79 resultados para Spawning season
em Publishing Network for Geoscientific
Resumo:
Mass mortalities of Pacific oysters Crassostrea gigas occur regularly when temperatures are high. Elevated temperatures facilitate the proliferation and spread of pathogens and simultaneously impose physiological stress on the host. Additionally, periods of high temperatures coincide with the oyster spawning season. Spawning is energetically costly and can further compromise oyster immunity. Most studies monitoring the underlying factors of oyster summer mortality in the field, point to the involvement of abiotic and biotic factors including low salinities, high temperatures, pollutants, toxic algae blooms, pathogen exposure and physical stress in conjunction with maturation. However, studies addressing more than two factors experi- mentally are missing thus far. Therefore, we investigated the combination of three main factors including abiotic as well as internal and external biotic stressors by conducting controlled infection experiments on pre-and post-spawning as well as on gravid oysters with opportunistic Vibrio sp. at two different tempera- tures. Based on mortality rates, infection intensity and cellular immune parameters, we provide experimental evidence that all three factors (i.e. reproductive investment, elevated temperatures and infection with oppor- tunistic Vibrio sp.) act additively to the phenomenon of oyster summer mortality, leaving post-spawning oyster more susceptible to SMS than pre-spawning and gravid oysters. While previous studies found that post-spawning oysters have a lower thermal tolerance and a reduced ability to withstand pathogen infec- tions, our study now allows to separate the relative contribution of different causative agents to oyster sum- mer mortality and pinpoint to infection with pathogenic Vibrio sp. being of highest importance. In addition we can add a mechanistic understanding for the higher losses after spawning during which the phagocytic ability of hemocytes was strongly impeded resulting in insufficient clearance of pathogens.
Resumo:
Experimental assessments of species vulnerabilities to ocean acidification are rapidly increasing in number, yet the potential for short- and long-term adaptation to high CO2 by contemporary marine organisms remains poorly understood. We used a novel experimental approach that combined bi-weekly sampling of a wild, spawning fish population (Atlantic silverside Menidia menidia) with standardized offspring CO2 exposure experiments and parallel pH monitoring of a coastal ecosystem. We assessed whether offspring produced at different times of the spawning season (April to July) would be similarly susceptible to elevated (1100 µatm, pHNIST = 7.77) and high CO2 levels (2300 µatm, pHNIST = 7.47). Early in the season (April), high CO2 levels significantly (p < 0.05) reduced fish survival by 54% (2012) and 33% (2013) and reduced 1 to 10 d post-hatch growth by 17% relative to ambient conditions. However, offspring from parents collected later in the season became increasingly CO2-tolerant until, by mid-May, offspring survival was equally high at all CO2 levels. This interannually consistent plasticity coincided with the rapid annual pH decline in the species' spawning habitat (mean pH: 1 April/31 May = 8.05/7.67). It suggests that parents can condition their offspring to seasonally acidifying environments, either via changes in maternal provisioning and/or epigenetic transgenerational plasticity (TGP). TGP to increasing CO2 has been shown in the laboratory but never before in a wild population. Our novel findings of direct CO2-related survival reductions in wild fish offspring and seasonally plastic responses imply that realistic assessments of species CO2-sensitivities must control for parental environments that are seasonally variable in coastal habitats.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.
Resumo:
Up to now, snow cover on Antarctic sea ice and its impact on radar backscatter, particularly after the onset of freeze/thaw processes, are not well understood. Here we present a combined analysis of in situ observations of snow properties from the landfast sea ice in Atka Bay, Antarctica, and high-resolution TerraSAR-X backscatter data, for the transition from austral spring (November 2012) to summer (January 2013). The physical changes in the seasonal snow cover during that time are reflected in the evolution of TerraSAR-X backscatter. We are able to explain 76-93% of the spatio-temporal variability of the TerraSAR-X backscatter signal with up to four snowpack parameters with a root-mean-squared error of 0.87-1.62 dB, using a simple multiple linear model. Over the complete study, and especially after the onset of early-melt processes and freeze/thaw cycles, the majority of variability in the backscatter is influenced by changes in snow/ice interface temperature, snow depth and top-layer grain size. This suggests it may be possible to retrieve snow physical properties over Antarctic sea ice from X-band SAR backscatter.
Resumo:
Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.