We investigated the influence of age on survival and breeding rates in a long-lived species Rissa tridactyla using models with individual random effects permitting variation and covariation in fitness components among individuals. Differences in survival or breeding probabilities among individuals are substantial, and there was positive covariation between survival and breeding probability; birds that were more likely to survive were also more likely to breed, given that they survived. The pattern of age-related variation in these rates detected at the individual level differed from that observed at the population level. Our results provided confirmation of what has been suggested by other investigators: within-cohort phenotypic selection can mask senescence. Although this phenomenon has been extensively studied in humans and captive animals, conclusive evidence of the discrepancy between population-level and individual-level patterns of age-related variation in life-history traits is extremely rare in wild animal populations. Evolutionary studies of the influence of age on life-history traits should use approaches differentiating population level from the genuine influence of age: only the latter is relevant to theories of life-history evolution. The development of models permitting access to individual variation in fitness is a promising advance for the study of senescence and evolutionary processes.

Summary 1.Multistate capture-recapture models are frequently used to estimate the survival and state transition parameters needed to parameterize stage-structured population models, tools that are important for conservation and management. Typically, such models assume that all encountered individuals can be assigned to a particular state without error or ambiguity, a requirement which is difficult to meet in practice. Model extensions to relax this assumption would increase the richness of ecological data sets available for estimating life-history and stage-transition parameters with multistate models. 2. One relatively common analytical approach when confronted with ambiguity in state determination is to censor all encounters where the state of an animal cannot be ascertained. Here, we present an alternative approach, which uses a hidden Markov (or multievent) modelling framework that can incorporate data from encounters of unknown state. Using simulation, we show that our approach leads to estimators of state-specific survival and transition probabilities that are more precise, and sometimes considerably so, than methods based on censoring. 3. We demonstrate our approach using field data from a study of the dynamics of conjunctivitis in the house finch Carpodacus mexicanus Müller. A fundamental challenge in modelling disease dynamics involves the estimation of the rates of entry and exit from one or more disease states, which can be complicated when disease state is uncertain. We show that incorporating data from unknown states made substantial improvements to parameter precision. 4. Synthesis and applications . Missing or incomplete records are an unfortunate but common feature of many ecological field studies, often diminishing the quality and quantity of data. Our approach of treating state as a hidden Markov process allows such records to be used, increasing the precision of survival and state transition parameters in multistate mark-recapture studies. Our approach is more general than other approaches in the literature, and does not require specialized sampling designs or ancillary information to inform state assignment. We suggest that ecologists consider using this modelling approach instead of censoring records whenever state information is missing.

We assessed the effectiveness of an extensive and unprecedented wildlife reduction effort directed at a wide‐ranging migratory population of geese. Population reduction efforts that targeted several populations of light geese (greater snow geese [Chen caerulescens atlantica], lesser snow geese [C. c. caerulescens], and Ross's geese [C. rossii]) began in 1999 in central and eastern North America. Such efforts were motivated by a broad consensus that abundance of these geese was causing serious ecological damage to terrestrial and salt marsh ecosystems in central and eastern parts of the Canadian Arctic and subarctic regions along Hudson Bay. Starting in February 1999, special conservation measures (or, in the U.S., a conservation order) were added to the respective federal regulations that permitted hunters to take snow geese (in parts of Canada and the U.S.) and Ross's geese (in parts of the U.S.) during specified harvest periods outside of the hunting season. These measures were accompanied by increase or removal of daily kill and possession limits and by permissions to use previously prohibited equipment for hunting these species in certain regions of the continent. The intent was to reduce adult survival through increased hunting mortality, which was judged to be the most cost‐effective approach to reversing population growth. Our principal goal was to assess the effectiveness of reduction efforts directed at the midcontinent population of lesser snow geese, which was thought to be the most serious threat to arctic and subarctic ecosystems of the 3 light goose populations. Our multiple objectives included the estimation and detection of change in the response measures of total annual harvest, harvest rate, survival rate, and abundance, using the 1998 hunting period (defined as 1 Aug 1998 to 31 Jul 1999) as a point of reference. We used information about hunter recoveries of leg‐banded snow geese and estimates of regular‐season harvest to estimate 1) conservation‐order harvest and total annual harvest, 2) geographic and temporal distribution of recoveries by age class, 3) survival and recovery probability, and 4) abundance of snow geese each August using Lincoln's (1930) method. We also modeled population growth to infer the form of population response to management efforts. Toward that end, we also proposed a method of estimating conservation‐order harvest and tested for differences in band‐reporting rate between Canada and the United States. Overall, the balance of evidence favored the conclusion that the midcontinent population has continued to grow during the conservation order, although perhaps at a reduced rate. We suggest that annual rate of population growth $({\hat {\lambda }})$, derived from estimates of annual population size in August, likely provides the most reliable inference about change in the midcontinent population. There was a decline in annual survival probability between these 2 periods from about 0.89 to about 0.83 among snow geese from the southern‐nesting stratum (south of 60°N...

Population control through harvest has the potential to reduce the abundance of nuisance and invasive species. However, demographic structure and density-dependent processes can confound removal efforts and lead to undesirable consequences, such as overcompensation (an increase in abundance in response to harvest) and instability (population cycling or chaos). Recent empirical studies have demonstrated the potential for increased mortality (such as that caused by harvest) to lead to overcompensation and instability in plant, insect, and fish populations. We developed a general population model with juvenile and adult stages to help determine the conditions under which control harvest efforts can produce unintended outcomes. Analytical and simulation analyses of the model demonstrated that the potential for overcompensation as a result of harvest was significant for species with high fecundity, even when annual stage-specific survivorship values were fairly low. Population instability as a result of harvest occurred less frequently and was only possible with harvest strategies that targeted adults when both fecundity and adult survivorship were high. We considered these results in conjunction with current literature on nuisance and invasive species to propose general guidelines for assessing the risks associated with control harvest based on life history characteristics of target populations. Our results suggest that species with high per capita fecundity (over discrete breeding periods), short juvenile stages, and fairly constant survivorship rates are most likely to respond undesirably to harvest. It is difficult to determine the extent to which overcompensation and instability could occur during real-world removal efforts, and more empirical removal studies should be undertaken to evaluate population-level responses to control harvests. Nevertheless, our results identify key issues that have been seldom acknowledged and are potentially generic across taxa.

