Applying a mechanistic model to predict interacting effects of chemical exposure and food availability on fish populations.

The potential environmental impacts of chemical exposures on wildlife are of growing concern. Freshwater ecosystems are vulnerable to chemical effects and wildlife populations, including fish, can be exposed to concentrations known to cause adverse effects at the individual level. Wild fish populations are also often subjected to numerous other stressors simultaneously which in temperate climates often include sustained periods of food limitation. The potential interactive effects of chemical exposures and food limitation on fish populations are however difficult to establish in the field. Mechanistic modelling approaches can be employed to help predict how the physiological effects of chemicals and food limitation on individuals may translate to population-level effects. Here an energy budget-individual-based model was developed and the control (no chemical) model was validated for the three-spined stickleback. Findings from two endocrine active chemical (EAC) case studies, (ethinyloestradiol and trenbolone) were then used to investigate how effects on individual fecundity translated into predicted population-level effects for environmentally relevant exposures. The cumulative effects of chemical exposure and food limitation were included in these analyses. Results show that effects of each EAC on the population were dependent on energy availability, and effects on population abundance were exacerbated by food limitation. Findings suggest that chemical effects and density dependent food competition interact to determine population responses to chemical exposures. Our study illustrates how mechanistic modelling approaches might usefully be applied to account for specific chemical effects, energy budgets and density-dependent competition, to provide a more integrated evaluation of population outcomes in chemical risk assessments.

Assessing pesticide risks to threatened and endangered species using population models: Findings and recommendations from a CropLife America Science Forum.

This brief communication reports on the main findings and recommendations from the 2014 Science Forum organized by CropLife America. The aim of the Forum was to gain a better understanding of the current status of population models and how they could be used in ecological risk assessments for threatened and endangered species potentially exposed to pesticides in the United States. The Forum panelists' recommendations are intended to assist the relevant government agencies with implementation of population modeling in future endangered species risk assessments for pesticides. The Forum included keynote presentations that provided an overview of current practices, highlighted the findings of a recent National Academy of Sciences report and its implications, reviewed the main categories of existing population models and the types of risk expressions that can be produced as model outputs, and provided examples of how population models are currently being used in different legislative contexts. The panel concluded that models developed for listed species assessments should provide quantitative risk estimates, incorporate realistic variability in environmental and demographic factors, integrate complex patterns of exposure and effects, and use baseline conditions that include present factors that have caused the species to be listed (e.g., habitat loss, invasive species) or have resulted in positive management action. Furthermore, the panel advocates for the formation of a multipartite advisory committee to provide best available knowledge and guidance related to model implementation and use, to address such needs as more systematic collection, digitization, and dissemination of data for listed species; consideration of the newest developments in good modeling practice; comprehensive review of existing population models and their applicability for listed species assessments; and development of case studies using a few well-tested models for particular species to demonstrate proof of concept. To advance our common goals, the panel recommends the following as important areas for further research and development: quantitative analysis of the causes of species listings to guide model development; systematic assessment of the relative role of toxicity versus other factors in driving pesticide risk; additional study of how interactions between density dependence and pesticides influence risk; and development of pragmatic approaches to assessing indirect effects of pesticides on listed species.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides.

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

Selfishness and altruism can coexist when help is subject to diminishing returns.

Altruism and selfishness are 30-50% heritable in man in both Western and non-Western populations. This genetically based variation in altruism and selfishness requires explanation. In non-human animals, altruism is generally directed towards relatives, and satisfies the condition known as Hamilton's rule. This nepotistic altruism evolves under natural selection only if the ratio of the benefit of receiving help to the cost of giving it exceeds a value that depends on the relatedness of the individuals involved. Standard analyses assume that the benefit provided by each individual is the same but it is plausible in some cases that as more individuals contribute, help is subject to diminishing returns. We analyse this situation using a single-locus two-allele model of selection in a diploid population with the altruistic allele dominant to the selfish allele. The analysis requires calculation of the relationship between the fitnesses of the genotypes and the frequencies of the genes. The fitnesses vary not only with the genotype of the individual but also with the distribution of phenotypes amongst the sibs of the individual and this depends on the genotypes of his parents. These calculations are not possible by direct fitness or ESS methods but are possible using population genetics. Our analysis shows that diminishing returns change the operation of natural selection and the outcome can now be a stable equilibrium between altruistic and selfish alleles rather than the elimination of one allele or the other. We thus provide a plausible genetic model of kin selection that leads to the stable coexistence in the same population of both altruistic and selfish individuals. This may explain reported genetic variation in altruism in man.

Case Study Part 2: Probabilistic modelling of long-term effects of pesticides on individual breeding success in birds and mammals.

Long term exposure of skylarks to a fictitious insecticide and of wood mice to a fictitious fungicide were modelled probabilistically in a Monte Carlo simulation. Within the same simulation the consequences of exposure to pesticides on reproductive success were modelled using the toxicity-exposure-linking rules developed by R.S. Bennet et al. (2005) and the interspecies extrapolation factors suggested by R. Luttik et al. (2005). We built models to reflect a range of scenarios and as a result were able to show how exposure to pesticide might alter the number of individuals engaged in any given phase of the breeding cycle at any given time and predict the numbers of new adults at the season's end.

