A Comparison of Two Methods for Enhancing the Recovery of Seagrasses into Propellor Scars: Mechanical Injection of a Nutrient and Growth Hormone Solution vs. Defecation by Roosting Seabirds: Final Report.

Based on the recovery rates for Thalassia testudinum measured in this study for scars of these excavation depths and assuming a linear recovery horizon, we estimate that it would take ~ 6.9 years (95% CI. = 5.4 to 9.6 years) for T. testudinum to return to the same density as recorded for the adjacent undisturbed population. The application of water soluble fertilizers and plant growth hormones by mechanical injection into the sediments adjacent to ten propellor scars at Lignumvitae State Botanical Site did not significantly increase the recovery rate of Thalassia testudinum or Halodule wrightii. An alternative method of fertilization and restoration of propellor scars was also tested by a using a method of “compressed succession” where Halodule wrightii is substituted for T. testudinum in the initial stages of restoration. Bird roosting stakes were placed among H.wrightii bare root plantings in prop scars to facilitate the defecation of nitrogen and phosphorus enriched feces. In contrast to the fertilizer injection method, the bird stakes produced extremely high recovery rates of transplanted H. wrightii. We conclude that use of a fertilizer/hormone injection machine in the manner described here is not a feasible means of enhancing T. testudinum recovery in propellor scars on soft bottom carbonate sediments. Existing techniques such as the bird stake approach provide a reliable, and inexpensive alternative method that should be considered for application to restoration of seagrasses in these environments. Document contains 40 pages)

A-SCALA: an age-structured statistical catch-at-length analysis for assessing tuna stocks in the eastern tropical Pacific Ocean

English: We describe an age-structured statistical catch-at-length analysis (A-SCALA) based on the MULTIFAN-CL model of Fournier et al. (1998). The analysis is applied independently to both the yellowfin and the bigeye tuna populations of the eastern Pacific Ocean (EPO). We model the populations from 1975 to 1999, based on quarterly time steps. Only a single stock for each species is assumed for each analysis, but multiple fisheries that are spatially separate are modeled to allow for spatial differences in catchability and selectivity. The analysis allows for error in the effort-fishing mortality relationship, temporal trends in catchability, temporal variation in recruitment, relationships between the environment and recruitment and between the environment and catchability, and differences in selectivity and catchability among fisheries. The model is fit to total catch data and proportional catch-at-length data conditioned on effort. The A-SCALA method is a statistical approach, and therefore recognizes that the data collected from the fishery do not perfectly represent the population. Also, there is uncertainty in our knowledge about the dynamics of the system and uncertainty about how the observed data relate to the real population. The use of likelihood functions allow us to model the uncertainty in the data collected from the population, and the inclusion of estimable process error allows us to model the uncertainties in the dynamics of the system. The statistical approach allows for the calculation of confidence intervals and the testing of hypotheses. We use a Bayesian version of the maximum likelihood framework that includes distributional constraints on temporal variation in recruitment, the effort-fishing mortality relationship, and catchability. Curvature penalties for selectivity parameters and penalties on extreme fishing mortality rates are also included in the objective function. The mode of the joint posterior distribution is used as an estimate of the model parameters. Confidence intervals are calculated using the normal approximation method. It should be noted that the estimation method includes constraints and priors and therefore the confidence intervals are different from traditionally calculated confidence intervals. Management reference points are calculated, and forward projections are carried out to provide advice for making management decisions for the yellowfin and bigeye populations. Spanish: Describimos un análisis estadístico de captura a talla estructurado por edad, A-SCALA (del inglés age-structured statistical catch-at-length analysis), basado en el modelo MULTIFAN- CL de Fournier et al. (1998). Se aplica el análisis independientemente a las poblaciones de atunes aleta amarilla y patudo del Océano Pacífico oriental (OPO). Modelamos las poblaciones de 1975 a 1999, en pasos trimestrales. Se supone solamente una sola población para cada especie para cada análisis, pero se modelan pesquerías múltiples espacialmente separadas para tomar en cuenta diferencias espaciales en la capturabilidad y selectividad. El análisis toma en cuenta error en la relación esfuerzo-mortalidad por pesca, tendencias temporales en la capturabilidad, variación temporal en el reclutamiento, relaciones entre el medio ambiente y el reclutamiento y entre el medio ambiente y la capturabilidad, y diferencias en selectividad y capturabilidad entre pesquerías. Se ajusta el modelo a datos de captura total y a datos de captura a talla proporcional condicionados sobre esfuerzo. El método A-SCALA es un enfoque estadístico, y reconoce por lo tanto que los datos obtenidos de la pesca no representan la población perfectamente. Además, hay incertidumbre en nuestros conocimientos de la dinámica del sistema e incertidumbre sobre la relación entre los datos observados y la población real. El uso de funciones de verosimilitud nos permite modelar la incertidumbre en los datos obtenidos de la población, y la inclusión de un error de proceso estimable nos permite modelar las incertidumbres en la dinámica del sistema. El enfoque estadístico permite calcular intervalos de confianza y comprobar hipótesis. Usamos una versión bayesiana del marco de verosimilitud máxima que incluye constreñimientos distribucionales sobre la variación temporal en el reclutamiento, la relación esfuerzo-mortalidad por pesca, y la capturabilidad. Se incluyen también en la función objetivo penalidades por curvatura para los parámetros de selectividad y penalidades por tasas extremas de mortalidad por pesca. Se usa la moda de la distribución posterior conjunta como estimación de los parámetros del modelo. Se calculan los intervalos de confianza usando el método de aproximación normal. Cabe destacar que el método de estimación incluye constreñimientos y distribuciones previas y por lo tanto los intervalos de confianza son diferentes de los intervalos de confianza calculados de forma tradicional. Se calculan puntos de referencia para el ordenamiento, y se realizan proyecciones a futuro para asesorar la toma de decisiones para el ordenamiento de las poblaciones de aleta amarilla y patudo.

