太平洋大青鯊種群結構及其管理策略評價研究
發(fā)布時間：2018-08-05 11:45
【摘要】：大青鯊是金槍魚延繩釣漁業(yè)的主要兼捕對象,處于海洋食物鏈的頂端,是海洋生態(tài)系統(tǒng)的高級營養(yǎng)生物,對維持海洋生態(tài)系統(tǒng)的平衡具有重要的作用。隨著人類捕撈壓力的增大,以及氣候變化對大青鯊的生長、分布等產(chǎn)生的影響,太平洋大青鯊的資源可持續(xù)利用面臨巨大的挑戰(zhàn)。鑒于太平洋大青鯊種群結構研究存在較大爭議,種群資源評估結果存在較大的不確定性,迫切的需要研究各種不確定條件下大青鯊種群資源的變化情況。本研究以金槍魚延繩釣科學觀察員采集的樣本為基礎,研究了太平洋大青鯊的種群結構現(xiàn)狀。根據(jù)單種群、雙種群和復合種群3種不同的“真實”種群結構,利用蒙特卡洛方法,模擬了太平洋大青鯊的漁業(yè)狀況,以剩余產(chǎn)量模型和年齡結構模型為評估模型,Fmsy(最大可持續(xù)產(chǎn)量對應的捕撈死亡率),40/10(種群產(chǎn)卵群體的生物量為初始生物量的0.25),恒定的捕撈產(chǎn)量和恒定的捕撈死亡率為捕撈控制規(guī)則,評價了評估模型采用單種群結構和雙種群結構對太平洋大青鯊的資源變化的影響。主要研究內(nèi)容和結果如下:(1)根據(jù)2011年-2014年,我國金槍魚延繩釣捕撈漁船在太平洋3個采樣位點收集到的大青鯊樣本,利用Cytb和COⅠ基因研究了太平洋大青鯊的種群遺傳結構。Cytb和COⅠ基因序列的多樣性分析表明,兩個標記基因分別檢測到3個變異位點,各獲得4種單倍型。Cytb和COⅠ基因序列的多樣性分析結果分別為:h=0.693,π=0.00100和h=0.624,π=0.00126。單倍型多樣性較高,而核苷酸多樣性較低。群體中性檢測結果顯示:Tajima’s D為非顯著的正值,而FU’S FU檢驗為顯著的負值,群體核苷酸錯配分布曲線為明顯的單峰,表明了群體在近期發(fā)生了種群的擴張。推算大青鯊的種群擴張時間大約發(fā)生在21-29萬年前。大青鯊種群分子方差分析顯示,變異主要發(fā)生在種群內(nèi)部的變異,發(fā)生在種群間的變異很少(Cytb基因為3.94%,COⅠ基因為2.16%)。3個采樣群體間的FST分析中,兩兩群體分析結果顯示為非顯著的群體分化。研究結果表明,太平洋大青鯊的不同地理群體之間存在廣泛的基因交流,不存在群體之間明顯的遺傳分化。(2)根據(jù)2011年到2014年中國金槍魚延繩釣科學觀察員計劃獲得的觀察數(shù)據(jù),利用了廣義可加模型(generalizedadditivemodels,gams)分析了生物學性狀(叉長、右鰭角長、攝食等級、性別和基因型)和環(huán)境指數(shù)(海表溫度、月份、經(jīng)度和緯度)之間的關系。結果表明,叉長與漁獲位置(經(jīng)度和緯度)和性別顯著相關,與海表溫度具有明確的正相關。整體上,東部太平洋大青鯊的個體大于西部太平洋大青鯊的群體個體,雄性個體大于雌性個體。海表溫度低于29℃時,叉長隨著海表溫度的升高而增大,超過29℃時,叉長隨著溫度的升高反而減小。叉長與攝食等級,捕撈月份和基因型沒有顯著的關系。右鰭角長與海表溫度和漁獲位置顯著相關,與捕撈月份具有一定的正相關。整體上,東太平洋海域大青鯊的右鰭角長比西部太平洋大青鯊的大,8月和9月捕撈到的大青鯊的右鰭角長明顯大于研究樣本中其他月份捕撈到的大青鯊的右鰭角長。海表溫度從27℃到29.3℃,右鰭角長隨著溫度的升高而減小,當海表溫度大于29.3℃,捕撈到的大青鯊的右鰭角長變大。右鰭角長與攝食等級和基因型之間不存在顯著的關系。根據(jù)目前對大青鯊種群結構的認識,進一步解釋了太平洋大青鯊不同種群結構假設的形成機制。(3)以剩余產(chǎn)量模型為評估模型,蒙特卡洛方法模擬太平洋大青鯊漁業(yè)。以3種種群結構為基礎,結合太平洋大青鯊生物學參數(shù)的研究結果,fmsy,40/10,恒定的捕撈產(chǎn)量和恒定的死亡系數(shù)四種捕撈控制規(guī)則做為管理目標,研究了12種管理策略下太平洋大青鯊的資源變動情況。結果顯示:1)當“真實”種群為復合種群時,4種捕撈控制規(guī)則下,種群的生物量相對誤差和捕撈死亡系數(shù)的相對誤差高于單種群和雙種群研究下的相對誤差;2)當生長系數(shù)k提高時,生物量和捕撈死亡系數(shù)的相對誤差變大;當自然死亡率增大時,生物量和捕撈死亡系數(shù)的相對誤差變大,表明了現(xiàn)階段高估了太平洋大青鯊的相關生物學參數(shù);3)4種不同的捕撈控制規(guī)則中,恒定的捕撈死亡率管理目標導致了大青鯊種群的生物量低于“真實”的bmsy,不能有效的推進太平洋大青鯊種群資源的可持續(xù)利用;fmsy和40/10的管理目標雖然能獲得較高的總可捕量,但其資源在后期將低于“真實”的bmsy。在短時間內(nèi),可以實現(xiàn)大青鯊種群的可持續(xù)利用,但是隨著時間的推移,大青鯊種群生物量下降,不利于大青鯊漁業(yè)的長遠發(fā)展;恒定的捕撈產(chǎn)量(2.3×107尾)控制規(guī)則下能獲得較高的總可捕量,其資源逐漸恢復,且保持較高的生物量,并呈逐漸增加的趨勢。在研究的4種捕撈控制規(guī)則中,恒定的捕撈產(chǎn)量策略更有利于推進太平洋大青鯊種群的可持續(xù)利用(4)采用年齡結構模型為評估模型,恒定的捕撈產(chǎn)量為捕撈控制規(guī)則,研究不同種群結構條件下太平洋大青鯊的資源變動情況。結果顯示:1)“真實”種群為單種群時,評估模型采用單種群結構能維持較高的群體補充量,且呈現(xiàn)繼續(xù)上升的趨勢,有利于大青鯊的可持續(xù)開發(fā),是一種科學的管理策略。當評估模型采用雙種群結構時,可能導致補充群體生物量的下降。2)“真實”種群為雙種群時,評估模型采用雙種群結構能維持較高的群體補充量,且呈現(xiàn)繼續(xù)上升的趨勢,有利于大青鯊的可持續(xù)利用。當評估模型采用單種群結構時,在短期內(nèi),補充群體的生物量高于采用雙種群的評估結果,但是,其群體補充量緩慢下降。3)“真實”種群為復合種群時,評估模型采用雙種群結構能維持較穩(wěn)定的群體補充量(R=7.5×106尾)。當評估模型采用單種群結構時,在短期內(nèi),補充群體的生物量高于R0,但是,在獲得較高的群體補充量后開始明顯下降。
[Abstract]:The Great Green shark is the main target of tuna longline fishing. At the top of the marine food chain, it is an advanced nutrient in the marine ecosystem. It plays an important role in maintaining the balance of the marine ecosystem. With the increase of the human fishing pressure and the influence of climate change on the growth and distribution of the Great Green sharks, the Pacific Ocean has the influence on the growth and distribution of the Great Green sharks. The sustainable utilization of the resources of great green sharks is facing great challenges. In view of the great controversy in the study of the population structure of the Pacific Great Green shark, the result of the population resource assessment has great uncertainty. It is urgent to study the change of the population resources of the Great Green sharks under various uncertain conditions. Based on the sample of the set, the population structure of the Pacific Great Green shark was studied. Based on 3 different "real" population structures of single, double and compound populations, the fishery status of Pacific Great Green shark was simulated by Monte Carlo method. The residual yield model and the age structure model were used as the evaluation model, Fmsy (the maximum sustainable yield). The corresponding