Adaptive variation of pelage color within and between species of the subterranean mole rat (Spalax ehrenbergi) in Israel

Summary Color notations of dorsal pelage were analyzed in 451 adult subterranean mole rats, comprising 19 populations and 4 chromosomal species (2n=52, 54, 58 and 60) of the Spalax ehrenbergi superspecies in Israel. In addition, the color notations of soil samples from the collection sites were measured. In an attempt to evaluate the degree of correlation between pelage color of mole rats and the local soil color, each color was compared both macro- and microgeographically. The macrogeographic comparisons were among populations of the 4 chromosomal species, and the microgeographic comparisons were among pairs of geographically neighboring subpopulations which occur under similar climatic conditions but differ in soil type and color. The results indicate that 1. no differences in pelage color notation exist between the sexes; 2. pelage of mole rats is generally characterized by an over-all grayish color, but its shades vary regionally and locally in accordance with varying soil color; 3. a positive correlation was found between pelage and local soil colors in the macrogeographic analysis and this correlation was verified in a microgeographic comparison; 4. specimens from populations of the northern chromosomal species (2n=52, 54) mainly inhabit terra rossa and basalt soils, respectively, with reddish brown tones, and they tend to have a more reddish shade, whereas animals from the central species (2n=58), which inhabits mainly dark soils including alluvial clays, terra rossa and brown rendzina and the souther species 2n=60, which occurs mainly in light soil types such as pale rendzina, sandy loams and loess, tend to have a more yellowish shade. The general appearance of specimens from 2n=58 was dark gray while that of 2n=60 specimens was light gray; 5. mole rats living in xeric environments (particularly 2n=60, but also 2n=54) are lighter than those which live in mesic environments (2n=52, 58). The results support the conclusion that pelage color of strictly subterranean mole rats is subject to selection pressures of overground predation of disharmonious types with their background soil color. The possibility that the pelage color variation and patterns also contributes to better thermoregulation while mole rats are above ground is discussed.     

ADAPTIVE DIVERGENCE BETWEEN FRESHWATER AND MARINE STICKLEBACKS: INSIGHTS INTO THE ROLE OF PHENOTYPIC PLASTICITY FROM AN INTEGRATED ANALYSIS OF CANDIDATE GENE EXPRESSION

Debate surrounding the integration of phenotypic plasticity within the neo‐Darwinian paradigm has recently intensified, but is largely dominated by conceptual abstractions. Advances in our capacities to identify candidate genes, and quantify their levels of expression, now facilitate the study of natural variation in inherently plastic traits, and may lead to a more concrete understanding of plasticity's role in adaptive evolution. We present data from parapatric threespine stickleback (Gasterosteus aculeatus) demes inhabiting geologically recent, freshwater and saltwater zones of a large estuary. Reaction norms for survival confirm adaptation to local salinity conditions. Analysis of osmoregulatory candidate gene expression within an ecological quantitative genetics framework suggests putative mechanisms underlying adaptive variation, and provides insights into the role of ancestral trait plasticity in this divergence. A sodium–potassium ATPase (ATP1A1) is identified as a candidate gene for freshwater adaptation. In addition to heritable variation for gene expression, we infer significant correlation between measures of expression and individual fitness. Overall results indicate a loss of plasticity in the freshwater deme. We discuss how this is consistent with adaptation facilitated by ancestral plasticity as a heuristic example that may prove useful for future, explicit tests of the genetic assimilation hypothesis.     

A latent contingency table approach to dose finding for combinations of two agents

Summary .  Two-agent combination trials have recently attracted enormous attention in oncology research. There are several strong motivations for combining different agents in a treatment: to induce the synergistic treatment effect, to increase the dose intensity with nonoverlapping toxicities, and to target different tumor cell susceptibilities. To accommodate this growing trend in clinical trials, we propose a Bayesian adaptive design for dose finding based on latent 2 × 2 tables. In the search for the maximum tolerated dose combination, we continuously update the posterior estimates for the unknown parameters associated with marginal probabilities and the correlation parameter based on the data from successive patients. By reordering the dose toxicity probabilities in the two-dimensional space, we assign each coming cohort of patients to the most appropriate dose combination. We conduct extensive simulation studies to examine the operating characteristics of the proposed method under various practical scenarios. Finally, we illustrate our dose-finding procedure with a clinical trial of agent combinations at M. D. Anderson Cancer Center.     

Emergence of complexity in evolving niche-model food webs

We have analysed mechanisms that promote the emergence of complex structures in evolving model food webs. The niche model is used to determine predator-prey relationships. Complexity is measured by species richness as well as trophic level structure and link density. Adaptive dynamics that allow predators to concentrate on the prey species they are best adapted to lead to a strong increase in species number but have only a small effect on the number and relative occupancy of trophic levels. The density of active links also remains small but a high number of potential links allows the network to adjust to changes in the species composition (emergence and extinction of species). Incorporating effects of body size on individual metabolism leads to a more complex trophic level structure: both the maximum and the average trophic level increase. So does the density of active links. Taking body size effects into consideration does not have a measurable influence on species richness. If species are allowed to adjust their foraging behaviour, the complexity of the evolving networks can also be influenced by the size of the external resources. The larger the resources, the larger and more complex is the food web it can sustain. Body size effects and increasing resources do not change size and the simple structure of the evolving networks if adaptive foraging is prohibited. This leads to the conclusion that in the framework of the niche model adaptive foraging is a necessary but not sufficient condition for the emergence of complex networks. It is found that despite the stabilising effect of foraging adaptation the system displays elements of self-organised critical behaviour.     

