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Espanola Giant Tortoise
Hood Island Giant Tortoise
Hood Island Giant Tortoise
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- Data packageData from: Allometric and temporal scaling of movement characteristics in Galapagos tortoises(2016-06-29) Bastille-Rousseau, Guillaume; Yackulic, Charles B.; Frair, Jacqueline L.; Cabrera, Freddy; Blake, StephenNOTE: An updated and larger version of this dataset is available. See https://doi.org/10.5441/001/1.6gr485fk. ABSTRACT: (1) Understanding how individual movement scales with body size is of fundamental importance in predicting ecological relationships for diverse species. One-dimensional movement metrics scale consistently with body size yet vary over different temporal scales. Knowing how temporal scale influences the relationship between animal body size and movement would better inform hypotheses about the efficiency of foraging behaviour, the ontogeny of energy budgets, and numerous life history trade-offs. (2) We investigated how the temporal scaling of allometric patterns in movement vary over the course of a year, specifically during periods of motivated (directional and fast movement) and unmotivated (stationary and tortuous movement) behaviour. We focused on a recently diverged group of species that displays wide variation in movement behaviour—giant Galapagos tortoises (Chelonoidis spp.)—to test how movement metrics estimated on a monthly basis scaled with body size. (3) We used state-space modelling to estimate seven different movement metrics of Galapagos tortoises. We used log-log regression of the power law to evaluate allometric scaling for these movement metrics, and contrasted relationships by species and sex. (4) Allometric scaling of movement was more apparent during motivated periods of movement. During this period, allometry was revealed at multiple temporal intervals (hourly, daily, and monthly), with values observed at daily and monthly intervals corresponding most closely to the expected ¼ scaling coefficient, albeit with wide credible intervals. We further detected differences in the magnitude of scaling among taxa uncoupled from observed differences in the temporal structuring of their movement rates. (5) Our results indicate that the definition of temporal scales is fundamental to the detection of allometry of movement, and should be given more attention in movement studies. Our approach not only provides new conceptual insights into temporal attributes in one-dimensional scaling of movement, but also generates valuable insights into the movement ecology of iconic yet poorly understood Galapagos giant tortoises.
- Data packageData from: Migration triggers in a large herbivore: Galápagos giant tortoises navigating resource gradients on volcanoes(2019-03-08) Bastille-Rousseau, Guillaume; Yackulic, Charles B.; Gibbs, James; Frair, Jacqueline L.; Cabrera, Freddy; Blake, StephenTo understand how migratory behavior evolved and to predict how migratory species will respond to global environmental change it is important to quantify the fitness consequences of intra- and inter-individual variation in migratory behavior. Intra-individual variation includes behavioral responses to changing environmental conditions and hence behavioral plasticity in the context of novel or variable conditions. Inter-individual variation determines the degree of variation on which selection can act and the rate of evolutionary responses to changes in average and extreme environmental conditions. Here we focus on variation in the partial migratory behavior of giant Galápagos tortoises (Chelonoidis spp.) and its energetic consequences. We evaluate the extent and mechanisms by which tortoises adjust migration timing in response to varying annual environmental conditions, and integrate movement data within a bioenergetic model of tortoise migration to quantify the fitness consequences of migration timing. We find strong inter-individual variation in the timing of migration, which was not affected by environmental conditions prevailing at the time of migration but rather by average expectations estimated from multi-annual averaged conditions. This variation is associated with an average annual loss in efficiency of ~15% relative to optimal timing based on year-specific conditions. These results point towards a limited ability of tortoises to adjust the timing of their migrations based on prevailing (and, by extension, future) conditions, suggesting that the adaptability of tortoise migratory behavior to changing conditions is predicated more by past “normal” conditions than responses to prevailing, changing conditions. Our work offers insights into the level of environmental-tuning in migratory behavior and a general framework for future research across taxa.
- Data packageData from: Suite of simple metrics reveals common movement syndromes across vertebrate taxa(2017-06-01) Abrahms, BrianaBackground: Because empirical studies of animal movement are most-often site- and species-specific, we lack understanding of the level of consistency in movement patterns across diverse taxa, as well as a framework for quantitatively classifying movement patterns. We aim to address this gap by determining the extent to which statistical signatures of animal movement patterns recur across ecological systems. We assessed a suite of movement metrics derived from GPS trajectories of thirteen marine and terrestrial vertebrate species spanning three taxonomic classes, orders of magnitude in body size, and modes of movement (swimming, flying, walking). Using these metrics, we performed a principal components analysis and cluster analysis to determine if individuals organized into statistically distinct clusters. Finally, to identify and interpret commonalities within clusters, we compared them to computer-simulated idealized movement syndromes representing suites of correlated movement traits observed across taxa (migration, nomadism, territoriality, and central place foraging). Results: Two principal components explained 70% of the variance among the movement metrics we evaluated across the thirteen species, and were used for the cluster analysis. The resulting analysis revealed four statistically distinct clusters. All simulated individuals of each idealized movement syndrome organized into separate clusters, suggesting that the four clusters are explained by common movement syndrome. Conclusions: Our results offer early indication of widespread recurrent patterns in movement ecology that have consistent statistical signatures, regardless of taxon, body size, mode of movement, or environment. We further show that a simple set of metrics can be used to classify broad-scale movement patterns in disparate vertebrate taxa. Our comparative approach provides a general framework for quantifying and classifying animal movements, and facilitates new inquiries into relationships between movement syndromes and other ecological processes.
- Data packageData from: Flexible characterization of animal movement pattern using net squared displacement and a latent state model(2016-11-29) Bastille-Rousseau, Guillaume; Potts, Jonathan R.; Yackulic, Charles B.; Frair, Jacqueline L.; Ellington, E. Hance; Blake, StephenNOTE: An updated and larger version of this dataset is available. See https://doi.org/10.5441/001/1.6gr485fk. ABSTRACT: Background: Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises (Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results: With respect to patterns of time spent and the number of transitions between modes, our approach out- performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions: Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.