Understanding movement data and movement processes: current and emerging directions.

By Robert S. Schick, Scott Loarie, F. Colchero, B. Best, A. Boustany, D. Conde, Patrick N. Halpin, Lucas Joppa, C. McClellan, James S. Clark. Ecology Letters, 2008

417 citations recorded by the source corpus.

Subfields: Ecology, Ecology, Evolution, Behavior and Systematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/efe74b0e13d39b8b02bbb5f1d10c13e79cb6b9cf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Ecology, Evolution, Behavior and Systematics

In Molecular Biology

Citations in the corpus

Linking movement behavior and fine-scale genetic structure to model landscape connectivity for bobcats (Lynx rufus) (2013, positive): “…link between movement and gene flow, movement models may need to incorporate behavioral complexity, such as accounting for ‘‘state switching’’ between foraging versus migrating behavior (Schick et al. 2008), as well as consider the potential differences in spatial scale of the processes involved.”
State-space models for bio-loggers: A methodological road map (2013, background): “Recent reviews (Patterson et al., 2008; Schick et al., 2008) have publicized the notion of state-space model (SSM(1)) approaches for studying animal movement and these tools are now being more widely applied.”
Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology (2010, background): “to match fine-scale animal location data Thirgood et al. (2004); Whittington et al.”
In search of greener pastures: Using satellite images to predict the effects of environmental change on zebra migration (2013, background): “[28] We have shown that movement models driven by spatiotemporal environmental data can reveal decision rules, speed of movement, and navigation mechanisms employed by migratory animals [Nathan et al., 2008; Schick et al., 2008].”
A novel method for identifying behavioural changes in animal movement data. (2009, background): “A fruitful body of research has emerged recently that addresses measurement error with the use of state-space models (Jonsen et al. 2003, 2005; Royer et al. 2005; Patterson et al. Ecology Letters, (2009) 12: 395–408 doi: 10.1111/j.1461-0248.2009.01293.x”
Understanding movements of organisms: it's time to abandon the Lévy foraging hypothesis (2015, methodology): “Such a process has been referred to as ‘scaling up’ by a number of authors (Morales & Ellner 2002; Schick et al. 2008; Reynolds 2012d).”
Competition, predation, and migration: Individual choice patterns of Serengeti migrants captured by hierarchical models (2014, background): “Progress in this field requires discerning the key factors that influence the choice patterns of individual animals within a population (Alerstam 2006, Schick et al. 2008, Morales et al. 2010).”
Quantifying habitat use and preferences of pelagic seabirds using individual movement data: a review (2009, methodology): “Recently, Schick et al. (2008) proposed incorporating RSFs and SSMs in a hierarchical Bayesian framework, effectively modeling a moving animal’s behavioral response to a habitat map centered on the present location (see also Christ et al. 2008).”
Biologging technologies: new tools for conservation. Introduction (2010, methodology): “…to interpret these 2 Bograd et al.: Biologging technologies: Introduction data have yielded powerful new tools for understanding animal behavior (Fauchald & Tveraa 2003, Jonsen et al. 2003, 2005, 2007, Tremblay et al. 2006, 2009, Bradshaw et al. 2007, Patterson et al. 2008, Schick et al. 2008).”
Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. (2011, background): “…(or remote-sensing device) does not necessarily represent relevant heterogeneity to a particular species group; cover types that we can distinguish are not necessarily functionally different for that species group and vice versa (Lima & Zollner 1996; Charrier et al. 1997; Schick et al. 2008).”
Combining resource selection and movement behavior to predict corridors for Canada lynx at their southern range periphery (2013, background): “Ideally, movement studies elucidate the behavioral response of organisms to environmental heterogeneity (Schick et al., 2008).”