a 100 m ET product by combining data from Sentinel-2 (S2) MultiSpectral Instrument (MSI) and Sentinel-3 (S3) land surface temperature (LST) with ERA5 climate reanalysis derived within the period 2017–2021 over four Mediterranean basins in Italy, Spain, France, and Tunisia (Po, Ebro, Hérault, and Medjerda). First, original S2 data are pre-processed before deriving 100 m inputs for the ET estimation. Next, biophysical variables, like leaf area index and fractional vegetation cover, are generated, and then they are temporally composited within a 10 d window according to S3 acquisitions. Consequently, decadal S2 mosaics are used to derive the remaining TSEB-PT inputs. In parallel, we sharpen 1 km S3 by exploiting the dependency between coarse-resolution LST and 100 m S2 reflectances using a decision tree algorithm. Afterwards, climate forcings are utilized to model energy fluxes and then for daily ET retrieval. The daily ET composites demonstrate reasonable TSEB-PT estimates. Based on the validation results against eight eddy covariance (EC) towers between 2017 and 2021, the model predicts 100 m ET with an average RMSE of 1.38 mm d−1 and a Pearson coefficient equal to 0.60. Regardless of some constraints mostly related to the high complexity of EC sites, TSEB-PT can effectively estimate 100 m ET, which opens up new opportunities for monitoring the hydrological cycle on a regional scale. The full dataset is freely available at https://doi.org/10.48784/b90a02d6-5d13-4acd-b11c-99a0d381ca9a, https://doi.org/10.48784/fb631817-189f-4b57-af6a-38cef217bad3, https://doi.org/10.48784/70cd192c-0d46-4811-ad1d-51a09734a2e9, and https://doi.org/10.48784/7abdbd94-ddfe-48df-ab09-341ad2f52e47 for the Ebro, Hérault, Medjerda, and Po catchments, respectively (Bartkowiak et al., 2023a–d).

Slow post-fire carbon balance recovery despite increased net uptake rates in Alaskan tundra

Abstract Increasing wildfire occurrence and intensity have immediate effects on northern ecosystems due to combustion of aboveground vegetation and belowground soil organic matter. These immediate impacts have indirect and longer term effects, including deepening of the active layer, changes in soil decomposition rates, and shifts in plant community composition. Despite the increasing fire impacts across the tundra region, the implications of wildfire on ecosystem carbon balance are not well understood. Using paired eddy covariance towers in unburned and burned tundra, we examined the effects of a 2015 wildfire on carbon dioxide and methane fluxes in a wetland tundra ecosystem in the Yukon-Kuskokwim Delta, Alaska, from 2020 to 2022. Wildfire increased the amplitude and variability of carbon uptake and release on seasonal and annual timescales and increased the temperature sensitivity of soil respiration. Seven years post fire, there was annual net uptake in both unburned and burned tundra based on net ecosystem exchange, with the sink strength of burned tundra exceeding that of the unburned tundra by 1.18 to 1.64 times. However, when considering emissions, it would take approximately 86 years to recover the carbon lost from the wildfire itself. Soil moisture was a dominant driver of fluxes and positively associated with higher rates of carbon dioxide uptake and release and methane release. This study underscores the importance of understanding the effects of wildfire-induced shifts on tundra carbon cycling, allowing better predictions of long-term landscape-scale climate feedbacks as the climate continues to warm.

A 30-m gross primary production dataset from 2016 to 2020 in China

Estimating gross primary production (GPP) of terrestrial ecosystems is important for understanding the terrestrial carbon cycle. However, existed nationwide GPP datasets are primarily driven by coarse spatial resolutions (≥500 m) remotely sensed data, which fails to capture the spatial heterogeneity of GPP across different ecosystem types at land surface. This paper introduces a new GPP dataset, Hi-GLASS GPP v1, with a fine spatial resolution (30-m) and monthly temporal resolution from 2016 to 2020 in China. The Hi-GLASS GPP v1 dataset is generated from 30-m Landsat data using a process based light use efficiency model. The Hi-GLASS GPP v1 model integrates a detailed map of maize plantations, a crucial C4 crop in China known for its higher photosynthetic efficiency compared to C3 crops. This inclusion helps correct the underestimation of GPP that typically occurs when all croplands are categorized as C3. The Hi-GLASS GPP v1 dataset demonstrates a robust correlation with GPP data derived from eddy covariance towers, thereby enabling a more accurate assessment of terrestrial carbon sequestration across China.

