scholarly journals Carbon Exchange and Accumulation in an Orinoco High Plains Native Savanna Ecosystem as Measured by Eddy Covariance

2021 ◽  
Vol 9 ◽  
Author(s):  
Luis A. Morales-Rincon ◽  
Andrea J. Hernandez ◽  
Nubia S. Rodriguez-Hernandez ◽  
Rodrigo Jimenez
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Ecosystem Respiration ◽  
High Plains ◽  
First Year ◽  
Drought Duration ◽  
C Cycle ◽  
The Impact

Savanna ecosystems cover ∼20% of the total land surface and account for ∼30% of the terrestrial global net primary production. They are also highly sensitive to climate change, since their carbon (C) sink capacity may decline under rising temperatures and irregular rainfall. These responses, which will define the future climate role of the savanna ecosystems, are currently not well understood. The Colombian Orinoco River basin (“Llanos”) natural savannas are being rapidly converted to agriculture. The impact of this transformation on C fluxes and accumulation is not clear. It is thus urgent to understand the Llanos natural savanna ecosystem services, including their C cycle and underlying mechanisms. Here we report and analyze 2 years of measurements of carbon dioxide fluxes from a naturally-restored (secondary) Llanos High Plains savanna ecosystem, using eddy covariance. Meteorological conditions, particularly rainfall, were quite variable during the measurement period. During the first year of measurements, the savanna was a weak carbon source (35 gC m−2), while during the second year, the system was a comparatively strong carbon sink (−273 gC m−2), despite receiving less rainfall than during the first year. As expected, the savanna net ecosystem exchange (NEE) was highly dependent on global solar radiation, soil water content, and ecosystem respiration. We found that after ∼10 days of nominal drought, i.e., with less than ∼5 mm/day of precipitation, the NEE became highly dependent on drought duration. The ecosystem reached a critical condition of low photosynthetic activity after ∼60 days of nominal drought. Based on these findings, we developed and applied a simple standard meteorology-based model that properly reproduced the observations. Our results indicate that a shift to a climate with similar total precipitation but split into extreme dry and wet seasons might eventually suppress the savanna C uptake capacity.

scholarly journals A successful prediction of the record CO 2 rise associated with the 2015/2016 El Niño

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170301 ◽  
Author(s):  
Richard A. Betts ◽  
Chris D. Jones ◽  
Jeff. R. Knight ◽  
Ralph. F. Keeling ◽  
John. J. Kennedy ◽  
...  
Keyword(s):  
El Niño ◽  
El Nino ◽  
Carbon Sink ◽  
Carbon Dioxide Concentration ◽  
Anthropogenic Emissions ◽  
First Year ◽  
Mauna Loa ◽  
Simple Extrapolation ◽  
Biosphere Model ◽  
The Impact

In early 2016, we predicted that the annual rise in carbon dioxide concentration at Mauna Loa would be the largest on record. Our forecast used a statistical relationship between observed and forecast sea surface temperatures in the Niño 3.4 region and the annual CO 2 rise. Here, we provide a formal verification of that forecast. The observed rise of 3.4 ppm relative to 2015 was within the forecast range of 3.15 ± 0.53 ppm, so the prediction was successful. A global terrestrial biosphere model supports the expectation that the El Niño weakened the tropical land carbon sink. We estimate that the El Niño contributed approximately 25% to the record rise in CO 2 , with 75% due to anthropogenic emissions. The 2015/2016 CO 2 rise was greater than that following the previous large El Niño in 1997/1998, because anthropogenic emissions had increased. We had also correctly predicted that 2016 would be the first year with monthly mean CO 2 above 400 ppm all year round. We now estimate that atmospheric CO 2 at Mauna Loa would have remained above 400 ppm all year round in 2016 even if the El Niño had not occurred, contrary to our previous expectations based on a simple extrapolation of previous trends. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

scholarly journals Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

scholarly journals Precipitation legacy effects on dryland ecosystem carbon fluxes: direction, magnitude and biogeochemical carryovers

