Sediment DNA Records the Critical Transition of Bacterial Communities in the Arid Lake DOI Creative Commons
Yang Hu, Jian Cai, Y. X. Song

et al.

Microbial Ecology, Journal Year: 2024, Volume and Issue: 87(1)

Published: May 9, 2024

Abstract It is necessary to predict the critical transition of lake ecosystems due their abrupt, non-linear effects on social-economic systems. Given promising application paleolimnological archives tracking historical changes ecosystems, it speculated that they can also record lake’s transition. We studied Lake Dali-Nor in arid region Inner Mongolia because profound shrinking experienced between 1300 s and 1600 s. reconstructed succession bacterial communities from a 140-cm-long sediment core at 4-cm intervals detected Our results showed trajectory 1200 2010s was divided into two alternative states: state1 state2 1400 2010s. Furthermore, late s, appearance tipping point slowing down implied existence By using multi-decadal time series sedimentary core, with general Lotka-Volterra model simulations, local stability analysis found were most unstable as approached transition, suggesting collapse triggers community shift an equilibrium state another state. harbored strongest antagonistic mutualistic interactions, which may imply detrimental role interaction strength stability. Collectively, our study DNA be used detect ecosystems.

Language: Английский

Picocyanobacterial-bacterial interactions sustain cyanobacterial blooms in nutrient-limited aquatic environments DOI
Huimin Li, Mengqi Jiang, Peng Li

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 260, P. 119508 - 119508

Published: June 28, 2024

Language: Английский

Citations

3
Machine Learning Provides Opportunities to Recognize Greenhouse Gas Emissions from Water at a Large Scale DOI
Peng Deng, Xiangang Hu, Mu Li

et al.

ACS ES&T Water, Journal Year: 2023, Volume and Issue: 4(3), P. 837 - 843

Published: Aug. 23, 2023

Water environments (e.g., oceans, lakes, and rivers) are important carbon sinks sources contribute to the cycle of earth's ecosystem. Machine learning provides a potential solution for recognizing greenhouse gas (GHG) emissions from water based on big data analysis. Data-driven machine can comprehensively recognize key environmental drivers that affect GHG emissions. However, several urgent issues should be addressed guarantee recognition water. For example, matching in situ databases is greatest challenge conducting large-scale research. It imperative unify collection methods improve database quality spatiotemporal high resolution). Quantifying contributions human activity climate change urgently needed resolve future challenges. Beyond providing prediction, learning, due its interpretability, optimize model; thus, empirical formulas deserve attention. Overall, manage complicated regarding

Language: Английский

Citations

8
Reviews and syntheses: Abrupt ocean biogeochemical change under human-made climatic forcing – warming, acidification, and deoxygenation DOI Creative Commons
Christoph Heinze, Thorsten Blenckner, Peter J. Brown

et al.

Published: Oct. 10, 2023

Abstract. Abrupt changes in ocean biogeochemical variables occur as a result of human-induced climate forcing well those which are more gradual and over longer timescales. These abrupt have not yet been identified quantified to the same extent ones. We review synthesise biogeochemistry under climatic forcing. specifically address carbon oxygen cycles because related processes acidification deoxygenation provide important ecosystem hazards. Since depend also on physical environment, we describe relevant warming, circulation, sea ice. include an overview reversibility or irreversibility marine changes. Important implications for ecosystems discussed. conclude that there is evidence increasing occurrence consequence rising greenhouse gas emissions.

Language: Английский

Citations

6
Long-term adaptation to elevated temperature but not CO2 alleviates the negative effects of ultraviolet-B radiation in a marine diatom DOI
Peng Jin,

Jiaofeng Wan,

Dai Xiao-ying

et al.

Marine Environmental Research, Journal Year: 2023, Volume and Issue: 186, P. 105929 - 105929

Published: Feb. 24, 2023

Language: Английский

Citations

4
Delta Connectome: Ecohydrology-Carbon Feedback and BioTerraforming Ecofolios DOI
Matteo Convertino

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 512 - 528

Published: Jan. 1, 2024

Language: Английский

Citations

1
Unveiling differential thermal sensitivities in marine phytoplankton within the China Seas DOI Creative Commons
Changyun Wang,

Shujie Cai,

Zhuyin Tong

et al.

