Challenges and opportunities for comparative studies of survival rates: An example with male pinnipeds

Survival rates are a central component of life-history strategies of large vertebrate species. However, comparative studies seldom investigate interspecific variation in survival rates with respect to other life-history traits, especially for males. The lack of such studies could be due to the challenges associated with obtaining reliable datasets, incorporating information on the 0-1 probability scale, or dealing with several types of measurement error in life-history traits, which can be a computationally intensive process that is often absent in comparative studies. We present a quantitative approach using a Bayesian phylogenetically controlled regression with the flexibility to incorporate uncertainty in estimated survival rates and quantitative life-history traits while considering genetic similarity among species and uncertainty in relatedness. As with any comparative analysis, our approach makes several assumptions regarding the generalizability and comparability of empirical data from separate studies. Our model is versatile in that it can be applied to any species group of interest and include any life-history traits as covariates. We used an unbiased simulation framework to provide "proof of concept" for our model and applied a slightly richer model to a real data example for pinnipeds. Pinnipeds are an excellent taxonomic group for comparative analysis, but survival rate data are scarce. Our work elucidates the challenges associated with addressing important questions related to broader ecological life-history patterns and how survival-reproduction trade-offs might shape evolutionary histories of extant taxa. Specifically, we underscore the importance of having high-quality estimates of age-specific survival rates and information on other life-history traits that reasonably characterize a species for accurately comparing across species.

Estimating Reproduction and Survival of Unmarked Juveniles Using Aerial Images and Marked Adults

Methods for estimating juvenile survival of wildlife populations often rely on intensive data collection efforts to capture and uniquely mark individual juveniles and observe them through time. Capturing juveniles in a time frame sufficient to estimate survival can be challenging due to narrow and stochastic windows of opportunity. For many animals, juvenile survival depends on postnatal parental care (e.g., lactating mammals). When a marked adult gives birth to, and provides care for, juvenile animals, investigators can use the adult mark to locate and count unmarked juveniles. Our objective was to leverage the dependency between juveniles and adults and develop a framework for estimating reproductive rates, juvenile survival, and detection probability using repeated observations of marked adult animals with known fates, but imperfect detection probability, and unmarked juveniles with unknown fates. Our methods assume population closure for adults and that no juvenile births or adoptions take place after monitoring has begun. We conducted simulations to evaluate methods and then developed a field study to examine our methods using real data consisting of a population of mule deer in a remote area in central Nevada. Using simulations, we found that our methods were able to recover the true values used to generate the data well. Estimates of juvenile survival rates from our field study were 0.96, (95% CRI 0.83–0.99) for approximately 32-day periods between late June and late August. The methods we describe show promise for many applications and study systems with similar data types, and our methods can be easily extended to unmanned aerial platforms and cameras that are already commercially available for the types of images we used.

Supplementary materials accompanying this paper appear online.

Reducing bias in survival under nonrandom temporary emigration

Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard survival parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration, unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates, and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified; nonetheless, there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable nonrandom temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data were effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naive constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, although still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several sources of data improved parameter estimates and reduced terminal bias. Efforts to incorporate or acquire such data should be considered by researchers and wildlife managers, especially in the years leading up to status assessments of species of interest. Simulation modeling is a very cost-effective method to explore the potential impacts of using different sources of data to produce high-quality demographic data to inform management.

Methods to examine reproductive biology in free-ranging, fully-marine mammals

Historical overexploitation of marine mammals, combined with present-day pressures, has resulted in severely depleted populations, with many species listed as threatened or endangered. Understanding breeding patterns of threatened marine mammals is crucial to assessing population viability, potential recovery and conservation actions. However, determining reproductive parameters of wild fully-marine mammals (cetaceans and sirenians) is challenging due to their wide distributions, high mobility, inaccessible habitats, cryptic lifestyles and in many cases, large body size and intractability. Consequently, reproductive biologists employ an innovative suite of methods to collect useful information from these species. This chapter reviews historic, recent and state-of-the-art methods to examine diverse aspects of reproduction in fully-aquatic mammals.

Copper and sewage inputs from recreational vessels at popular anchor sites in a semi-enclosed Bay (Qld, Australia): estimates of potential annual loads

Environmental impacts of vessels are well documented; Cu pollution as result of Cu based antifouling paints and nutrient pollution (such as N) from marine sewage are two examples of such disturbances. Understanding environmental impacts as well as the use of coastal waterways by recreational vessels is of concern to regulatory authorities, waterway users and local residents. In this study more than 55 aerial surveys were conducted of selected popular anchorages in eastern Moreton Bay, Queensland, Australia. Numbers of recreational vessels at certain times during the year were used in multiple linear regression analyses to develop predictive models for recreational vessel numbers. Over one year approximately 10,000 locally registered recreational craft (>6m length overall) generated an estimated 59,000 vessel nights. With Cu leaching rates from the literature, and estimates of sewage inputs (assuming little or no use of pump-out facilities), load estimates associated with overnight use of 20 popular anchor sites were calculated as 141+/-46 kg of Cu and 1.17+/-0.38 t of nitrogen (N) annually. More importantly, the models showed vessel activity to be highly variable, and focused at peak holiday times, with 14% of vessel activity and associated pollutant loads entering the environment during Christmas and Easter. This study highlighted the inherent difficulties in managing a popular maritime amenity and Marine Parks such as the Moreton Bay Marine Protected Area, Queensland, Australia with its variety of stakeholders and types and intensities of uses.