Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements

Biogeosciences, Journal Year: 2022, Volume and Issue: 19(3), P. 559 - 583

Published: Feb. 2, 2022

Abstract. Large changes in the Arctic carbon balance are expected as warming linked to climate change threatens destabilize ancient permafrost stocks. The eddy covariance (EC) method is an established technique quantify net losses and gains of between biosphere atmosphere at high spatiotemporal resolution. Over past decades, a growing network terrestrial EC tower sites has been across Arctic, but comprehensive assessment network's representativeness within heterogeneous region still lacking. This creates additional uncertainties when integrating flux data sites, for example upscaling fluxes constrain pan-Arctic budgets therein. study provides inventory (here > = 60∘ N) which also made available online (https://cosima.nceas.ucsb.edu/carbon-flux-sites/, last access: 25 January 2022). Our database currently comprises 120 only 83 listed active, just these active remain operational throughout winter. To map this network, we evaluated similarity environmental conditions observed locations those larger domain based on 18 bioclimatic edaphic variables. allows us assess general level ecosystem domain, while not necessarily reflecting greenhouse gas rates directly. We define two metrics score: one that measures whether location represented by with similar characteristics (ER1) second if minimum representation statistically rigorous extrapolation met (ER4). find half least tower, third enough towers allow reliable extrapolation. When consider methane measurements or year-round (including wintertime) measurements, values drop about 1/5 1/10 respectively. With majority located Fennoscandia Alaska, regions were assigned highest representativeness, large parts Siberia patches Canada classified underrepresented. Across mountainous particularly poorly current observation network. tested three different strategies identify new site upgrades existing optimally enhance While 15 can improve 20 %, upgrading few 10 capture during wintertime their respective ER1 coverage 28 % 33 %. targeted improvement could be shown clearly superior unguided selection therefore leading substantial improvements relatively small investments.

Language: Английский

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The ABCflux database: Arctic–boreal CO<sub>2</sub> flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Earth system science data, Journal Year: 2022, Volume and Issue: 14(1), P. 179 - 208

Published: Jan. 21, 2022

Abstract. Past efforts to synthesize and quantify the magnitude change in carbon dioxide (CO2) fluxes terrestrial ecosystems across rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited their geographical temporal coverage. Furthermore, these been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting potential be used large-scale budget assessments. To bridge gaps, we developed a standardized monthly database of CO2 (ABCflux) that aggregates situ measurements net ecosystem exchange its derived partitioned component fluxes: gross primary productivity respiration. The span from 1989 2020 70 supporting variables describe key conditions (e.g., vegetation disturbance type), micrometeorological environmental air soil temperatures), flux measurement techniques. Here, variables, spatial distribution observations, main strengths limitations database, research opportunities it enables. In total, ABCflux includes 244 sites 6309 observations; 136 2217 observations represent tundra, 108 4092 boreal biome. estimated chamber (19 % observations), snow diffusion (3 %) eddy covariance (78 largest number collected during climatological summer (June–August; 32 %), fewer available for autumn (September–October; 25 winter (December–February; 18 spring (March–May; %). can wide array empirical, remote sensing modeling studies improve understanding regional variability better estimate ABZ budget. is openly freely online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

Language: Английский

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Modeling carbon storage in urban vegetation: Progress, challenges, and opportunities

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2022, Volume and Issue: 114, P. 103058 - 103058

Published: Oct. 19, 2022

Urban vegetation (UV) and its carbon storage capacity are critical for terrestrial cycling global sustainable development goals (SDGs). With complex spatial distribution, composition ecological functions, UV is essential climate change. Therefore, improving modeling a research hotspot that deserves extensive investigation. However, the uniqueness of lead to great challenges in modeling, including (1) limitations data algorithms due sensitive urban environments; (2) severe scarcity in-city field observation (e.g., EC towers surveys); (3) difficulty parameter inversion canopy height, LAI, etc.); (4) poor transferability when migrating estimation models from natural scenarios. The progress settings reviewed, with detailed discussions on methods major challenges. We then propose strategies overcome existing challenges, implementing novel improved remote sensing (RS) techniques hyper-spectral, LiDAR, satellites, etc.) obtain enhanced structural functional information UV; nodes earth sensor network, especially distribution settings; leveraging "Model-Data Fusion" technology by integrating big reduce uncertainty estimations. This review provides new insights expected help community achieve better understanding towards neutrality.

Language: Английский

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Non-linearity between gross primary productivity and far-red solar-induced chlorophyll fluorescence emitted from canopies of major biomes

Remote Sensing of Environment, Journal Year: 2022, Volume and Issue: 271, P. 112896 - 112896

Published: Jan. 20, 2022

Language: Английский

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Practical Guide to Measuring Wetland Carbon Pools and Fluxes

Wetlands, Journal Year: 2023, Volume and Issue: 43(8)

Published: Nov. 28, 2023

Abstract Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, dioxide and methane emissions, aquatic C fluxes. However, underlying biogeochemical processes that affect wetland pools fluxes are complex dynamic, making measurements challenging. Over decades research, many observational, experimental, analytical approaches been developed to understand quantify C. Sampling range in their representation from short long timeframes local landscape spatial scales. This review summarizes common cutting-edge methodological for quantifying We first define each major provide rationale importance dynamics. For approach, we clarify what component is measured its temporal representativeness constraints. describe practical considerations such as where when an approach typically used, who can conduct (expertise, training requirements), how conducted, including equipment complexity costs. Finally, key covariates ancillary enhance interpretation findings facilitate model development. The protocols measure soil, water, vegetation, gases also relevant related disciplines ecology. Improved quality consistency data collection reporting across studies will help reduce uncertainties develop management strategies use wetlands nature-based climate solutions.

