Anthony R. Ives

TESTING FOR PHYLOGENETIC SIGNAL IN COMPARATIVE DATA: BEHAVIORAL TRAITS ARE MORE LABILE

Abstract The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal α = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.

Using the Past to Predict the Present: Confidence Intervals for Regression Equations in Phylogenetic Comparative Methods

Two phylogenetic comparative methods, independent contrasts and generalized least squares models, can be used to determine the statistical relationship between two or more traits. We show that the two approaches are functionally identical and that either can be used to make statistical inferences about values at internal nodes of a phylogenetic tree (hypothetical ancestors), to estimate relationships between characters, and to predict values for unmeasured species. Regression equations derived from independent contrasts can be placed back onto the original data space, including computation of both confidence intervals and prediction intervals for new observations. Predictions for unmeasured species (including extinct forms) can be made increasingly accurate and precise as the specificity of their placement on a phylogenetic tree increases, which can greatly increase statistical power to detect, for example, deviation of a single species from an allometric prediction. We reexamine published data for basal metabolic rates (BMR) of birds and show that conventional and phylogenetic allometric equations differ significantly. In new results, we show that, as compared with nonpasserines, passerines exhibit a lower rate of evolution in both body mass and mass‐corrected BMR; passerines also have significantly smaller body masses than their sister clade. These differences may justify separate, clade‐specific allometric equations for prediction of avian basal metabolic rates.

Estimating community stability and ecological interactions from time-series data

Natural ecological communities are continuously buffeted by a varying environment, often making it difficult to measure the stability of communities using concepts requiring the existence of an equilibrium point. Instead of an equilibrium point, the equilibrial state of communities subject to environmental stochasticity is a stationary distribution, which is characterized by means, variances, and other statistical moments. Here, we derive three properties of stochastic multispecies communities that measure different characteristics associated with community stability. These properties can be estimated from multispecies time-series data using first-order multivariate autoregressive (MAR(1)) models. We demonstrate how to estimate the parameters of MAR(1) models and obtain confidence intervals for both parameters and the measures of stability. We also address the problem of estimation when there is observation (measurement) error. To illustrate these methods, we compare the stability of the planktonic commun...

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called ‘early warning signals’, and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

Phylogenetic Measures of Biodiversity

We developed a theoretical framework based on phylogenetic comparative methods to integrate phylogeny into three measures of biodiversity: species variability, richness, and evenness. These metrics can be used in conjunction with permutation procedures to test for phylogenetic community structure. As an illustration, we analyzed data on the composition of 58 lake fish communities in Wisconsin. The fish communities showed phylogenetic underdispersion, with communities more likely to contain closely related species. Using information about differences in environmental characteristics among lakes, we demonstrated that phylogenetic underdispersion in fish communities was associated with environmental factors. For example, lakes with low pH were more likely to contain species in the same clade of acid‐tolerant species. Our metrics differ from existing metrics used to calculate phylogenetic community structure, such as net relatedness index and Faith’s phylogenetic diversity. Our metrics have the advantage of providing an integrated and easy‐to‐understand package of phylogenetic measures of species variability, richness, and evenness with well‐defined statistical properties. Furthermore, they allow the easy evaluation of contributions of individual species to different aspects of the phylogenetic organization of communities. Therefore, these metrics should aid with the incorporation of phylogenetic information into strategies for understanding biodiversity and its conservation.

Mutualisms in a changing world: an evolutionary perspective

Ecology Letters (2010) 13: 1459-1474 ABSTRACT: There is growing concern that rapid environmental degradation threatens mutualistic interactions. Because mutualisms can bind species to a common fate, mutualism breakdown has the potential to expand and accelerate effects of global change on biodiversity loss and ecosystem disruption. The current focus on the ecological dynamics of mutualism under global change has skirted fundamental evolutionary issues. Here, we develop an evolutionary perspective on mutualism breakdown to complement the ecological perspective, by focusing on three processes: (1) shifts from mutualism to antagonism, (2) switches to novel partners and (3) mutualism abandonment. We then identify the evolutionary factors that may make particular classes of mutualisms especially susceptible or resistant to breakdown and discuss how communities harbouring mutualisms may be affected by these evolutionary responses. We propose a template for evolutionary research on mutualism resilience and identify conservation approaches that may help conserve targeted mutualisms in the face of environmental change.

