Disentangling plastic and genetic changes in body mass of Siberian jays

Spatial and temporal phenotypic differentiation in mean body size is of commonplace occurrence, but the underlying causes remain often unclear: both genetic differentiation in response to selection (or drift) and environmentally induced plasticity can create similar phenotypic patterns. Studying changes in body mass in Siberian jays (Perisoreus infaustus) over three decades, we discovered that mean body mass declined drastically (ca. 10%) over the first two decades, but increased markedly thereafter back to almost the initial level. Quantitative genetic analyses revealed that although body mass was heritable (h² = 0.46), the pronounced temporal decrease in body mass was mainly a product of phenotypic plasticity. However, a concomitant and statistically significant decrease in predicted breeding values suggests a genetic component to this change. The subsequent increase in mean body mass was indicated to be entirely due to plasticity. Selection on body mass was estimated to be too weak to fully account for the observed genetic decline in body mass, but bias in selection differential estimates due to environmental covariance between body mass and fitness is possible. Hence, the observed body mass changes appear to be driven mainly by phenotypic plasticity. Although we were not able to identify the ecological driver of the observed plastic changes, the results highlight the utility of quantitative genetic approaches in disentangling genetic and phenotypic changes in natural populations.     

How predator functional responses and Allee effects in prey affect the paradox of enrichment and population collapses

In Rosenzweig-MacArthur models of predator-prey dynamics, Allee effects in prey usually destabilize interior equilibria and can suppress or enhance limit cycles typical of the paradox of enrichment. We re-evaluate these conclusions through a complete classification of a wide range of Allee effects in prey and predator's functional response shapes. We show that abrupt and deterministic system collapses not preceded by fluctuating predator-prey dynamics occur for sufficiently steep type III functional responses and strong Allee effects (with unstable lower equilibrium in prey dynamics). This phenomenon arises as type III functional responses greatly reduce cyclic dynamics and strong Allee effects promote deterministic collapses. These collapses occur with decreasing predator mortality and/or increasing susceptibility of the prey to fall below the threshold Allee density (e.g. due to increased carrying capacity or the Allee threshold itself). On the other hand, weak Allee effects (without unstable equilibrium in prey dynamics) enlarge the range of carrying capacities for which the cycles occur if predators exhibit decelerating functional responses. We discuss the results in the light of conservation strategies, eradication of alien species, and successful introduction of biocontrol agents.     

Untangling associations between chironomid taxa in Neotropical streams using local and landscape filters

1. Analyses of species association have major implications for selecting indicators for freshwater biomonitoring and conservation, because they allow for the elimination of redundant information and focus on taxa that can be easily handled and identified. These analyses are particularly relevant in the debate about using speciose groups (such as the Chironomidae) as indicators in the tropics, because they require difficult and time‐consuming analysis, and their responses to environmental gradients, including anthropogenic stressors, are poorly known. 2. Our objective was to show whether chironomid assemblages in Neotropical streams include clear associations of taxa and, if so, how well these associations could be explained by a set of models containing information from different spatial scales. For this, we formulated a priori models that allowed for the influence of local, landscape and spatial factors on chironomid taxon associations (CTA). These models represented biological hypotheses capable of explaining associations between chironomid taxa. For instance, CTA could be best explained by local variables (e.g. pH, conductivity and water temperature) or by processes acting at wider landscape scales (e.g. percentage of forest cover). 3. Biological data were taken from 61 streams in Southeastern Brazil, 47 of which were in well‐preserved regions, and 14 of which drained areas severely affected by anthropogenic activities. We adopted a model selection procedure using Akaike’s information criterion to determine the most parsimonious models for explaining CTA. 4. Applying Kendall’s coefficient of concordance, seven genera (Tanytarsus/Caladomyia, Ablabesmyia, Parametriocnemus, Pentaneura, Nanocladius, Polypedilum and Rheotanytarsus) were identified as associated taxa. The best‐supported model explained 42.6% of the total variance in the abundance of associated taxa. This model combined local and landscape environmental filters and spatial variables (which were derived from eigenfunction analysis). However, the model with local filters and spatial variables also had a good chance of being selected as the best model. 5. Standardised partial regression coefficients of local and landscape filters, including spatial variables, derived from model averaging allowed an estimation of which variables were best correlated with the abundance of associated taxa. In general, the abundance of the associated genera tended to be lower in streams characterised by a high percentage of forest cover (landscape scale), lower proportion of muddy substrata and high values of pH and conductivity (local scale). 6. Overall, our main result adds to the increasing number of studies that have indicated the importance of local and landscape variables, as well as the spatial relationships among sampling sites, for explaining aquatic insect community patterns in streams. Furthermore, our findings open new possibilities for the elimination of redundant data in the assessment of anthropogenic impacts on tropical streams.     