Language: Английский

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Development of a Benchmark Eddy Flux Evapotranspiration Dataset for Evaluation of Satellite-Driven Evapotranspiration Models Over the CONUS

Agricultural and Forest Meteorology, Journal Year: 2023, Volume and Issue: 331, P. 109307 - 109307

Published: Jan. 27, 2023

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced support intercomparison and evaluation OpenET satellite-based remote sensing (RSET) models could also be used evaluate data other approaches. is web-based service that makes field-delineated pixel-level estimates well-established RSET readily available water managers, agricultural producers, public. composed flux meteorological variety providers covering native vegetation settings. Flux footprint predictions developed for each station included static footprints based on average wind direction speed, as well dynamic hourly generated with physically model upwind source area. two prediction methods rigorously compared their relative spatial coverage. Data all sources consistent reproducible manner including handling, gap-filling, temporal aggregation, energy balance closure correction. resulting 243,048 daily 5,284 monthly values 194 stations, falling between 1995 2021. We assessed imbalance using 172 sites total 193,021 days data, finding overall turbulent fluxes understated by about 12% energy. Multiple linear regression analyses indicated latent may typically slightly more than sensible heat flux. This provide reference being wide range applications related accounting resources management at field watershed scales.

Language: Английский

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Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

AGU Advances, Journal Year: 2023, Volume and Issue: 4(5)

Published: Sept. 6, 2023

Abstract Wetlands are responsible for 20%–31% of global methane (CH 4 ) emissions and account a large source uncertainty in the CH budget. Data‐driven upscaling fluxes from eddy covariance measurements can provide new independent bottom‐up estimates wetland emissions. Here, we develop six‐predictor random forest model (UpCH4), trained on 119 site‐years flux data 43 freshwater sites FLUXNET‐CH4 Community Product. Network patterns site‐level annual means mean seasonal cycles were reproduced accurately tundra, boreal, temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 0.53). UpCH4 estimated 146 ± TgCH y −1 2001–2018 which agrees closely with current land surface models (102–181 overlaps top‐down atmospheric inversion (155–200 ). However, diverged both types spatial pattern dynamics tropical We conclude that has potential to produce realistic extra‐tropical will improve more data. To reduce upscaled estimates, researchers could prioritize along humid‐to‐arid climate gradients, major rainforest basins (Congo, Amazon, SE Asia), into monsoon (Bangladesh India) savannah (African Sahel) be paired improved knowledge extent these regions. The monthly products gridded at 0.25° available via ORNL DAAC ( https://doi.org/10.3334/ORNLDAAC/2253

Language: Английский

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Increased photosynthesis during spring drought in energy-limited ecosystems

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Nov. 29, 2023

Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of (gross primary productivity, GPP) drought across water-energy limitation spectrum. We find a consistent increase eddy covariance GPP spring ecosystems (83% sites). Half sensitivity precipitation was predicted solely from wetness index (R2 = 0.47, p < 0.001), with weaker relationships summer and fall. Our results suggest increases 55% vegetated Northern Hemisphere lands ( >30° N). then compare these terrestrial biosphere model outputs remote sensing products. In contrast trends detected data, mean always declined under deficits after controlling air temperature light availability. While products captured observed negative ecosystems, models proved insufficiently sensitive deficits.

Language: Английский

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Soil moisture dominates the variation of gross primary productivity during hot drought in drylands

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 899, P. 165686 - 165686

Published: July 21, 2023

Language: Английский

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Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates

Global Change Biology, Journal Year: 2023, Volume and Issue: 29(15), P. 4298 - 4312

Published: May 15, 2023

Abstract The recent rise in atmospheric methane (CH 4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH source, estimates of global wetland emissions vary widely among approaches taken by bottom‐up (BU) process‐based biogeochemical models top‐down (TD) inversion methods. Here, we integrate situ measurements, multi‐model ensembles, a machine learning upscaling product into International Land Model Benchmarking system to examine relationship between emission model performance. We find that using better‐performing identified observational constraints reduces spread 62% 39% for BU‐ TD‐based approaches, respectively. However, BU TD estimate discrepancies increased about 15% (from 31 36 TgCH year −1 when top 20% were used, although consider this result moderately uncertain given unevenly distributed observations. Our analyses demonstrate performance ranking is subject benchmark selection due large inter‐site variability, highlighting importance expanding coverage sites diverse environmental conditions. encourage future development move beyond static benchmarking focus on evaluating site‐specific ecosystem‐specific variabilities inferred from

Language: Английский

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