Global effects on soil respiration and its temperature sensitivity depend on nitrogen addition rate

Soil Biology and Biochemistry, Journal Year: 2022, Volume and Issue: 174, P. 108814 - 108814

Published: Sept. 1, 2022

Language: Английский

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Global warming accelerates soil heterotrophic respiration

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

Published: June 10, 2023

Carbon efflux from soils is the largest terrestrial carbon source to atmosphere, yet it still one of most uncertain fluxes in Earth's budget. A dominant component this flux heterotrophic respiration, influenced by several environmental factors, notably soil temperature and moisture. Here, we develop a mechanistic model micro global scale explore how changes water content affect respiration. Simulations, laboratory measurements, field observations validate new approach. Estimates show that respiration has been increasing since 1980s at rate about 2% per decade globally. Using future projections surface moisture, predicts increase 40% end century under worst-case emission scenario, where Arctic region expected experience more than two-fold increase, driven primarily declining moisture rather increase.

Language: Английский

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From remotely‐sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II—Harnessing data

Global Change Biology, Journal Year: 2023, Volume and Issue: 29(11), P. 2893 - 2925

Published: Feb. 18, 2023

Abstract Although our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency SIF datasets are still in an active stage research development. As a result, there considerable inconsistencies among diverse at all scales widespread applications them led to contradictory findings. The present review is second two companion reviews, data oriented. It aims (1) synthesize variety, scale, uncertainty existing datasets, (2) sector ecology, agriculture, hydrology, climate, socioeconomics, (3) clarify how such inconsistency superimposed with theoretical complexities laid out (Sun et al., 2023) may impact process interpretation various contribute inconsistent We emphasize that accurate functional relationships between other ecological indicators contingent upon complete understanding uncertainty. Biases uncertainties observations can significantly confound their respond environmental variations. Built syntheses, we summarize gaps current observations. Further, offer perspectives on innovations needed help improve informing ecosystem structure, function, service under climate change, including enhancing in‐situ capability especially “data desert” regions, improving cross‐instrument standardization network coordination, advancing by fully harnessing theory data.

Language: Английский

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Twenty Years of Progress, Challenges, and Opportunities in Measuring and Understanding Soil Respiration

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(2)

Published: Feb. 1, 2024

Abstract Soil respiration (Rs), the soil‐to‐atmosphere flux of CO 2 , is a dominant but uncertain part carbon cycle, even after decades study. This review focuses on progress in understanding Rs from laboratory incubations to global estimates. We survey key developments situ ecosystem‐scale observations and manipulations, synthesize meta‐analyses estimates, discuss most compelling challenges opportunities for future. Increasingly sophisticated lab experiments have yielded insights into interaction among heterotrophic respiration, substrate supply, enzymatic kinetics, extended incubation‐based analyses across space time. Observational manipulative field‐based used improved measurement approaches deepen our integrated effects environmental change disturbance Rs. Freely‐available observational databases enabled studies probing magnitude of, constraints on, flux. Key field include expanding measurements, experiments, under‐represented communities ecosystems; reconciling independent estimates fluxes trends; testing leveraging power machine learning process‐based models, both independently conjunction with each other; continuing field's tradition using novel explore diverse mechanisms ecosystems.

Language: Английский

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Tipping point in North American Arctic-Boreal carbon sink persists in new generation Earth system models despite reduced uncertainty

Environmental Research Letters, Journal Year: 2023, Volume and Issue: 18(2), P. 025008 - 025008

Published: Jan. 11, 2023

Abstract Estimating the impacts of climate change on global carbon cycle relies projections from Earth system models (ESMs). While ESMs currently project large warming in high northern latitudes, magnitude and sign future balance Arctic-Boreal ecosystems are highly uncertain. The new generation increased complexity Intergovernmental Panel Climate Change Sixth Assessment Report (IPCC AR6) is intended to improve projections. Here, we benchmark Coupled Model Intercomparison Project (CMIP) 5 6 (8 CMIP5 members 12 CMIP6 members) with International Land Benchmarking (ILAMB) tool over region NASA’s vulnerability experiment (ABoVE) North America. We show that projected average net biome production (NBP) 2100 higher than ABoVE domain, despite model spread being slightly narrower. Overall, shows better agreement contemporary observed variables (photosynthesis, respiration, biomass) CMIP5, except for soil turnover time. Although both CMIP ensemble domain will remain a sink by end 21st century, strength increases CO 2 emissions. ensembles indicate tipping point defined here as negative inflection NBP curve 2050–2080 independently shared socioeconomic pathway (SSP) or representative concentration (RCP) CMIP5. therefore suggest that, if keeps declining throughout America may become source next century.

Language: Английский

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Divergent data-driven estimates of global soil respiration

Communications Earth & Environment, Journal Year: 2023, Volume and Issue: 4(1)

Published: Dec. 6, 2023

Abstract The release of carbon dioxide from the soil to atmosphere, known as respiration, is second largest terrestrial flux after photosynthesis, but convergence data-driven estimates unclear. Here we collate all historical global respiration analyze and uncertainty in estimates. Despite development a dataset advanced scaling techniques last two decades, find that inter-model variability has increased. Reducing not an easy task, when puzzle pieces cycle fit together perfectly, climate change prediction will be more reliable.

