Evidence map›Paper›PMID 34519004›Full record

ArticleEnvironmental science and pollution research international2022

The response of net primary productivity to climate change and its impact on hydrology in a water-limited agricultural basin.

Shuping Ji, Shilong Ren, Yanran Li, Jiaohui Fang, Di Zhao, Jian Liu

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.0field-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

0 citing papers in PubMed, 11 citations in OpenAlex.

No citing paper in PubMed yet.

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 3 institutions in 1 country.

Shuping JiEnvironment Research Institute, Shandong University, Qingdao, 266237, China.
Shilong RenEnvironment Research Institute, Shandong University, Qingdao, 266237, China.
Yanran LiEnvironment Research Institute, Shandong University, Qingdao, 266237, China.
Jiaohui FangSchool of Life Sciences, Qufu Normal University, Qufu, 273100, China.
Di ZhaoInstitute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China.
Jian LiuEnvironment Research Institute, Shandong University, Qingdao, 266237, China. ecology@sdu.edu.cn.ORCID http://orcid.org/0000-0003-1920-2641
Shandong University · CNChinese Academy of Sciences · CNQufu Normal University · CN

Funding

National Natural Science Foundation of China 32071523Natural Science Foundation of Shandong Province, China ZR2017MC013
6 · The paper itself

Abstract

Climate change has remarkably altered growing-season vegetation growth, but the impacts of vegetation variability on the regional hydrological cycle remain poorly understood. Exploring the relationships between climate change, vegetation dynamics, and hydrologic factors would contribute to the sustainable management of ecosystems. Here, we investigated the response of vegetation dynamics to climate change and its impact on hydrologic factors in a traditional agricultural basin with limited water resources in China, Nansi Lake Basin (NLB). To this end, CASA (Carnegie-Ames-Stanford Approach) model and the SWAT (Soil and Water Assessment Tool) model were applied to simulate the net primary productivity (NPP), evapotranspiration (ET), and soil water in the growing season (April-October) from 2000 to 2016. Results showed that the mean growing-season NPP (NPP

Indexed as

Climate ChangeHydrologyAgricultureChinaEcosystemModels, TheoreticalWaterWaterCASAClimate variationHydrological cycleNPPSWATVegetation dynamics

Identifiers

PMID34519004
OpenAlexW3199794308

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.