Evidence map›Paper›PMID 25907628›Full record

ArticleEnvironmental science and pollution research international2015

Restoring ecosystem services to littoral zones of rivers in the urban core of Chongqing, China.

Xu-Dong Xian, Yi-Long Feng, J H Martin Willison, Li-Jiao Ai, Ping Wang, Zhi-Neng Wu

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Xu-Dong XianChongqing Landscape and Gardening Research Institute, 8 Fangyi Road, Baishiyi Town, Jiulongpo District, Chongqing, China, 401329.
Yi-Long Feng
J H Martin Willison
Li-Jiao Ai
Ping Wang
Zhi-Neng Wu
Shanghai Institute of Landscape Gardening · CNDalhousie University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two examples of the creation of naturalized areas in the littoral zone of the Three Gorges Reservoir in the urban core of Chongqing City, China, are described. The areas were created for the purpose of restoring ecological functions and services. Plants were selected based on surveys of natural wetland vegetation in the region, and experiments were conducted to discover the capacity of species of interest to survive the sometimes extreme hydrological regimes at the sites. Novel methods were developed to stabilize the plants against the rigors of extreme summer floods and constant swash, notably zigzag berms of rocks wrapped in iron mesh. The areas include native reeds, grasses, shrubs, and trees. Plant communities in the areas are zoned according to flooding stress, and their structure is less stable at lower elevations that are subjected to greater stress. The tall grass Saccharum spontaneum (widespread in Southern Asia) and the tree Pterocarya stenoptera (native to Southwest China) are notable for their utility at these sites in the center of a large city. Communities of tall reeds and grasses have become so dense and stable that they now provide the ecosystem services of capturing river sediments and resisting erosion of the river banks. It is recommended that extensive greening of the riparian zones in urban areas of the Three Gorges Reservoir be conducted for the purpose of providing ecosystem services, based in part on the experiences described here.

Indexed as

CitiesEcosystemEnvironment DesignPlant DevelopmentRiversWetlandsChinaFloodsJuglandaceaeSaccharumSpecies Specificity

Identifiers

PMID25907628
OpenAlexW2000658877

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.