Dermal mycobacteriosis and warming sea surface temperatures are associated with elevated mortality of striped bass in Chesapeake Bay

Temperature is hypothesized to alter disease dynamics, particularly when species are living at or near their thermal limits. When disease occurs in marine systems, this can go undetected, particularly if the disease is chronic and progresses slowly. As a result, population-level impacts of diseases can be grossly underestimated. Complex migratory patterns, stochasticity in recruitment, and data and knowledge gaps can hinder collection and analysis of data on marine diseases. New tools enabling quantification of disease impacts in marine environments include coupled biogeochemical hydrodynamic models (to hindcast key environmental data), and multievent, multistate mark-recapture (MMSMR) (to quantify the effects of environmental conditions on disease processes and assess population-level impacts). We used MMSMR to quantify disease processes and population impacts in an estuarine population of striped bass (Morone saxatilis) in Chesapeake Bay from 2005 to 2013. Our results supported the hypothesis that mycobacteriosis is chronic, progressive, and, frequently, lethal. Yearly disease incidence in fish age three and above was 89%, suggesting that this disease impacts nearly every adult striped bass. Mortality of diseased fish was high, particularly in severe cases, where it approached 80% in typical years. Severely diseased fish also had a 10-fold higher catchability than healthy fish, which could bias estimates of disease prevalence. For both healthy and diseased fish, mortality increased with the modeled average summer sea surface temperature (SST) at the mouth of the Rappahannock River; in warmer summers (average SST29 degrees C), a cohort is predicted to experience \u3e90% mortality in 1year. Regression of disease signs in mildly and moderately diseased fish wa

Statistical ecology comes of age

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.Peer reviewe

Does Your Species Have Memory? Analysing Capture-Recapture Data with Memory Models.

1. We examine memory models for multi-site capture-recapture data. This is an important topic,as animals may exhibit behaviour that is more complex than simple first-order Markov movement between sites, when it is necessary to devise and fit appropriate models to data. 2. We consider the Arnason-Schwarz model for multi-site capture-recapture data, which incorporates just first-order Markov movement, and also two alternative models that allow for memory, the Brownie model and the Pradel model. We use simulation to compare two alternative tests which may be undertaken to determine whether models for multi-site capture-recapture data need to incorporate memory. 3. Increasing the complexity of models runs the risk of introducing parameters that cannot be estimated, irrespective of how much data are collected, a feature which is known as parameter redundancy. Rouan et al (JABES, 2009, pp 338-355) suggest a constraint that may be applied to overcome parameter redundancy when it is present in multi-site memory models. For this case, we apply symbolic methods to derive a simpler constraint, which allows more parameters to be estimated, and give general results not limited to a particular configuration. We also consider the effect sparse data can have on parameter redundancy, and recommend minimum sample sizes. 4. Memory models for multi-site capture-recapture data can be highly complex, and difficult to fit to data. We emphasise the importance of a structured approach to modelling such data, by considering a priori which parameters can be estimated, which constraints are needed in order for estimation to take place, and how much data need to be collected. We also give guidance on the amount of data needed to use two alternative families of tests for whether models for multi-site capture-recapture data need to incorporate memory

Does Your Species Have Memory? Analysing Capture-Recapture Data with Memory Models.

1. We examine memory models for multi-site capture-recapture data. This is an important topic,as animals may exhibit behaviour that is more complex than simple first-order Markov movement between sites, when it is necessary to devise and fit appropriate models to data. 2. We consider the Arnason-Schwarz model for multi-site capture-recapture data, which incorporates just first-order Markov movement, and also two alternative models that allow for memory, the Brownie model and the Pradel model. We use simulation to compare two alternative tests which may be undertaken to determine whether models for multi-site capture-recapture data need to incorporate memory. 3. Increasing the complexity of models runs the risk of introducing parameters that cannot be estimated, irrespective of how much data are collected, a feature which is known as parameter redundancy. Rouan et al (JABES, 2009, pp 338-355) suggest a constraint that may be applied to overcome parameter redundancy when it is present in multi-site memory models. For this case, we apply symbolic methods to derive a simpler constraint, which allows more parameters to be estimated, and give general results not limited to a particular configuration. We also consider the effect sparse data can have on parameter redundancy, and recommend minimum sample sizes. 4. Memory models for multi-site capture-recapture data can be highly complex, and difficult to fit to data. We emphasise the importance of a structured approach to modelling such data, by considering a priori which parameters can be estimated, which constraints are needed in order for estimation to take place, and how much data need to be collected. We also give guidance on the amount of data needed to use two alternative families of tests for whether models for multi-site capture-recapture data need to incorporate memory

