Evidence map›Paper›PMID 23775494›Full record

ArticleEnvironmental management2013

Division scheme for environmental management regionalization in China.

Baorong Huang, Ting Fan, Yingming Li, Yi Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental management, 2013. 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
–field-weighted citation impact
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.

  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

4 authors.

Baorong HuangInstitute of Policy and Management, Chinese Academy of Sciences, Beijing 100085, China.
Ting Fan
Yingming Li
Yi Wang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on regional heterogeneity of environmental characteristics and factors influencing those characteristics, environmental units may be classified into homogeneous zones. Then, essential strategies and mitigation measures in each zone may be developed and environmental quality may be holistically improved using a system of environmental management regionalization (EMRZ). Here, an EMRZ scheme for China was devised by outlining regional management using integrated qualitative and quantitative methods. First, the land was subdivided into four environmental management domains using China's three physical geographic domains. Second, using a regionalization indicator system, the environmental characteristics of neighboring provinces in four domains was quantified using the one-dimensional Euclidean distance method; regions with high similarity were merged into one environmental management region (EMR) and the preliminary draft of EMRs was obtained. Based on the preliminary scheme, eight EMRs using prefecture-level administrative regions were obtained through boundary adjustment based on important natural geographical boundaries and existing regional plans. These include the Northeastern China Region, the North China Plain Region, the Loess Plateau Region, Southeast Coast Region, the Middle Reaches of the Yangtze River, the Southwestern China Region, the Northwestern China Region, and the Tibetan Plateau Region. Priority environmental problems of each EMR were discussed. The main contribution of this study is that it develops a novel methodological framework for EMRZ integrating qualitative and quantitative methodologies, and considers the spatial contiguity of each EMR and the spatial integrity of each administrative unit. Future research will focus on priority goals and establishment of suitable environmental management policies for each EMR based on known local environmental problems.

Indexed as

Conservation of Natural ResourcesAlgorithmsChinaGeography

Identifiers

What OpenQuestion holds

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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.