955 resultados para Evolutionary algorithm (EA)


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Ecosystem-based management is one of many indispensable components of objective, holistic management of human impacts on nonhuman systems. By itself, however, ecosystem-based management carries the same risks we face with other forms of current management; holism requires more. Combining single-species and ecosystem approaches represents progress. However, it is now recognized that management also needs to be evosystem-based. In other words, management needs to account for all coevolutionary and evolutionary interactions among all species; otherwise we fall far short of holism. Fully holistic practices are quite distinct from the approaches to the management of fisheries that are applied today. In this paper, we show how macroecological patterns can guide management consistently, objectively, and holistically. We present one particular macroecological pattern with two applications. The first application is a case study of fisheries from the Baltic Sea involving historical data for two species; the second involves a sample of 44 species of primarily marine fish worldwide. In both cases we evaluate historical fishing rates and determine holistic/systemic sustainable single-species fishing rates to illustrate that conventional fisheries management leads to much more extensive and pervasive overfishing than currently realized; harvests are, on average, over twenty-fold too large to be fully sustainable. In general, our approach involves not only the sustainability of fisheries and related resources but also the sustainability of the ecosystems and evosystems in which they occur. Using macroecological patterns accomplishes four important goals: 1) Macroecology becomes one of the interdisciplinary components of management. 2) Sustainability becomes an option for harvests from populations of individual species, species groups, ecosystems, and the entire marine environment. 3) Policies and goals are reality-based, holistic, or fully systemic; they account for ecological as well as evolutionary factors and dynamics (including management itself). 4) Numerous management questions can be addressed.

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Karenia brevis is the dominant toxic red tide algal species in the Gulf of Mexico. It produces potent neurotoxins (brevetoxins [PbTxs]), which negatively impact human and animal health, local economies, and ecosystem function. Field measurements have shown that cellular brevetoxin contents vary from 1–68 pg/cell but the source of this variability is uncertain. Increases in cellular toxicity caused by nutrient-limitation and inter-strain differences have been observed in many algal species. This study examined the effect of P-limitation of growth rate on cellular toxin concentrations in five Karenia brevis strains from different geographic locations. Phosphorous was selected because of evidence for regional P-limitation of algal growth in the Gulf of Mexico. Depending on the isolate, P-limited cells had 2.3- to 7.3-fold higher PbTx per cell than P-replete cells. The percent of cellular carbon associated with brevetoxins (%C-PbTx) was ~ 0.7 to 2.1% in P-replete cells, but increased to 1.6–5% under P-limitation. Because PbTxs are potent anti-grazing compounds, this increased investment in PbTxs should enhance cellular survival during periods of nutrient-limited growth. The %C-PbTx was inversely related to the specific growth rate in both the nutrient-replete and P-limited cultures of all strains. This inverse relationship is consistent with an evolutionary tradeoff between carbon investment in PbTxs and other grazing defenses, and C investment in growth and reproduction. In aquatic environments where nutrient supply and grazing pressure often vary on different temporal and spatial scales, this tradeoff would be selectively advantageous as it would result in increased net population growth rates. The variation in PbTx/cell values observed in this study can account for the range of values observed in the field, including the highest values, which are not observed under N-limitation. These results suggest P-limitation is an important factor regulating cellular toxicity and adverse impacts during at least some K. brevis blooms.

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Using an entropy argument, it is shown that stochastic context-free grammars (SCFG's) can model sources with hidden branching processes more efficiently than stochastic regular grammars (or equivalently HMM's). However, the automatic estimation of SCFG's using the Inside-Outside algorithm is limited in practice by its O(n3) complexity. In this paper, a novel pre-training algorithm is described which can give significant computational savings. Also, the need for controlling the way that non-terminals are allocated to hidden processes is discussed and a solution is presented in the form of a grammar minimization procedure. © 1990.

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A dynamic programming algorithm for joint data detection and carrier phase estimation of continuous-phase-modulated signal is presented. The intent is to combine the robustness of noncoherent detectors with the superior performance of coherent ones. The algorithm differs from the Viterbi algorithm only in the metric that it maximizes over the possible transmitted data sequences. This metric is influenced both by the correlation with the received signal and the current estimate of the carrier phase. Carrier-phase estimation is based on decision guiding, but there is no external phase-locked loop. Instead, the phase of the best complex correlation with the received signal over the last few signaling intervals is used. The algorithm is slightly more complex than the coherent Viterbi algorithm but does not require narrowband filtering of the recovered carrier, as earlier appproaches did, to achieve the same level of performance.