Evidence map›Paper›PMID 41521209›Full record

SynthesisScientific reports2026

Analysis of sustainability differences among various shrimp farming models: a systematic review and meta analysis.

Yuzhen Wang, Zhao Chen, Jiajia Wang, Zhiqiang Chang, Shuangyong Zhang, Gao Meng, Jian Li

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2026. 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
–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

0 citing papers in PubMed.

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

7 authors.

Yuzhen WangKey Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, 266003, Shandong Province, China.
Zhao ChenState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, Shandong, China.
Jiajia WangState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, Shandong, China.
Zhiqiang ChangState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, Shandong, China.
Shuangyong ZhangState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, Shandong, China.
Gao MengState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, Shandong, China.
Jian LiState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, Shandong, China. bigbird@ysfri.ac.cn.ORCID http://orcid.org/0000-0003-2527-7623

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aquaculture technology has diversified over the years, but its environmental impact and negative social effects have raised widespread concern. Currently, research on the differences in aquaculture models mainly focuses on a single dimension, lacking quantitative assessment methods for the various differences in farming models. This study employs a meta-analysis method to identify economic and ecological indicators' data from 136 pieces of literature published between 2002 and 2024. It systematically evaluates the impact of different aquaculture modes and technologies on the comprehensive (economic, ecological, and social) benefits of shrimp farming from multiple dimensions, exploring the differences in benefits between farming modes and the trends as they change with technology and indicators. The results indicate that the Pond Integrated Multi-Trophic Aquaculture model (PIMTA), which uses biological hierarchy technology, exhibits the best comprehensive benefits, followed by the Indoor Super Intensive Recirculating Culture (ISIC_Recirculation), while the Pond Monoculture model (PMC) shows the lowest comprehensive benefits (-1.6425). In terms of ecological benefits, the ISIC_Recirculation model and the PIMTA model perform the best, with total solids (TS), the Shannon index, and microplastics (MPS) significantly affecting the differences in ecological benefits. The Indoor Super Intensive Exchange Culture (ISIC_Exchange) model stands out in terms of social benefits. Regarding economic benefits, the PIMTA model and the Indoor Super Intensive culture models (ISIC) are significantly higher than the PMC model. Based on simulations using collected data, when the survival rate (SR) is greater than 68.37%, the impact of different farming techniques on comprehensive benefits gradually diminishes as the survival rate (SR) increases. Higher pH levels reduce the impact of these differences, while higher dissolved oxygen (DO) levels increase their impact. This study proposes an evaluation method for the differences in comprehensive benefits among aquaculture models and technologies based on meta-analysis. It provides a scientific basis for optimizing the selection of aquaculture models, enhancing farming efficiency, and predicting the long-term trends of benefits from different farming models, thereby promoting the green and sustainable development of the aquaculture industry.

Indexed as

AquaculturePenaeidaeAnimalsModels, TheoreticalEcological benefitsEconomic benefitsEffect sizeSocial benefitsSustainability

Identifiers

PMID41521209
PMCPMC12855254

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.