9 resultados para 646.10268

em Aquatic Commons


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The harbor seal (Phoca vitulina) is a large-bodied and abundant predator in the Salish Sea ecosystem, and its population has recovered since the 1970s after passage of the Marine Mammal Protection Act and the cessation of bounties. Little is known about how this large predator population may affect the recovery of fish stocks in the Salish Sea, where candidate marine protected areas are being proposed. We used a bioenergetics model to calculate baseline consumption rates in the San Juan Islands, Washington. Salmonids (Oncorhynchus spp.) and herring (Clupeidae) were the 2 most energetically important prey groups for biomass consumed by harbor seals. Estimated consumption of salmonids was 783 (±380 standard deviation [SD]) metric tons (t) in the breeding season and 675 (±388 SD t in the nonbreeding season. Estimated consumption of herring was 646 (±303 SD) t in the breeding season and 2151 (±706 SD) t in the nonbreeding season. Rockfish, a depressed fish stock currently in need of population recovery, composed one of the minor prey groups consumed by harbor seals (84 [±26 SD] t in the nonbreeding season). The variables of seal body mass and proportion of prey in seal diet explained >80% of the total variation in model outputs. Prey groups, such as rockfish, that are targeted for recovery may still be affected by even low levels of predation. This study highlights the importance of salmonids and herring for the seal population and provides a framework for refining consumption estimates and their confidence intervals with future data.

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The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.

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Thirteen morphometric and seven meristic characters, length-weight relationship and food and feeding habits of Otolithoides biauritus of Bombay coast (Maharashtra, India) were studied. Compared morphometric characters revealed positive allometric growth and high correlation ("r" ranging 0.898 - 0.996) between each other. Meristic characters were observed to be B sub(vii), D sub(1) 8-10, D sub(2) 27-31, P 17-20, V 5-7 and 7-10. Number of gill rackers on the first left gill arch ranged from 15 to 19. Length-weight relationship for both sexes together worked out to be W = 0.026, L super(2.646). The species is a predator, feeding mainly on motile Acetes, small fish and Loligo in order of preference.

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In order to carry out Biometric studies, 75 samples were caught from 3 locations ( Tajan river, Sefidrud and Shirud) using Salic and the length (±1 mm) and weights (± 5 gr) of samples were determined. Using One-way ANOVA by SPPSS software, there wasn’t significant difference between locations in length and fecondity (P ≥0.01(, but there was significant difference between Shirud and tajan samples with sefidrud in weight ) P≤0.01(. In order to carry out genetic variation studies, 210 fish were caught from 3 different regions of the Iranian coastline (Khoshkrud, Tonekabon, Gorganrud) and 1 region in Azerbaijan (Waters of the Caspian Sea close to Kura River mouth) during 2008-2009 . Genomic DNA was extracted of fin using the phenol-chloroform. The quantity and quality of DNA from samples were assessed by spectrophptometer and 1% agarose gel electro-phoresis. PCR was carried out using 15 paired microsatellite primers. PCR products were separated on 8% polyacrylamide gels that were stained using silver nitrate. Molecular weight calculate using UVTech software. The recorded microsatellite genotypes were used as input data for the GENALEX software version 6 package in order to calculate allele and genotype frequencies, observed (Ho) and (He) expected heterozygosities and to test for deviations from Hardy-Weinberg equilibrium. Genetic distance between two populations was estimated from Nei standard genetic distance and genetic similarity index (Nei, 1972). Genetic differentiation between populations was also evaluated by the calculation of pairwise estimates of Fst and Rst values. From 15 SSR markers were used in this investigation, 9 of them were polymorph. Average of expected and observed heterozygosity was 0.54 and 0.49 respectively. Significant deviations from Hardy-Weinberg expectations were observed in all of location except Anzali lagoon- autumn in AF277576 and EF144125, Khoshkrud in EF144125 and Gorganrud and Kura in AF277576. Using Fst and Rst there was significant difference between locations ) P≤0.01(. According to Fst , the highest population differentiation (Fst= 0.217) was between Gorganrud and Khoshkrud that have the lowest Nm and the lowest (Fst= 0.086) was between Gorganrud and Tonekabon that have the highest Nm. Using Rst the highest population differentiation (Rst= 0.271) was between Tonekabon and spring Anzali lagoon and the lowest (Rst= 0.026) was between Tonekabon and Autumn Anzali 159 lagoon. Also the difference between Spring Anzali lagoon and Autumn Anzali lagoon was noticeable (Fst=0.15). AMOVA analysis with consideration of 2 sampling regions (Iran and Azerbaijan) and 7 sampling locations (Iran: Khoshkrud, Tonekabon, Gorganrud, Spring Anzali lagoon and Autumn Anzali lagoon ; Azerbaijan: the Kura mouth) revealed that almost all of the variance in data namely 83% )P≤0.01( was within locations, Genetic variances among locations was 14% )P≤0.01( and among regions was 3% )P≤0.01(. The genetic distance was the highest (0.646) between Gorganrud and Autumn Anzali lagoon populations, whereas the lowest distance (0.237) was between Gorganrud and Tonekabon River. Result obtained from the present study show that at least 2 different population of Rutilus frissi kutum are found in the Caspian sea,which are including the kura river population and the southern Caspian sea samples and it appears that there is more than one population in southern Caspian sea that should be attantioned in artifical reproduction Center and stoke rebilding.

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Genetic diversity of Saccostrea cucullata in the northern coast lines of the Persian Gulf and the Sea of Oman were determined using DNA extraction and RAPD - PCR. A total of 300 samples were collected from 6 station along the coastline. Two out of six primers showed positive results namely GCG - ATC - CCC - A (Primer 1) and GTC - CAC - ACG - C (Primer 5) which were in accordance with morphometric analysis. The number of bands in the two above - mentioned primers in Khor - Tang and Chabahar station (Province of Sistan and Balouchestan) was significantly different from the number of produced bands in Dayer and Bushehr station (Province of Bushehr) as well as Gheshm and Bandar - Lengeh station (Province of Hormozgan). The cluster analisys was used to confirm the above variations. The results showed that the oyster population can be divided into two separate clusters. The first cluster included Bushehr Dayer Gheshm and Bandar - Lengeh species. The second cluster included Khor - Tang and Chabahar species. The analysis also showed that the first cluster can be divided into two Sub — cluster. Bushehr and Dayer belong to one Sub - cluster whereas Gheshm and Bandar - Lengeh form the other Sub — cluster. The formation of different vluster can be related to Physico - Chemical properties of water and climatic variations in different habitats along the Persion Gulf and the Sea of Oman. Key words: Molecular genetics, Population, RAND, PCR' Saccostrea cucullata