One challenge an analyst often encounters when dealing with complex mark-recapture models is how to limit the number of a priori models. While all possible combinations of model structures on the different parameters (e.g., /, p) can be considered, such a strategy often results in a burdensome number of models, leading to the use of ad hoc strategies to reduce the number of models constructed. For the Cormack-Jolly-Seber data type, one example of an ad hoc strategy is to hold a general / model structure constant while investigating model structures on p, and then to hold the resulting best structure on p constant and investigate structures on /. Many comparable strategies exist. The effect of following ad hoc strategies on parameter estimates as well as for variable selection and whether model averaging can ameliorate any problems are unknown. By means of a simulation study, we have investigated this informational gap by comparing the allcombinations model building strategy with two ad hoc strategies and with truth, as well as considering the results of model averaging. We found that model selection strategy had little effect on parameter estimator bias and precision and that model averaging did improve bias and precision slightly. In terms of variable selection (i.e., cumulative Akaike's information criterion weights), model sets based on ad hoc strategies did not perform as well as those based on all combinations, as less important variables often had higher weights with the former than with the all possible combinations strategy. Increased sample size resulted in increased variable weights, with an infinite sample size resulting in all variable weights equaling 1 for variables with any predictive influence. Thus, the distinction between statistical importance (dependent on sample size) and biological importance must be recognized when utilizing cumulative weights. We recommend that allcombinations model strategy and model averaging be used. However, if an ad hoc strategy is relied upon to reduce the computational demand, parameter estimates will generally be comparable to the all-combinations strategy, but variable weights will not correspond to the all-combinations strategy.

Estimates of species' vital rates and an understanding of the factors affecting those parameters over time and space can provide crucial information for management and conservation. We used mark-recapture, reproductive output, and territory occupancy data collected during 1985-2013 to evaluate population processes of Northern Spotted Owls (Strix occidentalis caurina) in 11 study areas in Washington, Oregon, and northern California, USA. We estimated apparent survival, fecundity, recruitment, rate of population change, and local extinction and colonization rates, and investigated relationships between these parameters and the amount of suitable habitat, local and regional variation in meteorological conditions, and competition with Barred Owls (Strix varia). Data were analyzed for each area separately and in a meta-analysis of all areas combined, following a strict protocol for data collection, preparation, and analysis. We used mixed effects linear models for analyses of fecundity, Cormack-Jolly-Seber open population models for analyses of apparent annual survival (/), and a reparameterization of the Jolly-Seber capture-recapture model (i.e. reverse Jolly-Seber; RJS) to estimate annual rates of population change (k RJS ) and recruitment. We also modeled territory occupancy dynamics of Northern Spotted Owls and Barred Owls in each study area using 2-species occupancy models. Estimated mean annual rates of population change (k) suggested that Spotted Owl populations declined from 1.2% to 8.4% per year depending on the study area. The weighted mean estimate of k for all study areas was 0.962 (6 0.019 SE; 95% CI: 0.925-0.999), indicating an estimated range-wide decline of 3.8% per year from 1985 to 2013. Variation in recruitment rates across the range of the Spotted Owl was best explained by an interaction between total winter precipitation and mean minimum winter temperature. Thus, recruitment rates were highest when both total precipitation (29 cm) and minimum winter temperature (À9.58C) were lowest. Barred Owl presence was associated with increased local extinction rates of Spotted Owl pairs for all 11 study areas. Habitat covariates were related to extinction rates for Spotted Owl pairs in 8 of 11 study areas, and a greater amount of suitable owl habitat was generally associated with decreased extinction rates. We observed negative effects of Barred Owl presence on colonization rates of Spotted Owl pairs in 5 of 11 study areas. The total amount of suitable Spotted Owl habitat was positively associated with colonization rates in 5 areas, and more habitat disturbance was associated with lower colonization rates in 2 areas. We observed strong declines in derived estimates of occupancy in all study areas. Mean fecundity of females was highest for adults (0.309 6 0.027 SE), intermediate for 2-yr-olds (0.179 6 0.040 SE), and lowest for 1-yr-olds (0.065 6 0.022 SE). The presence of Barred Owls and habitat covariates explained little of the temporal variation in fecundity in most study areas. Climate covariates ...

Predicting extinction risks has become a central goal for conservation and evolutionary biologists interested in population and community dynamics. Several factors have been put forward to explain risks of extinction, including ecological and life history characteristics of individuals. For instance, factors that affect the balance between natality and mortality can have profound effects on population persistence. Sexual selection has been identified as one such factor. Populations under strong sexual selection experience a number of costs ranging from increased predation and parasitism to enhanced sensitivity to environmental and demographic stochasticity. These findings have led to the prediction that local extinction rates should be higher for species͞populations with intense sexual selection. We tested this prediction by analyzing the dynamics of natural bird communities at a continental scale over a period of 21 years , using relevant statistical tools. In agreement with the theoretical prediction, we found that sexual selection increased risks of local extinction (dichromatic birds had on average a 23% higher local extinction rate than monochromatic species). However, despite higher local extinction probabilities, the number of dichromatic species did not decrease over the period considered in this study. This pattern was caused by higher local turnover rates of dichromatic species, resulting in relatively stable communities for both groups of species. Our results suggest that these communities function as metacommunities, with frequent local extinctions followed by colonization. Anthropogenic factors impeding dispersal might therefore have a significant impact on the global persistence of sexually selected species. O ne of the key assumptions of theoretical models of sexual selection is the antagonistic effect of natural and sexual selection on the evolution of exaggerated sexual advertisements (1). On one hand, competition among males and͞or female preference can result in the evolution of costly sexual traits; on the other hand, extravagant ornaments can incur survival costs. As a consequence, the evolution of exaggerated displays is thought to displace individuals harboring such traits from their survival optimum (2). Survival costs of sexual displays have been shown both at the intraspecific and interspecific level. In a pioneering study, Endler (3,4) showed that the number and size of color spots in guppies (Poecilia reticulata) were tightly linked to the distribution of predator species in the stream; the number of color spots decreased in areas with high visual predation. A laboratory study on experimental populations of guppies experiencing various predation regimes confirmed the causative link between expression of secondary sexual traits and predation (3, 4). Comparative evidence for survival costs of sexual advertisement comes from studies on birds. Using a phylogenetic framework, Promislow and coworkers (5, 6) have shown that sexual dichromatism was associated with higher mortality rate within...

