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Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits.

ABSTRACT: Wetlands provide multiple ecosystem services, the sustainable use of which requires knowledge of the underlying ecological mechanisms. Functional traits, particularly the community-weighted mean trait (CWMT), provide a strong link between species communities and ecosystem functioning. We here combine species distribution modeling and plant functional traits to estimate the direction of change of ecosystem processes under climate change. We model changes in CWMT values for traits relevant to three key services, focusing on the regional species pool in the Norrström area (central Sweden) and three main wetland types. Our method predicts proportional shifts toward faster growing, more productive and taller species, which tend to increase CWMT values of specific leaf area and canopy height, whereas changes in root depth vary. The predicted changes in CWMT values suggest a potential increase in flood attenuation services, a potential increase in short (but not long)-term nutrient retention, and ambiguous outcomes for carbon sequestration.

SUBMITTER: Moor H

PROVIDER: S-EPMC4288999 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits.

Moor Helen H Hylander Kristoffer K Norberg Jon J

Ambio 20150101

Wetlands provide multiple ecosystem services, the sustainable use of which requires knowledge of the underlying ecological mechanisms. Functional traits, particularly the community-weighted mean trait (CWMT), provide a strong link between species communities and ecosystem functioning. We here combine species distribution modeling and plant functional traits to estimate the direction of change of ecosystem processes under climate change. We model changes in CWMT values for traits relevant to thre ...[more]

PMID: 25576286

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Project description:With the far-reaching consequences of worldwide climate variationon ecosystems and human societies, understanding and predicting changes in cultural ecosystem services (CES) is essential for sustainable development policy and resource planning. Past studies have focused on changes and impacts on natural ecosystems, while relatively few studies have been conducted on predictions of CES. This study combines POI datasets with future climate variables under different scenarios into the Maxent model for forecasting the spatial and temporal distribution of CES, which provides strong support for future decision-making. The results indicate that: (1) Under the SSP126 and SSP585 scenarios, the CES values in the northern, western, central, and northeastern parts of the study area are relatively high, while those in the southwestern, southern, and southeastern parts are relatively low. (2) Under the SSP126 scenario, the total CES shows an increasing trend from 2021 to 2040, but slightly declines from 2061 to 2080. In contrast, under the SSP585 scenario, the total CES significantly decreases from 2021 to 2040, especially in the provinces of Guizhou, Hunan, Zhejiang, and Anhui. (3) Temperature has a significant impact on CES predictions, with the annual mean temperature (Bio1) positively correlated with total CES, contributing between 0.75 and 0.78 to the distribution of CES across different years and scenarios. Additionally, the maximum temperature of the hottest month (Bio5) and the mean temperature of the wettest quarter (Bio8) also significantly influence CES under different scenarios and years. These findings reveal the regional characteristics and variations in CES distribution under different climate scenarios, providing crucial scientific evidence for future policy-making, resource management, and climate adaptation strategies. They also offer important insights into the impact of global climate change on ecosystems and human society, serving as a valuable reference for future national decision-making.

Dataset Information

Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits.

Publications

Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits.

Similar Datasets

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