Do harvest refuges buffer kangaroos against evolutionary responses to selective harvesting?

There is a wealth of literature documenting a directional change of body size in heavily harvested populations. Most of this work concentrates on aquatic systems, but terrestrial populations are equally at risk. This paper explores the capacity of harvest refuges to counteract potential effects of size-selective harvesting on the allele frequency,of populations. We constructed a stochastic, individual-based model parameterized with data on red kangaroos. Because we do not know which part of individual growth would change in the course of natural selection, we explored the effects of two alternative models of individual growth in which alleles affect either the growth rate or the maximum size. The model results show that size-selective harvesting can result in significantly smaller kangaroos for a given age when the entire population is subject to harvesting. In contrast, in scenarios that include dispersal from harvest refuges, the initial allele frequency remains virtually unchanged.

The rising tide of ocean diseases: Unsolved problems and research priorities

New studies have detected a rising number of reports of diseases in marine organisms such as corals, molluscs, turtles, mammals, and echinoderms over the past three decades. Despite the increasing disease load, microbiological, molecular, and theoretical tools for managing disease in the world's oceans are underdeveloped. Review of the new developments in the study of these diseases identifies five major unsolved problems and priorities for future research: (1) detecting origins and reservoirs for marine diseases and tracing the flow of some new pathogens from land to sea; (2) documenting the longevity and host range of infectious stages; (3) evaluating the effect of greater taxonomic diversity of marine relative to terrestrial hosts and pathogens; (4) pinpointing the facilitating role of anthropogenic agents as incubators and conveyors of marine pathogens; (5) adapting epidemiological models to analysis of marine disease.

Improving precision and reducing bias in biological surveys: estimating false-negative error rates

The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods.

Exposing extinction risk analysis to pathogens: Is disease just another form of density dependence?

In the United States and several other countries., the development of population viability analyses (PVA) is a legal requirement of any species survival plan developed for threatened and endangered species. Despite the importance of pathogens in natural populations, little attention has been given to host-pathogen dynamics in PVA. To study the effect of infectious pathogens on extinction risk estimates generated from PVA, we review and synthesize the relevance of host-pathogen dynamics in analyses of extinction risk. We then develop a stochastic, density-dependent host-parasite model to investigate the effects of disease on the persistence of endangered populations. We show that this model converges on a Ricker model of density dependence under a suite of limiting assumptions, including. a high probability that epidemics will arrive and occur. Using this modeling framework, we then quantify: (1) dynamic differences between time series generated by disease and Ricker processes with the same parameters; (2) observed probabilities of quasi-extinction for populations exposed to disease or self-limitation; and (3) bias in probabilities of quasi-extinction estimated by density-independent PVAs when populations experience either form of density dependence. Our results suggest two generalities about the relationships among disease, PVA, and the management of endangered species. First, disease more strongly increases variability in host abundance and, thus, the probability of quasi-extinction, than does self-limitation. This result stems from the fact that the effects and the probability of occurrence of disease are both density dependent. Second, estimates of quasi-extinction are more often overly optimistic for populations experiencing disease than for those subject to self-limitation. Thus, although the results of density-independent PVAs may be relatively robust to some particular assumptions about density dependence, they are less robust when endangered populations are known to be susceptible to disease. If potential management actions involve manipulating pathogens, then it may be useful to. model disease explicitly.

A reassessment of genetic limits to evolutionary change

An absence of genetic variance in traits under selection is perhaps the oldest explanation for a limit to evolutionary change, but has also been the most easily dismissed. We review a range of theoretical and empirical results covering single traits to more complex multivariate systems, and show that an absence of genetic variance may be more common than is currently appreciated. From a single-trait perspective, we highlight that it is becoming clear that some trait types do not display significant levels of genetic variation, and we raise the possibility that species with restricted ranges may differ qualitatively from more widespread species in levels of genetic variance in ecologically important traits. A common misconception in many life-history studies is that a lack of genetic variance in single traits, and genetic constraints as a consequence of bivariate genetic correlations, are different causes of selection limits. We detail how interpretations of bivariate patterns are unlikely to demonstrate genetic limits to selection in many cases. We advocate a multivariate definition of genetic constraints that emphasizes the presence (or otherwise) of genetic variance in the multivariate direction of selection. For multitrait systems, recent results using longer term studies of organisms, in which more is understood concerning what traits may be under selection, have indicated that selection may exhaust genetic variance, resulting in a limit to the selection response.

Evaluating trends in abundance of immature green turtles, Chelonia mydas, in the Greater Caribbean

Many long-lived marine species exhibit life history traits. that make them more vulnerable to overexploitation. Accurate population trend analysis is essential for development and assessment of management plans for these species. However, because many of these species disperse over large geographic areas, have life stages inaccessible to human surveyors, and/or undergo complex developmental migrations, data on trends in abundance are often available for only one stage of the population, usually breeding adults. The green turtle (Chelonia mydas) is one of these long-lived species for which population trends are based almost exclusively on either numbers of females that emerge to nest or numbers of nests deposited each year on geographically restricted beaches. In this study, we generated estimates of annual abundance for juvenile green turtles at two foraging grounds in the Bahamas based on long-term capture-mark-recapture (CMR) studies at Union Creek (24 years) and Conception Creek (13 years), using a two-stage approach. First, we estimated recapture probabilities from CMR data using the Cormack-Jolly-Seber models in the software program MARK; second, we estimated annual abundance of green turtles. at both study sites using the recapture probabilities in a Horvitz-Thompson type estimation procedure. Green turtle abundance did not change significantly in Conception Creek, but, in Union Creek, green turtle abundance had successive phases of significant increase, significant decrease, and stability. These changes in abundance resulted from changes in immigration, not survival or emigration. The trends in abundance on the foraging grounds did not conform to the significantly increasing trend for the major nesting population at Tortuguero, Costa Rica. This disparity highlights the challenges of assessing population-wide trends of green turtles and other long-lived species. The best approach for monitoring population trends may be a combination of (1) extensive surveys to provide data for large-scale trends in relative population abundance, and (2) intensive surveys, using CMR techniques, to estimate absolute abundance and evaluate the demographic processes' driving the trends.

