Gross Primary Production Values Research Articles

Assessment of spongy moth infestation impacts on forest productivity and carbon loss using the Sentinel-2 satellite remote sensing and eddy covariance flux data

BackgroundDeciduous forests in eastern North America experienced a widespread and intense spongy moth (Lymantria dispar) infestation in 2021. This study quantified the impact of this spongy moth infestation on carbon (C) cycle in forests across the Great Lakes region in Canada, utilizing high-resolution (10 × 10 m2) Sentinel-2 satellite remote sensing images and eddy covariance (EC) flux data. Study results showed a significant reduction in leaf area index (LAI) and gross primary productivity (GPP) values in deciduous and mixed forests in the region in 2021.ResultsRemote sensing derived, growing season mean LAI values of deciduous (mixed) forests were 3.66 (3.18), 2.74 (2.64), and 3.53 (2.94) m2 m−2 in 2020, 2021 and 2022, respectively, indicating about 24 (14)% reduction in LAI, as compared to pre- and post-infestation years. Similarly, growing season GPP values in deciduous (mixed) forests were 1338 (1208), 868 (932), and 1367 (1175) g C m−2, respectively in 2020, 2021 and 2022, showing about 35 (22)% reduction in GPP in 2021 as compared to pre- and post-infestation years. This infestation induced reduction in GPP of deciduous and mixed forests, when upscaled to whole study area (178,000 km2), resulted in 21.1 (21.4) Mt of C loss as compared to 2020 (2022), respectively. It shows the large scale of C losses caused by this infestation in Canadian Great Lakes region.ConclusionsThe methods developed in this study offer valuable tools to assess and quantify natural disturbance impacts on the regional C balance of forest ecosystems by integrating field observations, high-resolution remote sensing data and models. Study results will also help in developing sustainable forest management practices to achieve net-zero C emission goals through nature-based climate change solutions.

Climate Warming Benefits Plant Growth but Not Net Carbon Uptake: Simulation of Alaska Tundra and Needle Leaf Forest Using LPJ-GUESS

Climate warming significantly impacts Arctic vegetation, yet its future role as a carbon sink or source is unclear. We analyzed vegetation growth and carbon exchange in Alaska’s tundra and needle leaf forests using the LPJ-GUESS model. The accuracy of the model is verified using linear regression of the measured data from 2004 to 2008, and the results are significantly correlated, which proves that the model is reliable, with R2 values of 0.51 and 0.46, respectively, for net ecosystem carbon exchange (NEE) at the tundra and needle leaf forest sites, and RMSE values of 22.85 and 23.40 gC/m2/yr for the tundra and needle forest sites, respectively. For the gross primary production (GPP), the R2 values were 0.66 and 0.85, and the RMSE values were 39.25 and 43.75 gC/m2/yr at the tundra and needle leaf forest sites, respectively. We simulated vegetation carbon exchanges for 1992–2014 and projected future exchanges for 2020–2100 using climate variables. Under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, GPP values increase with higher emissions, while the NEE showed great fluctuations without significant differences among the three pathways. Our results showed although climate warming can benefit vegetation growth, net carbon assimilation by vegetation may not increase accordingly in the future.

An inflection point-based method for estimating metrics of mangrove phenology combining climatic factors and Landsat NDVI time series

Abstract The present research evaluated the prospects of utilizing rainfall and temperature combined with Landsat-8 derived HANTS (Harmonic ANalysis of Time Series) reconstructed NDVI for estimating the metrics of the mangrove phenology. The selected period of the study was from 2013 to 2020 for the Pichavaram mangroves of Tamil Nadu. The NDVI and ERA5 (ECMWF Re-Analysis) datasets of rainfall and temperature were the input datasets for developing the new algorithm. The ‘z-score sum’ provided a measure of the cumulative impact of rainfall and temperature, displaying its most negative value coinciding with the peak positive value of the NDVI time series datasets. The algorithm developed for phenological metrics estimation identified the common inflection points of the z-score sum and NDVI curves. The temporal analysis of metrics revealed the average Length of Season (LoS) as 230 days. The metrics also identified the drought year 2016 with the shortest LoS and the least Gross Primary Productivity (GPP) values. The analysis showed the influences of the preceding year’s monsoon rainfall on the GPP values of the later part of the phenological cycle. The temperatures during the days of PoS were found to be the optimum temperature for the growth of mangroves.