Energy‐Water Asynchrony Principally Determines Water Available for Runoff From Snowmelt in Continental Montane Forests

ABSTRACTChanges in the volume, rate, and timing of the snowmelt water pulse have profound implications for seasonal soil moisture, evapotranspiration (ET), groundwater recharge, and downstream water availability, especially in the context of climate change. Here, we present an empirical analysis of water available for runoff using five eddy covariance towers located in continental montane forests across a regional gradient of snow depth, precipitation seasonality, and aridity. We specifically investigated how energy‐water asynchrony (i.e., snowmelt timing relative to atmospheric demand), surface water input intensity (rain and snowmelt), and observed winter ET (winter AET) impact multiple water balance metrics that determine water available for runoff (WAfR). Overall, we found that WAfR had the strongest relationship with energy‐water asynchrony (adjusted r2 = 0.52) and that winter AET was correlated to total water year evapotranspiration but not to other water balance metrics. Stepwise regression analysis demonstrated that none of the tested mechanisms were strongly related to the Budyko‐type runoff anomaly (highest adjusted r2 = 0.21). We, therefore, conclude that WAfR from continental montane forests is most sensitive to the degree of energy‐water asynchrony that occurs. The results of this empirical study identify the physical mechanisms driving variability of WAfR in continental montane forests and are thus broadly relevant to the hydrologic management and modelling communities.

Divergent apparent temperature sensitivity of forest-floor respiration across a managed boreal forest landscape

Understanding the apparent temperature sensitivity (Q10) of forest floor respiration (Q10Rff) and its plant autotrophic (Q10Ra) and soil heterotrophic (Q10Rh) components is critical for determining the strength and direction of forest carbon cycle-climate feedbacks. However, the spatial variability of Q10Rff and its controlling factors across the spatially heterogeneous boreal forest landscape remains poorly understood. In this study, we used chamber-based respiration measurements conducted on paired natural and trenching plots over three growing seasons (2016–2018) to determine Q10Rff, Q10Rh and Q10Ra to soil temperature across 50 diverse forest stands (ranging 5–211 years old) in a managed landscape in northern Sweden. Additionally, we estimated ecosystem- and landscape-scale Q10 based on conventional and tall tower eddy covariance measurements, respectively, conducted over the same landscape. Our results suggest manifold variations (i.e., 10th to 90th percentiles) of Q10Rff (1.7 to 6.6), with Q10Ra (0.9 to 7.4) showing a greater range than Q10Rh (1.6 to 5.3). Forest-floor understory biomass was the main control of variations in Q10Ra, whereas soil properties explained best those of Q10Rh. Furthermore, a seasonal hysteresis of Q10Rff was observed, with higher values mostly occurring during the late growing season. The magnitude of this hysteresis scaled with stand age in response to concurrent changes in net primary production. The Q10Rff to air temperature declined with increasing stand age, which was attributed to the increased decoupling of air and soil temperatures with canopy development. Despite the considerable stand-level variations, when averaged over the 50 forest stands, Q10Rff to air temperature converged with that of both ecosystem- and landscape-scale respiration. In conclusion, our study highlights the complexity of Q10Rff, which needs to be considered in predictions of the interactions of climate change and management with the carbon cycle of managed boreal forests.

The LTAR Cropland Common Experiment at Upper Mississippi River Basin-Morris.