2016 ◽  
Vol 13 (2) ◽  
pp. 425-439 ◽  
Author(s):  
W. Shen ◽  
G. D. Jenerette ◽  
D. Hui ◽  
R. L. Scott
Keyword(s):  
Plant Biomass ◽  
Net Primary Production ◽  
Ecosystem Respiration ◽  
Ecosystem Dynamics ◽  
Legacy Effects ◽  
Previous Period ◽  
Legacy Effect ◽  
Ecosystem Production ◽  
Legacy Impacts ◽  
The Impact

Abstract. The precipitation legacy effect, defined as the impact of historical precipitation (PPT) on extant ecosystem dynamics, has been recognized as an important driver in shaping the temporal variability of dryland aboveground net primary production (ANPP) and soil respiration. How the PPT legacy influences whole ecosystem-level carbon (C) fluxes has rarely been quantitatively assessed, particularly at longer temporal scales. We parameterized a process-based ecosystem model to a semiarid savanna ecosystem in the southwestern USA, calibrated and evaluated the model performance based on 7 years of eddy-covariance measurements, and conducted two sets of simulation experiments to assess interdecadal and interannual PPT legacy effects over a 30-year simulation period. The results showed that decreasing the previous period/year PPT (dry legacy) always increased subsequent net ecosystem production (NEP) whereas increasing the previous period/year PPT (wet legacy) decreased NEP. The simulated dry-legacy impacts mostly increased subsequent gross ecosystem production (GEP) and reduced ecosystem respiration (Re), but the wet legacy mostly reduced GEP and increased Re. Although the direction and magnitude of GEP and Re responses to the simulated dry and wet legacies were influenced by both the previous and current PPT conditions, the NEP responses were predominantly determined by the previous PPT characteristics including rainfall amount, seasonality and event size distribution. Larger PPT difference between periods/years resulted in larger legacy impacts, with dry legacies fostering more C sequestration and wet legacies more C release. The carryover of soil N between periods/years was mainly responsible for the GEP responses, while the carryovers of plant biomass, litter and soil organic matter were mainly responsible for the Re responses. These simulation results suggest that previous PPT conditions can exert substantial legacy impacts on current ecosystem C balance, which should be taken into account while assessing the response of dryland ecosystem C dynamics to future PPT regime changes.

scholarly journals Eddy covariance carbon flux in a scrub in the Mexican highland

2020 ◽  
Author(s):  
Aurelio Guevara-Escobar ◽  
Enrique González-Sosa ◽  
Mónica Cervantes-Jiménez ◽  
Humberto Suzán-Azpiri ◽  
Mónica Elisa Queijeiro-Bolaños ◽  
...  
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Vegetation Index ◽  
Carbon Sink ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Net Ecosystem Exchange ◽  
R Package ◽  
Dark Cycle ◽  
Remote Sensors

Abstract. Vegetation fixes C in its biomass through photosynthesis or might release it into the atmosphere through respiration. Measurements of these fluxes would help us understand ecosystem functioning. The eddy covariance technique (EC) is widely used to measure the net ecosystem exchange of C (NEE) which is the balance between gross primary production (GPP) and ecosystem respiration (Reco). Orbital satellites such as MODIS can also provide estimates of GPP. In this study, we measured NEE with the EC in a scrub at Bernal in Mexico, and then partitioned into gross primary production (GPP-EC) and Reco using the recent R package Reddyproc. Measurements of GPP-EC were related to the estimates from the MODIS satellite provided in product MOD17A2H, which contains data of the gross primary productivity (GPP-MODIS). The Bernal site was a carbon sink despite it was an overgrazed site, the average NEE during fifteen months of 2017 and 2018 was −0.78 g C m−2 d−1 and the flux was negative in all measured months. The GPP-MODIS underestimated the ground data when representing the relation with a Theil-Sen regression: GPP-EC = 1.866 + 1.861 GPP-MODIS; an ordinary less squares regression had similar coefficients and the R2 was 0.6. Although cacti (CAM), legume shrubs (C3) and herbs (C3) had a similar vegetation index, the nighttime flux was characterized by positive NEE suggesting that the photosynthetic dark-cycle flux of cacti was lower than Reco. The discrepancy among the GPP flux estimates stresses the need to understand the limitations of EC and remote sensors, while incorporating complementary monitoring and modelling schemes of nighttime Reco, particularly in the presence of species with different photosynthetic cycles.