fishing mortality rate), 40/10 (the biomass of the oviposition group was 0.25 of the initial biomass), the constant fishing production and the constant fishing mortality were the fishing control rules. The effects of the single population structure and the double population structure on the change of the resources of the Pacific Great Green shark were evaluated. (1) (1) according to the 2011 -2014, Chinese tuna longline fishing boats were collected at 3 sampling sites in the Pacific Ocean. Using the Cytb and CO I genes, the diversity analysis of the genetic structure of the population genetic structure of the Pacific Great Green shark and the sequence of the CO I gene of the Pacific Great Green shark showed that 3 mutation sites were detected by two marker genes, respectively. The diversity analysis results of 4 haplotype.Cytb and CO I gene sequences were h=0.693, PI =0.00100 and h=0.624, and the diversity of PI =0.00126. haplotypes was higher and the nucleotide diversity was lower. The results of population neutral detection showed that Tajima 's D was a non significant positive value, while FU' S FU test was a significant negative value, population nucleotide mismatch distribution. The curve is obvious single peak, indicating the population expansion in the near future. The population expansion time of the Great Green shark has been estimated about 21-29 million years ago. The variance analysis of the population of the Great Green shark population showed that the variation mainly occurred in the population, and the variation in the population was very few (Cytb gene was 3.94%, CO I was 2.16%).3 In the FST analysis among the sample groups, the results of the 22 group analysis showed a non significant group differentiation. The results showed that there were extensive genetic exchanges between different geographical groups in the Pacific Great Green sharks, and there was no obvious genetic differentiation between groups. (2) according to the Chinese tuna longline scientific observer program from 2011 to 2014 Generalizedadditivemodels (gams) was used to analyze the relationship between biological traits (fork length, right fin angle length, feeding grade, sex and genotype) and environmental index (sea surface temperature, month, longitude and latitude). The results showed that the fork length was significantly related to the location of catch (longitude and latitude) and sex, There is a clear positive correlation with the sea surface temperature. On the whole, the eastern Pacific Great Green shark is larger than the population of the Western Pacific Great Green shark. The male is larger than the female. When the sea surface temperature is below 29 degrees, the fork length increases with the rise of the sea surface temperature. When the temperature rises above 29, the fork length decreases with the increase of temperature. The right fin length has a significant correlation with the sea surface temperature and the catch position, and has a positive correlation with the fishing month. On the whole, the right fin angle of the East Pacific sea shark is larger than the Western Pacific Great Green shark. The right fin angle of the Great Green shark caught in August and September is obviously greater than that of the research. The right fin angle of the Great Green shark caught in the other month is long. The sea surface temperature is from 27 to 29.3, and the right fin angle decreases with the increase of temperature. When the sea surface temperature is greater than 29.3, the right fin angle of the captured shark is larger. The right fin angle is not significantly related to the feeding grade and genotype. The understanding of shark population structure further explained the formation mechanism of different species structure hypothesis of Pacific Great Green shark. (3) using residual yield model as evaluation model, Monte Carlo method simulated Pacific Great Green shark fishery. Based on 3 group structure, combined with the study results of biological parameters of Pacific Great Green