Summary1. Stephens et al . (2005) argue for 'pluralism' in statistical analysis, combining null hypothesis testing and information-theoretic (I-T) methods. We show that I-T methods are more informative even in single variable problems and we provide an ecological example. 2. I-T methods allow inferences to be made from multiple models simultaneously. We believe multimodel inference is the future of data analysis, which cannot be achieved with null hypothesis-testing approaches. 3. We argue for a stronger emphasis on critical thinking in science in general and less reliance on exploratory data analysis and data dredging. Deriving alternative hypotheses is central to science; deriving a single interesting science hypothesis and then comparing it to a default null hypothesis (e.g. 'no difference') is not an efficient strategy for gaining knowledge. We think this single-hypothesis strategy has been relied upon too often in the past. We clarify misconceptions presented by Stephens et al . (2005).5. We think inference should be made about models, directly linked to scientific hypotheses, and their parameters conditioned on data, Prob( H j | data). I-T methods provide a basis for this inference. Null hypothesis testing merely provides a probability statement about the data conditioned on a null model, Prob(data | H 0 ). 6. Synthesis and applications . I-T methods provide a more informative approach to inference. I-T methods provide a direct measure of evidence for or against hypotheses and a means to consider simultaneously multiple hypotheses as a basis for rigorous inference. Progress in our science can be accelerated if modern methods can be used intelligently; this includes various I-T and Bayesian methods.

Intermittent breeding is an important lifehistory strategy that has rarely been quantified in the wild and for which drivers remain unclear. It may be the result of a trade-off between survival and reproduction, with individuals skipping breeding when breeding conditions are below a certain threshold. Heterogeneity in individual quality can also lead to heterogeneity in intermittent breeding. We modelled survival, recruitment and breeding probability of the red-footed booby (Sula sula), using a 19 year mark -recapture dataset involving more than 11 000 birds. We showed that skipping breeding was more likely in El-Niñ o years, correlated with an increase in the local sea surface temperature, supporting the hypothesis that it may be partly an adaptive strategy of birds to face the trade-off between survival and reproduction owing to environmental constraints. We also showed that the age-specific probability of first breeding attempt was synchronized among different age-classes and higher in El-Niñ o years. This result suggested that pre-breeders may benefit from lowered competition with experienced breeders in years of high skipping probabilities.

Few studies have examined survivorship of animals in forest fragments differing in size, and none has used appropriate mark–recapture analysis techniques taking into account probability of recapture. Using Program MARK, a flexible mark–recapture software package, we estimated annual survival rates of four permanent‐resident woodland bird species over a 5‐yr period in a fragmented landscape. For Carolina Chickadees, White‐breasted Nuthatches, and Downy Woodpeckers, the probability of survival was related to site, with survival being highest in large woodlots, low in small woodlots, and either intermediate or lower in riparian woodlands. The presence of supplemental food had a positive influence on survivorship. Survivorship of the Tufted Titmouse was lower in years with heavy snow cover. There was some evidence for an age difference in apparent survival, with adult birds having higher survival rates. Overall, however, these age‐specific estimates had large variances or the differences disappeared when models were averaged, except in the chickadee, where young birds appeared to survive less well in forested river corridors. This last result was quite likely due, at least in part, to age‐specific dispersal, suggesting that river corridors function as important dispersal routes for young, transient birds of permanent‐resident species. These results suggest a strong additional cost of fragmentation: increased mortality. This cost has not been previously documented using modern mark–recapture analytical techniques.

We assessed variation in reporting probabilities of standard bands among species, populations, harvest locations, and size classes of North American geese to enable estimation of unbiased harvest probabilities. We included reward (US$10, $20, $30, $50, or $100) and control ($0) banded geese from 16 recognized goose populations of 4 species: Canada (Branta canadensis), cackling (B. hutchinsii), Ross's (Chen rossii), and snow geese (C. caerulescens). We incorporated spatially explicit direct recoveries and live recaptures into a multinomial model to estimate reporting, harvest, and band‐retention probabilities. We compared various models for estimating harvest probabilities at country (United States vs. Canada), flyway (5 administrative regions), and harvest area (i.e., flyways divided into northern and southern sections) scales. Mean reporting probability of standard bands was 0.73 (95% CI = 0.69–0.77). Point estimates of reporting probabilities for goose populations or spatial units varied from 0.52 to 0.93, but confidence intervals for individual estimates overlapped and model selection indicated that models with species, population, or spatial effects were less parsimonious than those without these effects. Our estimates were similar to recently reported estimates for mallards (Anas platyrhynchos). We provide current harvest probability estimates for these populations using our direct measures of reporting probability, improving the accuracy of previous estimates obtained from recovery probabilities alone. Goose managers and researchers throughout North America can use our reporting probabilities to correct recovery probabilities estimated from standard banding operations for deriving spatially explicit harvest probabilities.

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.