The Upper Mississippi River Basin (UMRB) Long-Term Agroecosystem Research (LTAR) watershed is hydrologically complex, with a notable temperature and precipitation gradient across four locations: Ames, IA; Platteville, WI; Morris, MN; and St. Paul, MN. Each location established LTAR Croplands Common Experiment (CCE) scenarios to fit local climatic and cultural practices. This paper describes the UMRB-Morris location, which was established in 2016 and is the most northern of the sites and contributes to the major watersheds of the UMRB and the Red River of the North. Both on-farm and plot-scale studies are included. The prevailing system is a corn (Zea mays L.)-soybean (Glycine max L.) rotation with annual deep ripping tillage. The signature alternative system is alternative 1, which is a shallow strip-till in a corn-soybean rotation. A second alternative system includes shallow tillage/rotational no-tillage in a corn-soybean-wheat (Triticum aestivum L.) with winter oilseed and cover crops, and it is considered a test ground for future alternative systems. On-farm fields are equipped with eddy covariance towers and include 16 geo-referenced soil core sampling sites for incremental samplings. Each field is sampled annually for crop yield and management data are recorded. Plot-scale versions of the treatments are managed at the Swan Lake Research Farm. On-farm and plot-scale fields are instrumented with Phenocams to capture continuous photographic records. The CCE at UMRB-Morris aims to integrate soil, crop, weather data, and image classification to assess benefits and challenges across different management strategies.

Carbon Flux Models in a Zonally Dry Tropical Forest Area (Caatinga)

Studies on energy exchange in ecosystems are critical for understanding carbon flows amid different vegetation patterns. In semi-arid areas, comprehending the variability in carbon absorption is essential for quantifying and anticipating the impacts of changes in the caatinga ecosystem. This study aims to calibrate and evaluate models for Gross Primary Production (GPP), Net Ecosystem Exchange (NEE), and Ecosystem Respiration (Reco) in the caatinga biome. NEE measurements were obtained and calculated at 30-minute intervals using EddyPro 3.6 software, from raw data measured at 10 Hz. GPP was estimated by partitioning NEE and Reco, all measured in micromoles of CO2 per square meter per second (μmol CO2m⁻²s⁻¹) using the eddy covariance (EC) tower, installed in a legal reserve at Embrapa Semiárido, in Petrolina, Pernambuco, within a section of the caatinga canopy. Following the measurement of carbon fluxes and ecosystem respiration, field measurements were conducted using a portableFieldSpec HandHeld spectroradiometer to obtain the reflectance of the canopy around the turbulent eddy covariance tower. These measurements were carried out in 2015 in a preserved caatinga area. Multiple linear regression models weredeveloped to estimate carbon fluxes from orbital images, enabling accurate estimation of GPP, NEE, and Reco, using the MODIS/Terra Daily Surface Reflectance product (MOD09GA). The primary results demonstrate the effectiveness of the developed models, particularly the GPP model, which exhibited the best statistical indices (R = 0.97; R² = 0.95; Root Mean Square Error = 0.20). Observations from the EC tower indicated that the models developed to estimate NEE, GPP, and Reco, using visible and near-infrared reflectance data, accurately represented the dry period and effectively captured the phenological aspects of the caatinga ecosystem.

Examining the Ecosystem-Scale GHG Exchange Following the Acrotelm Harvesting Method (ACM) in Eastern Quebec

Traditional horticultural peat production involves the removal of vegetation and drainage of peatlands, resulting in significant ecological disturbances and greenhouse gas (GHG) emissions. The Acrotelm Harvesting Method (ACM) was developed as a more sustainable alternative, designed to reduce these impacts by allowing peat extraction without large-scale ecosystem alterations. However, the ACM still necessitates the passage of machinery over the peat, potentially disturbing surface vegetation and altering the carbon dynamics. My project, based at a field site near Baie-Comeau, QC, represents the first comprehensive assessment of the ACM’s impact on net ecosystem exchanges of main GHGs. I focused on evaluating the ecosystem-scale effects by analyzing data collected from paired eddy covariance towers installed at both the control (unharvested) and harvested sites. These towers provide temporally continuous, spatially integrated flux measurements. Preliminary findings indicate that the site subjected to ACM exhibits altered surface topography, leading to overall wetter conditions, compaction of hummocks, and vegetation damage. These changes have resulted in reduced carbon dioxide uptake and increased methane emissions at the harvested site. Through the analysis and interpretation of this data, my research contributes to a better understanding of the ACM’s environmental impact and its potential as a sustainable peatland management strategy. This research was conducted under the supervision of Dr. Ian Strachan in the Atmospheric Environmental Research (AER) lab.

Two sub-annual timescales and coupling modes for terrestrial water and carbon cycles.

