Integrating evolution into ecological modelling: accommodating phenotypic changes in agent based models.

PMCID: PMC3733718This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Evolutionary change is a characteristic of living organisms and forms one of the ways in which species adapt to changed conditions. However, most ecological models do not incorporate this ubiquitous phenomenon. We have developed a model that takes a 'phenotypic gambit' approach and focuses on changes in the frequency of phenotypes (which differ in timing of breeding and fecundity) within a population, using, as an example, seasonal breeding. Fitness per phenotype calculated as the individual's contribution to population growth on an annual basis coincide with the population dynamics per phenotype. Simplified model variants were explored to examine whether the complexity included in the model is justified. Outputs from the spatially implicit model underestimated the number of individuals across all phenotypes. When no phenotype transitions are included (i.e. offspring always inherit their parent's phenotype) numbers of all individuals are always underestimated. We conclude that by using a phenotypic gambit approach evolutionary dynamics can be incorporated into individual based models, and that all that is required is an understanding of the probability of offspring inheriting the parental phenotype

Extra-pair parentage and personality in a cooperatively breeding bird

Why so much variation in extra-pair parentage occurs within and among populations remains unclear. Often the fitness costs and benefits of extra-pair parentage are hypothesised to explain its occurrence; therefore, linking extra-pair parentage with traits such as personality (behavioural traits that can be heritable and affect reproductive behaviour) may help our understanding. Here, we investigate whether reproductive outcomes and success are associated with exploratory behaviour in a natural population of cooperatively breeding Seychelles warblers (Acrocephalus sechellensis) on Cousin Island. Exploratory behaviour correlates positively with traits such as risk-taking behaviour and activity in other wild bird species and might promote extra-pair mating by increasing the rate at which potential extra-pair partners are encountered. We therefore predicted that fast-exploring individuals would have more extra-pair offspring. There is also a potential trade-off between pursuing extra-pair parentage and mate guarding in males. We therefore also predicted that fast-exploring males would be more likely to pursue extra-pair parentage and that this would increase the propensity of their mate to gain extra-pair parentage. We found that neither the total number of offspring nor the number of extra-pair offspring were associated with a male’s or female’s exploratory behaviour. However, there was a small but significant propensity for females to have extra-pair fertilisations in pairs that were behaviourally disassortative. Overall, we conclude that, due to the small effect size, the association between exploratory behaviour and extra-pair paternity is unlikely to be biologically relevant. Significance statement: True genetic monogamy is rare, even in socially monogamous systems, and multiple factors, such as behaviour, social structure, morphology and physiology, determined by the biological system can cause variation in extra-pair parentage (EPP). Therefore, investigating the inherent differences in these factors among individuals could be informative. We investigated whether reproductive outcomes/success are associated with differences in the propensity to explore novel environments/objects in a promiscuous, island-dwelling cooperatively breeding bird, the Seychelles warbler. Our results showed that exploratory behaviour was not associated with the number of offspring produced by an individual, and thus the long-term fitness consequences of different exploratory tendencies did not differ. We also found that the propensity to engage in EPP in females was higher in dissimilar behavioural pairs, but due to the small effect size, we hesitate to conclude that there are personality-dependent mating outcomes in the population

Recent Shift in Climate Relationship Enables Prediction of the Timing of Bird Breeding

Large-scale climate processes influence many aspects of ecology including breeding phenology, reproductive success and survival across a wide range of taxa. Some effects are direct, for example, in temperate-zone birds, ambient temperature is an important cue enabling breeding effort to coincide with maximum food availability, and earlier breeding in response to warmer springs has been documented in many species. In other cases, time-lags of up to several years in ecological responses have been reported, with effects mediated through biotic mechanisms such as growth rates or abundance of food supplies. Here we use 23 years of data for a temperate woodland bird species, the great tit (Parus major), breeding in deciduous woodland in eastern England to demonstrate a time-lagged linear relationship between the on-set of egg laying and the winter index of the North Atlantic Oscillation such that timing can be predicted from the winter index for the previous year. Thus the timing of bird breeding (and, by inference, the timing of spring events in general) can be predicted one year in advance. We also show that the relationship with the winter index appears to arise through an abiotic time-lag with local spring warmth in our study area. Examining this link between local conditions and larger-scale processes in the longer-term showed that, in the past, significant relationships with the immediately preceding winter index were more common than those with the time-lagged index, and especially so from the late 1930s to the early 1970s. However, from the mid 1970s onwards, the time-lagged relationship has become the most significant, suggesting a recent change in climate patterns. The strength of the current time-lagged relationship suggests that it might have relevance for other temperature-dependent ecological relationships

Family history of Alzheimer's disease alters cognition and is modified by medical and genetic factors

In humans, a first-degree family history of dementia (FH) is a well-documented risk factor for Alzheimer’s disease (AD); however, the influence of FH on cognition across the lifespan is poorly understood. To address this issue, we developed an internet-based paired-associates learning (PAL) task and tested 59,571 participants between the ages of 18–85. FH was associated with lower PAL performance in both sexes under 65 years old. Modifiers of this effect of FH on PAL performance included age, sex, education, and diabetes. The Apolipoprotein E ε4 allele was also associated with lower PAL scores in FH positive individuals. Here we show, FH is associated with reduced PAL performance four decades before the typical onset of AD; additionally, several heritable and non-heritable modifiers of this effect were identified.publishedVersionCopyright Talboom et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credite

Common BACE2 Polymorphisms are Associated with Altered Risk for Alzheimer's Disease and CSF Amyloid Biomarkers in APOE ε4 Non-Carriers