Response of Ecosystem Carbon–Water Fluxes to Extreme Drought in West Asia

Global warming has resulted in increases in the intensity, frequency, and duration of drought in most land areas at the regional and global scales. Nevertheless, comprehensive understanding of how water use efficiency (WUE), gross primary production (GPP), and actual evapotranspiration (AET)-induced water losses respond to exceptional drought and whether the responses are influenced by drought severity (DS) is still limited. Herein, we assess the fluctuation in the standardized precipitation evapotranspiration index (SPEI) over the Middle East from 1982 to 2017 to detect the drought events and further examine standardized anomalies of GPP, WUE, and AET responses to multiyear exceptional droughts, which are separated into five groups designed to characterize the severity of extreme drought. The intensification of the five drought events (based on its DS) increased the WUE, decreased the GPP and AET from D5 to D1, where both the positive and negative variance among the DS group was statistically significant. The results showed that the positive values of standardized WUE with the corresponding values of the negative GPP and AET were dominant (44.3% of the study area), where the AET values decreased more than the GPP, and the WUE fluctuation in this region is mostly controlled by physical processes, i.e., evaporation. Drought’s consequences on ecosystem carbon-water interactions ranged significantly among eco-system types due to the unique hydrothermal conditions of each biome. Our study indicates that forthcoming droughts, along with heightened climate variability, pose increased risks to semi-arid and sub-humid ecosystems, potentially leading to biome restructuring, starting with low-productivity, water-sensitive grasslands. Our assessment of WUE enhances understanding of water-carbon cycle linkages and aids in projecting ecosystem responses to climate change.

Identification of soil properties influencing primary productivity of fish ponds under red and lateritic soil zones

Aim: The present study aimed to identify the key soil factors influencing the primary productivity of water in the fish ponds situated under low productive red and lateritic soil zones. Methodology: General properties of fish pond soils (n=42) from different red and lateritic soil zones of West Bengal, India were determined along with the gross primary productivity (GPP) values of corresponding pond waters. All the soil properties were correlated with GPP values and the soil factors which were significantly correlated with GPP of pond water were further used for step down regression analysis with regard to GPP.This helped to develop a minimum data set of the key soil factors which showed maximum influence on GPP. The efficiency of the regression equation, generated with the critical soil parameters, in predicting the GPP values of other ponds was also assessed through a study on the variations in calculated and on-farm GPP values of eight fish ponds. Results: Among all the studied soil properties, pH and availability of three major nutrients viz. N, P and K were observed to contribute 84.15% variations in gross production of primary fish food organisms in these pond environment. Of these 4 soil properties, again, pH and available P values of the pond soils appeared to be more important. A regression equation was also developed to predict the GPP of such pond water using soil pH and available P values only. This equation showed a precision range of 83.0 to 99.7% and was found to be statistically at par with the GPP values observed under actual pond condition. Interpretation: High efficiency in predictability of pond GPP values using the minimum data set of two key soil factors viz. soil pH and available P indicates that proper management of these productivity attributing soil properties will be particularly helpful to improve the primary productivity levels of the predominantly low yielding fish ponds under the red and lateritic soil zones. Key words: Fish ponds, Minimum data set, Productivity attributes, Red and lateritic soil zones, Soil factors

Functioning of a canopy-dominated intertidal community during emersion: highly productive but heterotrophic at the annual scale

In order to address lack of data regarding coastal carbon budgets, we estimated the annual metabolic carbon budget of an intertidal rocky reef macroalgal community during emersion. This budget is based on direct in situ measurements during emersion and establishes the seasonal variations of the photosynthetic parameters of such a community. CO2 fluxes were measured hourly to study the response of community gross primary productivity (GPP) to irradiance and the variation of GPP and community respiration (CR) over the emersion period at different times of the year. These were combined together with existing monthly measures of GPP and CR hourly rates to model the variations of these fluxes as a function of irradiance and the tidal cycle throughout an entire calendar year. Daily, monthly and annual values of GPP, CR and net primary productivity (NPP) were calculated with a relatively low sensitivity to any of the parameters used. While GPP fluxes show comparable orders of magnitude to those measured in other systems, higher CR fluxes lead to a heterotrophic system during emersion, both under measured (NPP = −299 gC m−2 year−1) and theoretical irradiances (NPP = −119 gC m−2 year−1). This heterotrophy is directly linked to the light availability, varying according to combined daily, tidal and seasonal cycles, and to temperature at the seasonal scale. Measurements performed in situ at the community scale integrated interactions that are otherwise absent at the individual scale. This gives access to aspects of the functioning that cannot be otherwise identified.