scholarly journals Impact of Surface Albedo Assimilation on Snow Estimation

2020 ◽  
Vol 12 (4) ◽  
pp. 645 ◽  
Author(s):  
Sujay Kumar ◽  
David Mocko ◽  
Carrie Vuyovich ◽  
Christa Peters-Lidard
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Surface Albedo ◽  
Land Surface Model ◽  
Snow Accumulation ◽  
High Plains ◽  
Surface Model ◽  
Fractional Snow Cover ◽  
The Impact

Surface albedo has a significant impact in determining the amount of available net radiation at the surface and the evolution of surface water and energy budget components. The snow accumulation and timing of melt, in particular, are directly impacted by the changes in land surface albedo. This study presents an evaluation of the impact of assimilating Moderate Resolution Imaging Spectroradiometer (MODIS)-based surface albedo estimates in the Noah multi-parameterization (Noah-MP) land surface model, over the continental US during the time period from 2000 to 2017. The evaluation of simulated snow depth and snow cover fields show that significant improvements from data assimilation (DA) are obtained over the High Plains and parts of the Rocky Mountains. Earlier snowmelt and reduced agreements with reference snow depth measurements, primarily over the Northeast US, are also observed due to albedo DA. Most improvements from assimilation are observed over locations with moderate vegetation and lower elevation. The aggregate impact on evapotranspiration and runoff from assimilation is found to be marginal. This study also evaluates the relative and joint utility of assimilating fractional snow cover and surface albedo measurements. Relative to surface albedo assimilation, fractional snow cover assimilation is found to provide smaller improvements in the simulated snow depth fields. The configuration that jointly assimilates surface albedo and fractional snow cover measurements is found to provide the most beneficial improvements compared to the univariate DA configurations for surface albedo or fractional snow cover. Overall, the study also points to the need for improving the albedo formulations in land surface models and the incorporation of observational uncertainties within albedo DA configurations.

scholarly journals Impacts of active retrogressive thaw slumps on vegetation, soil, and net ecosystem exchange of carbon dioxide in the Canadian High Arctic

2017 ◽  
Vol 3 (2) ◽  
pp. 179-202 ◽  
Author(s):  
Alison E. Cassidy ◽  
Andreas Christen ◽  
Greg H.R. Henry
Keyword(s):  
Eddy Covariance ◽  
Ecosystem Respiration ◽  
Net Ecosystem Exchange ◽  
Growing Season ◽  
High Arctic ◽  
Vegetation Coverage ◽  
Soil Conditions ◽  
Soil Temperatures ◽  
The Impact ◽  
Chamber Measurements

Retrogressive thaw slumps (RTS) are permafrost disturbances common on the Fosheim Peninsula, Ellesmere Island, Canada. During the 2013 growing season, three different RTS were studied to investigate the impact on vegetation composition, soil, and growing season net ecosystem exchange (NEE) of CO2 by comparing to the adjacent undisturbed tundra. Eddy covariance and static chamber measurements were used to determine NEE and ecosystem respiration (Re), respectively. Vegetation cover was significantly lower in all active disturbances, relative to the surrounding tundra, and this affected the overall impact of disturbance on CO2 fluxes. Disturbances were characterized by greater Re compared to surrounding undisturbed tundra. Over the mid-growing season (34 days), eddy covariance NEE measurements indicated that there was greater net CO2 uptake in undisturbed versus disturbed tundra. At one site, the undisturbed tundra was a weak net sink (−0.05 ± 0.02 g C m−2 day−1), while the disturbed tundra acted as a weak net source (+0.07 ± 0.04 g C m−2 day−1). At the other site, the NEE of the undisturbed tundra was −0.20 ± 0.03 g C m−2 day−1 (sink), while the disturbed tundra still sequestered CO2, but less than the undisturbed tundra (NEE = −0.05 ± 0.04 g C m−2 day−1). Two of the RTS exhibited average soil temperatures that were greater compared to the surrounding undisturbed tundra. In one case, the opposite effect was observed. All RTS exhibited elevated soil moisture (+14%) and nutrient availability (specifically nitrogen) relative to the undisturbed tundra. We conclude that RTS, although limited in space, have profound environmental impacts by reducing vegetation coverage, increasing wet soil conditions, and altering NEE during the growing season in the High Arctic.