An extension os Simons' inequality and applications

This article is devoted to an extension of Simons' inequality. As a consequence, having a pointwise converging sequence of functions, we get criteria of uniform convergence of an associated sequence of functions

Estimating clutch frequency in the sea turtle Dermochelys coriacea using stopover duration

International audienc

Consequences of past and present harvest management in a declining flyway population of common eiders Somateria mollissima

International audienceHarvested species population dynamics are shaped by the relative contribution of natural and harvest mortality. Natural mortality is usually not under management control, so managers must continuously adjust harvest rates to prevent overexploitation. Ideally, this requires regular assessment of the contribution of harvest to total mortality and how this affects population dynamics.To assess the impact of hunting mortality on the dynamics of the rapidly declining Baltic/Wadden Sea population of common eiders Somateria mollissima, we first estimated vital rates of ten study colonies over the period 1970-2015. By means of a multi-event capture-recovery model, we then used the cause of death of recovered individuals to estimate proportions of adult females that died due to hunting or other causes. Finally, we adopted a stochastic matrix population modeling approach based on simulations to investigate the effect of past and present harvest regulations on changes in flyway population size and composition.Results showed that even the complete ban on shooting females implemented in 2014 in Denmark, where most hunting takes place, was not enough to stop the population decline given current levels of natural female mortality. Despite continued hunting of males, our predictions suggest that the proportion of females will continue to decline unless natural mortality of the females is reduced.Although levels of natural mortality must decrease to halt the decline of this population, we advocate that the current hunting ban on females is maintained while further investigations of factors causing increased levels of natural mortality among females are undertaken. Synthesis and applications. At the flyway scale, continuous and accurate estimates of vital rates and the relative contribution of harvest versus other mortality causes are increasingly important as the population effect of adjusting harvest rates is most effectively evaluated within a model-based adaptive management framework

Towards developing thresholds for waterbirds that take into account turnover

To attain international importance and thus protection as a Ramsar site or as a Special Protection Area (SPA) a wetland site must either “regularly” support at least 20,000 waterbirds or seabirds, or 1% of the individuals of a population of a species or subspecies of waterbird. In most cases, sites have been designated by using the maxima of individual counts. These counts will underestimate volume (i.e. total number) of birds passing through the site if turnover of birds occurs. Using count data, observations of individually marked birds and survival and recruitment mark-recapture models, we present three different methods (V1, V2 & V3) implemented in the StopOver Duration Analysis or SODA program (Choquet & Pradel 2007) for estimating the total volume of birds passing through a site. We use simulated data to determine their performance using both biased and unbiased data. Specifically, we tested whether the estimates of volume were biased where the following parameters varied: proportion of birds marked, daily resighting rate, timing of arrival, proportion of transients in the population, heterogeneity in the resighting rates (i.e. some individuals with a high or low resighting rate), variation in arrival and stopover time and count error. With a relatively simple dataset (single arrival, no biases), the proportion of individuals marked had little effect on the reliability of the resulting volume estimates for both V1 and V3. Estimates of volume from V2 were always overestimated. The major factor that caused a small positive bias in V1 and V3 was the resighting probability. Lower resighting probabilities caused a small positive bias in the volume estimates. Resighting heterogeneity (i.e. some birds more likely to be seen than others) caused a substantial positive bias for all estimators. Transience (i.e. some birds stopping over for shorter time than others) caused no bias in V1 and V3, but a strong negative bias in V2.Transience seemed to reduce the positive bias due to heterogeneity in V1 and V3 when both were present. The use of trap-dependent models (i.e. those that allow individuals to have differential recapture rates) showed some promise for V3 as little bias in the volume estimate was observed when there was a moderate amount of variation in individuals’ resighting rates. V1 & V3 performed well under scenarios of varying arrival and stopover duration as well as where error in the counts was introduced. V2 was consistently biased (see Table 4.1) The V3 method performed well and consistently had the highest precision; it is the method we recommend to use to estimate volume. It is important that goodness of fit tests are used to determine biases in the data and appropriate models are used in Program SODA. Although some biases in the data have little effect on the resulting volume estimates, care must be taken when setting up a study to reduce bias. We present eight different ways of ensuring that bias is reduced during the collection of data. Practical ways to deal with biases are discussed. Recommendations (see section 4.2 for further details) are to: (i) Count at the same time as reading colour rings; (ii) Count at approximately one-third of the length of stay interval, e.g. if the species is thought to stay ten days on a site during passage then count every 5 days; (iii) aim to resight > 30 individuals during every count period, although preferably more; obtain as far as is possible representative samples of the population being studied; (iv) the timing of marking of the study species, the number of sites included, and the timing of counts is discussed