2015-01-012024-05-17https://scholars.lib.ntu.edu.tw/handle/123456789/671675摘要：本研究支計劃目標為探討海洋環境因子如何影響秋刀魚在北太平洋的時空分佈。這裡，我們著重在探討海水溫度與海洋生產力（以葉綠素a為指標）的影響。本研究符合以生態系為基礎之漁業經營管理的範疇。 我們有以下主要工作：一 , 建立每個月的生物量分布圖，其空間解析度為0.5度方格。在此，生物量以漁獲單位努力量(CPUE)為代表，CPUE由每0.5度方格之漁獲及努力量換算得來。二, 利用衛星資料，建立每個月相對應的海水溫度與海洋生產力分布圖。三, 缺值的部分，利用內插法填補。四, 利用每個月的生物量分布圖，我們可以計算每個月或每年的生物分佈中心，分佈中心的時間序列變化，可以讓我們瞭解秋刀魚的遷徙。五, 使用泛線性模式（GLM），我們分析海水溫度與海洋生產力對秋刀魚生物量的時空分佈之影響，模式如下：Biomassi,j,k=α+β1SSTi,j,k+ β2Chlai,j,k+ β3SSTi,j,k*Chlai,j,k +εi,j,k, 在此 i 代表時間, j, k 代表經緯度, 而殘差部分包含時空上的自相關(ε~Normal(0, Σ), where Σ is variance-covariance matrix of the error term) 。 六，使用泛線性模式，我們分析北太平洋區域平均的海水溫度與海洋生產力如何影響秋刀魚的分佈中心，模式如下：Centrodi=α+β1SSTi+ β2Chlai +β3SSTi*Chlai +εi, 在此 i 代表時間(可以是月平均或年平均)，Centrod 可以是經度或緯度, SST 和Chla 代表海水溫度與海洋生產力的區域月或年平均值。此分析主要探討整個海域的環境變異如何影響秋刀魚的分佈中心。使用泛線性模式之結果，預測溫度上升對秋刀魚族群大小及空間變動之可能影響。 透過這些分析，我們預期可以解析環境因子如何影響秋刀魚在北太平洋的時空分佈。這些資訊，可以有助於秋刀魚之資源評估與管理。 <br> Abstract: The objective of this proposal is to investigate spatiotemporal variation of Pacific saury driven by ocean conditions, including sea surface temperature (SST) and chlorophyll a (Chla, as a proxy for ocean productivity). This objective falls importantly in the scope of ecosystem approach to fisheries. To achieve the goal, 1) we produce monthly map of biomass (using CPUE as a proxy) distribution of Pacific saury with spatial resolution of 0.5 by 0.5 degree from 2002 to 2013. CPUE data can be calculated from catch and effort data from the fishery agency. 2) We compile satellite data to construct corresponding monthly map of SST and Chla with the identical spatial resolution. 3) Missing data are imputed using interpolation. 4) We also calculate monthly distribution of biomass-weighted centroid in space, which can be used to track the migration of Pacific saury. 5) We employ generalized linear model (GLM) to investigate the relationship between biomass of saury versus SST and Chla, following Biomassi,j,k=α+β1SSTi,j,k+ β2Chlai,j,k+ β3SSTi,j,k*Chlai,j,k +εi,j,k, where i indicates time, j indicates latitude, and k indicates longitude, and the error term contains autocorrelation structure in space and time (ε~Normal(0, Σ), where Σ is variance-covariance matrix of the error term). 6) We also employ GLM to investigate the relationship between centroid of saury versus SST and Chla, following Centrodi=α+β1SSTi+ β2Chlai +β3SSTi*Chlai +εi, where i indicates time (monthly or yearly). Note here, Centrod can be latitude or longitude, and SST and Chla represents the monthly or yearly spatially-average value. The purpose here is to examine whether change in regional SST and/or Chla can affect the spatial distribution of Pacific saury. 7) Based on the results of GLM, we will explore the effects of increasing temperature on the abundance and distribution of saury population. From this project, we expect to obtain understandings of environmental impacts on abundance and distribution of the Pacific saury. The information gained in this research will be useful for managing the stock of Pacific saury.秋刀魚時空分析環境變異Cololabis sairaspatial-temporal analysisenvironmental variation