| Anchoveta(Engraulis ringens)is one of the small pelagic fish species living in the Southeast Pacific Ocean.As an important commercial fish,its fishery has formed the largest production in the world's single species fishery.Besides,Anchoveta's catch is also the main source of fishmeal.In this case,exploring the processes that its abundance and fishing grounds vary with oceanic environmental factors could help understand the variations in fish stocks and be beneficial for its sustainable utilization.Therefore,this study used the catch data collecting from Peru ports during ten years(2005 to 2014)combining with the oceanic environmental factors(temperature,sea surface wind stress,nino index,etc.)to study the following items:(1)the temporal and spatial variations of anchoveta's fishing grounds;(2)the relationship between anchoveta's fishing grounds and oceanic environmental factors deriving from remote sensing;(3)analysis to the forming mechanisms for the Anchoveta fishing ground by the Peruvian upwelling;(4)searching to the key isotherms which could indicate the productive fishing ground;(5)the changing patterns of anchoveta abundance in recent years(6)how to forecast the anchoveta's biomass.The followings are the main conclusions for this study:(1)The regular changing pattern for the fishing season and fishing ground of anchoveta in the coastal waters of Peru.In this area,there were two fishing seasons in one year.The beginning and end month was April and August for the first fishing season,while this time for the second fishing season was from November to the next year's January.The descriptive statistics for the catch and effort showed that the primary fishing period in first and second fishing season was from April to June and November to December,respectively.The coastal area from 7oS to 14oS was the main fishing area.There was no obviously change for the monthly CPUE in this area.In addition,the southern area(16-18 oS)could be seen as an another fishing location.In June and November which had the condition of seasonal shift,fishing in the area around 5oS could also have high CPUE.The standard deviation suggested that there was obvious annual difference of fishing ground(2)The relationship between the variations of Peru coastal anchoveta fishing ground and oceanic environmental factors.The ranges of optimum oceanic environmental factors had differences in each fishing months.There was decreasing trend of optimum sea surface temperature(SST)as month passed in the first fishing season while in the second fishing season there was increasing trend for the optimum SST from November to January.Each fishing month in both fishing season nearly had the same optimum sea surface height(SSH)range(29-41cm).However,there were not obvious regular changing patterns in the variations of optimum chlorophyll-a(chl-a)as month passed.But the range of chl-a was narrowed with the month passing in both fishing season.The empirical cumulative distribution function suggested that the optimum oceanic environmental and its ranges could be used as indicators for forecasting the fishing ground.But there was no obvious pattern for the nominal CPUE changing with each oceanic environmental factor.(3)The effects of Peru upwelling to the anchoveta fishing ground.In the first fishing season from 2005 to 2009,the upwelling velocity(UV),temperature(T)and temperature anomaly(TA)in the fishing ground was 1.42×10-5-7.44×10-5m·s-1,16.61–19.42?and 1.87– 1.69?,respectively.The results of generalized additive model(GAM)could effectively explain the changing trend of nominal CPUE.The optimum range for each factor based on GAM was UV: 4–4.6×10-5m·s-1;T: 18.4?–19.5? and TA:-2?–-0.2?.When UV was lower than 4.6×10-5m·s-1,the CPUE increased with UV.However,when UV was larger than this value,the GAM showed a decreasing trend of CPUE.The studies suggested that the upwelling's impact to the anchoveta fishing ground was not following the pattern “the higher,the better”.There was also optimum range of upwelling velocity for the fishing ground.The study showed that the optimum sea surface wind,moderate upwelling and appropriate temperature condition were beneficial for the fishing ground formation.(4)Effects of sea surface temperature variations on the fishing ground of anchoveta.This study developed the fishing ground index(FGI)which combined CPUE and fishing effort data.And anchoveta fishing ground were further divided into different types and related with the SST isotherms.Through the analysis of variance,significant differences(P<0.01)were found for FGI with the fishing periods(earlier stage,mid stage and later stage)and fishing areas(north area,middle area and south area).We defined the fishing ground of anchoveta as “A” type fishing ground and “B” type fishing ground.When the former type occurred,the warm surface waters(>20?)had not intruded into the near shore area;however,the latter type occurred,the warm surface waters(>20?)had intruded into the near shore area.It suggested that “A” type fishing ground is favorable for the formation of fishing ground in the earlier or mid stage of fishing periods.Moreover,the 19oC or 20oC SST isotherm in earlier stage and the 18 oC or 19 oC SST isotherm in mid stage being closest to the coast area could be used as the indicators to explore the productive fishing ground.(5)Temperal changing patterns of anchoveta abundance from 2005 to 2014.The studies used the GAM to standardize the nominal CPUE in order to get the temperal changing patterns of anchoveta abundance in recent years.This model could explain the 33.4% deviance of ln(CPUE).And the facor year could explain the largest deviance(14%).The annual changing patterns of anchoveta abundance from 2005 to 2011 was increased in volatility while during the next three years,this pattern became declining.The study showed that when El Ni?o happened(2005 and 2009),the abundance index was located at relatively low level during the ten years from 2005 to 2014.However,when La Ni?a occurred(2008 and 2011),there was a high level for the abundance index.This study also showed that the abundance index in one fishing season was negatively correlated with the temperature at the nino1+2 region from two months before fishing season to the month when fishing season occurred.(6)Forecasting model to the anchoveta biomass.This study used the biological factors(percentage of juvenile and previous biomass),catch and oceanic environmental factors(temperature status in the fishing ground and climatic variations)as forecasting variables to build the anchoveta biomass forecasting model combing the biomass data in seventeen fishing season(from 2006 to the first fishing season of 2014).The model was built by the methods of principal component analysis(PCA)and multiple linear regression.Besides,the study also evaluated the influence level of a factor to the changes of anchoveta biomass.With the increase of sample size,the mean of relative error of predicting sequences and actual sequences became smaller,and the correlation coefficient between them increased.Finally,model 5(modeling the data from 2006 to 2013 and validating the data in the first fishing season of 2014)can effectively fit out the trends of avchoveta biomass: the correlation coefficient of predicting sequences and actual sequences was 0.86(P<0.01)and the mean relative error for this two sequences was 12%.What's more,the relative error was only 1% for the predicting value in the first fishing season at 2014.The PCA showed that the order of factors affecting the anchoveta biomass was environmental factors,surplus population biomass,catch and their recruitment. |
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