Showing papers by "Benjamin M. Bolker published in 2013"

Tundra ecosystems observed to be CO2 sources due to differential amplification of the carbon cycle

Abstract: Are tundra ecosystems currently a carbon source or sink? What is the future trajectory of tundra carbon fluxes in response to climate change? These questions are of global importance because of the vast quantities of organic carbon stored in permafrost soils. In this meta-analysis, we compile 40 years of CO2 flux observations from 54 studies spanning 32 sites across northern high latitudes. Using time-series analysis, we investigated if seasonal or annual CO2 fluxes have changed over time, and whether spatial differences in mean annual temperature could help explain temporal changes in CO2 flux. Growing season net CO2 uptake has definitely increased since the 1990s; the data also suggest (albeit less definitively) an increase in winter CO2 emissions, especially in the last decade. In spite of the uncertainty in the winter trend, we estimate that tundra sites were annual CO2 sources from the mid-1980s until the 2000s, and data from the last 7 years show that tundra continue to emit CO2 annually. CO2 emissions exceed CO2 uptake across the range of temperatures that occur in the tundra biome. Taken together, these data suggest that despite increases in growing season uptake, tundra ecosystems are currently CO2 sources on an annual basis.

Interspecific Dominance Via Vocal Interactions Mediates Altitudinal Zonation in Neotropical Singing Mice

Abstract: Interspecific aggression between ecologically similar species may influence geographic limits by mediating competitive exclusion at the range edge. Advertisement signals that mediate competitive interactions within species may also provide social information that contributes to behavioral dominance and spatial segregation among species. We studied the mechanisms underlying altitudinal range limits in Neotropical singing mice (Scotinomys), a genus of muroid rodent in which males vocalize to repel rivals and attract mates. We first delineated replacement zones and described temperature regimes on three mountains in Costa Rica and Panama where Chiriqui singing mice (S. xerampelinus) abruptly replace Alston’s singing mice (S. teguina). Next, we conducted interspecific behavioral trials and reciprocal removal experiments to examine if interspecific aggression mediated species replacement. Finally, we performed reciprocal playback experiments to investigate whether response to song matched competitive i...

Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

Abstract: 1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

Predator density and timing of arrival affect reef fish community assembly.

Abstract: Most empirical studies of predation use simple experimental approaches to quantify the effects of predators on prey (e.g., using constant densities of predators, such as ambient vs. zero). However, predator densities vary in time, and these effects may not be well represented by studies that use constant predator densities. Although studies have independently examined the importance of predator density, temporal variability, and timing of arrival (i.e., early or late relative to prey), the relative contribution of these different predator regimes on prey abundance, diversity, and composition remains poorly understood. The hawkfish (Paracirrhites arcatus), a carnivorous coral reef fish, exhibits substantial variability in patch occupancy, density, and timing of arrival to natural reefs. Our field experiments demonstrated that effects of hawkfish on prey abundance depended on both hawkfish density and the timing of their arrival, but not on variability in hawkfish density. Relative to treatments without hawkfish, hawkfish presence reduced prey abundance by 50%. This effect increased with a doubling of hawkfish density (an additional 33% reduction), and when hawkfish arrived later during community development (a 34% reduction). Hawkfish did not affect within-patch diversity (species richness), but they increased between-patch diversity (beta) based on species incidence (22%), and caused shifts in species composition. Our results suggest that the timing of predator arrival can be as important as predator density in modifying prey abundance and community composition.

Predator density and competition modify the benefits of group formation in a shoaling reef fish

Abstract: Synthesis Predation risk experienced by individuals living in groups depends on the balance between predator dilution, competition for refuges, and predator interference or synergy. These interactions operate between prey species as well: the benefits of group living decline in the presence of an alternative prey species. We apply a novel model-fitting approach to data from field experiments to distinguish among competing hypotheses about shifts in predator foraging behavior across a range of predator and prey densities. Our study provides novel analytical tools for analyzing predator foraging behavior and offers insight into the processes driving the dynamics of coral reef fish. Studies of predator foraging behavior typically focus on single prey species and fixed predator densities, ignoring the potential importance of complexities such as predator dilution; predator-mediated effects of alternative prey; heterospecific competition; or predator–predator interactions. Neglecting the effects of prey density is particularly problematic for prey species that live in mixed species groups, where the beneficial effects of predator dilution may swamp the negative effects of heterospecific competition. Here we use field experiments to investigate how the mortality rates of a shoaling coral reef fish (a wrasse: Thalassoma amblycephalum), change as a result of variation in: 1) conspecific density, 2) density of a predator (a hawkfish: Paracirrhites arcatus), and 3) presence of an alternative prey species that competes for space (a damselfish: Pomacentrus pavo). We quantify changes in prey mortality rates from the predator's perspective, examining the effects of added predators or a second prey species on the predator's functional response. Our analysis highlights a model-fitting approach that discriminates amongst multiple hypotheses about predator foraging in a community context. Wrasse mortality decreased with increasing conspecific density (i.e. mortality was inversely density-dependent). The addition of a second predator doubled prey mortality rates, without significantly changing attack rate or handling time – i.e. there was no evidence for predator interference. The presence of a second prey species increased wrasse mortality by 95%; we attribute this increase either to short-term apparent competition (predator aggregation) or to a decrease in handling time of the predator (e.g. through decreased wrasse vigilance). In this system, 1) prey benefit from intraspecific group living though a reduced predation risk, and 2) the benefit of group living is reduced in the presence of an alternative prey species.