shark, fmsy, 40/10, constant capture Four fishing control rules for fishing output and constant death coefficient were used as management objectives, and the changes of the resources of the Pacific Great Green sharks were studied under 12 management strategies. The results showed that: 1) when the "real" population was a compound population, the relative error of the relative biomass and the fishing death coefficient of the population was higher than that of the 4 fishing control rules. Relative error of single and double population studies; 2) when the growth coefficient K increased, the relative error of biomass and fishing death coefficient increased; when the natural mortality increased, the relative error of biomass and fishing death coefficient became larger, indicating that the relative biological parameters of the Pacific Great Green shark were overestimated at the present stage; 3) 4 different kinds of fishing. In the control rules, the constant fishing mortality management goal led to the lower biomass of the Great Green shark population than the "true" bmsy, which could not effectively promote the sustainable utilization of the Pacific Great Green shark population; while the management target of fmsy and 40/10 could obtain higher total catch, but its resources would be lower than "real" bmsy. in the later period. In a short period of time, the sustainable utilization of the population of great green sharks can be achieved. However, with the passage of time, the biomass of the shark population decreases, which is not conducive to the long-term development of the Great Green shark fishery; the constant fishing output (2.3 x 107 tail) control rules can obtain a higher total catch, and its resources are gradually restored and maintain high biomass, and present a high biomass. In the 4 fishing control rules, the constant fishing production strategy is more conducive to the sustainable utilization of the Pacific Great Green shark population (4) the age structure model is used as the evaluation model, and the constant fishing yield is the fishing control rule, and the change of the resources of the Pacific Great Green shark under the different population structure conditions is studied. The results are as follows: 1) when the "real" population is a single population, the evaluation model can maintain a high population supplement with a single population structure and continue to rise. It is beneficial to the sustainable development of the Great Green shark. It is a scientific management strategy. When the model uses a double population structure, it may lead to the biomass of the supplemental population. When the "real" population is.2), when the "real" population is a double population, the evaluation model can maintain a high population supplement with a double population structure, and it will continue to rise, which is beneficial to the sustainable utilization of the Great Green shark. When the "real" population is slow down.3) when the "real" population is a compound population, the evaluation model uses a double population structure to maintain a stable population supplement (R=7.5 x 106). When the model uses a single population structure, the biomass of the supplemental group is higher than that of R0 in the short term. Drop.
【學位授予單位】：上海海洋大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：S931.1
本文編號：2165698
[Abstract]:The Great Green shark is the main target of tuna longline fishing. At the top of the marine food chain, it is an advanced nutrient in the marine ecosystem. It plays an important role in maintaining the balance of the marine ecosystem. With the increase of the human fishing pressure and the influence of climate change on the growth and distribution of the Great Green sharks, the Pacific Ocean has the influence on the growth and distribution of the Great Green sharks. The sustainable utilization of the resources of great green sharks is facing great challenges. In view of the great controversy in the study of the population structure of the Pacific Great