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Taking movement data to new depths: Inferring prey availability and patch profitability from seabird foraging behavior.

ABSTRACT: Detailed information acquired using tracking technology has the potential to provide accurate pictures of the types of movements and behaviors performed by animals. To date, such data have not been widely exploited to provide inferred information about the foraging habitat. We collected data using multiple sensors (GPS, time depth recorders, and accelerometers) from two species of diving seabirds, razorbills (Alca torda, N = 5, from Fair Isle, UK) and common guillemots (Uria aalge, N = 2 from Fair Isle and N = 2 from Colonsay, UK). We used a clustering algorithm to identify pursuit and catching events and the time spent pursuing and catching underwater, which we then used as indicators for inferring prey encounters throughout the water column and responses to changes in prey availability of the areas visited at two levels: individual dives and groups of dives. For each individual dive (N = 661 for guillemots, 6214 for razorbills), we modeled the number of pursuit and catching events, in relation to dive depth, duration, and type of dive performed (benthic vs. pelagic). For groups of dives (N = 58 for guillemots, 156 for razorbills), we modeled the total time spent pursuing and catching in relation to time spent underwater. Razorbills performed only pelagic dives, most likely exploiting prey available at shallow depths as indicated by the vertical distribution of pursuit and catching events. In contrast, guillemots were more flexible in their behavior, switching between benthic and pelagic dives. Capture attempt rates indicated that they were exploiting deep prey aggregations. The study highlights how novel analysis of movement data can give new insights into how animals exploit food patches, offering a unique opportunity to comprehend the behavioral ecology behind different movement patterns and understand how animals might respond to changes in prey distributions.

SUBMITTER: Chimienti M

PROVIDER: S-EPMC5723613 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Taking movement data to new depths: Inferring prey availability and patch profitability from seabird foraging behavior.

Chimienti Marianna M Cornulier Thomas T Owen Ellie E Bolton Mark M Davies Ian M IM Travis Justin M J JMJ Scott Beth E BE

Ecology and evolution 20171025 23

Detailed information acquired using tracking technology has the potential to provide accurate pictures of the types of movements and behaviors performed by animals. To date, such data have not been widely exploited to provide inferred information about the foraging habitat. We collected data using multiple sensors (GPS, time depth recorders, and accelerometers) from two species of diving seabirds, razorbills (Alca torda, N = 5, from Fair Isle, UK) and common guillemots (Uria aal ...[more]

PMID: 29238552

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Project description:BackgroundRecent technological advances have resulted in low-cost GPS loggers that are small enough to be used on a range of seabirds, producing accurate location estimates (± 5 m) at sampling intervals as low as 1 s. However, tradeoffs between battery life and sampling frequency result in studies using GPS loggers on flying seabirds yielding locational data at a wide range of sampling intervals. Metrics derived from these data are known to be scale-sensitive, but quantification of these errors is rarely available. Very frequent sampling, coupled with limited movement, can result in measurement error, overestimating movement, but a much more pervasive problem results from sampling at long intervals, which grossly underestimates path lengths.MethodsWe use fine-scale (1 Hz) GPS data from a range of albatrosses and petrels to study the effect of sampling interval on metrics derived from the data. The GPS paths were sub-sampled at increasing intervals to show the effect on path length (i.e. ground speed), turning angles, total distance travelled, as well as inferred behavioural states.ResultsWe show that distances (and per implication ground speeds) are overestimated (4% on average, but up to 20%) at the shortest sampling intervals (1-5 s) and underestimated at longer intervals. The latter bias is greater for more sinuous flights (underestimated by on average 40% when sampling > 1-min intervals) as opposed to straight flight (11%). Although sample sizes were modest, the effect of the bias seemingly varied with species, where species with more sinuous flight modes had larger bias. Sampling intervals also played a large role when inferring behavioural states from path length and turning angles.ConclusionsLocation estimates from low-cost GPS loggers are appropriate to study the large-scale movements of seabirds when using coarse sampling intervals, but actual flight distances are underestimated. When inferring behavioural states from path lengths and turning angles, moderate sampling intervals (10-30 min) may provide more stable models, but the accuracy of the inferred behavioural states will depend on the time period associated with specific behaviours. Sampling rates have to be considered when comparing behaviours derived using varying sampling intervals and the use of bias-informed analyses are encouraged.

Project description:Narrow foraging specialization may increase the vulnerability of marine predators to climate change. The red-legged kittiwake (Rissa brevirostris) is endemic to the Bering Sea and has experienced drastic population fluctuations in recent decades, presumably due to climate-driven changes in food resources. Red-legged kittiwakes are presumed to be a nocturnal surface-foraging seabird that feed almost entirely on deep water Myctophidae fishes. However, there is little empirical evidence confirming their nocturnal foraging activity during the breeding season. This study investigated the foraging behavior of red-legged kittiwakes by combining GPS tracking, accelerometry, and dietary analyses at the world's largest breeding colony of red-legged kittiwakes on St. George I. GPS tracking of 5 individuals revealed that 82.5% of non-flight behavior (including foraging and resting) occurred over the ocean basin (bottom depth >1,000 m). Acceleration data from 4 birds showed three types of behaviors during foraging trips: (1) flight, characterized by regular wing flapping, (2) resting on water, characterized by non-active behavior, and (3) foraging, when wing flapping was irregular. The proportions of both foraging and resting behaviors were higher at night (14.1 ± 7.1% and 20.8 ± 14.3%) compared to those during the day (6.5 ± 3.0% and 1.7 ± 2.7%). The mean duration of foraging (2.4 ± 2.9 min) was shorter than that of flight between prey patches (24.2 ± 53.1 min). Dietary analyses confirmed myctophids as the dominant prey (100% by occurrence and 98.4 ± 2.4% by wet-weight). Although the sample size was limited, these results suggest that breeding red-legged kittiwakes concentrated their foraging on myctophids available at the surface during nighttime in deep water regions. We propose that the diel patterns and ephemeral nature of their foraging activity reflected the availability of myctophids. Such foraging specialization may exacerbate the vulnerability of red-legged kittiwakes to climate change in the Bering Sea.

Dataset Information

Taking movement data to new depths: Inferring prey availability and patch profitability from seabird foraging behavior.

Publications

Taking movement data to new depths: Inferring prey availability and patch profitability from seabird foraging behavior.

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