Dietary carbohydrate requirement of Heterobranchus longifilis

The dietary carbohydrate requirement of Heterobranchus longifilis was evaluated in two separate experiments.In the first experiment, varying levels of carbohydrate ranging from 28, 24 to58 72% were fed to the fish of mean weight 1.83~c0.02g. Results revealed that the polynomial regression curve for the mean weight gain and the carbohydrate levels did not present a point where Y-max is equal to X-max and so the requirement was not obtained. The second experiment was therefore, conducted with lower levels of carbohydrate ranging from 17.00 to 20.86% and fed to fish with mean weight 0.49~c0.02g. Based on growth and feed efficiency data the carbohydrate requirement was determined to be 19.5%

Catches per unit of effort of bigeye tuna: a new analysis with regression trees and simulated annealing

ENGLISH: We analyzed catches per unit of effort (CPUE) from the Japanese longline fishery for bigeye tuna (Thunnus obesus) in the central and eastern Pacific Ocean (EPO) with regression tree methods. Regression trees have not previously been used to estimate time series of abundance indices fronl CPUE data. The "optimally sized" tree had 139 parameters; year, month, latitude, and longitude interacted to affect bigeye CPUE. The trend in tree-based abundance indices for the EPO was similar to trends estimated from a generalized linear model and fronl an empirical model that combines oceanographic data with information on the distribution of fish relative to environmental conditions. The regression tree was more parsimonious and would be easier to implement than the other two nl0dels, but the tree provided no information about the nlechanisms that caused bigeye CPUEs to vary in time and space. Bigeye CPUEs increased sharply during the mid-1980's and were more variable at the northern and southern edges of the fishing grounds. Both of these results can be explained by changes in actual abundance and changes in catchability. Results from a regression tree that was fitted to a subset of the data indicated that, in the EPO, bigeye are about equally catchable with regular and deep longlines. This is not consistent with observations that bigeye are more abundant at depth and indicates that classification by gear type (regular or deep longline) may not provide a good measure of capture depth. Asimulated annealing algorithm was used to summarize the tree-based results by partitioning the fishing grounds into regions where trends in bigeye CPUE were similar. Simulated annealing can be useful for designing spatial strata in future sampling programs. SPANISH: Analizamos la captura por unidad de esfuerzo (CPUE) de la pesquería palangrera japonesa de atún patudo (Thunnus obesus) en el Océano Pacifico oriental (OPO) y central con métodos de árbol de regresión. Hasta ahora no se han usado árboles de regresión para estimar series de tiempo de índices de abundancia a partir de datos de CPUE. EI árbol de "tamaño optimo" tuvo 139 parámetros; ano, mes, latitud, y longitud interactuaron para afectar la CPUE de patudo. La tendencia en los índices de abundancia basados en árboles para el OPO fue similar a las tendencias estimadas con un modelo lineal generalizado y con un modelo empírico que combina datos oceanográficos con información sobre la distribución de los peces en relación con las condiciones ambientales. EI árbol de regresión fue mas parsimonioso y seria mas fácil de utilizar que los dos otros modelos, pero no proporciono información sobre los mecanismos que causaron que las CPUE de patudo valiaran en el tiempo y en el espacio. Las CPUE de patudo aumentaron notablemente a mediados de los anos 80 y fueron mas variables en los extremos norte y sur de la zona de pesca. Estos dos resultados pueden ser explicados por cambios en la abundancia real y cambios en la capturabilidad. Los resultados de un arbal de regresión ajustado a un subconjunto de los datos indican que, en el OPO, el patudo es igualmente capturable con palangres regulares y profundos. Esto no es consistente con observaciones de que el patudo abunda mas a profundidad e indica que clasificación por tipo de arte (palangre regular 0 profundo) podría no ser una buena medida de la profundidad de captura. Se uso un algoritmo de templado simulado para resumir los resultados basados en el árbol clasificando las zonas de pesca en zonas con tendencias similares en la CPUE de patudo. El templado simulado podría ser útil para diseñar estratos espaciales en programas futuros de muestreo. (PDF contains 45 pages.)