Green shark, the result of the population resource assessment has great uncertainty. It is urgent to study the change of the population resources of the Great Green sharks under various uncertain conditions. Based on the sample of the set, the population structure of the Pacific Great Green shark was studied. Based on 3 different "real" population structures of single, double and compound populations, the fishery status of Pacific Great Green shark was simulated by Monte Carlo method. The residual yield model and the age structure model were used as the evaluation model, Fmsy (the maximum sustainable yield). The corresponding fishing mortality rate), 40/10 (the biomass of the oviposition group was 0.25 of the initial biomass), the constant fishing production and the constant fishing mortality were the fishing control rules. The effects of the single population structure and the double population structure on the change of the resources of the Pacific Great Green shark were evaluated. (1) (1) according to the 2011 -2014, Chinese tuna longline fishing boats were collected at 3 sampling sites in the Pacific Ocean. Using the Cytb and CO I genes, the diversity analysis of the genetic structure of the population genetic structure of the Pacific Great Green shark and the sequence of the CO I gene of the Pacific Great Green shark showed that 3 mutation sites were detected by two marker genes, respectively. The diversity analysis results of 4 haplotype.Cytb and CO I gene sequences were h=0.693, PI =0.00100 and h=0.624, and the diversity of PI =0.00126. haplotypes was higher and the nucleotide diversity was lower. The results of population neutral detection showed that Tajima 's D was a non significant positive value, while FU' S FU test was a significant negative value, population nucleotide mismatch distribution. The curve is obvious single peak, indicating the population expansion in the near future. The population expansion time of the Great Green shark has been estimated about 21-29 million years ago. The variance analysis of the population of the Great Green shark population showed that the variation mainly occurred in the population, and the variation in the population was very few (Cytb gene was 3.94%, CO I was 2.16%).3 In the FST analysis among the sample groups, the results of the 22 group analysis showed a non significant group differentiation. The results showed that there were extensive genetic exchanges between different geographical groups in the Pacific Great Green sharks, and there was no obvious genetic differentiation between groups. (2) according to the Chinese tuna longline scientific observer program from 2011 to 2014 Generalizedadditivemodels (gams) was used to analyze the relationship between biological traits (fork length, right fin angle length, feeding grade, sex and genotype) and environmental index (sea surface temperature, month, longitude and latitude). The results showed that the fork length was significantly related to the location of catch (longitude and latitude) and sex, There is a clear positive correlation with the sea surface temperature. On the whole, the eastern Pacific Great Green shark is larger than the population of the Western Pacific Great Green shark. The male is larger than the female. When the sea surface temperature is below 29 degrees, the fork length increases with the rise of the sea surface temperature. When the temperature rises above 29, the fork length decreases with the increase of temperature. The right fin length has a significant correlation with the sea surface temperature and the catch position, and has a positive correlation with the fishing month. On the whole, the right fin angle of the East Pacific sea shark is larger than the Western Pacific Great Green shark. The right fin angle of the Great Green shark caught in August and September is obviously greater than that of the research. The right fin angle of the Great Green shark caught in the other month is long. The sea surface temperature is from 27 to 29.3, and the right