DEB-IBM for predicting climate change and anthropogenic impacts on population dynamics of hairtail Trichiurus lepturus in the East China Sea

Tao Yang; Qingpeng Han; Harry Gorfine; Xiujuan Shan; Jeffrey S Ren

doi:10.1093/conphys/coac044

DEB-IBM for predicting climate change and anthropogenic impacts on population dynamics of hairtail Trichiurus lepturus in the East China Sea

Conserv Physiol. 2022 Jul 11;10(1):coac044. doi: 10.1093/conphys/coac044. eCollection 2022.

Authors

Tao Yang¹, Qingpeng Han¹, Harry Gorfine², Xiujuan Shan¹, Jeffrey S Ren³

Affiliations

¹ Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 106 Nanjing Road, Qingdao 266071, People's Republic of China.
² School of Biosciences, The University of Melbourne, Parkville 3010, Australia.
³ Function Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), 1 Wenhai Road, Aoshanwei, Jimo, Qingdao 266200, People's Republic of China.

Abstract

The hairtail Trichiurus lepturus supports the largest fisheries in the East China Sea. The stock has fluctuated in the past few decades and this variation has been attributed to human pressures and climate change. To investigate energetics of individuals and population dynamics of the species in responses to environmental variations and fishing efforts, we have developed a DEB-IBM by coupling a dynamic energy budget (DEB) model to an individual-based model (IBM). The parameter estimation of DEB model shows an acceptable goodness of fit. The DEB-IBM was validated with histological data for a period of 38 years. High fishing pressure was largely responsible for the dramatic decline of the stock in middle 1980s. The stock recovered from early 1990s, which coincided with introduction of fishing moratorium on spawning stocks in inshore waters and substantial decrease of fishing efforts from large fisheries companies. In addition, the population average age showed a trend of slight decrease. The model successfully reproduced these observations of interannual variations in the population dynamics. The model was then implemented to simulate the effect of climate change on the population performance under greenhouse gas emission scenarios projected for 2100. It was also used to explore population responses to changing fishing mortalities. These scenario simulations have shown that the population biomass under SSP1-1.9, SSP2-4.5 and SSP5-8.5 would decline by 7.5%, 16.6% and 30.1%, respectively, in 2100. The model predicts that increasing fishing mortality by 10% will cause 5.3% decline of the population biomass, whereas decrease of fishing mortality by 10% will result in 6.8% increase of the biomass. The development of the DEB-IBM provides a predictive tool to inform management decisions for sustainable exploitation of the hairtail stock in the East China Sea.

Keywords: DEB model; environment; fisheries; human pressure; population model.