To bridge the knowledge gap between (a) our (instantaneous-to-seasonal-scale) process understanding of plants and water and (b) our projections of long-term coupled feedbacks between the terrestrial water and carbon cycles, we must uncover what the dominant dynamics are linking fluxes of water and carbon. This study uses the simplest empirical dynamical systems models-two-dimensional linear models-and observation-based data from satellites, eddy covariance towers, weather stations, and machine-learning-derived products to determine the dominant sub-annual timescales coupling carbon uptake and (normalized) evaporation fluxes. We find two dominant modes across the Contiguous United States: (1) a negative correlation timescale on the order of a few days during which landscapes dry after precipitation and plants increase their carbon uptake through photosynthetic upregulation. (2) A slow, seasonal-scale positive covariation through which landscape drying leads to decreased growth and carbon uptake. The slow (positively correlated) process dominates the joint distribution of local water and carbon variables, leading to similar behaviors across space, biomes, and climate regions. We propose that vegetation cover/leaf area variables link this behavior across space, leading to strong emergent spatial patterns of water/carbon coupling in the mean. The spatial pattern of local temporal dynamics-positively sloped tangent lines to a convex long-term mean-state curve-is surprisingly strong, and can serve as a benchmark for coupled Earth System Models. We show that many such models do not represent this emergent mean-state pattern, and hypothesize that this may be due to lack of water-carbon feedbacks at daily scales.

Site-specific apparent optimum air temperature for vegetation photosynthesis across the globe

The apparent optimum air temperature for vegetation photosynthesis (Topt) is a key temperature parameter in terrestrial ecosystem models estimating daily photosynthesis or gross primary production (GPP, g C/m2/day). To date, most models use biome-specific Topt (Topt-biome) parameter values. Given vegetation acclimation and adaptation to local climate, site-specific Topt (Topt-site) is needed to reduce uncertainties in estimating daily GPP across the scales from site to region and the globe. Previous studies have demonstrated using the Enhanced Vegetation Index (EVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images and daytime air temperature data to estimate the Topt-site at the eddy covariance tower sites. This study used MODIS-derived EVI and ERA5 climate data to estimate and generate global Topt-site data products from 2000 to 2019. The Topt-site of individual pixels within a biome has large variation, which clearly cannot be represented accurately by the widely used Topt-biome. Therefore, using this global dataset of Topt-site estimates might significantly affect GPP simulation in current ecosystem models.

The Decline in Summer Fallow in the Northern Great Plains Cooled Near‐Surface Climate but had Minimal Impacts on Precipitation

AbstractLand management can moderate or intensify the impacts of a warming atmosphere. Since the early 1980s, nearly 116,000 km2 of cropland that was once held in fallow during the summer is now planted in the northern North American Great Plains. To simulate the impacts of this substantial land cover change on regional climate processes, convection‐permitting model experiments using the Weather Research and Forecasting model were performed to simulate modern and historical amounts of summer fallow. The control simulation was extensively validated using multiple observational data products as well as eddy covariance tower observations. Results of these simulations show that the transition from summer fallow to modern land cover led to ∼1.5°C cooler temperatures and decreased vapor pressure deficit by ∼0.15 kPa during the growing season across the study region, which is consistent with observed cooling trends. The cooler and wetter land surface with vegetation led to a shallower planetary boundary layer and lower lifted condensation level, creating conditions more conducive to convective cloud formation and precipitation. Our model simulations however show little widespread evidence of land surface changes effects on precipitation. The observed precipitation increase in this region is more likely related to increased moisture transport by way of the Great Plains Low Level Jet as revealed by the ERA5 reanalysis. Our results demonstrate that land cover change is consistent with observed regional cooling in the northern North American Great Plains but changes in precipitation cannot be explained by land management alone.

Validation of Gross Primary Production Estimated by Remote Sensing for the Ecosystems of Doñana National Park through Improvements in Light Use Efficiency Estimation

Doñana National Park is located in the southwest of the Iberian Peninsula, where water scarcity is recurrent, together with a high heterogeneity in species and ecosystems. Monitoring carbon assimilation is essential to improve knowledge of global change in natural vegetation cover. In this work, a light use efficiency (LUE) model was applied to estimate gross primary production (GPP) in two ecosystems of Doñana, xeric shrub (drought resistant) and seasonal marsh (with grasslands dependent on water hydroperiod) and validated with in situ data from eddy covariance (EC) towers installed in both ecosystems. The model was applied in two ways: (1) using the fraction of absorbed photosynthetically active radiation (FAPAR) from Sentinel-2 and meteorological data from reanalysis (ERA5), and (2) using Sentinel-2 FAPAR, reanalysis solar radiation (ERA5) and the Sentinel-2 land surface water index (LSWI). In both cases and for both ecosystems, the error values are acceptable (below 1 gC/m2) and in both ecosystems the model using the LSWI gave better results (R2 of 0.8 in marshes and 0.51 in xeric shrubs). The results also show a greater influence of the water status of the system than of the meteorological variables in this area.

