Evidence map›Paper›PMID 41896275›Full record

ArticleScientific reports2026

Multi-objective scenarios analysis for optimizing mariculture spatial allocation: a case study of Lianyungang, China.

Qiulu Wang, Changjuan Li, Yaning Li

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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
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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Evaluation of Overwintering Performance of Threeline Grunt (Animals : an open access journal from MDPI · 2026
    Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Qiulu WangNational Marine Data and Information Service, Tianjin, 300171, China. 87675694@qq.com.
Changjuan LiNankai University, Tianjin, 300071, China.
Yaning LiNational Marine Data and Information Service, Tianjin, 300171, China.

Funding

Key Laboratory of Marine Ecological Monitoring and Restoration Technology MEMRT2024JBGS01
6 · The paper itself

Abstract

Optimizing the spatial allocation of fishery production is crucial for implementing the China's "Blue Granary" strategy and achieving sustainable utilization of fishery resources. An optimization framework was constructed from three objectives dimensions: demand, pattern, and efficiency. Taking the sea area of Lianyungang in Jiangsu Province as a case study, compound annual growth rate models were used to predict the mariculture output in 2030. The spatial pattern was optimized through spatial identification of protected area and fishery resource, environmental suitability assessment, and spatial use compatibility analysis. Subsequently, an adaptation matrix aligning spatial zones and aquaculture mode was established, proposing multi-scenario mariculture spatial layouts. The results were as follows: 1) Based on 2018 and 2022 as reference years, the predicted mariculture outputs for Jiangsu in 2030 are 1.1375 million tonnes and 1.0658 million tonnes, respectively, with the study area contributing 173,200 tonnes and 158,800 tonnes;2) Spatial analysis identified 891.7 km² of fishery conservation zones and 1,853.8 km² of suitable aquaculture areas within the study region, including 1,205.4 km² suitable for deep-water aquaculture and 648.4 km² for shallow-water aquaculture, of which 188.3 km² are multifunctional three-dimensional spaces; 3) Four scenarios were simulated based on predicted yields and per-unit-area productivity, with spatial layouts optimized using method-specific spatial parameter matching. The spatial ranges for the four aquaculture methods under different scenarios are as follows: deep-water cage culture requires 3,715-4,035 cubic meters of water space, raft culture necessitates 1,755-2,165 hectares of marine area, suspended cage culture occupies 295-725 hectares of operational range, and bottom sowing requires 1,280-1,855 hectares of seabed area. This study presents a methodological framework for mariculture spatial optimization that may contribute to sustainable marine fisheries development.

Indexed as

Mariculture productionMulti-objectiveProduction modeSpatial allocationSpatial matching

Identifiers

PMID41896275
PMCPMC13039858

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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.