共查询到5条相似文献，搜索用时 6 毫秒
1.
热带大西洋金枪鱼延绳钓兼捕鲨鱼种类组成和渔获率及其与表温的关系 总被引：1，自引：0，他引：1
根据2007年12月~2008年3月采集的热带大西洋(05°37′~12°01′N、29°00′~36°51′W)金枪鱼延绳钓渔获物数据,分析了金枪鱼延绳钓兼捕鲨鱼的种类组成、渔获量、渔获率及其与表温的关系。本次调查共捕获鲨鱼8种,隶属3目7科7属,总渔获尾数为633 ind,总渔获量达26 837.4 kg,其中大青鲨为主要兼捕种类。各种鲨鱼渔获率平均值在0.003~1.524 ind/1 000 hooks之间,其中大青鲨最高,其值为1.524 ind/1 000 hooks,大眼砂锥齿鲨最低,其值为0.003 ind/1 000 hooks。各种鲨鱼渔获率月变化不明显(ANOVA,P=0.901)。鲨鱼总渔获率和大青鲨渔获率与表温都呈显著性负相关。大青鲨主要出现渔场的表温范围为24.6~25.8℃。 相似文献
2.
Relationships between albacore tuna (Thunnus alalunga) longline catch per unit effort (CPUE) and environmental variables from model outputs in New Caledonia’s Exclusive Economic Zone (EEZ) were examined through generalized linear models at a 1° spatial resolution and 10‐day temporal resolution. At a regional (EEZ) scale, the study demonstrated that a large part of albacore CPUE variability can be explained by seasonal, interannual and spatial variation of the habitat. Results of the generalized linear models indicated that catch rates are higher than average in the northwestern part of the EEZ at the beginning of the year (January) and during the second half of the year (July–December). In the northwestern region of the EEZ, high CPUEs are associated with waters <20.5° in the intermediate layer and with moderate values of primary production. Longline CPUE also appeared to be dependent on prey densities, as predicted from a micronekton model. Albacore CPUE was highest at moderate densities of prey in the epipelagic layer during the night and for relatively low prey densities in the mesopelagic layer during the day. We also demonstrated that the highest CPUEs were recorded from 1986 to 1998, which corresponds to a period with frequent El Niño events. 相似文献
3.
Ango C. Hsu Andre M. Boustany Jason J. Roberts Jui‐Han Chang Patrick N. Halpin 《Fisheries Oceanography》2015,24(6):508-520
To analyze the effects of mesoscale eddies, sea surface temperature (SST), and gear configuration on the catch of Atlantic bluefin (Thunnus thynnus), yellowfin (Thunnus albacares), and bigeye tuna (Thunnus obesus) and swordfish (Xiphias gladius) in the U.S. northwest Atlantic longline fishery, we constructed multivariate statistical models relating these variables to the catch of the four species in 62 121 longline hauls made between 1993 and 2005. During the same 13‐year period, 103 anticyclonic eddies and 269 cyclonic eddies were detected by our algorithm in the region 30–55°N, 30–80°W. Our results show that tuna and swordfish catches were associated with different eddy structures. Bluefin tuna catch was highest in anticyclonic eddies whereas yellowfin and bigeye tuna catches were highest in cyclonic eddies. Swordfish catch was found preferentially in regions outside of eddies. Our study confirms that the common practice of targeting tuna with day sets and swordfish with night sets is effective. In addition, bluefin tuna and swordfish catches responded to most of the variables we tested in the opposite directions. Bluefin tuna catch was negatively correlated with longitude and the number of light sticks used whereas swordfish catch was positively correlated with these two variables. We argue that overfishing of bluefin tuna can be alleviated and that swordfish can be targeted more efficiently by avoiding fishing in anticyclonic eddies and in near‐shore waters and using more light sticks and fishing at night in our study area, although further studies are needed to propose a solid oceanography‐based management plan for catch selection. 相似文献
4.
Modeling and understanding the catch rate dynamics of marine species is extremely important for fisheries management and conservation. For oceanic highly migratory species in particular, usually only fishery‐dependent data are available which have limitations in the assumption of independence and if often zero‐inflated and/or overdispersed. We tested different modeling approaches applied to the case study of blue shark in the South Atlantic, by using generalized linear models (GLMs), generalized linear mixed models (GLMMs), and generalized estimating equations (GEEs), as well as different error distributions to deal with the presence of zeros in the data. We used fractional polynomials to deal with non‐linearity in some of the explanatory variables. Operational (set level) data collected by onboard fishery observers, covering 762 longline sets (1,014,527 hooks) over a 9‐year period (2008–2016), were used. One of the most important variables affecting catch rates is leader material, with increasing catches when wire leaders are used. Spatial and seasonal variables are also important, with higher catch rates expected toward temperate southern waters and eastern longitudes, particularly between July and September. Environmental variables, especially SST, also affect catches. There were no major differences in the parameters estimated with GLMs, GLMMs, or GEEs; however, the use of GLMMs or GEEs should be more appropriate due to fishery dependence in the data. Comparing those two approaches, GLMMs seem to perform better in terms of goodness‐of‐fit and model validation. 相似文献
5.
David Chagaris Behzad Mahmoudi Frank Muller‐Karger Wade Cooper Keith Fischer 《Fisheries Oceanography》2015,24(3):257-273
Since 1995, landings of Atlantic Thread Herring (Opisthonema oglinum) on the Florida Panhandle averaged 124 mt each spring (April–June) but declined to nearly zero in 1996–97 and 2006. To elucidate causes of recurring periods of low landings, we used generalized additive mixed models (GAMMs) to examine the relationship between Atlantic Thread Herring catch in a trawl survey on the west‐central coast of Florida and four environmental variables. Chlorophyll‐a was significant in the models, indicating a direct relationship between local abundance of baitfish and their planktonic food. Temperature and depth were also significant whereas salinity was not. During 2003 and 2012, synoptic satellite‐derived temperature and chlorophyll‐a maps were used with the GAMMs to predict monthly spatial availability on the Florida Panhandle fishing grounds (long. 85–88o W and depth 12–25 m). The predicted monthly availability was significantly correlated with commercial catch rates (Pearson's r = 0.26, P = 0.004, d.f. = 118). We used multiple linear regression (MLR) with lags to describe the effect of river discharge and wind (as a transport mechanism) on surface chlorophyll‐a over the Panhandle fishing grounds. Discharge from local rivers was significant in all MLRs, and the Mississippi was only significant as an interaction with wind. We conclude that Atlantic Thread Herring are distributed over the Panhandle fishing grounds based on food availability that is driven by river discharge and eastward transport of Mississippi River plumes. This analysis improves our understating of baitfish dynamics, an important ecosystem component in the Gulf of Mexico. 相似文献
