The Influence of Spatial and Temporal Scales on Fisheries Modeling—An Example of Sthenoteuthis oualaniensis in the Nansha Islands, South China Sea

Abstract

The choice of spatial and temporal scales affects the performance of fisheries models and is particularly important in exploring the relationship between resource abundance and the marine environment. Traditional fishery models are constructed at a particular scale, and the results of the study hold only at that scale. Sthenoteuthis oualaniensis is one of the main target species of large-scale light falling-net fishing in the Nansha Islands in the South China Sea. We used the S. oualaniensis fishery in the Nansha Islands as an example to compare the performance of fisheries models for 12 spatial and temporal settings and to explore the relationship between the abundance of S. oualaniensis and the marine environment in the Nansha Islands under the optimal spatial and temporal settings. The results show that the spatial and temporal scale chosen in the construction of the fishery model is not as fine as possible in generalized additive models (GAMs) for abundance index-catch per unit effort (AI-CPUE)-based scenarios, and 0.5° with the season was the best spatial and temporal setting; meanwhile, in GAMs for AI-effort-based scenarios, 0.1° with the month was the best spatial and temporal setting. The distribution of S. oualaniensis resources in the Nansha Islands was characterized by significant seasonal variation, and the monthly center of gravity had a significant negative correlation with the Niño 3.4 index and the PDO index, with correlation coefficients of 100 and 1000, respectively. It is hypothesized that Pacific Decadal Oscillation and ENSO events affect the marine environment in the South China Sea by influencing the strength of the Kuroshio force and the degree of Kuroshio curvature, which in turn affects the distribution of S. oualaniensis in the Nansha Islands. The results help us to understand the influence of spatial and temporal scales on fisheries models and the environmental factors affecting the distribution of S. oualaniensis resources in the Nansha Islands. Thus, they provide a scientific basis for the sustainable development of S. oualaniensis fisheries in this region.