Post-windthrow differences of carbon and water fluxes between managed and unmanaged Norway spruce stands

Windthrow is a major forest disturbance source in Europe. The impact of management (salvage logging) and no-management (deadwood left in ecosystem) treatments on carbon and water fluxes of Norway spruce stand affected by windthrow were analysed. The net ecosystem production (NEP), gross primary production (GPP), ecosystem respiration (Reco) and evapotranspiration (ET) were measured with eddy-covariance tower during 2019–2022 period. Additional chamber gas-exchange measurements, and vegetation inventory were performed. The unmanaged site had greater vegetation diversity and plant abundance, with higher leaf area index (LAI). The managed site showed overall higher NEP, lower GPP, lower Reco, lower GPP based water-use efficiency (WUEGPP), but higher NEP based WUENEP, compared with unmanaged site. The ET showed no clear trend between the two treatments. The higher GPP of unmanaged site can be linked to greater abundance of herbaceous species, which showed significantly higher photosynthetic capacity than the tree species. Moreover, the higher WUEGPP of unmanaged site can be affected also by the higher LAI of the unmanaged site. Nevertheless, if the Reco is accounted for in WUENEP, the differences between sites are reversed and the unmanaged site had lower WUENEP compared to the managed site. The option to leave the disturbed site without management leads to more productive ecosystem (GPP), with greater species diversity and abundance, but also with greater Reco and lower WUENEP. The discrepancy between WUEGPP and WUENEP suggests that studies analysing natural ecosystems affected by disturbances should use WUENEP to account for Reco carbon losses and avoid mis-interpreting the ecosystem carbon-water balance with WUEGPP.

Assessing Spatial Representativeness of Global Flux Tower Eddy-Covariance Measurements Using Data from FLUXNET2015

Large datasets of carbon dioxide, energy, and water fluxes were measured with the eddy-covariance (EC) technique, such as FLUXNET2015. These datasets are widely used to validate remote-sensing products and benchmark models. One of the major challenges in utilizing EC-flux data is determining the spatial extent to which measurements taken at individual EC towers reflect model-grid or remote sensing pixels. To minimize the potential biases caused by the footprint-to-target area mismatch, it is important to use flux datasets with awareness of the footprint. This study analyze the spatial representativeness of global EC measurements based on the open-source FLUXNET2015 data, using the published flux footprint model (SAFE-f). The calculated annual cumulative footprint climatology (ACFC) was overlaid on land cover and vegetation index maps to create a spatial representativeness dataset of global flux towers. The dataset includes the following components: (1) the ACFC contour (ACFCC) data and areas representing 50%, 60%, 70%, and 80% ACFCC of each site, (2) the proportion of each land cover type weighted by the 80% ACFC (ACFCW), (3) the semivariogram calculated using Normalized Difference Vegetation Index (NDVI) considering the 80% ACFCW, and (4) the sensor location bias (SLB) between the 80% ACFCW and designated areas (e.g. 80% ACFCC and window sizes) proxied by NDVI. Finally, we conducted a comprehensive evaluation of the representativeness of each site from three aspects: (1) the underlying surface cover, (2) the semivariogram, and (3) the SLB between 80% ACFCW and 80% ACFCC, and categorized them into 3 levels. The goal of creating this dataset is to provide data quality guidance for international researchers to effectively utilize the FLUXNET2015 dataset in the future.