Restricted Access vs. Open Access Methods of Management: Toward More Effective Regulation of Fishing Effort

This paper gives an overview of the economic rationale for limited entry as a method of fishery management and discusses general advantages and disadvantages of license limitation and catch rights as the two primary methods of restricting access to marine fisheries. Traditional open-access methods of regulation (e.g., gear restrictions, size limits, trip limits, quotas, and closures) can be temporarily effective in protecting fish populations, but they generally fail to provide lasting biological or economic benefits to fishermen because they do not restrict access to the fishery. The general result of regulation with unrestricted access to a fishery is additional and more costly and complex regulations as competition increases for dwindling fishery resources. Regulation that restricts access to a fishery in conjunction with selected traditional methods of regulation would encourage efficient resource usage and minimize the need for future regulatory adjustments, provided that enforcement and monitoring costs are not too great. In theory, catch rights are superior to license limitation as a means of restricting access to a fishery.

"Cool" vs. "warm" winter precipitation and its effect on streamflow in California

Precipitation is a difficult variable to understand and predict. In this study, monthly precipitation in California is divided into two classes according to the monthly temperature to better diagnose the atmospheric circulation that causes precipitation, and to illustrate how temperature compounds the precipitation to runoff process.

Geographic patterns in the lag of temperature response to insolation for El Niño vs. La Niña conditions [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): The most important control on the annual cycle of temperature is insolation, with secondary influences from terms related to moisture, yet direct statistical analysis of the moisture-driven modulations (such as El Niño) of the response of temperature to insolation are not available. We have examined one aspect of the relationship between insolation and the instrumental record of maximum daily temperature - the lag between the two - at 252 stations in the western United States.

Ensaio sobre a forma de comunicaçāo dos resultados da investigaçāo de recursos pesqueiros à administraçāo pesqueira. Tema 1: Síntese dos resultados e métodos de análise utilizado na avaliaçāo do recurso de camarao de águas pouco profundas do Banco de Sofala.

The main goal of this paper is to provide samples of fishing methods analyses applied to studies on shrimps stock assessment in the Sofala Bank. Especially the authors provide the administrators with the main limits of application of described methods.

Impact of seafarming: fish farms vs. mussel farms

The article presents comparative impacts of fish and mussel seafarms. Specifically, it tackles the impacts of the two farms on the following: solid waste production, water flow and sedimentation, effect on native bottom fauna, effect on wild fish populations, the spread of toxic chemicals and drugs, and multi-use conflicts.