Inference of Gene Flow between Species under Misspecified Models

Genomic sequence data provide a rich source of information about the history of species divergence and interspecific hybridization or introgression. Despite recent advances in genomics and statistical methods, it remains challenging to infer gene flow, and as a result, one may have to estimate introgression rates and times under misspecified models. Here we use mathematical analysis and computer simulation to examine estimation bias and issues of interpretation when the model of gene flow is misspecified in analysis of genomic datasets, for example, if introgression is assigned to the wrong lineages. In the case of two species, we establish a correspondence between the migration rate in the continuous migration model and the introgression probability in the introgression model. When gene flow occurs continuously through time but in the analysis is assumed to occur at a fixed time point, common evolutionary parameters such as species divergence times are surprisingly well estimated. However, the time of introgression tends to be estimated towards the recent end of the period of continuous gene flow. When introgression events are assigned incorrectly to the parental or daughter lineages, introgression times tend to collapse onto species divergence times, with introgression probabilities underestimated. Overall, our analyses suggest that the simple introgression model is useful for extracting information concerning between-specific gene flow and divergence even when the model may be misspecified. However, for reliable inference of gene flow it is important to include multiple samples per species, in particular, from hybridizing species.     

Mathematical model of fructan biosynthesis and polymer length distribution in plants

Background and Aims

There are many unresolved issues concerning the biochemistry of fructan biosynthesis. The aim of this paper is to address some of these by means of modelling mathematically the biochemical processes.

Methods

A model has been constructed for the step-by-step synthesis of fructan polymers. This is run until a steady state is achieved for which a polymer distribution is predicted. It is shown how qualitatively different distributions can be obtained.

Key Results

It is demonstrated how a set of experimental results on polymer distribution can by simulated by a simple parameter adjustments.

Conclusions

Mathematical modelling of fructan biosynthesis can provide a useful tool for helping elucidate the details of the biosynthetic processes.     

Proteins searching for their target on DNA by one-dimensional diffusion: overcoming the “speed-stability” paradox

The sequence dependence of DNA-protein interactions that allows proteins to find the correct reaction site also slows down the 1D diffusion of the protein along the DNA molecule, leading to the so-called “speed-stability paradox,” wherein fast diffusion along the DNA molecule is seemingly incompatible with stable targeting of the reaction site. Here, we develop diffusion-reaction models that use discrete and continuous Gaussian random 1D diffusion landscapes with or without a high-energy cut-off, and two-state models with a transition to and from a “searching” mode in which the protein diffuses rapidly without recognizing the target. We show the conditions under which such considerations lead to a predicted speed-up of the targeting process, and under which the presence of a “searching” mode in a two-state model is nearly equivalent to the existence of a high-energy cut-off in a one-state model. We also determine the conditions under which the search is either diffusion-limited or reaction-limited, and develop quantitative expressions for the rate of successful targeting as a function of the site-specific reaction rate, the roughness of the DNA-protein interaction potential, and the presence of a “searching” mode. In general, we find that a rough landscape is compatible with a fast search if the highest energy barriers can be avoided by “hopping” or by the protein transitioning to a lower-energy “searching” mode. We validate these predictions with the results of Brownian dynamics, kinetic Metropolis, and kinetic Monte Carlo simulations of the diffusion and targeting process, and apply these concepts to the case of T7 RNA polymerase searching for its target site on T7 DNA.     

Composite analysis of black duck breeding population surveys in eastern North America

Waterfowl are monitored in eastern Canada and the northeastern United States with 2 surveys: a transect survey from fixed-wing aircraft and a plot survey conducted from helicopters. The surveys vary in extent, but overlap exists in a core area of 9 strata covering portions of all provinces from Ontario east to Newfoundland. We estimated population change for American black ducks (Anas rubripes) and mallards (Anas platyrhynchos) from these surveys using a log-linear hierarchical model that accommodates differences in sample design and visibility associated with these survey methods. Using a combined analysis of the surveys based on total indicated birds, we estimate the American black duck population to be 901,700 (95% CI: 715,200–1,274,000) in 2011, with 526,900 (95% CI: 357,500–852,300) mallards in the surveyed area. Precision of estimates varies widely by species and region, with transect surveys providing less precise results than plot surveys for black ducks in areas of overlap. The combined survey analysis for black ducks in the eastern survey region produced estimates with an average yearly coefficient of variation (CV) of 12.1% for the entire area and an average CV of 6.9% in the plot survey area. Mallards, which had a more limited distribution in the region, had an average yearly CV of 22.1% over the entire region, and an average CV of 27.7% in the plot survey area. Hierarchical models provide a rich framework for analyzing and combining results from complex survey designs, providing useful spatial and temporal information on population size and change in these economically important species. © 2012 The Wildlife Society.