The Beverton-Holt length-based mortality estimator has received widespread use primarily due to its applicability in data-limited situations. The mean length of animals that are fully vulnerable to the sampling gear can be used to estimate total mortality from basic growth parameters and a known length at first capture. This method requires equilibrium conditions because the mean length of a population will change only gradually after a change in mortality. In this study, we derive the transitional behavior of the mean length statistic for use in nonequilibrium conditions. We investigate conditions affecting the reliability of the Beverton-Holt results and then develop a new procedure that allows a series of mortality rates to be estimated from mean length data representing nonequilibrium conditions in multiple years. We then examine an assessment of goosefish Lophius americanus that was criticized for its use of the Beverton-Holt estimator under nonequilibrium conditions. Using data from the 1963-2002 National Marine Fisheries Service annual fall groundfish surveys off the northeastern United States and assuming a single change in total mortality, we used the maximum likelihood method to estimate that the total mortality of goosefish in the southern assessment region increased from 0.31 to 0.60 per year in 1977. Estimates of the new mortality rate made three or more years after the change were relatively stable and only ranged from 0.55 to 0.71 per year, while estimates from the standard Beverton-Holt approach ranged from 0.37 to 1.1 per year. The results for goosefish in the northern assessment region showed that total mortality changed from 0.14 to 0.29 per year in 1978 and then to 0.55 per year in 1987. The new nonequilibrium estimator allows a change in mortality to be characterized reliably several years faster than would occur with the use of the Beverton-Holt estimator.

Abstract.-Leslie matrices and life tables are demographic models commonly used to evaluate the ability of specific elasmobranch life history strategies to sustain given levels and patterns of fishing pressure. These models are generally density independent and provide an instantaneous rate of population growth for a specified set of life history traits that correspond to a specific population size. Many investigators are using these models to compute rates of population growth that they claim are estimates of the maximum population growth rate (r intrinsic ); they then use these estimates to compute purported estimates of maximum sustainable fishing mortality. However, neither a Leslie matrix nor a life table can be used to estimate r intrinsic without additional information, except in the special case where a severely depleted population is modeled. Only in a severely depleted population will competition for resources be at a minimum and both density-dependent compensation and the rate of population growth be at a maximum (i.e., at r intrinsic ). The fundamental problem is to determine the life history parameters that would occur if the population were extremely depleted because extensive observations on extremely depleted populations are rare. In the absence of such data, r intrinsic can only be estimated from these types of density-independent models by extrapolating observed population growth rates toward zero population size. We illustrate the problems in, and describe methods for, estimating r intrinsic and present information on two species of elasmobranch: barndoor skate Dipturus laevis and lemon shark Negaprion brevirostris.Classic demographic analysis, based on a life table or Leslie matrix, provides an estimate of the exponential (or, more properly, geometric) rate of population growth or decline based on a fixed set of life history parameters. Alternatively, the model can be thought of as providing the current (short-term) rate of population change under current conditions. For the elasmobranchs, where many stocks have been severely depleted, the question is to what extent these populations can withstand fishing pressure. Recently, this question has been approached by attempting to use demographic models to determine the intrinsic or maximum rate of population increase (r intrinsic ) and therefore the maximum sustainable fishing pressure. However, fundamental errors in the interpretation of the models are common.Problems in the use of a basic demographic analysis for estimating r intrinsic arise from the density-independent nature of its structure and the use of static life history parameter inputs. In reality, at least some life history traits must be pliable and able to respond to changes in population size. This forms the basic logic behind density-dependent compensation, which explains why populations rarely go extinct and cannot grow beyond the bounds fixed by limiting factors (such as food resources or space) for extended periods (i.e., there is a carrying capacity of the environment).Throughou...

Understanding how and why animals are distributed through time and space has always been a fundamental component of ecology and is an essential prerequisite for effective conservation and/or management. However, for highly mobile K-selected species, behavioural predictability is rarely considered over appropriate scales relative to life history. To address this point, a multidisciplinary approach combining telemetry, external tagging, physical assessment, environmental monitoring and genetic analysis was adopted to determine a spatial framework for the movements of adult lemon sharks Negaprion brevirostris at multiple spatial and temporal scales from 2007 to 2011. Lemon sharks (n = 83) were tracked with passive acoustic telemetry, revealing a winter residency in the southeast Florida region. Detections from individuals recorded within the core winter habitat for > 20 d (n = 56) were incorporated into generalized linear mixedeffects models to investigate the influence of water temperature, photoperiod, moon phase, month and year on presence. The findings of this study suggest a temperature driven 'migrationresidency' model for mature lemon shark distribution across the USA eastern seaboard. Lemon sharks are distributed across a wide geographical area in the summer months and migrate south concentrating off southeast Florida in the winter, with this pattern repeated each year. From comparative genetic analysis and the absence of any evidence of mating behaviour during the winter residency period, mating and parturition most probably occur in May/June between northern Florida and the Carolinas. This study highlights the importance of determining the specific dynamics and proximate causes of animal movement and distribution over appropriate spatial and temporal scales relative to life history.

The barndoor skate (Dipturus laevis) has been reported to be close to extinction in parts of its northern range and is believed to be particularly vulnerable to fishing mortality due to its relatively large size. A lack of basic life history information, however, has hampered an accurate assessment and management of north Atlantic populations. In an attempt to fill this void, information was collected from 2 310 specimens caught during commercial sea scallop dredging in the southern section of Georges Bank Closed Area II. Eighty-seven fish were determined to be mature from a visual inspection of reproductive tracts and the allometric growth of claspers, oviducal glands and developing ova. Sexual dimorphism was apparent in length at 50% maturity with females maturing at 116.3 cm and males at 107.9 cm. A preliminary analysis of 118 vertebrae indicates faster growth (k = 0.14 to 0.18) and younger female maturation (6.5 to 7.2 yr) than previously believed. Thus, resilience of the barndoor skate to overfishing may be higher than recently assumed.

A majority of fisheries across the globe are data-and/or capacitylimited, in that they lack data and/or resources to generate statistical estimates of stock status, often leading to ineffective or nonexistent management. Improving management actions and outcomes could be accomplished by using analytical methods and management measures 061 Assessing and Managing Data-Limited Fish Stocks that are effective even when data and capacity are limited, positively impacting the livelihoods of millions of people and generating significant conservation benefits. Cost-effective methods for analyzing and managing data-limited fisheries exist, but they are challenging to navigate due to the myriad options, different data requirements, unique outputs, and a lack of understanding of the relative costs and advantages of each approach. There is also an increasing body of general guidance for the process of developing management strategies, i.e., the pre-agreed system of monitoring, assessment, and decision rules used to achieve management objectives for data-limited fisheries. However, this body of guidance has yet to be organized in a way that allows fishery management practitioners to apply it easily. Thus, there remains a disconnect between the development of assessment approaches and decision rule options, and their on-the-ground implementation in a management context. To fill this gap, we have developed FishPath: a decision support system that allows users to characterize their fishery with respect to (i) available data; (ii) biological/life history attributes of relevant species; (iii) fishery operational characteristics; (iv) socioeconomic characteristics; and (v) governance context. FishPath allows users to identify a subset of management strategy options appropriate for the fishery based on this characterization. We are currently applying FishPath to a range of data-limited fisheries globally to evaluate its efficacy. FishPath is the first ever comprehensive and standardized approach to guiding the selection of monitoring, assessment, and decision rule options for data-limited fisheries. If widely applied, FishPath will help ensure that more data-limited, capacity-limited fisheries, particularly those in developing countries, become assessed and managed, leading to improved conservation and fishery outcomes.