scholarly journals Spatial, Phenological, and Inter-Annual Variations of Gross Primary Productivity in the Arctic from 2001 to 2019

2021 ◽  
Vol 13 (15) ◽  
pp. 2875
Author(s):  
Dujuan Ma ◽  
Xiaodan Wu ◽  
Xuanlong Ma ◽  
Jingping Wang ◽  
Xingwen Lin ◽  
...  
Keyword(s):  
Land Cover ◽  
Carbon Cycle ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
The Arctic ◽  
Spatiotemporal Variations ◽  
Land Cover Types ◽  
Annual Variations ◽  
Terrestrial Carbon Cycle

Quantifying the spatial, seasonal (phenological), and inter-annual variations of gross primary productivity (GPP) in the Arctic is critical for comprehending the terrestrial carbon cycle and its feedback to climate warming in this region. Here, we evaluated the accuracy of the MOD17A2H GPP product using the FLUXNET 2015 dataset in the Arctic, then explored the spatial patterns, seasonal variations, and interannual trends of GPP, and investigated the dependence of the spatiotemporal variations in GPP on land cover types, latitude, and elevation from 2001 to 2019. The results showed that MOD17A2H was consistent with in situ measurements (R = 0.8, RMSE = 1.26 g C m−2 d−1). The functional phenology was also captured by the MOD17A2H product (R = 0.62, RMSE = 9 days) in the Arctic. The spatial variation of the seasonal magnitude of GPP and its interannual trends is partly related to land cover types, peaking in forests and lowest in grasslands. The interannual trend of GPP decreased as the latitude and elevation increased, except for the latitude between 62°~66° N and elevation below 700 m. Our study not only revealed the variation of GPP in the Arctic but also helped to understand the carbon cycle over this region.

scholarly journals New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity

2011 ◽  
Vol 38 (17) ◽  
pp. n/a-n/a ◽  
Author(s):  
Christian Frankenberg ◽  
Joshua B. Fisher ◽  
John Worden ◽  
Grayson Badgley ◽  
Sassan S. Saatchi ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle

scholarly journals Terrestrial Carbon Cycle Variability

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2371 ◽  
Author(s):  
Dennis Baldocchi ◽  
Youngryel Ryu ◽  
Trevor Keenan
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Carbon Cycle ◽  
Primary Productivity ◽  
Carbon Sink ◽  
Global Scale ◽  
Gross Primary Productivity ◽  
Arid Ecosystems ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle

A growing literature is reporting on how the terrestrial carbon cycle is experiencing year-to-year variability because of climate anomalies and trends caused by global change. As CO2 concentration records in the atmosphere exceed 50 years and as satellite records reach over 30 years in length, we are becoming better able to address carbon cycle variability and trends. Here we review how variable the carbon cycle is, how large the trends in its gross and net fluxes are, and how well the signal can be separated from noise. We explore mechanisms that explain year-to-year variability and trends by deconstructing the global carbon budget. The CO2 concentration record is detecting a significant increase in the seasonal amplitude between 1958 and now. Inferential methods provide a variety of explanations for this result, but a conclusive attribution remains elusive. Scientists have reported that this trend is a consequence of the greening of the biosphere, stronger northern latitude photosynthesis, more photosynthesis by semi-arid ecosystems, agriculture and the green revolution, tropical temperature anomalies, or increased winter respiration. At the global scale, variability in the terrestrial carbon cycle can be due to changes in constituent fluxes, gross primary productivity, plant respiration and heterotrophic (microbial) respiration, and losses due to fire, land use change, soil erosion, or harvesting. It remains controversial whether or not there is a significant trend in global primary productivity (due to rising CO2, temperature, nitrogen deposition, changing land use, and preponderance of wet and dry regions). The degree to which year-to-year variability in temperature and precipitation anomalies affect global primary productivity also remains uncertain. For perspective, interannual variability in global gross primary productivity is relatively small (on the order of 2 Pg-C y-1) with respect to a large and uncertain background (123 +/- 4 Pg-C y-1), and detected trends in global primary productivity are even smaller (33 Tg-C y-2). Yet residual carbon balance methods infer that the terrestrial biosphere is experiencing a significant and growing carbon sink. Possible explanations for this large and growing net land sink include roles of land use change and greening of the land, regional enhancement of photosynthesis, and down regulation of plant and soil respiration with warming temperatures. Longer time series of variables needed to provide top-down and bottom-up assessments of the carbon cycle are needed to resolve these pressing and unresolved issues regarding how, why, and at what rates gross and net carbon fluxes are changing.

scholarly journals Potential strong contribution of future anthropogenic land-use and land-cover change to the terrestrial carbon cycle

2018 ◽  
Vol 13 (6) ◽  
pp. 064023 ◽  
Author(s):  
Benjamin Quesada ◽  
Almut Arneth ◽  
Eddy Robertson ◽  
Nathalie de Noblet-Ducoudré
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Carbon Cycle ◽  
Land Cover Change ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle ◽  
Anthropogenic Land Use

scholarly journals Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system

2014 ◽  
Vol 11 (13) ◽  
pp. 3547-3602 ◽  
Author(s):  
P. Ciais ◽  
A. J. Dolman ◽  
A. Bombelli ◽  
R. Duren ◽  
A. Peregon ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Cycle ◽  
Fossil Fuel ◽  
The Arctic ◽  
Observation System ◽  
Observation Data ◽  
Current State ◽  
Spatial Coverage

Abstract. A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.

