Chongliang Zhang

Dr. Chongliang Zhang

orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2020 in Fisheries Research
Verified
Journal Article
Closed access
JLJing Luan
Jing Luan
CZChongliang Zhang
Chongliang Zhang
BXBinduo Xu
Binduo Xu
YXYing Xue
Ying Xue
YRYiping Ren
Yiping Ren

16 April 2015 in Environmental Monitoring and Assessment
Verified
Journal Article
Closed access
PDF file
BXBinduo Xu
Binduo Xu
CZChongliang Zhang
Chongliang Zhang
YXYing Xue
Ying Xue
YRYiping Ren
Yiping Ren
YCYong Chen
Yong Chen

1 May 2020 in Fisheries Research
Verified
Journal Article
Closed access
KWKun Wang
Kun Wang
CZChongliang Zhang
Chongliang Zhang
BXBinduo Xu
Binduo Xu
YXYing Xue
Ying Xue
YRYiping Ren
Yiping Ren

19 May 2015 in ICES Journal of Marine Science
Verified
Journal Article
Open access
PDF file
CZChongliang Zhang
Chongliang Zhang
YCYong Chen
Yong Chen
YRYiping Ren
Yiping Ren
Ecosystem models, specifically multispecies dynamic models, have been increasingly used to project impacts of fishing activity on the trophodynamics of ecosystems to support ecosystem-based fisheries management. Uncertainty is unavoidable in modelling processes and needs to be recognized and properly quantified before models are utilized. Uncertainty was assessed in this study for a multispecies size-spectrum model that quantifies community structure and ecological characteristics. The uncertainty was assumed to result from errors in fish life-history and metabolic scale parameters, environmental variability, fishing variability, and sampling errors. Given the same level of imprecision, metabolic scale parameters had the dominant influence on the uncertainty of the size spectrum modelling results, followed by life-history parameters. Both types of errors led to “scenario uncertainty”, suggesting the possible existence of alternative states of community structure. Environmental variability, fishing variability, and observation errors resulted in “statistical uncertainty”, implying that such uncertainty can be described adequately in statistical terms. The results derived from such a simulation study can provide guidance for identifying research priorities to help narrow the gap in scientific knowledge and reduce the uncertainty in fisheries management.

2 February 2018 in Ecography
Verified
Journal Article
Closed access
PDF file
CZChongliang Zhang
Chongliang Zhang
YCYong Chen
Yong Chen
BXBinduo Xu
Binduo Xu
YXYing Xue
Ying Xue
YRYiping Ren
Yiping Ren

1 September 2017 in Ecological Modelling
Verified
Journal Article
Closed access
DHDongyan Han
Dongyan Han
YCYong Chen
Yong Chen
CZChongliang Zhang
Chongliang Zhang
YRYiping Ren
Yiping Ren
YXYing Xue
Ying Xue
RWRong Wan
Rong Wan