Dataset Information

Functional identity enhances aboveground productivity of a coastal saline meadow mediated by Tamarix chinensis in Laizhou Bay, China.

ABSTRACT: Research in recent decades has confirmed that biodiversity influences ecosystem productivity; however, the potential mechanisms regulating this process remain subject to controversy, due to variation across ecosystems. Here, the effects of biodiversity on ecosystem productivity were evaluated using three variables of biodiversity (taxonomic diversity, functional identity, and functional diversity) and surrounding environmental conditions in a coastal saline meadow located on the south coast of Laizhou Bay, China. At this site, the shrub and field layers were primarily dominated by Tamarix chinensis and natural mesic grasses, respectively. Our results showed that functional identity, which is quantified as the community weighted mean of trait values, had greater explanatory ability than taxonomic and functional diversity. Thus, ecosystem productivity was determined disproportionately by the specific traits of dominant species. T. chinensis coverage was a biotic environmental factor that indirectly affected ecosystem productivity by increasing the community weighted mean of plant maximum height, which simultaneously declined with species richness. The present study advances our understanding of the mechanisms driving variation in the productivity of temperate coastal saline meadows, providing evidence supporting the "mass ratio" hypothesis.

SUBMITTER: Yi S

PROVIDER: S-EPMC7118169 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Functional identity enhances aboveground productivity of a coastal saline meadow mediated by Tamarix chinensis in Laizhou Bay, China.

Yi Shijie S Wu Pan P Peng Xiqiang X Bai Fenghua F Gao Yanan Y Zhang Wenxin W Du Ning N Guo Weihua W

Scientific reports 20200402 1

Research in recent decades has confirmed that biodiversity influences ecosystem productivity; however, the potential mechanisms regulating this process remain subject to controversy, due to variation across ecosystems. Here, the effects of biodiversity on ecosystem productivity were evaluated using three variables of biodiversity (taxonomic diversity, functional identity, and functional diversity) and surrounding environmental conditions in a coastal saline meadow located on the south coast of L ...[more]

PMID: 32242029

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Project description:With a shifting climate pattern and enhancement of human activities, coastal areas are exposed to threats of groundwater environmental issues. This work takes the eastern coast of Laizhou Bay as a research area to study the response of a coastal groundwater system to natural and human impacts with a combination of statistical, hydrogeochemical, and fuzzy classification methods. First, the groundwater level dynamics from 1980 to 2017 were analyzed. The average annual groundwater level dropped 13.16 m with a descent rate of 0.379 m/a. The main external environmental factors that affected the groundwater level were extracted, including natural factors (rainfall and temperature), as well as human activities (irrigated area, water-saving irrigated area, sown area of high-water-consumption crops, etc.). Back-propagation artificial neural network was used to model the response of groundwater level to the above driving factors, and sensitivity analysis was conducted to measure the extent of impact of these factors on groundwater level. The results verified that human factors including irrigated area and water-saving irrigated area were the most important influencing factors on groundwater level dynamics, followed by annual precipitation. Further, groundwater samples were collected over the study area to analyze the groundwater hydrogeochemical signatures. With the hydrochemical diagrams and ion ratios, the formation of groundwater, the sources of groundwater components, and the main hydrogeochemical processes controlling the groundwater evolution were discussed to understand the natural background of groundwater environment. The fuzzy C-means clustering method was adopted to classify the groundwater samples into four clusters based on their hydrochemical characteristics to reveal the spatial variation of groundwater quality in the research area. Each cluster was spatially continuous, and there were great differences in groundwater hydrochemical and pollution characteristics between different clusters. The natural and human factors resulted in this difference were discussed based on the natural background of the groundwater environment, and the types and intensity of human activity.

Dataset Information

Functional identity enhances aboveground productivity of a coastal saline meadow mediated by Tamarix chinensis in Laizhou Bay, China.

Publications

Functional identity enhances aboveground productivity of a coastal saline meadow mediated by Tamarix chinensis in Laizhou Bay, China.

Similar Datasets

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