A movement ecology paradigm for unifying organismal movement research

By Ran Nathan, Wayne M. Getz, E. Revilla, M. Holyoak, R. Kadmon, David Saltz, Peter E. Smouse. Proceedings of the National Academy of Sciences of the United States of America, 2008

2,781 citations recorded by the source corpus.

Subfields: Ecology, Ecology, Evolution, Behavior and Systematics, Genetics

View Paper: https://www.semanticscholar.org/paper/04e5207b064f47bd4b0b5b29a72c5abd047c40cb

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Citations in the corpus

Satellite remote sensing for applied ecologists: opportunities and challenges (2014, background): “The combination of detailed data on animal movement with frequent SRS-based information on environmental conditions indeed makes it possible for a unified framework to explore the determinants of movement patterns at multiple spatial and temporal scales (Nathan et al. 2008).”
Ecological and Evolutionary Consequences of Environmental Change and Management Actions for Migrating Fish (2019, background): “However, recent technological developments in bio-logging have advanced the ability to obtain high-resolution data on fish movements, inform about internal and external drivers of movements, help illuminate the consequences of movements for individual performance and population fitness, and provide ”
Phenotypic response to environmental cues, orientation and migration costs in songbirds flying halfway around the world (2012, background): “Understanding the movement ecology of species requires a high spatiotemporal resolution of migration including the meteorological andmagnetic conditions encountered en route (Alerstam 2006; Nathan et al. 2008; Shamoun-Baranes et al. 2010).”
Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses (2018, background): “Nathan et al. (2008) introduced the movement ecology paradigm, that conceptually connects diﬀerent factors shaping the realized movement path of animals (e.g., the internal state of an animal, interaction with intra-and conspeciﬁcs, and varying environmental conditions).”
Using the movement patterns of reintroduced animals to improve reintroduction success (2014, background): “ger subsequent changes to the organism’s movement behavior (Fryxell et al., 2008; Nathan et al., 2008).”
Plant functional connectivity – integrating landscape structure and effective dispersal (2017, positive): “For example, the movement ecology paradigm, which aims to unify research relating to different types of movement across species and scales, considers that a range of external factors can affect how and where organisms move (Nathan et al. 2008).”
Effect of local weather on butterfly flight behaviour, movement, and colonization: significance for dispersal under climate change (2011, background): “…for dispersal, and assume that dispersal propensity will increase as individuals of species fly over longer bout durations, increase their tendency to start flying, spend more time flying, and fly over longer distances (cf. Morales and Ellner 2002; Nathan et al. 2008; Van Dyck and Baguette 2005).”
Integrating dispersal proxies in ecological and environmental research in the freshwater realm (2017, background): “At the same time, dispersal is also one of the 51 most difficult phenomena to study even for a single individual or a single species in nature 52 (Bilton et al. 2001; Nathan et al. 2008).”
Lessons from integrating behaviour and resource selection: activity‐specific responses of African wild dogs to roads (2016, background): “Management efforts aimed at preserving landscape connectivity have thus skyrocketed, and the effect of natural and human-built landscape features on animal movement and resource selection has become a central issue in ecology and conservation (Turner, 1989; Nathan et al., 2008).”
Ecological connectivity research in urban areas (2015, background): “Functional Ecology © 2015 British Ecological Society goal best achieved through studies that integrate the internal and external processes that affect movement at multiple temporal and spatial scales (Nathan et al. 2008; Jeltsch et al. 2013).”
Difference in spatiotemporal patterns of wildlife road-crossings and wildlife-vehicle collisions (2012, background): “Animal movement patterns are the result of decision-making among behavioral trade-offs including an individual’s internal state, and its environment at different spatiotemporal scales (Johnson et al., 2002; Nathan et al., 2008).”
Regional and seasonal flight speeds of soaring migrants and the role of weather conditions at hourly and daily scales (2015, background): “We thus studied the influence of wind on flight after they decided how to compensate for side winds and, therefore, wind compensation decisions may account for small seasonal differences in regional behavior (Shamoun-Baranes et al. 2007, Nathan et al. 2008, Klaassen et al. 2011, Kemp et al. 2012).”
Phenological matching across hemispheres in a long‐distance migratory bird (2013, background): “How and why animals migrate and disperse over space and time is a poorly understood yet fundamental aspect of animal ecology (Nathan et al., 2008).”
Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology (2010, background): “…sophisticated tools that allow us to statistically distinguish between different movement modes in a GPS movement dataset (Morales et al. 2004; Nathan et al. 2008; Patterson et al. 2008; Schick et al. 2008), we only have a nascent idea of what animals were really doing from a behavioural…”