Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes
Habitat models have gradually become important tools for assessing and predicting the spatio-temporal distribution of marine organisms. Species are closely associated with each other through biological processes such as predation, competition and mutualism. Neglecting the interaction between species...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-05-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X22002977 |
| _version_ | 1818274699312889856 |
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| author | Yunlei Zhang Chongliang Zhang Binduo Xu Yupeng Ji Yiping Ren Ying Xue |
| author_facet | Yunlei Zhang Chongliang Zhang Binduo Xu Yupeng Ji Yiping Ren Ying Xue |
| author_sort | Yunlei Zhang |
| collection | DOAJ |
| description | Habitat models have gradually become important tools for assessing and predicting the spatio-temporal distribution of marine organisms. Species are closely associated with each other through biological processes such as predation, competition and mutualism. Neglecting the interaction between species might lead to biased prediction of species distributions, especially for the mid-trophic level species. In this study, the performance of three different kinds of habitat models, i.e., single species distribution model (Generalized linear regression, GLM), ensemble species distribution model (ESDM), and joint species distribution model (JSDM), were evaluated and compared to investigate how trophic interactions will impact the spatio-temporal distributions of mid-trophic fish species in the central and southern Yellow Sea. Potential variations in the distribution and abundance of five mid-trophic level fishes in the central and southern Yellow Sea under climate changes were also analyzed. Results showed that mutually associations derived from food web could explain a large proportion of the positive interactions among species. It was proved that JSDMs could reduce the bias in the estimation of abundance for mid-trophic level fishes by incorporating species trophic interactions, especially for species with low prevalence. The geographic center of gravity of five fishes showed a northward shift of less than 20 km under ocean warming scenarios. Ignoring species trophic interactions would result to overestimate or underestimate abundance of species under climate changes. The abundance of one species (Big head croaker Collichthys lucidus) would decrease, while the other four species would increase because of their different response to climate changes. This study is expected to improve our understanding of the importance of species interactions in predicting the spatio-temporal distribution of species, and will provide guidance for the spatial management strategies of fisheries resources under future climate changes. |
| first_indexed | 2024-12-12T22:18:00Z |
| format | Article |
| id | doaj.art-5a66fca3fa9b4c5185b72093ff06fc13 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-12-12T22:18:00Z |
| publishDate | 2022-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-5a66fca3fa9b4c5185b72093ff06fc132022-12-22T00:10:00ZengElsevierEcological Indicators1470-160X2022-05-01138108826Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishesYunlei Zhang0Chongliang Zhang1Binduo Xu2Yupeng Ji3Yiping Ren4Ying Xue5College of Fisheries, Ocean University of China, Qingdao 266003, ChinaCollege of Fisheries, Ocean University of China, Qingdao 266003, China; Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, ChinaCollege of Fisheries, Ocean University of China, Qingdao 266003, China; Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, ChinaCollege of Fisheries, Ocean University of China, Qingdao 266003, China; Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, ChinaCollege of Fisheries, Ocean University of China, Qingdao 266003, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China; Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, ChinaCollege of Fisheries, Ocean University of China, Qingdao 266003, China; Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, China; Corresponding author.Habitat models have gradually become important tools for assessing and predicting the spatio-temporal distribution of marine organisms. Species are closely associated with each other through biological processes such as predation, competition and mutualism. Neglecting the interaction between species might lead to biased prediction of species distributions, especially for the mid-trophic level species. In this study, the performance of three different kinds of habitat models, i.e., single species distribution model (Generalized linear regression, GLM), ensemble species distribution model (ESDM), and joint species distribution model (JSDM), were evaluated and compared to investigate how trophic interactions will impact the spatio-temporal distributions of mid-trophic fish species in the central and southern Yellow Sea. Potential variations in the distribution and abundance of five mid-trophic level fishes in the central and southern Yellow Sea under climate changes were also analyzed. Results showed that mutually associations derived from food web could explain a large proportion of the positive interactions among species. It was proved that JSDMs could reduce the bias in the estimation of abundance for mid-trophic level fishes by incorporating species trophic interactions, especially for species with low prevalence. The geographic center of gravity of five fishes showed a northward shift of less than 20 km under ocean warming scenarios. Ignoring species trophic interactions would result to overestimate or underestimate abundance of species under climate changes. The abundance of one species (Big head croaker Collichthys lucidus) would decrease, while the other four species would increase because of their different response to climate changes. This study is expected to improve our understanding of the importance of species interactions in predicting the spatio-temporal distribution of species, and will provide guidance for the spatial management strategies of fisheries resources under future climate changes.http://www.sciencedirect.com/science/article/pii/S1470160X22002977Climate changeYellow SeaJoint species distribution modelEnsemble species distribution modelSpatio-temporal distribution |
| spellingShingle | Yunlei Zhang Chongliang Zhang Binduo Xu Yupeng Ji Yiping Ren Ying Xue Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes Ecological Indicators Climate change Yellow Sea Joint species distribution model Ensemble species distribution model Spatio-temporal distribution |
| title | Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes |
| title_full | Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes |
| title_fullStr | Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes |
| title_full_unstemmed | Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes |
| title_short | Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes |
| title_sort | impacts of trophic interactions on the prediction of spatio temporal distribution of mid trophic level fishes |
| topic | Climate change Yellow Sea Joint species distribution model Ensemble species distribution model Spatio-temporal distribution |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X22002977 |
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