Estimating Potential Yield For Neon Flying Squid (Ommastrephes Bartramii) In The Northwest Pacific Ocean Based On Habitat Suitability Index Model

Neon flying squid （Ommastrephes bartramii） mainly caught by China （includingTaiwan province） and Japan is one of the most important economic species in theNorthwest Pacific Ocean. The western winter-spring cohort is the traditional targetspecies for Chinese squid jigging fleets in the Northwest Pacific Ocean. In recent years,the sustainable use and development of oceanic fishery resources is drawing more andmore international communities’ attention. The North Pacific Regional FisheryManagement Organization （NPRFMO） established by the United States, Japanese,Chinese and other countries regions has decided to manage the resource of O.bartramii. To evaluate the situation of this resource and estimate the potential yield isthe base of achieving the sustainable use and management of this resource of squid.As an index of evaluating the suitability of wildlife, the habitat suitability index（HSI） model has been wildly used in terrestrial wildlife habitat evaluation. HSI modelhas been of great concern and attention by biologists, ecologists and decision-makers,and is increasely applied in fishery resource exploitation, management, assessment andprotection. In this paper, based on the data of Chinese mainland squid fishery for yearsand environment of squid habitats, including Sea Surface Temperature （SST）, theGradient of SST （GSST） and Sea surface Height （SSH） in the feeding ground, weanalyzed the relationship between the fishing areas and environmental factors for O.bartramii in Northwest Pacific Ocean, and focused on the evaluation of the role of thespace and temporal scale in quantifying the squid habitat. The importance of weightingfor multi-variable HSI model for O. bartramii in Northwest Pacific Ocean had beenemphasized. On the above results, we estimated the potential yield of this squid inNorthwest Pacific Ocean. The results were as follows: （1） The distribution of fishing ground of O. bartramii in Northwest Pacific Oceanwas closely related to the environmental factors. SST, GSST and SSH were threeimportant environmental factors indicating the fishing ground for O. bartramii. Basedon the commercial fishery data from Chinese squid jigging fleets in the NorthwestPacific Ocean and SST, GSST and SSH data from August to October during2003-2008,the relationship between the fishing ground of O. bartramii and the environmentalvariables has been analyzed monthly. The results showed that the central fishingground was concentrated in the range of19-23℃for SST,0.5-1.5℃for GSST, and-15--10cm and-5-10cm for SSH in August. In September, the center of fishing groundwas manly distributed at the SST value of15-18℃, GSST value of0-1.5℃and2-2.5℃, and SSH value of-15-10cm. In October, the central fishing ground was highlyconcentrated in the SST range of15-16℃, GSST range of0.5-2℃and SSH range of0-10cm.（2） Evaluate roles of spatio-temporal scales in quantifying the habitat of westernstock of winter-spring cohort of neon flying squid in the Northwest Pacific Ocean. Weused the fishery-dependent data from Chinese Mainland Squid Jigging TechnicalGroup and SST data from remote sensing, and evaluated differences in a HSI modelresulting from aggregating data among12scenarios of different spatial scales with acombinations of three latitude scales （0.5°,1°and2°） and four longitude scale（0.5°,1°,2°and4°） for three temporal scales （week, fortnight, and month）. The coefficient ofvariations （CV） of the weekly, biweekly and monthly SIs were compared to determinewhich temporal and spatial scale of SI model is relatively more precise. The totaldifferences between ScenarioⅠand other scenarios summed up all percentage offishing effort in each SI value reflect the impact of spatial scales used in aggregatingdata. A mean relative difference index （MRDI） was calculated for each scenario toquantify the impact. This study showed that temporal and spatial scales used for dataaggregation can greatly influence habitat suitability modeling. The CVs tended toincrease with the longitude scales and when the latitude scale was fixed. When thelongitude scales were fixed, the lowest CV was found at the latitude scale of1°forweekly scenarios. For biweekly data, the CVs tended to increase with latitude scale.The same trend could be found for all monthly scenarios. MRDI values for weekly dataincrease quickly with the spatial scales, but the increase lessened when the spatial scalewas larger than2°squares. The same trend could be found for month scenarios, butlarge MRDI values were received. For biweekly data, MRDI values showed much variation across the area of spatial grids. MRDI values increased when the size wassmaller than2°squares, and then decreased quickly and slowly increased from4°squares to8°squares. Large differences in MRDI values among scenarios with thesame area but different latitude and longitude scales for all of the temporal scale offishing effort. We conclude that habitat model developed with an optimal scale with thetime step of week and the space of0.5°longitude and0.5°latitude can improveforecasting fishing ground.（3） Evaluate and analyze the impact of weightings for different environmentalfactors in HSI modeling. Weighting for habitat variables used in a multi-factors HSImodeling reflect different influences of the variables on distribution of winter-springcohort of neon flying squid in the Northwest Pacific Ocean. HSI model was establishedby SST, GSST and SSH. Ten weighting schemes were considered for these threevariables in HSI modeling （0.33-0.33-0.33,0.4-0.4-0.2,0.4-0.3-0.3,0.5-0.4-0.1,0.5-0.3-0.2,0.5-0.25-0.25,0.6-0.3-0.1,0.6-0.2-0.2,0.7-0.2-0.1,0.7-0.15-0.15）. Toevaluate the impact of different weighting schemes on the HSI model, the HSI valueswere compared among the10weighting schemes using a relative difference index（RD）. This study showed that weighting could greatly influence HSI modeling. Theperformance of different HSI models with different weights for each of the threevariables were evaluated and compared to identify the most suitable HSI model basedon the residual standard error （RSR）. The model that yielded the minimum RSR valuewas chosen as the best model. And the results showed that the most suitable model wasestablished by SST, GSST and SSH with the weights of0.5,0.25and0.25respectively.（4） Estimate the potential yield using HSI model for neon flying squid in theNorthwest Pacific Ocean. HSI and the estimation of potential yield for each specificfishing area are dirived from the basis of information on three environmental variables,namely sea surface temperature （SST）, the gradient of SST （GSST） and sea surfaceheight （SSH）. All samples are from1130fishing area in the Northwest Pacific Oceanfrom Agust to October. This study have been showed that there were a linear regressionmodel between the maxmum potential weekly yield in each fishing area and HSI（Y=2000HSI） and an exponential model between the average weekly yield and HSI(Y=30.08e^1.83HSI). The standard error is large in which the HSI is low （0-0.1） and high（0.9-1）. The exponential model predictions are conservative when the HSI is between0.9and1. The results of predictions from2003to2008have been showed that theexpontential model can make better predictions of the yield for O. bartramii.