Summary 1.We considered the impact of an emerging pathogen ( Mycoplasma gallisepticum Edward and Kanarek) on apparent survival, encounter and transition rates in a population of a novel host (the house finch, Carpodacus mexicanus Müller). We used a multistate analysis of mark-encounter data from individually marked birds. Individual birds were categorized to a particular disease 'state'; transition rates among states, conditional on apparent survival, were analogous to rates of new infection and recovery from infection. We hypothesized that M. gallisepticum infection would reduce the apparent survival of infected individuals, and that the magnitude of this reduction would vary as a function of the physiological condition of the host (which was characterized in our analyses by including a demographic and an environmental surrogate as covariates). 2. We found consistent support for the hypothesis that M. gallisepticum infection resulted in lower apparent survival among infected individuals, and that recovery rates (from infected to non-infected) were greater than infection rates in this population. We also found strong evidence indicating that infected individuals were less likely to be encountered than were non-infected individuals. Although we predicted that both sex and temperature (proxies for physiological condition) would explain a significant proportion of the variation in our data, only marginal influences of both factors on apparent survival, encounter and state transition rates were detected. 3. Our analyses identified several factors that may be important to studies of disease in the wild. First, disease state assignment may be uncertain, which can complicate parameter estimation. Secondly, encounter rate for infected individuals in our study was low relative to that for non-infected individuals, reflecting possible behavioural changes in infected individuals. Low encounter rates reduces precision of estimated parameters, especially for multistate models. Finally, our results (and mark-recapture models in general) assume independence among individual birds. However, we are aware that there is a social structuring in house finches (and in general for many bird species). Accounting for such non-independence may be especially important for situations where the state transitions are directly related to the pattern of social contact.

Markov chain Monte Carlo (MCMC) is a statistical innovation that allows researchers to fit far more complex models to data than is feasible using conventional methods. Despite its widespread use in a variety of scientific fields, MCMC appears to be underutilized in wildlife applications. This may be due to a misconception that MCMC requires the adoption of a subjective Bayesian analysis, or perhaps simply to its lack of familiarity among wildlife researchers. We introduce the basic ideas of MCMC and software BUGS (Bayesian inference using Gibbs sampling), stressing that a simple and satisfactory intuition for MCMC does not require extraordinary mathematical sophistication. We illustrate the use of MCMC with an analysis of the association between latent factors governing individual heterogeneity in breeding and survival rates of kittiwakes (Rissa tridactyla). We conclude with a discussion of the importance of individual heterogeneity for understanding population dynamics and designing management plans.

We examined the influence of timing of reproduction and brood size on growth rates of goslings of nidifugous Lesser Snow Geese (Anser caerulescens) using data collected at La Perouse Bay, Manitoba from 1978 to the present, Gosling growth rates declined significantly during the season, and the declines were independent of the parental genotype. Goslings from larger broods grew significantly faster, but there was no significant annual variation in the seasonal growth rate patterns with either hatch date or brood size. The hatch date and brood size effects could not be accounted for by systematic differences in either egg size or body size of the female parent. Goslings that grew more slowly due to the effects of hatch date or brood size were significantly smaller as adults. Because gosling growth rates influence final adult size, they may have a significant effect on various life history traits in this species.

Investigations of disease dynamics in wild animal populations often use estimated prevalence or incidence as a measure of true disease frequency. Such indices, almost always based solely on raw counts of infected and uninfected individuals, are often used as the basis for analysis of temporal and spatial dynamics of diseases. Generally, such studies do not account for potential differences in observer detection probabilities of host individuals stratified by biotic and/or abiotic factors. We demonstrate the potential effects of heterogeneity in state-specific detection probabilities on estimated disease prevalence using mark-recapture data from previous work in a House Finch (Carpodacus mexicanus) and Mycoplasma gallisepticum system. In this system, detection probabilities of uninfected finches were generally higher than infected individuals. We show that the magnitude and seasonal pattern of variation in estimated prevalence, corrected for differences in detection probabilities, differed markedly from uncorrected (apparent) prevalence. When the detection probability of uninfected individuals is higher than infected individuals (as in our study), apparent prevalence is negatively biased, and vice versa. In situations where state-specific detection probabilities strongly interact over time, we show that the magnitude and pattern of apparent prevalence can change dramatically; in such cases, observed variations in prevalence may be completely spurious artifacts of variation in detection probability, rather than changes in underlying disease dynamics. Accounting for differential detection probabilities in estimates of disease frequency removes a potentially confounding factor in studies seeking to identify biotic and/or abiotic drivers of disease dynamics. Given that detection probabilities of different groups of individuals are likely to change temporally and spatially in most field studies, our results underscore the importance of estimating and incorporating detection probabilities in estimated disease prevalence (specifically), and more generally, any ecological index used to estimate some parameter of interest. While a mark-recapture approach makes it possible to estimate detection probabilities, it is not always practical, especially at large scales. We discuss several alternative approaches and categorize the assumptions under which analysis of uncorrected prevalence may be acceptable.