Case Study Part 1: How to calculate appropriate deterministic long-term toxicity to exposure ratios (TERs) for birds and mammals.

In the European Union, first-tier assessment of the long-term risk to birds and mammals from pesticides is based on calculation of a deterministic long-term toxicity/exposure ratio (TER(lt)). The ratio is developed from generic herbivores and insectivores and applied to all species. This paper describes two case studies that implement proposed improvements to the way long-term risk is assessed. These refined methods require calculation of a TER for each of five identified phases of reproduction (phase-specific TERs) and use of adjusted No Observed Effect Levels (NOELs) to incorporate variation in species sensitivity to pesticides. They also involve progressive refinement of the exposure estimate so that it applies to particular species, rather than generic indicators, and relates spraying date to onset of reproduction. The effect of using these new methods on the assessment of risk is described. Each refinement did not necessarily alter the calculated TER value in a way that was either predictable or consistent across both case studies. However, use of adjusted NOELs always reduced TERs, and relating spraying date to onset of reproduction increased most phase-specific TERs. The case studies suggested that the current first-tier TER(lt )assessment may underestimate risk in some circumstances and that phase-specific assessments can help identify appropriate risk-reduction measures. The way in which deterministic phase-specific assessments can currently be implemented to enhance first-tier assessment is outlined.

Population-level assessment of risks of pesticides to birds and mammals in the UK.

It is generally acknowledged that population-level assessments provide a better measure of response to toxicants than assessments of individual-level effects. Population-level assessments generally require the use of models to integrate potentially complex data about the effects of toxicants on life-history traits, and to provide a relevant measure of ecological impact. Building on excellent earlier reviews we here briefly outline the modelling options in population-level risk assessment. Modelling is used to calculate population endpoints from available data, which is often about individual life histories, the ways that individuals interact with each other, the environment and other species, and the ways individuals are affected by pesticides. As population endpoints, we recommend the use of population abundance, population growth rate, and the chance of population persistence. We recommend two types of model: simple life-history models distinguishing two life-history stages, juveniles and adults; and spatially-explicit individual-based landscape models. Life-history models are very quick to set up and run, and they provide a great deal of insight. At the other extreme, individual-based landscape models provide the greatest verisimilitude, albeit at the cost of greatly increased complexity. We conclude with a discussion of the implications of the severe problems of parameterising models.

Risk assessment of UK skylark populations using life-history and individual-based landscape models.

Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al. (2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

Effects of stone chewing by outdoor sows on their teeth and stomachs.

Stone chewing is a common behaviour in outdoor sows, but its effects on their teeth and stomachs have not been investigated. Tooth wear and damage was assessed by examining the heads of 58 sows culled from outdoor units and 23 culled from indoor units. Tooth damage was found in 28 per cent of outdoor and 30 per cent of the indoor sows, and tooth wear affected 88 per cent of the outdoor and 91 per cent of the indoor sows. The outdoor sows were more prone to wear on the lower molars and premolars, a pattern of wear associated with stone chewing. The stomachs of 152 outdoor sows and 47 indoor sows were examined. Stones were found in 59 of the outdoor sows but in none of those kept indoors. There was no evidence that the presence of stones damaged the stomach, or that stone chewing affected the health of the sows. The teeth of the outdoor sows were worn, but probably not sufficiently to affect their ability to eat during their relatively short productive lives.

Are current species extrapolation models a good basis for ecological risk assessment?

Extrapolating the effects of toxicants with either the fixed application factor approach or one of the species sensitivity distribution models currently in widespread use presumes that toxicant effects on single, individual-level endpoints (e.g., survival, fecundity, and growth) reflect effects at the population level. Here, we consider if extrapolations derived on the basis of individual-level endpoints might be misleading with regard to risk assessment and, hence, risk management decisions for ecosystems. Both analytically and by simulation, we demonstrate that for populations with multiplication rates close to one, effects of toxicants at the population level likely are less than or equal to effects on individual life-cycle traits, suggesting that risk assessments based on the latter likely are protective of population-level impacts. We used Monte Carlo simulations to explore how both the frequency of different life-cycle types in a community as well as their relative sensitivity to toxicants influence the toxicant sensitivity distribution of the community as a whole. We compared the output of our simulations with predicted no-effect concentrations derived by an application factor approach and a log-normal distribution-based model, using no-observed-effect concentrations for juvenile survival as input variables in both cases. Our analyses suggest that current extrapolation approaches appear to be protective, and may often be very overprotective, but we have identified conditions in which this may not be the case. We recommend that additional consideration be given to the relative frequency of different life-cycle types, to the proportions of sensitive and insensitive taxonomic groups in communities, and to the role of density-dependent influences on population dynamics to ensure that we develop environmental quality criteria that are sufficiently--but not overly--protective.