scholarly journals Addressing Biases in Arctic-Boreal Carbon Cycling in the Community Land Model Version 5

2020 ◽  
Author(s):  
Leah Birch ◽  
Christopher R. Schwalm ◽  
Sue Natali ◽  
Danica Lombardozzi ◽  
Gretchen Keppel-Aleks ◽  
...  
Keyword(s):  
Carbon Cycling ◽  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Carbon Allocation ◽  
Ecosystem Respiration ◽  
Terrestrial Ecosystem ◽  
The Arctic ◽  
Community Land Model ◽  
Warming World

Abstract. The Arctic-boreal zone (ABZ) is experiencing amplified warming, actively changing biogeochemical cycling of vegetation and soils. The land-to-atmosphere fluxes of CO2 in the ABZ have the potential to increase in magnitude and feedback to the climate causing additional large scale warming. The ability to model and predict this vulnerability is critical to preparation for a warming world, but Earth system models have biases that may hinder understanding the rapidly changing ABZ carbon fluxes. Here we investigate circumpolar carbon cycling represented by the Community Land Model 5 (CLM5.0) with a focus on seasonal gross primary productivity (GPP) in plant functional types (PFTs). We benchmark model results using data from satellite remote sensing products and eddy covariance towers. We find consistent biases in CLM5.0 relative to observational constraints: (1) the onset of deciduous plant productivity to be late, (2) the offset of productivity to lag and remain abnormally high for all PFTs in fall, (3) a high bias of grass, shrub, and needleleaf evergreen tree productivity, and (4) an underestimation of productivity of deciduous trees. Based on these biases, we focus model development of alternate phenology, photosynthesis schemes, and carbon allocation parameters at eddy covariance tower sites. Although our improvements are focused on productivity, our final Model Recommendation results in other component CO2 fluxes, e.g. Net Ecosystem Exchange (NEE) and Terrestrial Ecosystem Respiration (TER), that are more consistent with observations. Results suggest that algorithms developed for lower latitudes and more temperate environments can be inaccurate when extrapolated to the ABZ, and that many land surface models may not accurately represent carbon cycling and its recent rapid changes in high latitude ecosystems, especially when analyzed by individual PFTs.

scholarly journals Carbon cycle uncertainty in the Alaskan Arctic

2014 ◽  
Vol 11 (15) ◽  
pp. 4271-4288 ◽  
Author(s):  
J. B. Fisher ◽  
M. Sikka ◽  
W. C. Oechel ◽  
D. N. Huntzinger ◽  
J. R. Melton ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Primary Production ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
The Arctic ◽  
Regional Patterns ◽  
Alaskan Arctic

Abstract. Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for the Alaskan Arctic from four recent model intercomparison projects – NACP (North American Carbon Program) site and regional syntheses, TRENDY (Trends in net land atmosphere carbon exchanges), and WETCHIMP (Wetland and Wetland CH4 Inter-comparison of Models Project) – we provide a baseline of terrestrial carbon cycle uncertainty, defined as the multi-model standard deviation (σ) for each quantity that follows. Mean annual absolute uncertainty was largest for soil carbon (14.0 ± 9.2 kg C m−2), then gross primary production (GPP) (0.22 ± 0.50 kg C m−2 yr−1), ecosystem respiration (Re) (0.23 ± 0.38 kg C m−2 yr−1), net primary production (NPP) (0.14 ± 0.33 kg C m−2 yr−1), autotrophic respiration (Ra) (0.09 ± 0.20 kg C m−2 yr−1), heterotrophic respiration (Rh) (0.14 ± 0.20 kg C m−2 yr−1), net ecosystem exchange (NEE) (−0.01 ± 0.19 kg C m−2 yr−1), and CH4 flux (2.52 ± 4.02 g CH4 m−2 yr−1). There were no consistent spatial patterns in the larger Alaskan Arctic and boreal regional carbon stocks and fluxes, with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic and larger boreal region.