A model for the evolutionary dynamics of cross-feeding polymorphisms in microorganisms

 Understanding mechanisms of evolutionary diversification is central to evolutionary biology. Microbes constitute promising model systems for observing processes of diversification directly in the laboratory. One of the main existing paradigms for microbial diversification is the evolution of cross-feeding polymorphisms, in which a strain specializing on a primary resource coexists with a cross-feeding strain that specializes on a waste product resulting from consumption of the primary resource. Here I propose a theoretical model for the evolutionary dynamics through which cross-feeding polymorphisms can gradually emerge from a single ancestral strain. The model is based on the framework of adaptive dynamics, which has proved to be very useful for studying adaptive processes of divergence under sympatric conditions. In particular, the phenomenon of evolutionary branching serves as a general paradigm for diversification. I show that evolutionary branching naturally occurs in evolutionary models of cross-feeding if (1) there is a trade-off between uptake efficiencies on the primary and secondary resources, and (2) this trade-off has positive curvature. The model also suggests that the evolution of cross-feeding should be more likely in chemostat cultures than in serial batch cultures, which conforms with empirical observations. Overall, the model provides a theoretical metaphor for the evolution of cross-feeding polymorphisms. Received: February 19, 2002 / Accepted: May 8, 2002     

The species flocks of lacustrine gastropods: <Emphasis Type="Italic">Tylomelania</Emphasis> on Sulawesi as models in speciation and adaptive radiation

Endemic radiations provide splendid opportunities for studies in evolutionary biology. Species flocks in ancient lakes, such as in Tanganyika, Malawi or Baikal, have featured prominently in evolutionary biology, viewing these “evolutionary theatres” as hotspots of diversification. However, following a century of neglect, the endemic evolution of limnic cerithioidean gastropods in the two central lake systems on the Indonesian island of Sulawesi (i.e. Lake Poso and the lakes of the Malili system, e.g. Danau Matano, Mahalona and Towuti) also provide instructive model cases for the study of speciation mechanisms, adaptive radiation and annidation (i.e. niche exploitation). We here discuss the evolutionary and taxonomic implications of the lacustrine species flocks in Tylomelania from these lakes in Sulawesi as an exceptional endemic assemblage of morphologically distinct viviparous pachychilid gastropods. This first comprehensive compilation of data on both ancient lake systems, Poso and Malili, offers a new perspective on ecological differentiation in this radiation. Presented here within the framework of the theory of evolutionary ecology it provides a research program for acquiring a synthetical perspective that includes morphology, molecular genetics, ecology and biogeography. In this context, it will be possible to compare the species flocks of these truly “Darwinian snails” on Sulawesi with the long enigmatic, so-called thalassoid (i.e. marine-like) gastropod radiation in East African’s Lake Tanganyika.     

Internal pilots for observational studies

Study planning often involves selecting an appropriate sample size. Power calculations require specifying an effect size and estimating “nuisance” parameters, e.g. the overall incidence of the outcome. For observational studies, an additional source of randomness must be estimated: the rate of the exposure. A poor estimate of any of these parameters will produce an erroneous sample size. Internal pilot (IP) designs reduce the risk of this error ‐ leading to better resource utilization ‐ by using revised estimates of the nuisance parameters at an interim stage to adjust the final sample size. In the clinical trials setting, where allocation to treatment groups is pre‐determined, IP designs have been shown to achieve the targeted power without introducing substantial inflation of the type I error rate. It has not been demonstrated whether the same general conclusions hold in observational studies, where exposure‐group membership cannot be controlled by the investigator. We extend the IP to observational settings. We demonstrate through simulations that implementing an IP, in which prevalence of the exposure can be re‐estimated at an interim stage, helps ensure optimal power for observational research with little inflation of the type I error associated with the final data analysis.     

Bayesian semiparametric intensity estimation for inhomogeneous spatial point processes

In this work we propose a fully Bayesian semiparametric method to estimate the intensity of an inhomogeneous spatial point process. The basic idea is to first convert intensity estimation into a Poisson regression setting via binning data points on a regular grid, and then model the log intensity semiparametrically using an adaptive version of Gaussian Markov random fields to smooth the corresponding counts. The inference is carried by an efficient Markov chain Monte Carlo simulation algorithm. Compared to existing methods for intensity estimation, for example, parametric modeling and kernel smoothing, the proposed estimator not only provides inference regarding the dependence of the intensity function on possible covariates, but also uses information from the data to adaptively determine the amount of smoothing at the local level. The effectiveness of using our method is demonstrated through simulation studies and an application to a rainforest dataset.