Albatross populations in peril: a population trajectory for black-browed albatrosses at south Georgia.

Simulation modeling was used to reconstruct Black-browed Albatross (Diomedea melanophris) population trends. Close approximations to observed data were accomplished by annually varying survival rates, reproductive success, and probabilities of returning to breed given success in previous years. The temporal shift in annual values coincided with the start of longline fishing at South Georgia and potential changes in krill abundance. We used 23 years of demographic data from long-term studies of a breeding colony of this species at Bird Island, South Georgia, to validate our model. When we used annual parameter estimates for survival, reproductive success, and probabilities of returning to breed given success in previous years, our model trajectory closely followed the observed changes in breeding population size over time. Population growth rate was below replacement (lambda < 1) in most years and was most sensitive to changes in adult survival. This supports the recent IUCN uplisting of this species from "Vulnerable" to "Endangered." Comparison of pre-1988 and post-1988 demography (before and after the inception of a longline fishery in the breeding area) reveals a decrease in lambda from 0.963 to 0.910. A life table response experiment (LTRE) showed that this decline in lambda was caused mostly by declines in survival of adults. If 1988-1998 demographic rates are maintained, the model predicts a 98% chance of a population of fewer than 25 pairs within 78 years. For this population to recover to a status under which it could be "delisted," a 10% increase in survival of all age classes would be needed.     

Population level risk assessment: practical considerations for evaluation of population models from a risk assessor's perspective

Population models are increasingly being considered as a tool for pesticide risk assessment in order to evaluate how potential effects act on the population level and population recovery. While the importance and difficulties of such models have been discussed by various authors during the past decade, mainly with a focus on how to describe or develop such models, several biological and methodological aspects have never been addressed so far, which are relevant for the application of models in risk assessment. These include a critical review of our knowledge of a species, the use of field data by taking methodological constraints into account, how to include uncertainty in model validation or how to measure effects. Although these aspects will be critical for the acceptance of population models by authorities, most of them apply not only to population models, but also to standard risk assessment. In the present article, we give practical recommendations for addressing these questions in population level risk assessments.     

Trade-offs between time, predation risk and life history, and their implications for biogeography: A systems modelling approach with a primate case study

Group sizes are often considered to be the result of a trade-off between predation risk and the costs of feeding competition. We develop a model to explore the interaction between different ecological constraints on group sizes, using a primate (baboons) case study. The model uses climatic correlates of time budgets to predict maximum ecologically tolerable group size, and climatic predictors of predation risk (reflected mainly in predator density and female body mass) to predict minimum tolerable group size for any given habitat. As well as defining the range of sustainable group sizes for a given habitat, the model also allows us to reliably predict our exemplar taxon's biogeographical distribution across Africa. We also explore the life history implications of the model to ask whether baboons form group sizes which maximise survival or fecundity in the classic trade off between these two key life history variables. Our results indicate that, within the range of study sites in our sample, baboons prefer to maximise fecundity. However, the data indicate that in higher predation risk habitats they would switch to maximising survival at the expense of fecundity. We argue that this is due to the fact that interbirth interval and developmental rates have a ceiling that cannot be breached. Thus, while females can shorten interbirth intervals to compensate for increased predation risk, there is a limit to how much these life history variables can be altered, and when this is reached the best strategy is to maximise survivorship.