Responses of Marginal and Intrinsic Water‐Use Efficiency to Changing Aridity Using FLUXNET Observations

AbstractAccording to classic stomatal optimization theory, plant stomata are regulated to maximize carbon assimilation for a given water loss. A key component of stomatal optimization models is marginal water‐use efficiency (mWUE), the ratio of the change of transpiration to the change in carbon assimilation. Although the mWUE is often assumed to be constant, variability of mWUE under changing hydrologic conditions has been reported. However, there has yet to be a consensus on the patterns of mWUE variabilities and their relations with atmospheric aridity. We investigate the dynamics of mWUE in response to vapor pressure deficit (VPD) and aridity index using carbon and water fluxes from 115 eddy covariance towers available from the global database FLUXNET. We demonstrate a non‐linear mWUE‐VPD relationship at a sub‐daily scale in general; mWUE varies substantially at both low and high VPD levels. However, mWUE remains relatively constant within the mid‐range of VPD. Despite the highly non‐linear relationship between mWUE and VPD, the relationship can be informed by the strong linear relationship between ecosystem‐level inherent water‐use efficiency (IWUE) and mWUE using the slope, m*. We further identify site‐specific m* and its variability with changing site‐level aridity across six vegetation types. We suggest accurately representing the relationship between IWUE and VPD using Michaelis–Menten or quadratic functions to ensure precise estimation of mWUE variability for individual sites.

Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment

We investigated the spatiotemporal variability of remotely sensed gross primary productivity (GPP) over Türkiye based on MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2 GPP products. The differences in various GPP products were assessed using Kruskal–Wallis and Mann–Whitney U methods, and long-term trends were analyzed using Modified Mann–Kendall (MMK), innovative trend analysis (ITA), and empirical mode decomposition (EMD). Our results show that at least one GPP product significantly differs from the others over the seven geographic regions of Türkiye (χ2 values of 50.8, 21.9, 76.9, 42.6, 149, 34.5, and 168; p < 0.05), and trend analyses reveal a significant increase in GPP from all satellite-based products over the latter half of the study period. Throughout the year, the average number of months in which each dataset showed significant increases across all study regions are 6.7, 8.1, 5.9, 9.6, and 8.7 for MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2, respectively. The ITA and EMD methods provided additional insight into the MMK test in both visualizing and detecting trends due to their graphical techniques. Overall, the GPP products investigated here suggest ‘greening’ for Türkiye, consistent with the findings from global studies, but the use of different statistical approaches and satellite-based GPP estimates creates different interpretations of how these trends have emerged. Ground stations, such as eddy covariance towers, can help further improve our understanding of the carbon cycle across the diverse ecosystem of Türkiye.

Beyond the visible: Accounting for ultraviolet and far-red radiation in vegetation productivity and surface energy budgets.

Photosynthetically active radiation (PAR) is typically defined as light with a wavelength within 400-700 nm. However, ultra-violet (UV) radiation within 280-400 nm and far-red (FR) radiation within 700-750 nm can also excite photosystems, though not as efficiently as PAR. Vegetation and land surface models (LSMs) typically do not explicitly account for UV's contribution to energy budgets or photosynthesis, nor FR's contribution to photosynthesis. However, whether neglecting UV and FR has significant impacts remains unknown. We explored how canopy radiative transfer (RT) and photosynthesis are impacted when explicitly implementing UV in the canopy RT model and accounting for UV and FR in the photosynthesis models within a next-generation LSM that can simulate hyperspectral canopy RT. We validated our improvements using photosynthesis measurements from plants under different light sources and intensities and surface reflection from an eddy-covariance tower. Our model simulations suggested that at the whole plant level, after accounting for UV and FR explicitly, chlorophyll content, leaf area index (LAI), clumping index, and solar radiation all impact the modeling of gross primary productivity (GPP). At the global scale, mean annual GPP within a grid would increase by up to 7.3% and the increase is proportional to LAI; globally integrated GPP increases by 4.6 PgC year-1 (3.8% of the GPP without accounting for UV + FR). Further, using PAR to proxy UV could overestimate surface albedo by more than 0.1, particularly in the boreal forests. Our results highlight the importance of improving UV and FR in canopy RT and photosynthesis modeling and the necessity to implement hyperspectral or multispectral canopy RT schemes in future vegetation and LSMs.

