摘要:了解漁業與氣候變遷對漁撈族群的協同效應,是進行生態系漁業管理的重要課題,比較不同緯度生態系統內生活史特性各異的魚群,可釐清漁業捕撈是否會增加族群對環境敏感度。因此,本研究將對魚群時空變化進行統合分析,了解受高撈漁壓力的魚種是否對環境變化有較明顯反應。
空間分析部份將分析各地之長期魚群分佈資料,了解魚群分佈位移是否隨環境變化(如溫度等氣候變化參數)改變;在考慮生活史差異後,漁撈是否仍有顯著影響。本研究將驗證以下兩項假說:一、高緯度物種對氣候變化的反應較低緯度劇烈。二、同一,但漁撈影響隨緯度增加而下降。假說驗證則是將各魚種的分佈中心或界線之時間序列對氣候因子作迴歸,再以廣義線性混合模式分析生活史、緯度與漁撈的影響。
時間分析將收集全球漁業資源評估報告中之親魚量、添加量與年齡結構進行統合分析,並將驗證以下兩項假說:一、親魚量、添加量與族群成長率(將年齡結構以Leslie矩陣模型估算)與環境變化的相關性隨著漁撈死亡率上升而增加。二、族群變動程度隨死亡率上升而增加。此分析將以窗區法進行迴歸分析,並檢驗此結果是否與生活史特性和緯度有關。
本研究目的為發展分析氣候與漁撈對捕撈魚群之協同效應的準則,此研究結果有助於對氣候變遷下的資源管理提出因應策略。
Abstract: Understanding synergistic effects of fishing and climate on exploited fishes is critical in ecosystem-based fisheries management. Chance of achieving such understanding can be greatly enhanced if comparative studies encompassing species of different life history traits from various ecosystems across latitudes can be conducted. Specifically, we ask whether and why fishing may enhance environmental sensitivity of exploited stocks. To do this, we aim to carry out meta-analysis to examine whether fishes under stronger fishing pressure would show a clearer response to environmental variation. Our study includes both spatial and temporal components.
For spatial analyses, we carry out a meta-analysis using long-term distributional data of fishes from the east and west coast of US, North Sea, Bering Sea, and Japan Sea to investigate to what extent the distributional shift of marine fishes was determined by environmental changes (such as temperature or climate patterns) and whether fishing plays a role, after accounting for life history variation. We tested the hypotheses: 1) Species in the high latitude have stronger response rate and they are more sensitive to climate than those in low latitude. 2) The exploited species are more sensitive to climate than unexploited species, but the effects (contribution) of fishing decreases with increasing latitude. To test the hypothesis, we first carry out regression analysis on time series of latitudinal centers (or boundaries) of the fish population versus temperature (or climate indices) for each species (including exploited and unexploited species), also accounting for abundance and time series autocorrelation. We then analyze the semi-partial R-square and slope values of the regression analyses in relation to life history traits, latitude, and fishing, using a generalize linear mixed effects model.
For temporal analyses, we carry out a meta-analysis using long-term time series data of stock spawning biomass (SSB), recruitment, and age structure compiled from the global fisheries assessment reports. Using the Leslie matrix model, we can estimate the time series of population growth rates from the population age structure data. We test the hypotheses: 1) The SSB, recruitment, and population growth rates exhibit an increasing correlation with environmental variation as fishing mortality increases. 2) The population variability increases with fishing mortality. To analyze each species, we predetermine a window, calculate the correlation coefficient between the population metrics (SSB, recruitment, and growth rate) versus environmental variation, and slide the window forward. We then examine whether the windowed correlation coefficients show a positive relationship with the fishing mortality averaged within that window. Likewise, we calculate the variability of the population metrics within the predetermined window. Then, we exam whether the population variability increases with fishing mortality when the window slides forward. Sensitivity analyses shall be done on the effect of window size. Meta-analysis shall then be carried out to examine whether the pattern is related with the life history traits and latitude.
Here, we aim to develop a guideline for analyzing synergistic effects of climate and fishing on exploited stocks. The information obtained from our study should help design management strategies in fisheries facing a changing climate.