A maximum-likelihood approach to fitting equilibrium models of microsatellite evolution.

Here, we develop a new approach to Markov chain modeling of microsatellite evolution through polymerase slippage and introduce new models: a "constant-slippage-rate" model, in which there is no dependence of slippage rate on microsatellite length, as envisaged by Moran; and a "linear-with-constant" model, in which slippage rate increases linearly with microsatellite length, but the line of best fit is not constrained to go through the origin. We show how these and a linear no-constant model can be fitted to data hierarchically using maximum likelihood. This has advantages over previous methods in allowing statistical comparisons between models. When applied to a previously analyzed data set, the method allowed us to statistically establish that slippage rate increases with microsatellite length for dinucleotide microsatellites in humans, mice, and fruit flies, and suggested that no slippage occurs in very short microsatellites of one to four repeats. The suggestion that slippage rates are zero or close to zero for very short microsatellites of one to four repeats has important implications for understanding the mechanism of polymerase slippage.

Why are organisms usually bigger in colder environments? Making sense of a life history puzzle.

Environmental effects on body size are of widespread ecological and economic importance but our understanding of these effects has been obscured by an apparent paradox. Life history analysis suggests that it is adaptive for adults to emerge smaller if reared in conditions that slow down juvenile growth. However, whereas smaller adults emerge if growth is limited by food availability, the reverse is usually observed if growth is limited by temperature. The resolution of this apparent paradox may be that the response of adult size to temperature is adaptive, but is constrained by a trade-off that can be understood in terms of von Bertalanffy's classic theory of growth. Alternatively, the response may be the unavoidable consequence of a fundamental relationship between cell size and temperature.

Estimation of the weight and body condition of ostriches (Struthio camelus) from body measurements.

The body dimensions and weights of over 100 ostriches were analysed to investigate which body measurements provided the best estimators of bodyweight. The data were divided between growing and adult birds (below and above two years old) for regression analyses. The residual standard deviation of weight was 0.117 for growing birds, using tibiotarsal length and abdominal girth as predictors. The analogous figure for adults was 0.078 using back length and abdominal girth. An assessment of body condition was made by calculating the average weight-for-size of a bird from skeletal measurements which are unaffected by gross changes in weight, and then comparing it with its estimated or actual weight. These estimates of the weight of a typical ostrich should be useful in veterinary practice, particularly when the weight of a bird is required for the administration of medication.

Time budget and colour preferences (with specific reference to feeding) of ostrich (Struthio camelus) chicks in captivity.

1. Time budget analysis of the typical behaviours of young ostrich chicks showed that chicks spent over 50% of their time foraging and walking. 2. Food presented in bowls was largely ignored whereas food scattered on the floor was readily taken. 3. A colour preference test showed that green was the preferred colour.

An allelocentric view of life-history evolution.

For the case of weak selection, random assortment of gametes, and density-independent population regulation, we here establish the conditions under which an allele will spread in a population, with particular reference to the life-history effects of the allele, its level of dominance, and sex differences in its effects. Our treatment is simpler than that of Charlesworth (1980), but the results are essentially the same. We show that two quantities govern the selective dynamics of a two-allele single-locus system; these are level of dominance, and the difference between the per copy rates of increase of the alleles in homozygous populations. Our main conclusion is that the eventual outcome of evolution is unaffected by an allele's level of dominance, or sex differences in its effects, provided there is no overdominance. However, speed of progress to fixation is, of course, affected by these factors, and equations are derived to show how level of dominance affects speed of progress to fixation. When a dominant allele only affects the life history of one sex, its rate of spread is half that if both sexes are affected. The relationship between actual and intrinsic rates of increase is discussed and formulae are given showing the relationship for the case of weak selection.

Testing life-cycle theory by computer simulation--I. Introduction of genetical structure.

Computer simulation was used to relax assumptions of analytical life-cycle theory about the eventual outcome of evolution in a constant environment. The computer simulation models, of diploid one-locus genetic systems, are described in detail. Good agreement was obtained between the analytical and simulation outcomes, except in some cases of discrepancy between the male and female life cycles.

Testing life-cycle theory by computer simulation--II. Bet-hedging revisited.

Analytical and computer models were used to reexamine bet-hedging, the reduction in fecundity that is evolutionarily advantageous in conditions of greater variation in juvenile survivorship or less variation in adult survivorship. The computer simulation models represent diploid one-locus genetic systems with semidominance. Schaffer's (1974) predictions proved remarkably robust when variations were symmetrical, and a simple modification allowed successful prediction for the asymmetries that occurred in the computer simulations when variations were large.

Gas diffusion through non-tubular pores.

An equation is derived for quantifying the diffusion of gases through the funnel-shaped pores of eggshells. Calculations based on this approach indicate that diffusion in such pores is largely determined by the inner pore radius and that the thickness of the eggshell and its cuticle are relatively unimportant. The approach is extended to include other noncylindrical pores.