A general mathematical framework for the analysis of spatiotemporal point processes

Abstract: Spatial and stochastic models are often straightforward to simulate but difficult to analyze mathematically. Most of the mathematical methods available for nonlinear stochastic and spatial models are based on heuristic rather than mathematically justified assumptions, so that, e.g., the choice of the moment closure can be considered more of an art than a science. In this paper, we build on recent developments in specific branch of probability theory, Markov evolutions in the space of locally finite configurations, to develop a mathematically rigorous and practical framework that we expect to be widely applicable for theoretical ecology. In particular, we show how spatial moment equations of all orders can be systematically derived from the underlying individual-based assumptions. Further, as a new mathematical development, we go beyond mean-field theory by discussing how spatial moment equations can be perturbatively expanded around the mean-field model. While we have suggested such a perturbation expansion in our previous research, the present paper gives a rigorous mathematical justification. In addition to bringing mathematical rigor, the application of the mathematically well-established framework of Markov evolutions allows one to derive perturbation expansions in a transparent and systematic manner, which we hope will facilitate the application of the methods in theoretical ecology.

A Method for Detecting Positive Growth Autocorrelation without Marking Individuals

Abstract: In most ecological studies, within-group variation is a nuisance that obscures patterns of interest and reduces statistical power. However, patterns of within-group variability often contain information about ecological processes. In particular, such patterns can be used to detect positive growth autocorrelation (consistent variation in growth rates among individuals in a cohort across time), even in samples of unmarked individuals. Previous methods for detecting autocorrelated growth required data from marked individuals. We propose a method that requires only estimates of within-cohort variance through time, using maximum likelihood methods to obtain point estimates and confidence intervals of the correlation parameter. We test our method on simulated data sets and determine the loss in statistical power due to the inability to identify individuals. We show how to accommodate nonlinear growth trajectories and test the effects of size-dependent mortality on our method's accuracy. The method can detect significant growth autocorrelation at moderate levels of autocorrelation with moderate-sized cohorts (for example, statistical power of 80% to detect growth autocorrelation ρ (2) = 0.5 in a cohort of 100 individuals measured on 16 occasions). We present a case study of growth in the red-eyed tree frog. Better quantification of the processes driving size variation will help ecologists improve predictions of population dynamics. This work will help researchers to detect growth autocorrelation in cases where marking is logistically infeasible or causes unacceptable decreases in the fitness of marked individuals.

Translating Probability Density Functions: From R to BUGS and Back Again

Abstract: The ability to implement statistical models in the BUGS language facilitates Bayesian inference by automating MCMC algorithms. Software packages that interpret the BUGS language include OpenBUGS, WinBUGS, and JAGS. R packages that link BUGS software to the R environment, including rjags and R2WinBUGS, are widely used in Bayesian analysis. Indeed, many packages in the Bayesian task view on CRAN (http://cran.r-project.org/web/views/Bayesian.html) depend on this integration. However, the R and BUGS languages use different representations of common probability density functions, creating a potential for errors to occur in the implementation or interpretation of analyses that use both languages. Here we review different parameterizations used by the R and BUGS languages, describe how to translate between the languages, and provide an R function, r2bugs.distributions, that transforms parameterizations from R to BUGS and back again. Distribution Lang. Parameterization Use Notes

Virulence evolution in a host–parasite system in the absence of viral evolution

Abstract: Question How does virulence evolve in the Drosophila melanogaster/sigma virus (DMelSV) system? Organisms Drosophila melanogaster (host) and DMelSV (parasite). Empirical methods Artificial selection on whole-carcass viral titre of infected flies, including two selection regimes (maternal and biparental transmission) and three treatments within each regime (increased titre, decreased titre, and control). The maternal transmission selection regime lasted for six generations, while the biparental transmission selection regime lasted for twelve generations. We further quantified virulence by estimating the fecundity, viability, and development time of infected flies. Finally, we sequenced virus strains at the end of selection. Predictions and conclusions Titre is defined here as the number of viral genomes inside a single fly, while virulence is defined as harm to host. We predicted that titre would respond to both increased and decreased selection, that virulence would evolve as a positively correlated response, and that sequence evolution in the viruses would be responsible for these changes. Titre did respond to selection in the biparental regime, although both high and control lines both demonstrated increased titre, while the titre of the low lines did not change. One component of virulence, development time, was positively correlated with titre in the biparental transmission lines (maternal transmission lines were not scored for virulence). However, we detected few (and in some cases, no) genomic changes in the virus, making viral evolution unlikely to be responsible for the response to selection and the association between development time and titre.