Stock Assessment of the Argentine Shortfin Squid Illex argentinus (Cephalopoda: Ommastrephidae) in the Southwest Atlantic
|Keywords:||阿根廷魷;南極震盪指數;經驗模式;地學統計;半變異圖;Illex argentinus;Antarctic Oscillation index;empirical model;geostatistical;semi-variogram||Issue Date:||2016||Abstract:||
本研究以1986年至2013年間，臺灣魷釣漁船在西南大西洋進行阿根廷魷(Illex argentinus)漁業之經log轉換之單位努力漁獲量(logU)為指標，從時間與空間二個維度探討阿根廷魷資源量變化與環境因子間之關聯。 研究結果顯示， logU沒有年度間的相互作用，而與巴塔哥尼亞陸棚南方2月、3月及4月的近表層水溫（在5 m深度）呈負相關(r值依序為-0.573、-0.596及-0.573，P值均小於0.05)，同時也與前一年巴塔哥尼亞陸棚3月的近表層水溫有負相關。 logU也與漁季二年前11月和12月的南極震盪（Antarctic oscillation, AAO）有負相關(r值依序為-0.478及-0.564，P值均小於0.05)，並與漁季二年前3月和5月的AAO有正相關(r值依序為0.565及0.436，P值均小於0.05)。 以泛線性模式所構建的經驗模式將漁季二年前11月和3月的AAO，以及前一年與當年3月巴塔哥尼亞陸棚南方之近表層水溫被納入為預測因子，模式決定係數為0.83。 漁季前一年及漁季中阿根廷魷棲息環境的低水溫，為阿根廷魷高資源豐度的重要條件。 由於阿根廷魷無重疊年級群，AAO無法直接影響二年後的阿根廷魷資源量，因此某些生物或非生物的關聯可能存在於阿根廷魷資源量與大氣環流的變動之間。 在空間維度方面，半變異數分析顯示阿根廷魷在西南大西洋的分布，因豐度的不同，而存有不同的空間結構。 除了2010年外，球形模式可解釋大多數阿根廷魷魚度的年度空間分布樣態。 以克利金法(Kriging)估計阿根廷魷之資源分布顯示高豐度位置系沿南緯40度至50度間之200 m等深線分布。 在高資源豐度的年度，例如1999和2007年，豐度的橢圓等值線從200 m等深線向大陸斜坡延伸。 而低豐度的年度，例如2004年，阿根廷魷資源呈現散亂斑塊分布。 以克利金法估計之阿根廷魷總生物量顯示，在西南大西洋漁場中，阿根廷魷系群的開發率在2到34%之間，其系群仍屬於健康的狀況。 本研究表明經驗模式與地學統計方法可有效應用於阿根廷魷資源量之預測、年度空間分布之描述及總資源量之估算，而本研究發展之模式所產生的參數可估算阿根廷魷每年的總生物量與來年可能的資源趨勢。
With data from Taiwanese jiggers that targeted the Argentine shortfin squid (Illex argentinus) in the southwest Atlantic between 1986 and 2013, the log-transformed catch per unit of effort (logU) was used as an index of the abundance of this squid to explore squid recruitment fluctuation in response to environmental conditions in temporal and spatial scales. The results indicated that the logU exhibited no inter-annual interaction. The logU were negatively correlated with subsurface seawater temperature (at 5-m depth) in the southern Patagonian Shelf in February, March and April (r = -0.573, -0.596 and -0.573, respectively; all P values were less than 0.05). The logU also negatively correlated with subsurface seawater temperature in the Patagonian Shelf in previous March. The logU was also correlated with the Antarctic Oscillation (AAO), negatively correlated in November and December of the previous 2 years (r = -0.478, and -0.564, respectively; all P values were less than 0.05), and positively correlated in March and May of the previous 2 years l(r = 0.565 and 0.436, respectively; all P values were less than 0.05). GLM analysis selected AAOs in November and March of the previous two years and subsurface seawater temperature in March of the current and previous year, in which coefficient of multiple determination was 0.83. A low seawater temperature in the Argentine shortfin squid habitat in previous 1 year and in fishing season was important conditions of high resource abundance. Because the Argentina shortfin squid was no overlapping groups, AAO can’t directly affect the amount of resources of the Argentine shortfin squid after two years, therefore associated with certain biological or non-biological variation may exist between the Argentina shortfin squid resources and atmospheric circulation. In terms of spatial dimensions, semi-variance analysis showed that the distribution of the Argentine shortfin squid in the Southwest Atlantic had different spatial structures, due to the different of abundance. In all years except 2010, spherical model for semi-variograms extracted the most spatial information from annual distribution maps of the squid abundance. The Kriging interpolation map exhibited a general pattern of aggregation of the squid along the 200-m depth from 40°S to as far as 50°S. The shape of abundance isopleth lines was elliptical, that extended its long axis further from the 200-m isobath toward shelf side in high abundance years, such as 1999 and 2007. Scattered patches of low values were observed in the very low-abundance year of 2004. In Kriging method to estimate the total biomass of the Argentine shortfin squid showed that the exploitation rate of the Argentine short squid in the Southwest Atlantic fishing ground was between 2-34%, which was still a healthy stock status. This study shows that empirical models and geostatistical procedures can be applied to predict the Argentine shortfin squid resource, describe the annual spatial distribution, and estimate the total biomass. The models and parameters can estimate the total biomass of the Argentine shortfin squid and possible annual resource trends in next year.
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