Language: Английский

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Progress and challenges in remotely sensed terrestrial carbon fluxes

Geo-spatial Information Science, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 21

Published: May 1, 2024

Accurate evaluation of terrestrial carbon balance is essential for designing climate change mitigation policies, and capabilities remote sensing techniques in monitoring fluxes are widely recognized their great contributions to regional global budget accounting. In this review, we synthesized satellite-based data methodologies estimate the main flux components uncertainties over past two decades. The gross primary production (GPP) during period 2001–2022 134 ± 14 PgC yr−1, nearly half them occurs tropical forest regions such as South America Africa. Less than 2% GPP converted into a net sink 2.28 1.12 yr−1 using atmospheric inversion 2015–2020, comparable stock change-based (2.49 yr−1) but twice large model-based (1.08 0.78 yr−1). By decomposing satellite-derived different terms including emissions from land-use wildfires (3.55 yr−1), inferred that ~ 43% would be respired through soil microbes (57.1 which higher previous bottom-up (39–46 We then propose an accurate requires enhance representations photosynthetic responses rising CO2 disturbances, develop satellite-constrained belowground dynamics separate natural anthropogenic emissions, by integrating multi-source satellite sensors orbit, revolutionized with focused field campaigns data-scarce regions.

Language: Английский

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Investigating carbon and nitrogen conservation in reported CMIP6 Earth system model data

Geoscientific model development, Journal Year: 2025, Volume and Issue: 18(7), P. 2111 - 2136

Published: April 7, 2025

Abstract. Reliable, robust, and consistent data are essential foundations for analysis of carbon cycle feedbacks. Here, we consider the from multiple Earth system models (ESMs) participating in Coupled Model Intercomparison Project Phase 6 (CMIP6). We identify a mass conservation issue reported nitrogen data, with few exceptions specific reporting levels. The accumulated imbalance can amount to hundreds gigatons or by end simulated period, largely exceeding total carbon–nitrogen pool size changes over same period. Nitrogen is evident across all organic inorganic pools, mineral exhibiting most significant cumulative imbalance. Due lack detail cannot uniquely cause this However, postulate that primarily arises missing fluxes inconsistencies between these definitions provided C4MIP protocol (e.g., land-use fire emissions), rather than an underlying themselves. Our findings suggest future CMIP protocols should incorporating into their validation processes so such issues caught before users have deal them, forcing handle own way. In addition, attention model groups detailed diagnostic request definitions, along quality control, will also help avoid future. Given no additional CMIP6 currently being published none expected future, recommend rely on closed address potential flux imbalances using workarounds study.

Language: Английский

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Retrieval of Chlorophyll-a Concentrations Using Sentinel-2 MSI Imagery in Lake Chagan Based on Assessments with Machine Learning Models

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(19), P. 4924 - 4924

Published: Oct. 1, 2022

Chlorophyll-a (Chl-a) is an important characterized parameter of lakes. Monitoring it accurately through remote sensing thus great significance for early warnings water eutrophication. Sentinel Multispectral Imager (MSI) images from May to September between 2020 and 2021 were used along with in-situ measurements estimate Chl-a in Lake Chagan, which located Jilin Province, Northeast China. In this study, the extreme gradient boosting (XGBoost) Random Forest (RF) models, had similar performances, generated by six single bands band combinations. The RF model was then selected based on assessments (R2 = 0.79, RMSE 2.51 μg L−1, MAPE 9.86%), since its learning input features conformed bio-optical properties Case 2 waters. study considered concentrations Chagan as a seasonal pattern according K-Nearest-Neighbors (KNN) classification. also showed relatively stable performance three seasons (spring, summer autumn) applied map whole lake. research presents more reliable machine (ML) higher precision than previous empirical shown effects linked biological mechanisms Chl-a. Its robustness revealed temporal spatial distributions concentrations, consistent map. This capable revealing current ecological situation can serve reference inland

Language: Английский

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Underestimated Interannual Variability of Terrestrial Vegetation Production by Terrestrial Ecosystem Models

Global Biogeochemical Cycles, Journal Year: 2023, Volume and Issue: 37(4)

Published: March 25, 2023

Abstract Vegetation gross primary production (GPP) is the largest terrestrial carbon flux and plays an important role in regulating sink. Current ecosystem models (TEMs) are indispensable tools for evaluating predicting GPP. However, to which degree TEMs can capture interannual variability (IAV) of GPP remains unclear. With large data sets remote sensing, situ observations, predictions at a global scale, this study found that current substantially underestimate IAV comparison observations towers. Our results also showed larger underestimations nonforest types than forest types, especially arid semiarid grassland shrubland. One cause underestimation predicted by strongly dependent on canopy structure, is, leaf area index (LAI), changes physiology responding climate change. On other hand, simulated variations LAI much less observed. highlight importance improving precisely characterizing contribution physiological clarifying reason underestimated LAI. these efforts, it may be possible accurately predict stability sink context

Language: Английский

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