Bayesian hierarchical mixture models for otolith microchemistry analysis

The field of fisheries research commonly uses classical statistical classification methods to estimate the proportion of fish that return to natal spawning grounds to spawn. With the advent of otolith microchemical analysis, researchers are able to extract information from fish ear stones (otoliths) about the chemical composition of water in which fish have spent distinct periods of their lives. Here we present a method of analysis set in the Bayesian statistical paradigm which enables explicit incorporation of habitat information into the analysis. The ecological system is seen as arising from a mixture of disparate fish populations and information from the biological relationships inherent in otolith formation is exploited through the hierarchical model structure. We present the model and motivation, demonstrate the validity of the model through simulation studies, and conclude with an analysis of a data set from Lake Erie.     

Multiseasonal management of an agricultural pest II: the economic optimization problem

The problem of selecting a pesticide application strategy in the face of increasing resistance to the pesticide in the pest population is dealt with. The grower in this situation may do better by sacrificing a portion of the present crop in return for a reduced resistance to future applications. The model presented represents an attempt to forge a compromise between excessive complexity, rendering the model difficult to study, and excessive simplicity, rendering the model useless. The effects of timing of the application of the pesticide within the season are discussed. The principle conclusions are the following: (i) If immigration of pests from refugia is significant then proper timing of the application of pesticide may be used to help alleviate resistance growth. (ii) Resistance growth may best be reduced by spraying earlier than what would otherwise be the best time. (iii) The value of the discount rate (and of the time horizon) has a profound effect on the nature of the optimal policy.     

Modelling the effects of UV radiation on the survival of Antarctic krill (Euphausia superba Dana) in the face of limited data

Antarctic krill, Euphausia superba, is a keystone species of the Antarctic ecosystem. A fishery for krill may compete with land-based predators (penguins and seals), particularly during the breeding season. The Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) is moving towards management in small scale units. The management models specify predation and fishing mortality as space and time dependent but do not yet include non-predation natural mortality. Krill are known to be highly susceptible to ultraviolet radiation (UV) but there are limited empirical data. We develop a model for krill mortality caused by UV and parameterize and assess it by comparison with experimental data. The analysis allows us to identify key parameters that should be measured in future experiments and also leads to suggestions about modification of experimental procedure. We illustrate the method for krill found in the Livingston Island area and show that (a) it is possible to estimate the component of natural mortality due to UV-induced damage and (b) that cohorts born in 1979, 1984, or 1997 have different survival in the first 5 years of life, associated with differential UV exposure. In particular, those born in 1997 may have experienced as much as 10% lower survival than those born in 1979. The method developed here allows a potentially important source of krill mortality to be incorporated into the management models and suggests key experiments and field work in the future.     

Multiseasonal management of an agricultural pest. I: Development of the theory

A framework for analyzing the trade-off between economic yield from a crop and buildup of resistance to pesticide caused by repeated applications of pesticide is developed. The analysis begins with the case of age-independent pest dynamics, in which pests infest a field by arriving from an external pool. Initially, it is assumed that the pest genetics of interest are single locus, two allele, with resistance to pesticide dominant and susceptible pests more fit in the absence of spraying. The pesticide is applied only once during the season, with timing and intensity of the application as control variables. Interseasonal pest and crop dynamics are studied by solving appropriate ordinary differential equations. Intraseasonal pest dynamics are assumed to follow the Hardy-Weinberg formula. It is shown that the three class diploid model can be replaced by a two class haploid model with essentially no change in the results. A model based on partial differential equations is developed, for the case in which pest dynamics depend upon age, and it is shown that the partial differential equation model can be replaced by a pair of coupled ordinary differential equations. The main operational conclusion in this paper is that the timing of the application of pesticide can be used to control buildup of resistance and that the intensity of the application can be used to control the crop yield.     