Quantitative assessment of the scale conversion from instantaneous to daily GPP under various sky conditions based on MODIS local overpassing time

ABSTRACT With the increasing frequency of extreme events, daily gross primary productivity (GPP) is necessary to be accurately assessed to determine when and how much it is affected. Fluctuating environmental conditions contribute to diverse diurnal photosynthetic patterns influenced by changing atmospheric factors, including solar radiation, CO2 concentrations, and leaf temperature. This complexity underscores the challenge of accurately estimating daily GPP. We quantitatively assessed three temporal upscaling approaches – cosine of the solar zenith angle, extraterrestrial solar irradiance, and photosynthetic active radiation(PAR) – under varying sky conditions. Additionally, we introduced a novel correction method for universal temporal upscaling ratios. Instantaneous GPP values from the FLUXNET2015 dataset, acquired around the MODIS overpassing time, were utilized. The upscaled daily GPP exhibited minimal deviation from the half-hourly GPPs collected between 11 am and 1 pm, with increased discrepancies for GPPs later in the afternoon. The PAR-based approach demonstrated superior accuracy in the afternoon, effectively capturing incoming radiation changes due to clouds. Instant environmental variables-GPP relationships were weak under clear skies but exhibited moderate-to-high positive correlations under cloudy conditions. Analyzing the impact of the diffuse ratio of incoming photosynthetic active radiation on instantaneous GPP revealed limited enhancement at short time scales. On a daily scale, all three temporal upscaling approaches, under different ranges of clearness index, consistently underestimated daily GPP. We proposed a novel correction method, normalizing the difference between maximum and minimum air temperature in a day, notably reduced errors by approximately 10.69 and 21.07 gC m−2 d−1 for cosine of the solar zenith angle and extraterrestrial solar irradiance-based temporal upscaling approaches. We recommend adopting the corrected temporal upscaling factor globally due to its simplicity and improved accuracy.

Gross primary production of Mediterranean watersheds: Using isotope mass balance approach to improve estimations

AbstractGlobal‐scale estimates of carbon fluxes from satellite data‐driven models are constrained by considerable uncertainties regarding Gross Primary Production (GPP) and the lack of the watershed‐scale measurements required for model calibration. Recently conducted global modelling efforts indicate that semiarid ecosystems dominate the increasing trends and inter‐annual variation of net CO2 exchange with the atmosphere, but semi‐arid regions have received little attention with regard to GPP estimation. In this study, we used the distinct isotope effect of transpiration and evaporation to calculate transpiration losses and subsequently CO2 uptake by terrestrial vegetation through the water and carbon cycle using the water use efficiency of plants. By studying two Mediterranean watersheds with contrasted environmental conditions over several hydrological years, we found a strong dependence of GPP on annual and seasonal water availability. The results demonstrated that when compared to GPP values obtained in worldwide biomes using biological methods, our isotope approach was validated, highlighting the limitations of satellite‐data‐driven models like MODIS in capturing the impact of water stress on photosynthesis and GPP estimates. These results encourage investigation of GPP by the isotope mass balance approach where direct carbon flux measurements are rare or absent in order to help to substantiate, modify or shed doubt on interpolated GPP for those regions and achieve consensus on global GPP estimates. Given the relevant role of semi‐arid ecosystems in the global carbon balance as well as the limitation of existing data sets, our improved method based on the isotope mass balance approach helps to obtain rapid and affordable estimates of GPP for semi‐arid ecosystems.

Sensitivities of Vegetation Gross Primary Production to Precipitation Frequency in the Northern Hemisphere from 1982 to 2015

Vegetation of the Northern Hemisphere plays a vital role in global ecosystems and the carbon cycle. Variations in precipitation profoundly affect vegetation productivity, plant growth, and species communities. Precipitation frequency directly controls soil moisture availability, which has an impact on the vegetation carbon sink. However, it is unclear how precipitation frequency affects the vegetation productivity of different land cover types in different seasons. In this study, the sensitivities of the gross primary production (GPP) of six vegetation types (forest, cropland, grassland, shrubland, tundra and barren land) in response to the frequency of five categories of precipitation (trace: 0.1–5 mm/day, small: 5–10 mm/day, moderate: 10–15 mm/day, heavy: 15–20 mm/day, and very heavy: >20 mm/day) were analyzed based on the XGBoost model. The results showed that, between 1982 and 2015, precipitation frequency declined in most land cover types but increased significantly in the pan-Arctic. Differences in the sensitivity to precipitation frequency were observed between seasons and precipitation categories in northern latitudes. The GPP values of forest and barren land vegetation were less sensitive to precipitation frequency than grassland, shrubland and tundra. This may be related to different vegetation community structures and underlying surfaces and gradually increasing drought resistance capability. The sensitivity to precipitation frequency declined for moderate and heavy precipitation in cropland, but it increased in winter. As the frequency of trace precipitation diminishes in winter, the sensitivity of each vegetation type reduces by an average of 0.03%/decade. Conversely, the sensitivities to small and moderate rain increase by 0.01%/decade and 0.02%/decade, respectively, for ecosystems such as cultivated land, forests, and shrubs. However, shrubs and tundra exhibit distinct behaviors, where shifts in precipitation frequency align directly with trends in sensitivity. These results show that the frequency of precipitation significantly affects vegetation productivity and has different sensitivities, and vegetation shows different feedback mechanisms in the face of environmental changes.