fin angle decreases with the increase of temperature. When the sea surface temperature is greater than 29.3, the right fin angle of the captured shark is larger. The right fin angle is not significantly related to the feeding grade and genotype. The understanding of shark population structure further explained the formation mechanism of different species structure hypothesis of Pacific Great Green shark. (3) using residual yield model as evaluation model, Monte Carlo method simulated Pacific Great Green shark fishery. Based on 3 group structure, combined with the study results of biological parameters of Pacific Great Green shark, fmsy, 40/10, constant capture Four fishing control rules for fishing output and constant death coefficient were used as management objectives, and the changes of the resources of the Pacific Great Green sharks were studied under 12 management strategies. The results showed that: 1) when the "real" population was a compound population, the relative error of the relative biomass and the fishing death coefficient of the population was higher than that of the 4 fishing control rules. Relative error of single and double population studies; 2) when the growth coefficient K increased, the relative error of biomass and fishing death coefficient increased; when the natural mortality increased, the relative error of biomass and fishing death coefficient became larger, indicating that the relative biological parameters of the Pacific Great Green shark were overestimated at the present stage; 3) 4 different kinds of fishing. In the control rules, the constant fishing mortality management goal led to the lower biomass of the Great Green shark population than the "true" bmsy, which could not effectively promote the sustainable utilization of the Pacific Great Green shark population; while the management target of fmsy and 40/10 could obtain higher total catch, but its resources would be lower than "real" bmsy. in the later period. In a short period of time, the sustainable utilization of the population of great green sharks can be achieved. However, with the passage of time, the biomass of the shark population decreases, which is not conducive to the long-term development of the Great Green shark fishery; the constant fishing output (2.3 x 107 tail) control rules can obtain a higher total catch, and its resources are gradually restored and maintain high biomass, and present a high biomass. In the 4 fishing control rules, the constant fishing production strategy is more conducive to the sustainable utilization of the Pacific Great Green shark population (4) the age structure model is used as the evaluation model, and the constant fishing yield is the fishing control rule, and the change of the resources of the Pacific Great Green shark under the different population structure conditions is studied. The results are as follows: 1) when the "real" population is a single population, the evaluation model can maintain a high population supplement with a single population structure and continue to rise. It is beneficial to the sustainable development of the Great Green shark. It is a scientific management strategy. When the model uses a double population structure, it may lead to the biomass of the supplemental population. When the "real" population is.2), when the "real" population is a double population, the evaluation model can maintain a high population supplement with a double population structure, and it will continue to rise, which is beneficial to the sustainable utilization of the Great Green shark. When the "real" population is slow down.3) when the "real" population is a compound population, the evaluation model uses a double population structure to maintain a stable population supplement (R=7.5 x 106). When the model uses a single population structure, the biomass of the supplemental group is higher than that of R0 in the short term. Drop.
【學位授予單位】：上海海洋大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：S931.1
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