It was recently suggested that beta-site amyloid precursor protein (APP)-cleaving enzyme 2 (BACE2) functions as an amyloid beta (Aβ)-degrading enzyme; in addition to its better understood role as an APP secretase. Due to this finding we sought to understand the possible genetic risk contributed by the BACE2 locus to the development of late-onset Alzheimer's disease (AD). In this study, we report that common single nucleotide polymorphism (SNP) variation in BACE2 is associated with altered AD risk in apolipoprotein E gene (APOE) epsilon 4 variant (ε4) non-carriers. In addition, in ε4 non-carriers diagnosed with AD or mild cognitive impairment (MCI), SNPs within the BACE2 locus are associated with cerebrospinal fluid (CSF) levels of Aβ1-42. Further, SNP variants in BACE2 are also associated with BACE2 RNA expression levels suggesting a potential mechanism for the CSF Aβ1-42 findings. Lastly, overexpression of BACE2 in vitro resulted in decreased Aβ1-40 and Aβ1-42 fragments in a cell line model of Aβ production. These findings suggest that genetic variation at the BACE2 locus modifies AD risk for those individuals who don't carry the ε4 variant of APOE. Further, our data indicate that the biological mechanism associated with this altered risk is linked to amyloid generation or clearance possibly through BACE2 expression changes

Climate change, phenological shifts, eco-evolutionary responses and population viability: toward a unifying predictive approach

The debate on emission targets of greenhouse gasses designed to limit global climate change has to take into account the ecological consequences. One of the clearest ecological consequences is shifts in phenology. Linking these shifts to changes in population viability under various greenhouse gasses emission scenarios requires a unifying framework. We propose a box-in-a-box modeling approach that couples population models to phenological change. This approach unifies population modeling with both ecological responses to climate change as well as evolutionary processes. We advocate a mechanistic embedded correlative approach, where the link from genes to population is established using a periodic matrix population model. This periodic model has several major advantages: (1) it can include complex seasonal behaviors allowing an easy link with phenological shifts; (2) it provides the structure of the population at each phase, including the distribution of genotypes and phenotypes, allowing a link with evolutionary processes; and (3) it can incorporate the effect of climate at different time periods. We believe that the way climatologists have approached the problem, using atmosphere–ocean coupled circulation models in which components are gradually included and linked to each other, can provide a valuable example to ecologists. We hope that ecologists will take up this challenge and that our preliminary modeling framework will stimulate research toward a unifying predictive model of the ecological consequences of climate change

Climate-induced phenology shifts linked to range expansions in species with multiple reproductive cycles per year

Advances in phenology (the annual timing of species’ life-cycles) in response to climate change are generally viewed as bioindicators of climate change, but have not been considered as predictors of range expansions. Here, we show that phenology advances combine with the number of reproductive cycles per year (voltinism) to shape abundance and distribution trends in 130 species of British Lepidoptera, in response to ~0.5 °C spring-temperature warming between 1995 and 2014. Early adult emergence in warm years resulted in increased within- and between-year population growth for species with multiple reproductive cycles per year (n = 39 multivoltine species). By contrast, early emergence had neutral or negative consequences for species with a single annual reproductive cycle (n = 91 univoltine species), depending on habitat specialisation. We conclude that phenology advances facilitate polewards range expansions in species exhibiting plasticity for both phenology and voltinism, but may inhibit expansion by less flexible species

Predation Danger Can Explain Changes in Timing of Migration: The Case of the Barnacle Goose

Understanding stopover decisions of long-distance migratory birds is crucial for conservation and management of these species along their migratory flyway. Recently, an increasing number of Barnacle geese breeding in the Russian Arctic have delayed their departure from their wintering site in the Netherlands by approximately one month and have reduced their staging duration at stopover sites in the Baltic accordingly. Consequently, this extended stay increases agricultural damage in the Netherlands. Using a dynamic state variable approach we explored three hypotheses about the underlying causes of these changes in migratory behavior, possibly related to changes in (i) onset of spring, (ii) potential intake rates and (iii) predation danger at wintering and stopover sites. Our simulations showed that the observed advance in onset of spring contradicts the observed delay of departure, whereas both increased predation danger and decreased intake rates in the Baltic can explain the delay. Decreased intake rates are expected as a result of increased competition for food in the growing Barnacle goose population. However, the effect of predation danger in the model was particularly strong, and we hypothesize that Barnacle geese avoid Baltic stopover sites as a response to the rapidly increasing number of avian predators in the area. Therefore, danger should be considered as an important factor influencing Barnacle goose migratory behavior, and receive more attention in empirical studies

A Visual Data Mining Tool that Facilitates Reconstruction of Transcription Regulatory Networks

Background: Although the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators. One difficulty lies in the interpretation of a list of differentially expressed genes, or in how to plan new experiments given that knowledge. Clustering methods can be used to identify groups of genes with similar expression patterns, and genes with unknown function can be provisionally annotated based on the concept of ‘‘guilt by association’’, where function is tentatively inferred from the known functions of genes with similar expression patterns. These methods frequently suffer from two limitations: (1) visualization usually only gives access to group membership, rather than specific information about nearest neighbors, and (2) the resolution or quality of the relationships are not easily inferred. Methodology/Principal Findings: We have addressed these issues by improving the precision of similarity detection over that of a single experiment and by creating a tool to visualize tractable association networks: we (1) performed metaanalysis computation of correlation coefficients for all gene pairs in a heterogeneous data set collected from 2,145 publicly available micorarray samples in mouse, (2) filtered the resulting distribution of over 130 million correlation coefficients to build new, more tractable distributions from the strongest correlations, and (3) designed and implemented a new Web based tool (StarNet