Evaluating the effectiveness of different variable retention harvesting treatments on forest carbon uptake using remote sensing

Variable retention harvesting (VRH) is an ecologically based forest management practice applied to emulate natural post-disturbance residual canopy structure and increase the biodiversity and resilience of a regenerating stand. The pattern and density of canopy retention also influences the productivity, mortality, and carbon (C) sequestration rates of residual trees. In this study, we used high-resolution satellite and drone remote sensing data to evaluate the effect of five different VRH treatments on growth and C uptake of a 90-year-old red pine (Pinus resinosa Ait.) plantation forest in southern Ontario, Canada. The treatments included four different combinations of harvesting intensity residual tree distribution including 33% aggregate retention (33A), 55% aggregate retention (55A), 33% dispersed retention (33D), and 55% dispersed retention (55D) and unharvested control (CN) each replicated four times in 1 ha plots. Satellite- and drone-derived normal difference vegetation index (NDVI) and gross primary productivity (GPP) were estimated for each treatment during the growing seasons from 2010 to 2020. Over this period, observed mean daily NDVI values ranged from 0.25 to 0.86 among treatments, where the 55D treatment consistently showed the highest NDVI values. Overall, the highest mean daily GPP values were observed in the CN treatment, followed by the 55D, 55A, 33D, and 33A treatments. Remote sensing-derived mean annual GPP for the entire 20 ha study site was 1651 ± 89 g C m−2 year−1, with a range of 1407–1864 g C m−2 year−1 from 2010 to 2020. Satellite-derived annual GPP values were linearly related with observed annual GPP (R2 = 0.88, p = 0.032) measured using the eddy covariance technique in an adjacent white pine plantation of similar age and height over the study period. Study results suggested that VRH treatments that create a uniformly dispersed residual canopy retaining more than half of the initial basal area (e.g. 55D) is a viable forest management practice where optimizing forest growth and C uptake is a primary management objective. Our study will help forest managers and researchers to develop methodologies to evaluate the effectiveness of forest management practices, tailor them to achieve climate mitigation and adaptation goals and to develop forest management pathways for nature-based climate solutions.

Dynamics of major environmental disasters involving fire in the Brazilian Pantanal

The 2020 environmental catastrophe in Pantanal has highlighted the fragility of environmental policies and practices for managing and fighting fires in this biome. Therefore, it is essential to know the causes and circumstances that potentiate these fires. This study aimed to: (I) assess the relationship between fire foci and carbon absorption (GPP), precipitation, and carbon dioxide (CO2) flux; (ii) analyze vegetation recovery using the differenced normalized burn ratio (ΔNBR) in Brazilian Pantanal between 2001 and 2022; and (iii) identify priority areas, where the highest intensities of fire foci have occurred, in order to guide public policies in Brazil to maintain local conservation. To this purpose, fire foci were detected using data from the MODIS MOD14/MYD14 algorithm, annual precipitation with CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), and CO2 flux using the MODIS/MODO9A1 product, and Gross Primary Production (GPP) with the MODIS/MOD17A2 product. The severity of the burned area was also assessed using the ΔNBR index and the risk areas were determined using the averages of these images. During the time series studied, a total of 300,127 fire foci were detected throughout the Pantanal, where 2020 had the highest number of foci and the lowest accumulated precipitation. The years with the highest precipitation were 2014 and 2018. The year 2018 was also the second year with the highest GPP value. The Pettit test showed a trend for 2008 and 2011 as the points of change in the CO2 flux and GPP variables. Principal component analysis clustered fire foci and precipitation on opposite sides, as well as GPP and CO2 flux, while ΔNBR clustered HS, MHS and MLS classes with the years 2020, 2019, 2002 and 2021. There was a high negative correlation between fire foci × rainfall and GPP × CO2 flux. The years with the largest areas of High severity (HS), Moderate-high severity (MHS) and Moderate-low severity (MLS) classes were 2020 and 2019, respectively. The most vulnerable areas for severe fires were the municipalities of Cáceres, Poconé, and Corumbá. The major fire catastrophe in 2020 is correlated with the low precipitation in 2019, the high precipitation in 2018, and the increased GPP, as well government policies unfavorable to the environment.

