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農漁業健康環境形塑--運用客製化天氣與氣候資訊

  • 日期:107-02-20
  • 計畫編號:107農科-7.8.5-水-A1
  • 年度:2018
  • 領域:農糧與農環科技研發
  • 主持人:張可揚
  • 研究人員:張庭槐、陳玉姬

劍尖槍魷( Uroteuthis edulis )為臺灣燈火漁業的重要漁獲物種之一。由於頭足類 資源多受環境影響而呈現年間波動,因此易受過度捕撈的影響,導致資源的崩潰 ,凸顯資源評估之重要。本研究以單位努力漁獲量 (catch per unit of effort, CPUE) 為資源指標,與月別北極震盪指數、月別海洋Niño指數及不同時空之海表面 水溫 (surface water temperature, SST)、海表面葉綠素濃度 (sea surface chlorophyll-a, SSC) 等環境因子進行相關分析及廣義線性模式(generalized linear model, GLM)套適,以建立劍尖槍鎖管資源評估模式,掌握資源變動趨勢。 為進行資源趨勢預測,以所得模式帶入中央氣象局提供之SST預測資料,進行下一年 度鎖管資源變化趨勢之評估。在加入新的漁獲資料後,在所有環境因子中,臺灣北 部海域湧升流區 (主要繁殖場) 在繁殖季間 (漁期當年3月) 的SST與劍尖槍魷資源 量有正相關,而東海陸棚 (主要成長海域) 在漁季前一年11月 之SST與劍尖槍魷資 源量則為負相關。經AIC選擇之GLM將前述二項因子納入模式,解釋率為92.4%

研究報告摘要(英)


Uroteuthis edulis as the main catch species of the torch light fishery in Taiwan. Due to the cephalopod resources was affected by the environment and fluctuated between years, it was so vulnerable to the impact of overfishing and led to the collapse, highlighting the importance of resource assessment. In this study, the catch per unit effort (CPUE) was used as the resource index to correlate with the environmental factors such as the monthly Arctic Oscillation Index, the monthly Niño Index, and the sea surface temperature (SST) and sea surface chlorophyll-a (SSC) in different temporal and spatial and generalized linear model (GLM) was used to establish the U. edulis resource assessment model to grasp the trend of resource. In order to forecast the resource trend, the SST forecast data provided by the Central Meteorological Administration brought into the income model to evaluate the trend of the lock resource change in the next year. After adding new catch data, among all environmental factors, the SST in the upwelling area (main breeding ground) in northern Taiwan waters during the breeding season (the March of the fishing season) is positively correlated with the amount of theU. edulis . In the East China Sea Shed (mainly growing sea area), the SST in November of the year before the fishing season was negatively correlated with the amount of U. edulis . The GLM selected by AIC incorporates the aforementioned two factors into the model with an interpretation rate of 92.4%.