Evaluating the precise grapevine water stress detection using unmanned aerial vehicles and evapotranspiration-based metrics

AbstractPrecise irrigation management requires accurate knowledge of crop water demand to adequately optimize water use efficiency, especially relevant in arid and semi-arid regions. While unoccupied aerial vehicles (UAV) have shown great promise to improve the water management for crops such as vineyards, there still remains large uncertainties to accurately quantify vegetation water requirements, especially through physically-based methods. Notably, thermal remote sensing has been shown to be a promising tool to evaluate water stress at different scales, most commonly through the Crop Water Stress Index (CWSI). This work aimed to evaluate the potential of a UAV payload to estimate evapotranspiration (ET) and alternative ET-based crop water stress indices to better monitor and detect irrigation requirements in vineyards. As a case study, three irrigation treatments within a vineyard were implemented to impose weekly crop coefficient (Kc) of 0.2 (extreme deficit irrigation), 0.4 (typical deficit irrigation) and 0.8 (over-irrigated) of reference ET. Both the original Priestley-Taylor initialized two-source energy balance model (TSEB-PT) and the dual temperature TSEB (TSEB-2T), which takes advantage of high-resolution imagery to discriminate canopy and soil temperatures, were implemented to estimate ET. In a first step, both ET models were evaluated at the footprint level using an eddy covariance (EC) tower, with modelled fluxes comparing well against the EC measurements. Secondly, in-situ physiological measurements at vine level, such as stomatal conductance (gst), leaf (Ψleaf) and stem (Ψstem) water potential, were collected simultaneously to UAV overpasses as plant proxies of water stress. Different variants of the CWSI and alternative metrics that take advantage of the partitioned ET from TSEB, such as Crop Transpiration Stress Index (CTSI) and the Crop Stomatal Stress Index (CSSI), were also evaluated to test their statistical relationship against these in-situ physiological indicators using the Spearman correlation coefficient (ρ). Both TSEB-PT and TSEB-2T CWSI related similarly to in-situ measurements (Ψleaf: ρ ~ 0.4; Ψstem: ρ ~ 0.55). On the other hand, stress indicators using canopy fluxes (i.e. CTSI and CSSI) were much more effective when using TSEB-2 T (Ψleaf: ρ = 0.45; Ψstem: ρ = 0.62) compared to TSEB-PT (Ψleaf: ρ = 0.18; Ψstem: ρ = 0.49), revealing important differences in the ET partitioning between model variants. These results demonstrate the utility of physically-based models to estimate ET and partitioned canopy fluxes, which can enhance the detection of vine water stress and quantitatively assess vine water demand to better manage irrigation practices.

Unraveling phenological and stomatal responses to flash drought and implications for water and carbon budgets

Abstract. In recent years, extreme droughts in the United States have increased in frequency and severity, underlining a need to improve our understanding of vegetation resilience and adaptation. Flash droughts are extreme events marked by the rapid dry down of soils due to lack of precipitation, high temperatures, and dry air. These events are also associated with reduced preparation, response, and management time windows before and during drought, exacerbating their detrimental impacts on people and food systems. Improvements in actionable information for flash drought management are informed by atmospheric and land surface processes, including responses and feedbacks from vegetation. Phenologic state, or growth stage, is an important metric for modeling how vegetation modulates land–atmosphere interactions. Reduced stomatal conductance during drought leads to cascading effects on carbon and water fluxes. We investigate how uncertainty in vegetation phenology and stomatal regulation propagates through vegetation responses during drought and non-drought periods by coupling a land surface hydrology model to a predictive phenology model. We assess the role of vegetation in the partitioning of carbon, water, and energy fluxes during flash drought and carry out a comparison against drought and non-drought periods. We selected study sites in Kansas, USA, that were impacted by the flash drought of 2012 and that have AmeriFlux eddy covariance towers which provide ground observations to compare against model estimates. Results show that the compounding effects of reduced precipitation and high vapor pressure deficit (VPD) on vegetation distinguish flash drought from other drought and non-drought periods. High VPD during flash drought shuts down modeled stomatal conductance, resulting in rates of evapotranspiration (ET), gross primary productivity (GPP), and water use efficiency (WUE) that fall below those of average drought conditions. Model estimates of GPP and ET during flash drought decrease to rates similar to what is observed during the winter, indicating that plant function during drought periods is similar to that of dormant months. These results have implications for improving predictions of drought impacts on vegetation.