Home buyouts and household recovery: neighborhood differences three years after Hurricane Sandy

Home buyout programs facilitate the permanent relocation of residents away from areas considered to be at risk from future hazards, though few studies have examined the impacts of home buyout programs on affected households and communities beyond the program implementation period. In this paper, we examine between-neighborhood variation in key recovery indicators for three neighborhoods that followed different paths to recovery after Hurricane Sandy: one that rebuilt in situ, one that participated in a buyout and relocated, and one located immediately adjacent to the buyout zone. Three years post-disaster, buyout participants are faring worse in terms of place attachment and social capital compared to residents in the other two neighborhoods, while the neighborhood adjacent to the buyout zone is also showing signs of decline. These findings suggest that the social costs of buyouts extend well into the recovery period, and that the place-based ties and social networks that would typically help individuals cope with disaster impacts and persevere through adversity may be diminished for buyout participants, ultimately hindering their recovery. We conclude with a discussion of the implications of buyouts on participating and affected communities, as well as implications for research and policy.     

Hitchhikers reveal cryptic host behavior: new insights from the association between Planes major and sea turtles in the Pacific Ocean

Studies that incorporate information from habitat-specific ecological interactions (e.g., epibiotic associations) can reveal valuable insights into the cryptic habitat-use patterns and behavior of marine vertebrates. Sea turtles, like other large, highly mobile marine vertebrates, are inherently difficult to study, and such information can inform the implementation of conservation measures. The presence of epipelagic epibionts, such as the flotsam crab Planes major, on sea turtles strongly suggests that neritic turtles have recently occupied epipelagic habitats (upper 200 m in areas with >200 m depth) and that epipelagic turtles spend time at or near the surface. We quantified the effects of turtle species, turtle size, and habitat (neritic or epipelagic) on the frequency of epibiosis (F ₀) by P. major on sea turtles in the Pacific Ocean. In neritic habitats, we found that loggerhead (F ₀ = 27.6 %) and olive ridley turtles (F ₀ = 26.2 %) host crabs frequently across a wide range of body sizes, and green turtles almost never host crabs (F ₀ = 0.7 %). These results suggest that loggerheads and olive ridleys display variable/flexible epipelagic-neritic transitions, while green turtles tend to transition unidirectionally at small body sizes. In epipelagic habitats, we found that loggerheads host crabs (F ₀ = 92.9 %) more frequently than olive ridleys (F ₀ = 50 %) and green turtles (F ₀ = 38.5 %). These results suggest that epipelagic loggerheads tend to spend more time at or near the surface than epipelagic olive ridleys and green turtles. Results of this study reveal new insights into habitat-use patterns and behavior of sea turtles and display how epibiont data can supplement data from more advanced technologies to gain a better understanding of the ecology of marine vertebrates during cryptic life stages.     

Exploring the effects of reductions in krill biomass in the Southern Ocean on blue whales using a state-dependent foraging model

Many species of baleen whales were hunted to near extinction in the Southern Hemisphere. The recovery of these populations will be affected by the availability of krill, a major dietary component, in the Southern Ocean. We combine a novel energetics model for baleen whales with a state dependent foraging model to explore the impacts of an expanding krill fishery on baleen whales. We parameterize the model for blue whales, but with simple modifications it could be applied to most baleen whales. We predict that an expanding fishery will have a small but significant impact on the blue whale population through decreased birth rates. However, spreading the catch limit throughout the range of krill can reduce these effects. In addition, whales may be able to reduce these impacts through adaptive changes in foraging behavior. The relationship between krill abundance and blue whale foraging and reproductive success is nonlinear, such that larger reductions in krill biomass, potentially following a loss of sea ice due to climate change, could have a much larger negative impact on the recovery of blue whales.     

Aggregation and fishery dynamics: Multiple time scales,times to extinction,and random environments

This paper is a mathematical study of the models introduced by C.W. Clark and M. Mangel to describe the tropical tuna purse seine fishery. By casting the equations into dimensionless form, it is easy to study the bifurcations of the system models and to study the dynamical behavior of the models. The dynamics are analyzed by using singular perturbation theory. A number of stochastic problems related to the dynamics of the models are formulated and solutions are obtained by using the diffusion approximation and asymptotic analysis. Finally, the question of model identification is addressed, and two methods for model identification are sketched.