Exploring carbon sequestration in broad-leaved Korean pine forests: Insights into photosynthetic and respiratory processes

A comprehensive understanding of carbon assimilation and sequestration in broad-leaved Korean pine forests is crucial for accurately estimating this significant aspect of temperate forests at a regional scale. In this study, we introduced a high-temporal resolution model designed for carbon assimilation insights at the plot scale, focusing on specific parameters such as leaf area dynamics, vertical leaf distribution, photosynthetically active radiation (PAR) fluctuations, and the photosynthetic traits of tree species. The findings reveal that most tree species in broad-leaved Korean pine forests exhibit an inverted U-shaped pattern in leaf area dynamics, with shorter leaf drop periods than leaf expansion events. Leaf distribution varies significantly among different canopy heights, with approximately 80 % of the leaves above 15 m. PAR decreases as canopy height decreases, with PAR at 25 m accounting for about 60 % of the PAR above the canopy. Our framework incorporates a leaf-scale light-response curve and empirical photosynthesis-temperature relationships to estimate forest carbon assimilation on daily and hourly scales accurately. Using the model, we assess the gross primary productivity (GPP), leaf net photosynthetic assimilation (LNPA), and carbon increment (ΔC) of broad-leaved Korean pine forests from 2017 to 2020. The results demonstrate GPP, LNPA, and ΔC values of 21.4 t·ha−1·a−1, 17.4 t·ha−1·a−1, and 4.0 t·ha−1·a−1, respectively. Regarding efficiency, GPP, LNPA, and ΔC per square meter of leaf per year are 179 g, 146 g, and 33 g, respectively. Notably, tree species in the canopy layer of the forest exhibit significantly higher efficiency than those in the understory layer. This research significantly contributes to our understanding of carbon cycling and the responses of forest ecosystems to climate change. Moreover, it provides a practical tool for forest management and the development of carbon sequestration strategies.

Diel variations in dissolved oxygen concentration and algal growth in the Laver pit lake, northern Sweden

The diel oxygen technique relying on automated in-situ measurements of dissolved oxygen was used as an indicator of seasonal and diurnal variations of photosynthesis in the circumneutral Laver pit lake in northern Sweden. From July to September 2017, surface water temperature, electrical conductivity, pH, and dissolved oxygen were continuously measured at a time resolution of 30 min using sensors mounted on a floating buoy. The data could be monitored in real-time using a browser-based software and permitted calculation of gross primary production (GPP), net ecosystem production (NEP), and respiration (R) in the lake. The dissolved O2 concentration showed a consistent pattern of diel variations that reached up to 0.5 mg L−1 during the warmer summer period (July–August). Towards the end of August these variations decreased in magnitude and remained at ∼0.1 mg L−1 throughout September. pH showed diel variations that mimicked those of dissolved O2, with maximum daily variations of 0.4–0.5 pH units during July and August. A seven-day moving average of GPP showed a peak during July to mid-August, and the maximum GPP value of 0.55 mg O2 L−1 day−1 is similar to those found in natural oligotrophic lakes. A phytoplankton sample showed a total biomass concentration of 24 μg L−1, with the species Chrysophyceae, Chlorophyta, and Bacillariophyta occurring in the water. Diel oxygen data indicated that respiration by autotrophs and respiration of autochthonous labile organic matter by heterotrophs dominated in the lake, as is often the case in lakes where planktonic primary production is the main supplier of labile organic carbon. A close coupling between R and GPP suggests that nearly all GPP was respired in the epilimnion. The study shows that the diel oxygen technique can be used for real-time monitoring of seasonal and diurnal variations of dissolved oxygen and pH in pit lakes. This would be a useful technique in pit lake remediation projects where fertilization is used to stimulate algal growth and metal sequestering by algae.

An Empirical Model of Gross Primary Productivity (GPP) and Relations between GPP and Its Driving Factors, Biogenic Volatile Organic Compounds in a Subtropical Conifer Plantation in China

Measurements of net ecosystem exchange (NEE), solar global radiation, photosynthetically active radiation (PAR) and meteorological parameters were carried out on a subtropical conifer plantation in China from 2013 to 2016. These observations were used to develop and evaluate an empirical model of gross primary production (GPP) (EMGPP) with 3-factor and 2-factor models. Using a 3-factor model, the simulated hourly GPP values were consistent with observations with a relative bias of 9.96% and normalized mean square error values of 0.07 mg CO2 m−2 s−1 for the scattering factor S/Q (S and Q are diffuse and global solar radiation) < 0.5 and 15.52% and 0.15 mg CO2 m−2 s−1 for S/Q ≥ 0.5. Validations of the EMGPP for hourly, daily, monthly, and annual GPP values were carried out and showed that both 3-factor and 2-factor EMGPP models can accurately capture diurnal, seasonal and interannual variations in GPP, but most simulated GPP overestimated the observed value. When the scattering factor is not available, the 2-factor EMGPP can be used. The EMGPP using 3-factor and 2-factor models was applied to simulate GPP under all sky conditions from 2013–2016, and the estimated GPP were in reasonable agreement with the measured values and showed systematic overestimations of 31% and 29% for mean hourly GPP and 41% and 29% for annual amounts, respectively. The sensitivity test demonstrated that GPP values were more sensitive to changes in PAR than to changes in water vapor and scattering factor at low S/Q, but were more sensitive to changes in water vapor than to PAR and S/Q at high S/Q. The sensitivity test revealed some mechanisms of GPP and its related processes, including the relationships between GPP and scattering of PAR, GPP and water vapor, which were in good agreement with other observations and model studies. An empirical model based on PAR energy balance can better describe the multiple interactions between GPP and its driving factors (PAR, water vapor, S/Q). The ratio of the emissions of biogenic volatile organic compounds (BVOCs) to net ecosystem exchange clearly varied between forests in different climate zones.

