Predicting demographic group structures based on DNA sequence data

The ability to infer relationships between groups of sequences, either by searching for their evolutionary history or by comparing their sequence similarity, can be a crucial step in hypothesis testing. Interpreting relationships of human immunodeficiency virus type 1 (HIV-1) sequences can be challenging because of their rapidly evolving genomes, but it may also lead to a better understanding of the underlying biology. Several studies have focused on the evolution of HIV-1, but there is little information to link sequence similarities and evolutionary histories of HIV-1 to the epidemiological information of the infected individual. Our goal was to correlate patterns of HIV-1 genetic diversity with epidemiological information, including risk and demographic factors. These correlations were then used to predict epidemiological information through analyzing short stretches of HIV-1 sequence. Using standard phylogenetic and phenetic techniques on 100 HIV-1 subtype B sequences, we were able to show some correlation between the viral sequences and the geographic area of infection and the risk of men who engage in sex with men. To help identify more subtle relationships between the viral sequences, the method of multidimensional scaling (MDS) was performed. That method identified statistically significant correlations between the viral sequences and the risk factors of men who engage in sex with men and individuals who engage in sex with injection drug users or use injection drugs themselves. Using tree construction, MDS, and newly developed likelihood assignment methods on the original 100 samples we sequenced, and also on a set of blinded samples, we were able to predict demographic/risk group membership at a rate statistically better than by chance alone. Such methods may make it possible to identify viral variants belonging to specific demographic groups by examining only a small portion of the HIV-1 genome. Such predictions of demographic epidemiology based on sequence information may become valuable in assigning different treatment regimens to infected individuals.     

Estimating the Mahalanobis distance from mixed continuous and discrete data

We present a method for estimating the Mahalanobis distance between two multivariate normal populations when a subset of the measurements is observed as ordered categorical responses. Asymptotic properties of the proposed estimator are developed. Two examples are discussed.     

Estimating stature in fossil hominids: which regression model and reference sample to use?

coResearchers have long appreciated the significant relationship between body size and an animal's overall adaptive strategy and life history. However, much more emphasis has been placed on interpreting body size than on the actual calculation of it. One measure of size that is especially important for human evolutionary studies is stature. Despite a long history of investigation, stature estimation remains plagued by two methodological problems: (1) the choice of the statistical estimator, and (2) the choice of the reference population from which to derive the parameters.This work addresses both of these problems in estimating stature for fossil hominids, with special reference to A.L. 288-1 (Australopithecus afarensis) and WT 15000 (Homo erectus). Three reference samples of known stature with maximum humerus and femur lengths are used in this study: a large (n=2209) human sample from North America, a smaller sample of modern human pygmies (n=19) from Africa, and a sample of wild-collected African great apes (n=85). Five regression techniques are used to estimate stature in the fossil hominids using both univariate and multivariate parameters derived from the reference samples: classical calibration, inverse calibration, major axis, reduced major axis and the zero-intercept ratio model. We also explore a new diagnostic to test extrapolation and allometric differences with multivariate data, and we calculate 95% confidence intervals to examine the range of variation in estimates for A.L. 288-1, WT 15000 and the new Bouri hominid (contemporary with [corrected] Australopithecus garhi). Results frequently vary depending on whether the data are univariate or multivariate. Unique limb proportions and fragmented remains complicate the choice of estimator. We are usually left in the end with the classical calibrator as the best choice. It is the maximum likelihood estimator that performs best overall, especially in scenarios where extrapolation occurs away from the mean of the reference sample. The new diagnostic appears to be a quick and efficient way to determine at the outset whether extrapolation exists in size and/or shape of the long bones between the reference sample and the target specimen.     

The evolution of body size in birds. II. The role of reproductive power

Given that body mass evolves non-randomly in birds, it is important to ask what factors might be responsible. One suggestion is that the rate at which individuals turn resources into offspring, termed reproductive power, might explain this non-randomness. This is because, in mammals, the body mass with the highest reproductive power is the most common (modal) one. Reproductive power was estimated for birds from data on energetic content of eggs and population productivity. According to the formulation of Brown et al. (1993), reproductive power is composed of two component processes: acquisition (acquiring resources and storing them in reproductive biomass) and conversion (converting reproductive biomass into offspring). As with mammals, estimates of reproductive power indicate that the most common body mass in birds is also the body mass that maximizes reproductive power. The relationship between reproductive power and diversity is different for species smaller than this modal body mass when compared to those that are larger. The relationship of body mass and reproductive power is different between birds and mammals in two ways: (1) the body mass that maximizes reproductive power is smaller in birds (33g) than in mammals (100g), and (2) mammals generate more reproductive power than an equivalent-sized bird. Reproductive power is determined primarily by acquisition in small birds and mammals, while it is determined by conversion in the largest birds and mammals. It is likely that reproductive power is closely tied to the evolution and diversification of body masses because it constrains the ways in which traits affecting fitness can evolve.     

