## 3 Results
### Ensemble Model Application Effect  
To explore the application effect of the ELM on the forecast of different grades of al-bacore fishing grounds in the South Pacific, based on the longitude, latitude and environmental data from January to December of 2009 to 2017, the ELM was used to forecast the distribution of different grades of albacore fishing grounds from January to December of 2018 to 2019, as shown in Figure 7. Table 3 shows each accuracy index of the ELM for forecasting the distribution of albacore fishing grounds in different months. Because the operation of fishing vessels will be subject to the relevant legal system and weather con-straints in the South Pacific Ocean, CPUE does not fully represent the true grade of fishing grounds. Therefore, this paper used the high-yield recall (\(R_{2}\)) and low-yield recall (\(R_{1}\)) as the main evaluation indexes of the ELM for the forecast accuracy of high-yield and low-yield albacore fishing grounds in the South Pacific Ocean, respectively, and integrated other model evaluation indexes as the test method for the forecast accuracy of albacore fishing grounds. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Month** & **ACC** & **R\({}_{\mathbf{1}}\)** & **R\({}_{\mathbf{2}}\)** & **P\({}_{\mathbf{1}}\)** & **P\({}_{\mathbf{2}}\)** \\ \hline
1 & 88.42\% & 95.00\% & 86.67\% & 65.52\% & 98.48\% \\
2 & 85.44\% & 96.15\% & 81.82\% & 64.10\% & 98.44\% \\
3 & 87.25\% & 72.97\% & 95.38\% & 90.00\% & 86.11\% \\
4 & 81.74\% & 65.79\% & 89.61\% & 75.76\% & 84.15\% \\
5 & 81.94\% & 58.33\% & 92.52\% & 77.78\% & 83.19\% \\
6 & 74.71\% & 47.37\% & 88.50\% & 67.50\% & 76.92\% \\
7 & 88.30\% & 75.51\% & 93.44\% & 82.22\% & 90.48\% \\
8 & 92.02\% & 82.98\% & 95.69\% & 88.64\% & 93.28\% \\
9 & 92.96\% & 80.95\% & 98.00\% & 94.44\% & 92.45\% \\
10 & 93.81\% & 88.89\% & 96.10\% & 91.43\% & 94.87\% \\
11 & 92.98\% & 85.71\% & 96.20\% & 90.91\% & 93.83\% \\
12 & 83.50\% & 74.29\% & 88.24\% & 76.47\% & 86.96\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of accuracy of each evaluation index based on ELM forecasts for different grades of albacore fishing grounds in January–December 2018–2019. Figure 7: Distribution of different grades of albacore fishing grounds by month in 2018–2019 based on ELM forecasts. To test the effect of the ELM on the forecast of different grades of albacore fishing grounds, the fishing ground grades obtained from the forecast of each month were superimposed on the real fishing ground grades in the original sea area based on the ARCGIS software (Figure 7). As shown in Table 3, the ranges of the different accuracy indicators of the ELM for the South Pacific albacore fishing ground forecast from January to December were 74.71-93.81% (_ACC_), 47.37-96.15% (_R_1), 81.82-98.00% (_R_2), 64.10-94.44% (_P_1) and 76.92-98.48% (_P_2). Among them, the ELM achieved the highest forecast precision (_P_2) for the high-yield albacore fishing grounds in January (98.48%). The high-yield fishing grounds were mainly concentrated between 10\({}^{\circ}\) S-25\({}^{\circ}\) S and 145\({}^{\circ}\) E-170\({}^{\circ}\) W, as shown in Figure 7, where the fishing grounds were more scattered in the waters between 170\({}^{\circ}\) W and 130\({}^{\circ}\) W, while no fishing grounds appeared between 25\({}^{\circ}\) S and 35\({}^{\circ}\) S. The high-yield fishing grounds appeared between 35\({}^{\circ}\) S-40\({}^{\circ}\) S and 175\({}^{\circ}\) E-180\({}^{\circ}\) waters, while the low-yield fishing grounds were mainly distributed between 0\({}^{\circ}\) S and 10\({}^{\circ}\) S, and the areas where the actual high-yield fishing grounds were incorrectly forecast as low-yield fishing grounds were almost all distributed between 0\({}^{\circ}\) S and 10\({}^{\circ}\) S. The ELM had the highest recall rate (_R_1 = 96.15%) for low-yield albacore fishing grounds in February (Table 3), but the high-yield recall (_R_2 = 81.82%) and low-yield precision (_P_1 = 64.10%) forecasted by the ELM for albacore fishing grounds were the lowest in February.