Offspring size effects mediate competitive interactions in a colonial marine invertebrate

Over the past 30 years, numerous attempts to understand the relationship between offspring size and fitness have been made, and it has become clear that this critical relationship is strongly affected by environmental heterogeneity. For marine invertebrates, there has been a long-standing interest in the evolution of offspring size, but there have been very few empirical and theoretical examinations of post-metamorphic offspring size effects, and almost none have considered the effect of environmental heterogeneity on the offspring size/fitness relationship. We investigated the post-metamorphic effects of offspring size in the field for the colonial marine invertebrate Botrylloides violaceus. We also examined how the relationship between offspring size and performance was affected by three different types of intraspecific competition. We found strong and persistent effects of offspring size on survival and growth, but these effects depended on the level and type of intraspecific competition.. Generally, competition strengthened the advantages of increasing maternal investment. Interestingly, we found that offspring size determined the outcome of competitive interaction: juveniles that had more maternal investment were more likely to encroach on another juvenile's territory. This suggests that mothers have the previously unrecognized potential to influence the outcome of competitive interactions in benthic marine invertebrates. We created a simple optimality model, which utilized the data generated from our field experiments, and found that increasing intraspecific competition resulted in an increase,in predicted optimal size. Our results suggest that the relationship between offspring size and fitness is highly variable in the marine environment and strongly dependent on the density of conspecifics.

Should managed populations be monitored every year?

We often need to estimate the size of wild populations to determine the appropriate management action, for example, to set a harvest quota. Monitoring is usually planned under the assumption that it must be carried out at fixed intervals in time, typically annually, before the harvest quota is set. However, monitoring can be very expensive, and we should weigh the cost of monitoring against the improvement that it makes in decision making. A less costly alternative to monitoring annually is to predict the population size using a population model and information from previous surveys. In this paper, the problem of monitoring frequency is posed within a decision-theory framework. We discover that a monitoring regime that varies according to the state of the system call outperform fixed-interval monitoring This idea is illustrated using data for a red kangaroo (Macropits rufus) population in South Australia. Whether or not one should monitor in a given year is dependent on the estimated population density in the previous year, the uncertainty in that population estimate, and past rainfall. We discover that monitoring is-important when a model-based prediction of population density is very uncertain. This may occur if monitoring has not taken place for several years, or if rainfall has been above average. Monitoring is also important when prior information suggests that the population is near a critical threshold in population abundance. However, monitoring is less important when the optimal management action would not be altered by new information.

The role of habitat disturbance and recovery in metapopulation persistence

Classical metapopulation theory assumes a static landscape. However, empirical evidence indicates many metapopulations are driven by habitat succession and disturbance. We develop a stochastic metapopulation model, incorporating habitat disturbance and recovery, coupled with patch colonization and extinction, to investigate the effect of habitat dynamics on persistence. We discover that habitat dynamics play a fundamental role in metapopulation dynamics. The mean number of suitable habitat patches is not adequate for characterizing the dynamics of the metapopulation. For a fixed mean number of suitable patches, we discover that the details of how disturbance affects patches and how patches recover influences metapopulation dynamics in a fundamental way. Moreover, metapopulation persistence is dependent not only oil the average lifetime of a patch, but also on the variance in patch lifetime and the synchrony in patch dynamics that results from disturbance. Finally, there is an interaction between the habitat and metapopulation dynamics, for instance declining metapopulations react differently to habitat dynamics than expanding metapopulations. We close, emphasizing the importance of using performance measures appropriate to stochastic systems when evaluating their behavior, such as the probability distribution of the state of the. metapopulation, conditional on it being extant (i.e., the quasistationary distribution).

Roost tree characteristics determine use by the white-striped freetail bat (Tadarida australis, Chiroptera : Molossidae) in suburban subtropical Brisbane, Australia

We examined factors affecting roost tree selection by the white-striped freetail bat Tadarida australis (Chiroptera: Molossidae), a large insectivorous bat in suburban Brisbane, Australia. We compared biophysical characteristics associated with 34 roost trees and 170 control trees of similar diameter, height and tree senescence characters. Roost trees used by the white-striped freetail bat had significantly higher numbers of hollows in the trunk and branches (P < 0.003) and were more likely to contain a large trunk cavity with an internal diameter of > 30 cm (P < 0.001) than control trees. These trees also accommodated more species of hollow-using fauna (P = 0.005). When comparing roost trees with control trees of similar diameters and heights, roost trees were on average at a later stage of tree senescence (P < 0.001). None of the roost trees were found in the large forest reserves fringing the Brisbane metropolitan area despite these areas being used for foraging by the white-striped freetail bat. Although all tree locations in this study were in modified landscapes, roost trees tended to be surrounded by groups of trees and undergrowth. Roost trees provide important habitat requirements for hollow-using fauna in suburban, rural and forested environments.