Evolutionary associations between sand seatrout (Cynoscion arenarius) and silver seatrout (C. nothus) inferred from morphological characters, mitochondrial DNA, and microsatellite markers

The evolutionary associations between closely related fish species, both contemporary and historical, are frequently assessed by using molecular markers, such as microsatellites. Here, the presence and variability of microsatellite loci in two closely related species of marine fishes, sand seatrout (Cynoscion arenarius) and silver seatrout (C. nothus), are explored by using heterologous primers from red drum (Sciaenops ocellatus). Data from these loci are used in conjunction with morphological characters and mitochondrial DNA haplotypes to explore the extent of genetic exchange between species offshore of Galveston Bay, TX. Despite seasonal overlap in distribution, low genetic divergence at microsatellite loci, and similar life history parameters of C. arenarius and C. nothus, all three data sets indicated that hybridization between these species does not occur or occurs only rarely and that historical admixture in Galveston Bay after divergence between these species was unlikely. These results shed light upon the evolutionary history of these fishes and highlight the genetic properties of each species that are influenced by their life history and ecology.

Systematics of the North American menhadens: molecular evolutionary reconstructions in the genus Brevoortia (Clupeiformes: Clupeidae)

Evolutionary associations among the four North American species of menhadens (Brevoortia spp.) have not been thoroughly investigated. In the present study, classifications separating the four species into small-scaled and large-scaled groups were evaluated by using DNA data, and genetic associations within these groups were explored. Specifically, data from the nuclear genome (microsatellites) and the mitochondrial genome (mtDNA sequences) were used to elicit patterns of recent and historical evolutionary associations. Nuclear DNA data indicated limited contemporary gene flow among the species, and also indicated higher relatedness within the small-scaled and large-scaled menhadens than between these groups. Mitochondrial DNA sequences of the large-scaled menhadens indicated the presence of two ancestral lineages, one of which contained members of both species. This result may indicate genetic diver-gence (reproductive isolation) followed by secondary contact (hybridization) between these species. In contrast, a single ancestral lineage indicated incomplete genetic divergence between the small-scaled menhaden. These results are discussed in the context of the biology and demographics of each species.

A prior for steepness in stock-recruitment relationships, based on an evolutionary persistence principle

Priors are existing information or beliefs that are needed in Bayesian analysis. Informative priors are important in obtaining the Bayesian posterior distributions for estimated parameters in stock assessment. In the case of the steepness parameter (h), the need for an informative prior is particularly important because it determines the stock-recruitment relationships in the model. However, specifications of the priors for the h parameter are often subjective. We used a simple population model to derive h priors based on life history considerations. The model was based on the evolutionary principle that persistence of any species, given its life history (i.e., natural mortality rate) and its exposure to recruitment variability, requires a minimum recruitment compensation that enables the species to rebound consistently from low critical abundances (Nc). Using the model, we derived the prior probability distributions of the h parameter for fish species that have a range of natural mortality, recruitment variabilities, and Nt values.

Holistic fisheries management: combining macroecology, ecology, and evolutionary biology

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.

Increased toxicity of Karenia brevis during phosphate limited growth: ecological and evolutionary implications

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.

Validation of a semi-Lagrangian, canonical regression model of climates in the southwestern United States

EXTRACT (SEE PDF FOR FULL ABSTRACT): A local climate model (LCM) has been developed to simulate the modern and 18 ka climate of the southwestern United States. ... LCM solutions indicate summers were about 1°C cooler and winters 11°C cooler at 18 ka. Annual PREC increased 68% at 18 ka, with large increases in spring and fall PREC and diminished summer monsoonal PREC. ... Validation of simulations of 18 ka climate indicate general agreement with proxy estimates of climate for that time. However, the LCM estimates of summer temperatures are about 5 to 10°C higher than estimates from proxy reconstructions.

Cumulative inbreeding rate in hatchery-reared indian major carps of Karnataka and Maharashtra states

The state fisheries department hatcheries are the major suppliers of seed to the farmers in Karnataka and Maharashtra. The brood stocks of these hatcheries are genetically closed units. In the present study, effective population size and cumulative inbreeding rates were estimated. The cumulative inbreeding rates ranged from 2.69 to 13.75, 8.63 to 15.21 and 3.02 to 5.88 per cent for catla, mrigal and rohu, respectively, in Karnataka state hatcheries. In Maharashtra, the cumulative inbreeding rates for catla ranged from 7.81 to 39.34 per cent and it was 5.84 to 14.09 and 2.46 to 10.20 per cent for mrigal and rohu, respectively. To estimate the inbreeding rates in future generations, predictive models were developed using linear regression, and polynomial and power equations separately for each hatchery. Their multiple correlation and standard errors suggested that simple linear regression can predict the future inbreeding rate efficiently.