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Spawning location and timing are critical for understanding fish larval survival. The impact of a changing environment on spawning patterns is, however, poorly understood. A novel approach is to consider the impact of the environment on individual life histories and subsequent spawnings. In the present work, we extend the Dynamic Energy Budget (DEB) theory to investigate how environment variability impacts the spawning timing and duration of a multiple-batch spawning species. The model is successfully applied to reproduce the growth and reproduction of anchovy (Engraulis encrasicolus) in the Bay of Biscay. The model captures realistically the start and ending of the spawning season, including the timing of the spawning events, and the change in egg number per batch. Using a realistic seasonal forcing of temperature and food availability derived from a bio-physical model, our simulation results show that two thirds of the total spawned mass already accumulates before the start of the spawning season and that the condition factor increases with body length. These simulation results are in accordance with previous estimations and observations on growth and reproduction of anchovy. Furthermore, we show how individuals of equal length can differ in reproductive performance according to the environmental conditions they encounter prior to the spawning season. Hatch date turns out to be key for fecundity at age-1 as it partly controls the ability to build up reserves allocated to reproduction. We suggest the model can be used to realistically predict spawning in spatially and temporally varying environments and provide initial conditions for bio-physical models used to predict larval survival. 相似文献
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G. Lassalle J. Lobry F. Le Loc’h P. Bustamante G. Certain D. Delmas C. Dupuy C. Hily C. Labry O. Le Pape E. Marquis P. Petitgas C. Pusineri V. Ridoux J. Spitz N. Niquil 《Progress in Oceanography》2011,91(4):561-575
The Bay of Biscay (North-East Atlantic) has long been subjected to intense direct and indirect human activities that lead to the excessive degradation and sometimes overexploitation of natural resources. Fisheries management is gradually moving away from single-species assessments to more holistic, multi-species approaches that better respond to the reality of ecosystem processes. Quantitative modelling methods such as Ecopath with Ecosim can be useful tools for planning, implementing and evaluating ecosystem-based fisheries management strategies. The aim of this study was therefore to model the energy fluxes within the food web of this highly pressured ecosystem and to extract practical information required in the diagnosis of ecosystem state/health. A well-described model comprising 30 living and two non-living compartments was successfully constructed with data of local origin, for the Bay of Biscay continental shelf. The same level of aggregation was applied to primary producers, mid-trophic-levels and top-predators boxes. The model was even more general as it encompassed the entire continuum of marine habitats, from benthic to pelagic domains. Output values for most ecosystem attributes indicated a relatively mature and stable ecosystem, with a large proportion of its energy flow originating from detritus. Ecological network analysis also provided evidence that bottom-up processes play a significant role in the population dynamics of upper-trophic-levels and in the global structuring of this marine ecosystem. Finally, a novel metric based on ecosystem production depicted an ecosystem not far from being overexploited. This finding being not entirely consistent over indicators, further analyses based on dynamic simulations are required. 相似文献
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Pierre Petitgas Mathieu Woillez Mathieu Doray Jacques Rivoirard 《Mathematical Geosciences》2018,50(2):187-208
Marine research survey data on fish stocks often show a small proportion of very high-density values, as for many environmental data. This makes the estimation of second-order statistics, such as the variance and the variogram, non-robust. The high fish density values are generated by fish aggregative behaviour, which may vary greatly at small scale in time and space. The high values are thus imprecisely known, both in their spatial occurrence and order of magnitude. To map such data, three indicator-based geostatistical methods were considered, the top-cut model, min–max autocorrelation factors (MAF) of indicators, and multiple indicator kriging. In the top-cut and MAF approaches, the variable is decomposed into components and the most continuous ones (those corresponding to the low and medium values) are used to guide the mapping. The methods are proposed as alternatives to ordinary kriging when the variogram is difficult to estimate. The methods are detailed and applied on a spatial data set of anchovy densities derived from a typical fish stock acoustic survey performed in the Bay of Biscay, which show a few high-density values distributed in small spatial patches and also as solitary events. The model performances are analyzed by cross-validating the data and comparing the kriged maps. Results are compared to ordinary kriging as a base case. The top-cut model had the best cross-validation performance. The indicator-based models allowed mapping high-value areas with small spatial extent, in contrast to ordinary kriging. Practical guidelines for implementing the indicator-based methods are provided. 相似文献