Search and foraging behaviors from movement data: A comparison of methods

Abstract

Search behavior is often used as a proxy for foraging effort within studies of animal movement, despite it being only one part of the foraging process, which also includes prey capture. While methods for validating prey capture exist, many studies rely solely on behavioral annotation of animal movement data to identify search and infer prey capture attempts. However, the degree to which search correlates with prey capture is largely untested. This study applied seven behavioral annotation methods to identify search behavior from GPS tracks of northern gannets (Morus bassanus), and compared outputs to the occurrence of dives recorded by simultaneously deployed time–depth recorders. We tested how behavioral annotation methods vary in their ability to identify search behavior leading to dive events. There was considerable variation in the number of dives occurring within search areas across methods. Hidden Markov models proved to be the most successful, with 81% of all dives occurring within areas identified as search. k‐Means clustering and first passage time had the highest rates of dives occurring outside identified search behavior. First passage time and hidden Markov models had the lowest rates of false positives, identifying fewer search areas with no dives. All behavioral annotation methods had advantages and drawbacks in terms of the complexity of analysis and ability to reflect prey capture events while minimizing the number of false positives and false negatives. We used these results, with consideration of analytical difficulty, to provide advice on the most appropriate methods for use where prey capture behavior is not available. This study highlights a need to critically assess and carefully choose a behavioral annotation method suitable for the research question being addressed, or resulting species management frameworks established.

Divergent foraging strategies during incubation of an unusually wide-ranging seabird, the Murphy’s petrel

“…Nonetheless, our results suggest that while Murphy’s petrels do conduct ARS, the majority of prey search and capture appears to take place in long directed movement phases. That birds make regular landings without conducting stereotypic ARS behaviour emphasises that it may not always be suitable to infer foraging modes from behavioural classification of step lengths and turning angles alone (Bennison et al 2017). …”

Marine hotspots of activity inform protection of a threatened community of pelagic species in a large oceanic jurisdiction

“…To identify the most critical areas within the EEZ, we first calculated the proportion of time that each species spent in a unit area in each given season and used these species-level metrics of the intensity of space use to estimate patterns of spatial association. Although birds and seals commute, forage and rest at sea, and these behaviours could be distinguished by tracking data (Bennison et al, 2018), we deliberately used all offshore tracking data because all areas where animals spend significant proportions of time are significant for management, regardless of the particular behaviour displayed in an area.…”

Tidal drift removes the need for area-restricted search in foraging Atlantic puffins

“…15: 20190208 ROMS maximum tide velocity (2.3 m s 21 ) were correlated to account for potential periods of flight occurring within 15-min fixes. Speed thresholds produced from movement datasets were used to determine behaviour[33], using the midpoint between mean puffin flight speed (13.2 m s 21 ) [34-36] and peak current velocity (2.3 m s 21 ) to differentiate flight and surface behaviours as both could occur within 15-min relocations.Dive data were retrieved from two TDR deployments (due to GPS tag failure, only one TDR deployment had accompanying location data) in 2017 and from three Ecotone tags in 2018. TDR data were reduced to a time series of dives consisting of dive depth (metres below the surface) and dive duration (seconds).…”