Limnology and Oceanography Letters, Journal Year: 2024, Volume and Issue: 9(5), P. 583 - 592

Published: May 22, 2024

Abstract In this study, we explored the realized thermal sensitivities of various phytoplankton groups in natural seawater, a crucial aspect for understanding dynamics marine ecosystems under climate change. Utilizing decadal pigment dataset (2002–2015) from China Seas and employing generalized additive mixed models coupled with maximum entropy modeling, discerned sensitivity differentiations among nine groups, encompassing full‐size spectrum. Our findings revealed that cryptophytes were exceptionally thermally sensitive, strong correlation between temperature changes biomass variance. Characterized by preference cooler waters, had low mean niche narrow breadth. Notably, they exhibited lowest tipping point, highlighting their heightened vulnerability to warming trends. These underscored significance cryptophytes, an often‐overlooked group, ecosystem responses shifts, emphasized potential role as key indicators ecological studies global warming.

Language: Английский

Citations

1
Nutrient enrichment and climate warming drive carbon production of global lake ecosystems DOI
Junjie Jia, Jennifer A. J. Dungait, Guirui Yu

et al.

Earth-Science Reviews, Journal Year: 2024, Volume and Issue: unknown, P. 104968 - 104968

Published: Oct. 1, 2024

Language: Английский

Citations

1
B-tipping points in plankton dynamics: Stochasticity and early warning signals DOI
Shankha Narayan Chattopadhyay, Arvind Kumar Gupta

Physical review. E, Journal Year: 2024, Volume and Issue: 110(6)

Published: Dec. 19, 2024

Near a tipping point, critical transition occurs when small changes in input conditions lead to abrupt, often irreversible shifts dynamical system's state. This phenomenon is observed various biological and physical systems, including the collapse of species ecosystems. Several statistical indicators, known as early warning signals (EWSs), have been developed anticipate such collapses, garnering significant attention for their broad applicability. paper investigates stochastic versions bistable algae-zooplankton food-chain model under demographic environmental noise. Our findings show that an increase predatory fish population, which consumes zooplankton, triggers zooplankton abundance through saddle-node bifurcation. Basin stability measure reveals resilience underexploited steady state significantly diminishes system approaches point. We evaluate efficacy generic EWSs predicting sudden collapses both types noise analysis. The robustness AR(1) variance are assessed comprehensive sensitivity analysis processing parameters. also calculate conditional heteroskedasticity, minimizes false positive time series. results indicate prediction accuracy heteroskedasticity remains independent type. However, skewness perform better presence

Language: Английский

Citations

1
Environmental tipping points for global soil carbon fixation microorganisms DOI Creative Commons

Yueqi Hao,

Hao Liu, Jiawei Li

et al.

iScience, Journal Year: 2023, Volume and Issue: 26(11), P. 108251 - 108251

Published: Oct. 27, 2023

Carbon fixation microorganisms (CFMs) are important components of the soil carbon cycle. However, global distribution CFMs and whether they will exceed environmental tipping points remain unclear. According to machine learning models, total content, nitrogen fertilizer, precipitation play dominant roles in CFM abundance. Obvious stimulation inhibition effects on abundance only happened at low levels precipitation, where were 6.1 g·kg

Language: Английский

Citations

2
Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean DOI Creative Commons
Samuel Mogen, Nicole S. Lovenduski, Stephen Yeager

et al.

Earth s Future, Journal Year: 2023, Volume and Issue: 11(11)

Published: Nov. 1, 2023

Abstract Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long‐term trends, short term variability stressors can have major implications for ecosystems their management. As such, there is a growing need predictions ecosystem on monthly, seasonal, multi‐month timescales. Previous studies demonstrated ability to make reliable surface ocean physical biogeochemical state months years advance, but few investigated forecast skill multiple simultaneously or assessed below surface. Here, we use Community Earth System Model (CESM) Seasonal Multiyear Large Ensemble (SMYLE) along with novel observation‐based products quantify predictive dissolved inorganic (DIC), oxygen, temperature subsurface ocean. CESM SMYLE demonstrates high advance key oceanic regions frequently outperforms persistence forecasts. We find up 10 skillful forecasts, particularly Northeast Pacific (Gulf Alaska California Current Marine Ecosystems) temperature, DIC, oxygen. Our findings suggest that dynamical prediction could support actionable advice decision making.

Language: Английский

Citations

2