Back

Biodiversity and local interaction complexity promote sustainable fisheries in large food webs

Werner, A.; Albert, G.; Brose, U.; Gauzens, B.

2022-12-12 ecology
10.1101/2022.12.08.519558 bioRxiv
Show abstract

On a global scale, fisheries harvest an estimated 96 million tonnes of fish biomass annually, making them one of the most important drivers of marine ecosystem biodiversity. Yet little is known about the interactions between fisheries and the dynamics of complex food webs in which the harvested species are embedded. We have developed a synthetic model that combines resource economics with complex food webs to examine the direct effects of fishing on exploited species and the indirect impact on other species in the same community. Our model analyses show that the sensitivity of the targeted species increases with its trophic level and decreases with its local interaction complexity (i.e. its number of interactions with prey, predators, and competitors). In addition, we also document a strikingly positive effect of community species richness on the resilience of the harvested species to this disturbance. The indirect effects on other species show specific patterns of spreading across trophic modules that differ systematically from how other disturbances spread across ecological networks. While these results call for further research on how human resource exploitation in general and fishery in particular affect ecological dynamics and biodiversity in naturally complex systems, they also allow for some cautious conclusions. Taken together, our results suggest that the sustainability concerning fishery yield and ecosystem integrity can be maximised by focusing the harvest on low trophic level species with a high local interaction complexity in high biodiversity ecosystems. In this sense, our complex network approach offers a promising avenue for integrating the necessities of generating economic revenue with the protection of natural biodiversity.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Ecological Modelling
24 papers in training set
Top 0.1%
19.2%
2
Scientific Reports
3102 papers in training set
Top 4%
12.4%
3
PLOS Computational Biology
1633 papers in training set
Top 4%
8.3%
4
PLOS ONE
4510 papers in training set
Top 23%
8.3%
5
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 1%
6.3%
50% of probability mass above
6
Ecology and Evolution
232 papers in training set
Top 1%
3.5%
7
Frontiers in Ecology and Evolution
60 papers in training set
Top 1%
3.0%
8
Theoretical Ecology
21 papers in training set
Top 0.1%
2.8%
9
Nature Communications
4913 papers in training set
Top 44%
2.7%
10
Bulletin of Mathematical Biology
84 papers in training set
Top 0.8%
2.3%
11
Royal Society Open Science
193 papers in training set
Top 1%
2.1%
12
Oikos
74 papers in training set
Top 0.3%
1.8%
13
Mathematical Biosciences
42 papers in training set
Top 0.6%
1.7%
14
Journal of The Royal Society Interface
189 papers in training set
Top 3%
1.6%
15
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 35%
1.5%
16
The American Naturalist
114 papers in training set
Top 1%
1.5%
17
Science of The Total Environment
179 papers in training set
Top 4%
1.3%
18
Journal of Clinical Medicine
91 papers in training set
Top 5%
1.2%
19
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 4%
1.2%
20
Peer Community Journal
254 papers in training set
Top 3%
1.2%
21
Journal of Theoretical Biology
144 papers in training set
Top 1%
0.9%
22
PeerJ
261 papers in training set
Top 12%
0.9%
23
Conservation Letters
11 papers in training set
Top 0.4%
0.9%
24
Ecological Applications
28 papers in training set
Top 0.7%
0.7%