Information and allometry

Many life-history parameters have condition-dependent optima, but individuals are often required to set the values of such parameters relatively early in development, before the relevant conditions can be assessed with full accuracy. If cues are available that predict such future conditions, then the condition-dependent parameter should evolve to assume values that deviate from the mean in the direction implied by the cues, but these deviations should regress towards the mean to the degree that the cues are less than fully reliable. Under mild assumptions, the slopes of the resulting relationships between condition-dependent life-history parameters and the variable conditions on which their optima depend will be the ideal slopes (those that would maximize fitness if the parameter could be chosen on the basis of full information) devalued by the squared correlation between the condition and the parameter.     

Adaptive differences in plant physiology and ecosystem paradoxes: insights from metabolic scaling theory

The link between variation in species‐specific plant traits, larger scale patterns of productivity, and other ecosystem processes is an important focus for global change research. Understanding such linkages requires synthesis of evolutionary, biogeograpahic, and biogeochemical approaches to ecological research. Recent observations reveal several apparently paradoxical patterns across ecosystems. When compared with warmer low latitudes, ecosystems from cold northerly latitudes are described by (1) a greater temperature normalized instantaneous flux of CO₂ and energy; and (2) similar annual values of gross primary production (GPP), and possibly net primary production. Recently, several authors attributed constancy in GPP to historical and abiotic factors. Here, we show that metabolic scaling theory can be used to provide an alternative ‘biotically driven’ hypothesis. The model provides a baseline for understanding how potentially adaptive variation in plant size and traits associated with metabolism and biomass production in differing biomes can influence whole‐ecosystem processes. The implication is that one cannot extrapolate leaf/lab/forest level functional responses to the globe without considering evolutionary and geographic variation in traits associated with metabolism. We test one key implication of this model – that directional and adaptive changes in metabolic and stoichiometric traits of autotrophs may mediate patterns of plant growth across broad temperature gradients. In support of our model, on average, mass‐corrected whole‐plant growth rates are not related to differences in growing season temperature or latitude. Further, we show how these changes in autotrophic physiology and nutrient content across gradients may have important implications for understanding: (i) the origin of paradoxical ecosystem behavior; (ii) the potential efficiency of whole‐ecosystem carbon dynamics as measured by the quotient of system capacities for respiration, R, and assimilation, A; and (iii) the origin of several ‘ecosystem constants’– attributes of ecological systems that apparently do not vary with temperature (and thus with latitude). Together, these results highlight the potential critical importance of community ecology and functional evolutionary/physiological ecology for understanding the role of the biosphere within the integrated earth system.     

More food,less habitat: how necromass and leaf litter decomposition combine to regulate a litter ant community

1. In brown food webs of the forest floor, necromass (e.g. insect carcasses and frass) falling from the canopy feeds both microbes and ants, with the former decomposing the homes of the latter. In a tropical litter ant community, we added necromass to 1 m² plots, testing if it added as a net food (increasing ant colony growth and recruitment) or destroyer of habitat (by decomposing leaf litter). 2. Maximum, but not mean, colony growth rates were higher on +food plots. However, neither average colony size, nor density was higher on +food plots. In contrast, +food plots saw diminished availability of leaf litter and higher microbial decomposition of cellulose, a main component of the organic substrate that comprises litter habitat. 3. Furthermore, necromass acted as a limiting resource to the ant community only when nest sites were supplemented on +food plots in a second experiment. Many of these +food +nest plots were colonised by the weedy species Wasmannia auropunctata. 4. Combined, these results support the more food–less habitat hypothesis and highlight the importance of embedding studies of litter ant ecology within broader decomposer food web dynamics.     

The size-grain hypothesis: a phylogenetic and field test

Abstract.  1. The size-grain hypothesis predicts that environmental rugosity results in positive allometric scaling of leg length on body length because of changes in locomotion costs.
2. The scaling of leg length and body length in ants was re-examined using phylogenetic independent contrast methods, and the allometric relationship found by Kaspari and Weiser ( Functional Ecology , 13 , 530–538, 1999) was supported.
3. The size-grain hypothesis was tested further by comparing the body sizes of ants from areas of contrasting habitat complexity in two different savanna habitats. No support for the size-grain hypothesis was found. Small body size classes were no more speciose in the rugose than in the more planar environment, and small ants were more abundant in the planar environment.     

Sensitivity of volatile monoterpene emission to changes in canopy structure: a model-based exercise with a process-based emission model

This paper investigates the dependence of monoterpene emissions at the canopy scale on total leaf area and leaf distribution. Simulations were carried out for a range of hypothetical but realistic forest canopies of the evergreen Quercus ilex (holm oak). Two emission models were applied that either did (SIM-BIM2) or did not (G93) account for cumulative responses to temperature and light. Both were embedded into a canopy model that considered spatial and temporal variations of foliage properties. This canopy model was coupled to a canopy climate model (CANOAK) to determine the micrometeorological conditions at the leaf scale. Structural properties considerably impacted monoterpene emission. The sensitivities to changes in total leaf area and to leaf area distribution were found to be of similar magnitude. The two different models performed similarly on a whole-year basis but showed clear differences during certain episodes. The analysis showed that structural indices have to be carefully evaluated for proper scaling of emission from leaves to canopy. Further research is encouraged on seasonal dynamics of emission potentials.