Combining multiple data sources with different biases in state-space models for population dynamics.

The resolution at which animal populations can be modeled can be increased when multiple datasets corresponding to different life stages are available, allowing, for example, seasonal instead of annual descriptions of dynamics. However, the abundance estimates used for model fitting can have multiple sources of error, both random and systematic, namely bias. We focus here on the consequences of, and how to address, differing and unknown observation biases when fitting models.

Improving inference for nonlinear state-space models of animal population dynamics given biased sequential life stage data.

State-space models (SSMs) are a popular tool for modeling animal abundances. Inference difficulties for simple linear SSMs are well known, particularly in relation to simultaneous estimation of process and observation variances. Several remedies to overcome estimation problems have been studied for relatively simple SSMs, but whether these challenges and proposed remedies apply for nonlinear stage-structured SSMs, an important class of ecological models, is less well understood.

Social rank overrides environmental and community fluctuations in determining meat access by female chimpanzees in the Taï National Park, Côte d'Ivoire.

Meat, long hypothesized as an important food source in human evolution, is still a substantial component of the modern human diet, with some humans relying entirely on meat during certain times of the year. Understanding the socio-ecological context leading to the successful acquisition and consumption of meat by chimpanzees (), our closest living relative, can provide insight into the emergence of this trait because humans and chimpanzees are unusual among primates in that they both (i) hunt mammalian prey, (ii) share meat with community members, and (iii) form long-term relationships and complex social hierarchies within their communities. However, females in both human hunter-gatherer societies as well as chimpanzee groups rarely hunt, instead typically accessing meat via males that share meat with group members.

Spatio-temporal complexity of chimpanzee food: How cognitive adaptations can counteract the ephemeral nature of ripe fruit.

Ecological complexity has been proposed to play a crucial role in primate brain-size evolution. However, detailed quantification of ecological complexity is still limited. Here we assess the spatio-temporal distribution of tropical fruits and young leaves, two primary chimpanzee (Pan troglodytes) foods, focusing on the predictability of their availability in individual trees.

Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state-space models.

Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State-space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water.

Wild chimpanzees plan their breakfast time, type, and location.

Not all tropical fruits are equally desired by rainforest foragers and some fruit trees get depleted more quickly and carry fruit for shorter periods than others. We investigated whether a ripe-fruit specialist, the chimpanzee (Pan troglodytes verus), arrived earlier at breakfast sites with very ephemeral and highly sought-after fruit, like figs, than sites with less ephemeral fruit that can be more predictably obtained throughout the entire day. We recorded when and where five adult female chimpanzees spent the night and acquired food for a total of 275 full days during three fruit-scarce periods in a West African tropical rainforest.

Spatial cohesion of adult male chimpanzees (Pan troglodytes verus) in Taï National Park, Côte d'Ivoire.

Group living animals can exhibit fission-fusion behavior whereby individuals temporarily separate to reduce the costs of living in large groups. Primates living in groups with fission-fusion dynamics face numerous challenges in maintaining spatial cohesion, especially in environments with limited visibility. Here we investigated the spatial cohesion of adult male chimpanzees (Pan troglodytes verus) living in Taï National Park, Côte d'Ivoire, to better understand the mechanisms by which individuals maintain group cohesion during fission-fusion events.

Generalized additive mixed models for disentangling long-term trends, local anomalies, and seasonality in fruit tree phenology.

Quantifying temporal patterns of ephemeral plant structures such as leaves, flowers, and fruits gives insight into both plant and animal ecology. Different scales of temporal changes in fruits, for example within- versus across-year variability, are driven by different processes, but are not always easy to disentangle. We apply generalized additive mixed models (GAMMs) to study a long-term fruit presence-absence data set of individual trees collected from a high-altitude Afromontane tropical rain forest site within Bwindi Impenetrable National Park (BINP), Uganda.

Using diel movement behavior to infer foraging strategies related to ecological and social factors in elephants.

Background: Adaptive movement behaviors allow individuals to respond to fluctuations in resource quality and distribution in order to maintain fitness. Classically, studies of the interaction between ecological conditions and movement behavior have focused on such metrics as travel distance, velocity, home range size or patch occupancy time as the salient metrics of behavior. Driven by the emergence of very regular high frequency data, more recently the importance of interpreting the autocorrelation structure of movement as a behavioral metric has become apparent.

A framework for understanding the architecture of collective movements using pairwise analyses of animal movement data.

The study of collective or group-level movement patterns can provide insight regarding the socio-ecological interface, the evolution of self-organization and mechanisms of inter-individual information exchange. The suite of drivers influencing coordinated movement trajectories occur across scales, resulting from regular annual, seasonal and circadian stimuli and irregular intra- or interspecific interactions and environmental encounters acting on individuals. Here, we promote a conceptual framework with an associated statistical machinery to quantify the type and degree of synchrony, spanning absence to complete, in pairwise movements.

From moonlight to movement and synchronized randomness: Fourier and wavelet analyses of animal location time series data.

High-resolution animal location data are increasingly available, requiring analytical approaches and statistical tools that can accommodate the temporal structure and transient dynamics (non-stationarity) inherent in natural systems. Traditional analyses often assume uncorrelated or weakly correlated temporal structure in the velocity (net displacement) time series constructed using sequential location data. We propose that frequency and time-frequency domain methods, embodied by Fourier and wavelet transforms, can serve as useful probes in early investigations of animal movement data, stimulating new ecological insight and questions.

Likelihood ridges and multimodality in population growth rate models.

A central problem in population ecology is to use time series data to estimate the form of density dependence in the per capita growth rate (pgr). This is often accomplished with phenomenological models such as the theta-Ricker or generalized Beverton-Holt. Using the theta-Ricker model as a simple but flexible description of density dependence, we apply theory and simulations to show how multimodality and ridges in the likelihood surface can emerge even in the absence of model misspecification or observation error.

Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses.

The internal state of an individual-as it relates to thirst, hunger, fear, or reproductive drive-can be inferred by referencing points on its movement path to external environmental and sociological variables. Using time-series approaches to characterize autocorrelative properties of step-length movements collated every 3 h for seven free-ranging African elephants, we examined the influence of social rank, predation risk, and seasonal variation in resource abundance on periodic properties of movement. The frequency domain methods of Fourier and wavelet analyses provide compact summaries of temporal autocorrelation and show both strong diurnal and seasonal based periodicities in the step-length time series.

Empirical models of pollen limitation, resource acquisition, and mast seeding by a bee-pollinated wildflower.

Synchronous mast seeding is increasingly recognized as common in plant populations. Recent theoretical models show that synchronous mast seeding could be a consequence of resource allocation and storage within individual plants, coupled by pollen limitation in low-flowering years. We used long-term population and weather data to parameterize models of flowering based on stored resources and pollen limitation in Astragalus scaphoides, a bee-pollinated plant that flowers in alternate years.