Regional‐Scale Wilting Point Estimation Using Satellite SIF, Radiative‐Transfer Inversion, and Soil‐Vegetation‐Atmosphere Transfer Simulation: A Grassland Study

AbstractAlthough water availability strongly controls gross primary production (GPP), the impact of soil moisture content (SMC) (wilting point) is poorly quantified on regional and global scales. In this study, we used 10 years of observations of solar‐induced chlorophyll fluorescence (SIF) from the Greenhouse gases Observing Satellite (GOSAT) satellite to estimate the wilting point of a semiarid grassland on the Mongolian Plateau. Radiative‐transfer model inversion and soil‐vegetation‐atmosphere transfer simulation were sequentially conducted to distinguish the drought impacts on plant physiology from the changes in the leaf‐canopy optical properties. We modified an existing inversion algorithm and the widely used Soil‐Canopy Observation of Photosynthesis and Energy fluxes model to adequately evaluate dryland features, for example, sparse canopy and strong convection. The modified model, with retrieved parameters and calibration to GOSAT SIF, predicted realistic GPP values. We found that (a) the SIF yield estimated from GOSAT showed a clear sigmoidal pattern in relation to drought, and the estimated wilting point matched ground‐based observations in the literature within ∼0.01 m3 m−3 for the SMC, (b) tuning the maximum carboxylation rate improved the SIF prediction after considering the changes in the leaf‐canopy optical properties, implying that GOSAT detected drought stress in leaf‐level photosynthesis, and (c) the surface energy balance significantly impacted the grassland's SIF; the modified model reproduced observed SIF well (mean bias = 0.004 mW m−2 nm−1 sr−1 in summer), whereas the original model predicted substantially low values under weak horizontal wind conditions. Some model‐observation mismatches in the SIF suggest that more research is needed for fluorescence parametrization (e.g., photoinhibition) and for additional observation constraints.

Identifying the Responses of Vegetation Gross Primary Productivity and Water Use Efficiency to Climate Change under Different Aridity Gradients across China

Despite the fact that gross primary productivity (GPP) and water use efficiency (WUE) have been widely used as indicators to evaluate the water-carbon cycle, uncertainties exist in the patterns of GPP and WUE responses to climate variability along different aridity gradients. In this study, the aridity index was used to divide China into four arid-humid zones. The spatiotemporal variability of multiple vegetation types GPP and WUE in response to climate change under different arid-humid zones were investigated based on remote sensing data. The results indicated that the increasing trend of WUE in the four arid-humid zones of China was less pronounced than GPP from 2001 to 2021. The GPP value decreased gradually from the humid to the arid zone, and the WUE value in the arid zone was slightly higher than in the semi-arid zone. The GPP of all vegetation types in China showed a tendency to increase, while shrubland and wetland WUE tended to decrease. The major vegetation types (e.g., forest, cropland and grassland) in each aridity gradient contributed to the changes in local GPP and WUE. However, in individual arid-humid zones, wetland and shrubland also exhibited high GPP and WUE values that were not inferior to forest and cropland. Temperature and precipitation were the main climatic factors responsible for the increase in vegetation GPP in different aridity gradients, with a higher positive correlation for temperature than precipitation. WUE showed a distinct positive and negative correlation with the thermal factors (temperature and net radiation) and the moisture factors (precipitation and relative humidity); this pattern was more pronounced in the humid and semi-humid zones. Net radiation and precipitation may be the main climatic factors causing a slight upward trend in WUE across the arid-humid zones, while the decrease in shrubland and wetland WUE may be related to relative humidity and precipitation.