Simulating Gross Primary Productivity of vegetation under soil water stress using in-situ and reanalysis soil moisture data inputs

2020 ◽  
Author(s):  
Timothy Lam ◽  
Amos P. K. Tai
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Efficiency Coefficient ◽  
Community Land Model ◽  
Soil Water Stress ◽  
Soil Moisture Data

<p>This study utilises in-situ and reanalysis soil moisture data inputs from various sources to evaluate the effect of soil water stress on Gross Primary Productivity (GPP) of different Plant Functional Types (PFTs) using Terrestrial Ecosystem Model in R (TEMIR), which is under development by Tai Group of Atmosphere-Biosphere Interactions (Tai et al. in prep.). An empirical soil water stress function with reference to Community Land Model (CLM) Version 4.5 is employed to quantify water stress experienced by vegetation which hinders stomatal conductance and thus carboxylation rate. The model results are compared against observations at FLUXNET sites in semi-arid regions across the globe at daily timescale where in-situ GPP data is available and water stress inhibits plant functions to some extent. By dividing the soil into two layers (topsoil and root zone), GPP simulation improves significantly comparing with using single layer bulk soil (Modified Nash-Sutcliffe Model Efficiency Coefficient N increases from -0.686 to -0.586). Such upgrade is particularly substantial for vegetation with shallow roots such as grass PFTs. Despite this improvement, the model is characterised by an overall overestimation of GPP when water stress occurs, and inconsistency of accuracy subject to PFTs and degree of water stress experienced. This study informs responses of various PFTs to soil water stress, capacity of TEMIR in simulating the responses, and possible drawbacks of empirical soil water stress functions, and highlights the importance of topsoil moisture data input for vegetation drought monitoring.</p><p>Keywords: Soil water stress, Terrestrial model representation, Photosynthesis, In-situ data, Reanalysis data, FLUXNET</p>

scholarly journals A multi-method autonomous assessment of primary productivity and export efficiency in the springtime North Atlantic

2018 ◽  
Author(s):  
Nathan Briggs ◽  
Kristinn Guðmundsson ◽  
Ivona Cetinić ◽  
Eric D'Asaro ◽  
Eric Rehm ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
North Atlantic ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Test Method ◽  
Significant Advance ◽  
Diatom Bloom ◽  
Diel Cycles ◽  
Parameterized Model

Abstract. Fixation of organic carbon by phytoplankton is the foundation of nearly all open-ocean ecosystems and a critical part of the global carbon cycle. But quantification and validation of ocean primary productivity at large scale remains a major challenge, due to limited coverage of ship-based measurements and the difficulty of validating diverse measurement techniques. Accurate primary productivity measurements from autonomous platforms would be highly desirable, due to much greater potential coverage. In pursuit of this goal we estimate gross primary productivity over two months in the springtime North Atlantic from an autonomous Lagrangian float using diel cycles of particulate organic carbon derived from optical beam attenuation. We test method precision and accuracy by comparison against entirely independent estimates from a locally parameterized model based on chlorophyll α and light measurements from the same float. During nutrient replete conditions (80 % of the study period), we obtain strong relative agreement between the independent methods across an order of magnitude of productivities (r2 = 0.97), with slight under-estimation by the diel cycles method (−19 ± 5 %). At the end of the diatom bloom, this relative difference increases to −58 % for a six-day period, likely a response to SiO4 limitation, which is not included in the model. In addition, we estimate gross oxygen productivity from O2 diel cycles and find strong correlation with diel cycles-based gross primary productivity over the entire deployment, providing further qualitative support to both methods. Finally, simultaneous estimates of net community productivity, carbon export and particle size suggest that bloom growth is halted by a combination of reduced productivity due to SiO4 limitation and increased export efficiency due to rapid aggregation. After the diatom bloom, high chlorophyll α normalized productivity indicates that low net growth during this period is due to increased heterotrophic respiration and not nutrient limitation. These findings represent a significant advance in the accuracy and completeness of upper ocean carbon cycle measurements from an autonomous platform.

scholarly journals No impact of tropospheric ozone on the gross primary productivity of a Belgian pine forest

2017 ◽  
Vol 14 (7) ◽  
pp. 1839-1855 ◽  
Author(s):  
Lore T. Verryckt ◽  
Maarten Op de Beeck ◽  
Johan Neirynck ◽  
Bert Gielen ◽  
Marilyn Roland ◽  
...  
Keyword(s):  
Scots Pine ◽  
Primary Productivity ◽  
Crop Yields ◽  
Gross Primary Productivity ◽  
Carbon Uptake ◽  
Tree Seedlings ◽  
Mixing Ratio ◽  
Negative Effects ◽  
Uptake Rates

Abstract. High stomatal ozone (O3) uptake has been shown to negatively affect crop yields and the growth of tree seedlings. However, little is known about the effect of O3 on the carbon uptake by mature forest trees. This study investigated the effect of high O3 events on gross primary productivity (GPP) for a Scots pine stand near Antwerp, Belgium over the period 1998–2013. Stomatal O3 fluxes were modelled using in situ O3 mixing ratio measurements and a multiplicative stomatal model, which was parameterised and validated for this Scots pine stand. Ozone-induced GPP reduction is most likely to occur during or shortly after days with high stomatal O3 uptake. Therefore, a GPP model within an artificial neural network was parameterised for days with low stomatal O3 uptake rates and used to simulate GPP during periods of high stomatal O3 uptake. Possible negative effects of high stomatal O3 uptake on GPP would then result in an overestimation of GPP by the model during or after high stomatal O3 uptake events. The O3 effects on GPP were linked to AOT40 and POD1. Although the critical levels for both indices were exceeded in every single year, no significant negative effects of O3 on GPP were found, and no correlations between GPP residuals and AOT40 and POD1 were found. Overall, we conclude that no O3 effects were detected on the carbon uptake by this Scots pine stand.

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