scholarly journals Soil erosion is unlikely to drive a future carbon sink in Europe

2018 ◽  
Vol 4 (11) ◽  
pp. eaau3523 ◽  
Author(s):  
Emanuele Lugato ◽  
Pete Smith ◽  
Pasquale Borrelli ◽  
Panos Panagos ◽  
Cristiano Ballabio ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Large Scale ◽  
Agricultural Soils ◽  
Carbon Sink ◽  
Rainfall Erosivity ◽  
The European Union ◽  
Model Framework ◽  
Erosion Rates ◽  
C Cycle ◽  
The Impact

Understanding of the processes governing soil organic carbon turnover is confounded by the fact that C feedbacks driven by soil erosion have not yet been fully explored at large scale. However, in a changing climate, variation in rainfall erosivity (and hence soil erosion) may change the amount of C displacement, hence inducing feedbacks onto the land C cycle. Using a consistent biogeochemistry-erosion model framework to quantify the impact of future climate on the C cycle, we show that C input increases were offset by higher heterotrophic respiration under climate change. Taking into account all the additional feedbacks and C fluxes due to displacement by erosion, we estimated a net source of 0.92 to 10.1 Tg C year−1 from agricultural soils in the European Union to the atmosphere over the period 2016–2100. These ranges represented a weaker and stronger C source compared to a simulation without erosion (1.8 Tg C year−1), respectively, and were dependent on the erosion-driven C loss parameterization, which is still very uncertain. However, when setting a baseline with current erosion rates, the accelerated erosion scenario resulted in 35% more eroded C, but its feedback on the C cycle was marginal. Our results challenge the idea that higher erosion driven by climate will lead to a C sink in the near future.

scholarly journals COMPREHENSIVE EVALUATION OF URBAN SPRAWL ON ECOLOGICAL ENVIRONMENT USING MULTI-SOURCE DATA: A CASE STUDY OF BEIJING

2016 ◽  
Vol XLI-B8 ◽  
pp. 1073-1077 ◽  
Author(s):  
Hao Wang ◽  
Xiaogang Ning ◽  
Weiwei Zhu ◽  
Fei Li
Keyword(s):  
Urban Sprawl ◽  
Land Surface ◽  
Comprehensive Evaluation ◽  
Net Primary Production ◽  
Ecological Environment ◽  
Vegetation Coverage ◽  
Landsat Images ◽  
Rapid Urbanization ◽  
Ring Road ◽  
The Impact

With urban population growing and urban sprawling, urban ecological environment problems appear. Study on spatiotemporal characteristics of urban sprawl and its impact on ecological environment is useful for ecological civilization construction. Although a lot of work has been conducted on urban sprawl and its impact on ecological environment, resolution of images to extract urban boundary was relatively coarse and most studies only focused on certain indicators of ecological environment, rather than comprehensive evaluation of urban ecological environmental impact. In this study, high-resolution remote sensing images of Beijing from aerial photography in 2002 and 2013 respectively are employed to extract urban boundary with manual interpretation. Fractional Vegetation Coverage (FVC), Water Density (WD), Impervious Surfaces Coverage (ISC), Net Primary Production (NPP), and Land Surface Temperature (LST) are adopted to represent ecological environment. The ecological environment indicators are measured with some general algorithms by combining Landsat images, GIS data and metrological data of 243 day, 2001 and 244 day, 2013. In order to evaluate the impact of urban sprawl on ecological environment, pseudo changes due to metrological variation and other noise in this time period are removed after images calibration. The impact of urban sprawl on ecological environment is evaluated at different scales of urban extent, Beijing ring road and watershed. Results show that Beijing had been undergoing a rapid urbanization from 2002 to 2013, with urban area increase from 600 square kilometres to 987 square kilometres. All ecological environment indicators except LST became terrible in urban sprawl region, with carbon reduction of approximate 40508 tons. The Beiyun River watershed of Beijing degraded seriously since ISC increased to 0.59. Gratifyingly, ecological environment indicators including NDVI, NPP, and LST inside of 4<sup>th</sup> Ring Road became well.

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