Dataset Information

The uncertain climate footprint of wetlands under human pressure.

ABSTRACT: Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.

SUBMITTER: Petrescu AM

PROVIDER: S-EPMC4403212 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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The uncertain climate footprint of wetlands under human pressure.

Petrescu Ana Maria Roxana AM Lohila Annalea A Tuovinen Juha-Pekka JP Baldocchi Dennis D DD Desai Ankur R AR Roulet Nigel T NT Vesala Timo T Dolman Albertus Johannes AJ Oechel Walter C WC Marcolla Barbara B Friborg Thomas T Rinne Janne J Matthes Jaclyn Hatala JH Merbold Lutz L Meijide Ana A Kiely Gerard G Sottocornola Matteo M Sachs Torsten T Zona Donatella D Varlagin Andrej A Lai Derrick Y F DY Veenendaal Elmar E Parmentier Frans-Jan W FJ Skiba Ute U Lund Magnus M Hensen Arjan A van Huissteden Jacobus J Flanagan Lawrence B LB Shurpali Narasinha J NJ Grünwald Thomas T Humphreys Elyn R ER Jackowicz-Korczyński Marcin M Aurela Mika A MA Laurila Tuomas T Grüning Carsten C Corradi Chiara A R CA Schrier-Uijl Arina P AP Christensen Torben R TR Tamstorf Mikkel P MP Mastepanov Mikhail M Martikainen Pertti J PJ Verma Shashi B SB Bernhofer Christian C Cescatti Alessandro A

Proceedings of the National Academy of Sciences of the United States of America 20150323 15

Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a w ...[more]

PMID: 25831506

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Project description:The alpine wetlands in western Sichuan are distributed along the eastern section of the Qinghai-Tibet Plateau (QTP), where the ecological environment is fragile and highly sensitive to global climate change. These wetlands are already experiencing severe ecological and environmental issues, such as drought, retrogressive succession, and desertification. However, due to the limitations of computational models, previous studies have been unable to adequately understand the spatiotemporal change trends of these alpine wetlands. We employed a large sample and composite supervised classification algorithms to classify alpine wetlands and generate wetland maps, based on the Google Earth Engine cloud computing platform. The thematic maps were then grid-sampled for predictive modeling of future wetland changes. Four species distribution models (SDMs), BIOCLIM, DOMAIN, MAXENT, and GARP were innovatively introduced. Using the WorldClim dataset as environmental variables, we predicted the future distribution of wetlands in western Sichuan under multiple climate scenarios. The Kappa coefficients for Landsat 8 and Sentinel 2 were 0.89 and 0.91, respectively. Among the four SDMs, MAXENT achieved a higher accuracy (α = 91.6%) for the actual wetland compared to the thematic overlay analysis. The area under the curve (AUC) of the MAXENT model simulations for wetland spatial distribution were all greater than 0.80. This suggests that incorporating the SDM model into land change simulations has high generalizability and significant advantages on a large scale. Furthermore, simulation results reveal that between 2021 and 2100 years, with increasing emission concentrations, highly suitable areas for wetland development exhibit significant spatial differentiation. In particular, wetland areas in high-altitude regions are expected to increase, while low-altitude regions will markedly shrink. The changes in the future spatial distribution of wetlands show a high level of consistency with historical climate changes, with warming being the main driving force behind the spatiotemporal changes in alpine wetlands in western Sichuan, especially evident in the central high-altitude and northern low-altitude areas.

Dataset Information

The uncertain climate footprint of wetlands under human pressure.

Publications

The uncertain climate footprint of wetlands under human pressure.

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