INTERACTIONS BETWEEN SPECIALIST AND GENERALIST NATURAL ENEMIES: PARASITOIDS, PREDATORS, AND PEA APHID BIOCONTROL

Most biological control systems involve a diverse community of natural enemies. We investigated how specialist and generalist natural enemies differ as biological control agents of pea aphids (Acyrthosiphon pisum), and how interactions among natural enemies affect successful control. In alfalfa, pea aphids are attacked by a specialist parasitoid wasp, Aphidius ervi, and a guild of generalist predators primarily made up of Nabis and Orius bugs, coccinellid and carabid beetles, and web-building spiders. In three field experiments, we manipulated the parasitoid, then the generalist predator guild, and finally both classes of natural enemy, and recorded resulting impacts on pea aphid population control. The parasitoid caused little immediate reduction in aphid population growth but caused a large decline after a delay corresponding to the generation time of the parasitoid. In contrast, the generalist guild caused an immediate decline in the aphid population growth rate. However, the generalists did not exert density-dependent control, so aphid densities continued to increase throughout the experiment. The third field experiment in which we simultaneously manipulated parasitoids and predators investigated the possibility of “nonadditive effects” on aphid control. Densities of parasitoid pupae were 50% lower in the presence of generalist predators, indicating intraguild predation. Nonetheless, the ratio of parasitoids to aphids was not changed, and the impact of the two types of natural enemies was additive. We constructed a stage-structured model of aphid, parasitoid, and predator dynamics and fit the model to data from our field experiments. The model supports the additivity of parasitoid and predator effects on aphid suppression but suggests that longer-term experiments (32 d rather than 20 d) would likely reveal nonadditive effects as predation removes parasitoids whose response to aphid densities occurs with a delay. The model allowed us to explore additional factors that could influence the additivity of parasitoid and predator effects. Aphid density-dependent population growth and predator immigration in response to aphid density would likely have little influence on the additivity between parasitism and predation. However, if a parasitoid were to show a strong Type II functional response, in contrast to A. ervi whose functional response is nearly Type I, interactions with predators would likely be synergistic. These analyses reveal factors that should be investigated in other systems to address whether parasitism and predation act additively on host densities. Corresponding Editor: E. Evans.

Morphometrics of the Avian Small Intestine Compared with That of Nonflying Mammals: A Phylogenetic Approach

Flying animals may experience a selective constraint on gut volume because the energetic cost of flight increases and maneuverability decreases with greater digesta load. The small intestine is the primary site of absorption of most nutrients (e.g., carbohydrates, proteins, fat) in both birds and mammals. Therefore, we used a phylogenetically informed approach to compare small intestine morphometric measurements of birds with those of nonflying mammals and to test for effects of diet within each clade. We also compared the fit of nonphylogenetic and phylogenetic models to test for phylogenetic signal after accounting for effects of body mass, clade, and/or diet. We provide a new MATLAB program (Regressionv2.m) that facilitates a flexible model‐fitting approach in comparative studies. As compared with nonflying mammals, birds had 51% less nominal small intestine surface area (area of a smooth bore tube) and 32% less volume. For animals <365 g in body mass, birds also had significantly shorter small intestines (20%–33% shorter, depending on body mass). Diet was also a significant factor explaining variation in small intestine nominal surface area of both birds and nonflying mammals, small intestine mass of mammals, and small intestine volume of both birds and nonflying mammals. On the basis of the phylogenetic trees used in our analyses, small intestine length and nominal surface area exhibited statistically significant phylogenetic signal in birds but not in mammals. Thus, for birds, related species tended to be similar in small intestine length and nominal surface area, even after accounting for relations with body mass and diet. A reduced small intestine in birds may decrease the capacity for breakdown and active absorption of nutrients. Birds do not seem to compensate for reduced digestive and absorptive capacity via a longer gut retention time of food, but we found some evidence that birds have an increased mucosal surface area via a greater villus area, although not enough to compensate for reduced nominal surface area. We predict that without increased rate of enzyme hydrolysis and/or mediated transport and without increased passive absorption of water‐soluble nutrients, birds may operate with a reduced digestive capacity, compared with that of nonflying mammals, to meet an increase in metabolic needs (i.e., a reduced spare capacity).

Reptile Extinctions on Land‐Bridge Islands: Life‐History Attributes and Vulnerability to Extinction

One of the central questions of conservation biology is what life‐history traits render a species prone to extinction. We addressed this problem by calculating extinction rates for 35 species of turtles and squamates (lizards and snakes) occurring on 87 land‐bridge islands in the Mediterranean Sea. We calculated extinction rates in two ways: first, by incorporating the known sequence of historical island separations and second by ignoring history and assuming that the islands became isolated simultaneously. The second procedure is simpler and more frequently used in the literature and produces estimates of extinction rates that are similar to the first, more complex procedure. We then determined the relationship between extinction rates (calculated using both methods) and body mass, longevity, habitat specialization, and population abundance using two methods: first, by accounting for the phylogenetic relationships among species and, second, by ignoring them. Only population abundance and habitat specialization explained a significant amount of the observed variation in species extinction rates. Body mass itself did not explain variation in extinction rates, although it was strongly correlated with abundance. These conclusions were obtained using both procedures for calculating extinction rates and both procedures for correlating extinction rates with life‐history traits.

Measuring resilience in stochastic systems

This paper develops mathematical and statistical techniques for measuring the resilience of inherently stochastic ecological systems. To correspond to the deterministic idea of resilience measured by the return time to equilibrium following perturbation, resilience in stochastic systems is defined as the variability in population densities relative to environmentally driven variability in population growth rates. Stochastic resilience defined in this way is calculated from a community matrix describing the average interaction strengths within and among species. The procedure to calculate stochastic resilience is demonstrated on simulated data sets consisting of time series of population densities. The simplicity of the procedure makes it a potential tool for application to a wide range of ecological communities. See full-text article at JSTOR