Parameter δ18O in the Marine Environment Ecosystem Studies on the Example of the Barents Sea

The isotopic parameter δ18O in oceanography is used for the calculation of mixing proportions of the Atlantic, rivers, and melted waters as well as the relative content of ice-forming waters. Using these values, as well as nutrient concentrations in the nuclei of these waters, it is possible to calculate a conservative concentration, which is determined only by the water’s mixing. These values are the points of reference for water nutrients reserve changes at the expense of the «nonconservative» factors (photosynthesize and geochemical sedimentation). This approach in the calculation of primary production allows moving from the use of the constant stoichiometric ratios to the floating ones, which is observed in the actual ecosystem. Based on the proposed method, the nutrient consumption features and production changes in the Barents Sea were studied. According to the maximum value of production in the summer, the following areas were identified—an early autumn period in the Barents Sea, an area with the maximum values of gross primary production (GPP > 150 g C m−2), three regions with increased values (GPP > 100 g C m−2), and two regions with relatively low values (GPP < 100 g C m−2). The use of this technique with a long-term data series available on salinity and the content of nutrients will allow the future to proceed to the study of the climatic variability of these parameters, ranging from the nutrient consumption variability to the productivity variability of the study area.

石羊河流域水分利用效率及其对饱和水汽压差的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 石羊河流域水分利用效率及其对饱和水汽压差的响应 DOI: 10.5846/stxb202111243322 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学青年基金项目(41705062,32071606); 甘肃省气象局研究型业务重点项目(ZD2021-02); 云南省教育厅项目"云南省高校山地实景点云数据处理及应用重点实验室" Spatial-temporal dynamics of water use efficiency and responding to vapor pressure deficit in Shiyang River Basin, northwestern China Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:水分利用效率(WUE)是叶片通过光合作用调节水分生理过程的指标,是联系生态系统碳循环与水循环关系的关键,反映了植被生态系统对立地环境快速调整和资源的变化适应策略。基于卫星遥感和地面观测数据,利用光能利用率模型和蒸散发经验估算模型,模拟石羊河流域2000-2019年植被总初级生产力(GPP)和蒸散发(ET)数据,估算2000-2019年不同植被类型的WUE空间分布特征,研究GPP/ET/WUE与饱和水汽压差(VPD)的相关性,探讨干旱区不同类型植被对水分利用及胁迫的适应策略。结果表明:(1) 2000-2019年石羊河流域植被WUE、GPP和ET的平均值分别为0.80 gC m-2 mm-1、256.52 gC/m2和302.52 mm,其三者的空间分布特征表现为"南高北低",即由流域源头至下游逐渐减少的空间分布。(2) 近20年内,流域内WUE、GPP和ET的变化率的平均值分别为0.017 gC m-2 mm-1 a-1,6.99 gC m-2 a-1和3.80 mm/a,流域总体呈现波动上升的趋势,但城区和民勤耕地-荒漠交接区呈不同程度的减少趋势。(3) 流域内不同类型植被的WUE平均值关系为:森林>农作物>草地>灌丛>荒漠植被>湿地植被,WUE增加速度的平均值关系为:农作物>森林>草地>灌丛>荒漠植被>湿地植被,与GPP基本一致,其中ET在灌丛、荒漠植被、湿地植被地区呈现降低趋势。(4) 研究区内GPP/ET/WUE与VPD相关性的空间分布特征与石羊河径流方向具有高度一致性,WUE与VPD相关性分布特征受土地利用以及径流方向影响显著。WUE与VPD呈正相关的区域主要分布在河西走廊绿洲东部和荒漠区东部,呈负相关区域主要分布在祁连山高海拔地区、河西走廊绿洲中部和荒漠区西部。因此,正确揭示内陆河植被GPP/ET/WUE的空间分异以及变化趋势及其对驱动因素VPD的响应,是了解流域尺度中干旱区植被对全球干旱加剧的适应性策略前提,进而为生态保护提供决策服务。 Abstract:Water use efficiency (WUE) is the regulation index of leaf photosynthesis on the water physiological process, as the key to link the relationship between the ecosystem carbon cycle and the water cycle, and directly reflects the rapid adjustment of the ecosystem to the site environment and the adaptation strategy of resource changes. The Gross primary production (GPP) temporal and spatial characteristics derived from the data of MODIS-NDVI by the Light Energy Utilization Model, and the Evapotranspiration (ET) temporal and spatial characteristics derived from the meteorological data by the Thornthwaite Evapotranspiration Model during 2000-2019 in Shiyang River Basin (SRB). In this research, we estimated the spatial pattern and temporal variations of the GPP, ET and WUE in different vegetation types from 2000 to 2019, investigated the co-relationship between GPP/ET/WUE and Vapor pressure deficit (VPD), and discussed the response of adaptation strategies for water utilization and stress in the arid area among the different vegetation. The results show that: (1) from 2000 to 2019, the average annual value of total WUE, GPP, and ET in SRB were 0.80 gC m-2 mm-1, 256.52 gC/m2, and 302.52 mm, respectively; The spatial patterns of average annual WUE, GPP and ET in the SRB's vegetated areas varied widely, and the values decreased from upstream on the south side of the Qilian Mountains and middle to downstream on the north side of the desert. (2) During the 20 years, the average slope of WUE, GPP, and ET showed an obvious upward trend in almost whole basin, with the rate of 0.017 gC m-2 mm-1 a-1, 6.99 gC m-2 a-1 and 3.80 mm/a. The change rates of WUE, GPP and ET within the basin exhibited an upward trend, except for Liangzhou and the areas surrounding Minqin cropland according to the urbanization and industrial adjustment. (3) The WUE, GPP and ET annual average values, and slope of trends among the different land use types also varied significantly. Among various vegetation types, the highest values of WUE, GPP and ET appeared in forests, and the lowest values presented in wetlands; the highest change rate of different vegetation was forest, and the lowest one was the wetland. (4) Correlation analysis and statistical results indicated that the correlation distribution characteristics of GPP/ET/WUE and VPD in the study area were highly consistent with the runoff direction of the SRB. As the WUE was determined by GPP and ET, the correlation distribution between WUE and VPD had obviously spatial heterogeneity with the land-use and SRB runoff direction. The positive correlation was distributed in the eastern part of the Hexi Corridor oasis and the eastern desert area, and the negative correlation was distributed in the high-altitude areas of the Qilian Mountains, the middle of the Hexi Corridor oasis and the western part of the desert area. Overall, correctly revealing the spatial differentiation and changing trend of GPP/ET/WUE of inland river vegetation and its response to the driving factor VPD was the premise of understanding the adaptive strategy of vegetation in arid areas at the watershed scale to the intensification of global drought, to provide decision-making services for ecological protection. 参考文献 相似文献 引证文献

Features of Plankton Metabolism: Results of Automated Measurements in the Mozhaisk Reservoir

Plankton metabolism determines fluctuations in the oxygen concentrations of a water body, its ecological condition, and exchange of СО2 with the atmosphere. We used an automated device that allowed us to make mass measurements of intraday values of the gross primary production (GPP) and respiration (R) of plankton. During our studies of the Mozhaisk reservoir (Russia) in the summer of 2017, we established an important fact: the maximum values of GPP are observed essentially earlier in the daytime than those of R. This is explained by the fact that GPP is related to solar radiation (the maximum values are observed at noon), whereas R is related to the temperature of water, which reaches its maximum several hours after in the afternoon. As a result, the maximum value of dissolved oxygen is observed in the second half of the day, when GPP and R become even. The device we have designed may be used for continuous monitoring of metabolism of plankton and of its responses to various hydrometeorological, hydrochemical and anthropogenic impacts.

Evaluating biochemical and biophysical characteristics of tropical deciduous forests of eastern India using remote sensing and in-situ parameter estimation

Owing to such a crucial role that forests perform in an ecosystem, studying the vegetation dynamics in terms of its productivity becomes inevitable. The study aimed to assess forest productivity and biochemical variability of Dalma Wildlife Sanctuary (DWS), Eastern India coupling remote sensing and in-situ measurements of 51 samples comprising 17 different species. Vegetative Photosynthesis Model (VPM) was incorporated for measuring the gross primary productivity (GPP) using Sentinel-2A data. The result showed that microclimatic conditions that determine the nutrient content of the plant, as some plant species(Shorea robusta) present at different locations showed different concentrations of chlorophyll(25.4 mgg-1), N(2.2%), P(0.5%), and K(2.0%). The relationship between biophysical and biochemical properties of the forest was analyzed by coupling laboratory-based leaf samples analysis and satellite-based retrieval methods. High values of GPP was present in the dense forested (core) region dominated by species like Shorea robusta, Bauhinia tomentosa, Butea monosperma, Syzygium cumini, Cleistanthus collinus, Diospyros melanoxylon, etc. as compared to buffer regions. The central region of DWS dominated by dense vegetation contributed higher GPP value of 21 gCm-2day-1 to 24 gCm-2day-1. The degraded peripheral area exhibited GPP value of 8 gCm-2day-1. Shorea robusta being the most dominant species in this region, exhibited total chlorophyll of 25.4 mgg-1 (lab estimates) with a standard error of 2.0 mgg-1. Correlation analysis between Sentinel-2 satellite-based biophysical parameters and laboratory-based biochemical parameters showed a close relationship between the variables. The correlation between GPP and FAPAR was found to be more profound (R2 = 0.625), whereas GPP and LAI showed a moderate correlation of R2 = 0.58. Nitrogen and Phosphorous content in leaf samples showed a negative relationship (R2 = 0.414) indicating their individual concentration do not actuate to the coefficient of correlation. With rational limitations, the study finds wide application for studying carbon cycle and biochemical assessment in the region with remote sensing driven techniques backed by in-situ parameter estimation.