Can We Predict Foraging Success in a Marine Predator from Dive Patterns Only? Validation with Prey Capture Attempt Data

Predicting how climatic variations will affect marine predator populations relies on our ability to assess foraging success, but evaluating foraging success in a marine predator at sea is particularly difficult. Dive metrics are commonly available for marine mammals, diving birds and some species of fish. Bottom duration or dive duration are usually used as proxies for foraging success. However, few studies have tried to validate these assumptions and identify the set of behavioral variables that best predict foraging success at a given time scale. The objective of this study was to assess if foraging success in Antarctic fur seals could be accurately predicted from dive parameters only, at different temporal scales. For this study, 11 individuals were equipped with either Hall sensors or accelerometers to record dive profiles and detect mouth-opening events, which were considered prey capture attempts. The number of prey capture attempts was best predicted by descent and ascent rates at the dive scale; bottom duration and descent rates at 30-min, 1-h, and 2-h scales; and ascent rates and maximum dive depths at the all-night scale. Model performances increased with temporal scales, but rank and sign of the factors varied according to the time scale considered, suggesting that behavioral adjustment in response to prey distribution could occur at certain scales only. The models predicted the foraging intensity of new individuals with good accuracy despite high inter-individual differences. Dive metrics that predict foraging success depend on the species and the scale considered, as verified by the literature and this study. The methodology used in our study is easy to implement, enables an assessment of model performance, and could be applied to any other marine predator.

[1]  Sophie Bestley,et al.  Predicting feeding success in a migratory predator: integrating telemetry, environment, and modeling techniques. , 2010, Ecology.

[2]  H. Weimerskirch,et al.  Seasonal variation in oceanographic habitat and behaviour of white-chinned petrels Procellaria aequinoctialis from Kerguelen Island , 2010 .

[3]  Ruth M. Casper,et al.  The influence of diet on foraging habitat models: a case study using nursing Antarctic fur seals , 2010 .

[4]  Y. Naito,et al.  Krill-feeding behaviour in a chinstrap penguin compared to fish-eating in Magellanic penguins: a pilot study. , 2004 .

[5]  Deborah Austin,et al.  Stomach temperature telemetry reveals temporal patterns of foraging success in a free-ranging marine mammal. , 2006, The Journal of animal ecology.

[6]  Sabrina Fossette,et al.  Dive and beak movement patterns in leatherback turtles Dermochelys coriacea during internesting intervals in French Guiana. , 2008, The Journal of animal ecology.

[7]  E. Charnov.  Optimal foraging, the marginal value theorem. , 1976, Theoretical population biology.

[8]  Robert M. Suryan,et al.  Foraging destinations and marine habitat use of short-tailed albatrosses: A multi-scale approach using first-passage time analysis , 2006 .

[9]  Gerald L. Kooyman,et al.  Fur seal diving behaviour in relation to vertical distribution of krill , 1985 .

[10]  Daniel Fortin,et al.  Inference from habitat-selection analysis depends on foraging strategies. , 2010, The Journal of animal ecology.

[11]  Jaime A. Ramos,et al.  How area restricted search of a pelagic seabird changes while performing a dual foraging strategy , 2010 .

[12]  Deborah Austin,et al.  Linking movement, diving, and habitat to foraging success in a large marine predator. , 2006, Ecology.

[13]  J. Calambokidis,et al.  Insights into the Underwater Diving, Feeding, and Calling Behavior of Blue Whales from a Suction-Cup-Attached Video-Imaging Tag (CRITTERCAM) , 2007 .

[14]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[15]  Daniel P Costa,et al.  Time to eat: measurements of feeding behaviour in a large marine predator, the northern elephant seal Mirounga angustirostris. , 2009, The Journal of animal ecology.

[16]  F. Roquet,et al.  Successful foraging zones of southern elephant seals from the Kerguelen Islands in relation to oceanographic conditions , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.

[17]  Rory P. Wilson,et al.  In-depth studies of Magellanic penguin (Spheniscus magellanicus) foraging: can we estimate prey consumption by perturbations in the dive profile? , 2003 .

[18]  John Calambokidis,et al.  Kinematics of foraging dives and lunge-feeding in fin whales , 2006, Journal of Experimental Biology.

[19]  Y. Naito,et al.  Krill-feeding behaviour in a chinstrap penguin Pygoscelis antarctica compared with fish-eating in Magellanic penguins Spheniscus magellanicus: a pilot study , 2004 .

[20]  M. Hindell,et al.  A validated approach for supervised dive classification in diving vertebrates , 2008 .

[21]  Christophe Guinet,et al.  A maximum likelihood approach for identifying dive bouts improves accuracy, precision and objectivity , 2007 .

[22]  Y. Ropert‐Coudert,et al.  Lip-reading in remote subjects: an attempt to quantify and separate ingestion, breathing and vocalisation in free-living animals using penguins as a model , 2002 .

[23]  Scott A. Shaffer,et al.  A comparison of indirect measures of feeding behaviour based on ARGOS tracking data , 2007 .

[24]  Peter L. Boveng,et al.  Monitoring the Prey-Field of Marine Predators: Combining Digital Imaging With Datalogging Tags , 2002 .

[25]  Rory P. Wilson,et al.  Penguins predict their performance , 2003 .

[26]  J A Swets,et al.  Measuring the accuracy of diagnostic systems. , 1988, Science.

[27]  Nicholas J. Gales,et al.  FAST, SAFE, FIELD‐PORTABLE GAS ANESTHESIA FOR OTARIIDS , 1998 .

[28]  Yves Handrich,et al.  Measuring foraging activity in a deep-diving bird: comparing wiggles, oesophageal temperatures and beak-opening angles as proxies of feeding , 2010, Journal of Experimental Biology.

[29]  Burt P. Kotler,et al.  Behavioral Indicators for Conserving Mammal Diversity , 2009, Annals of the New York Academy of Sciences.

[30]  M. Hindell,et al.  Determining feeding events and prey encounter rates in a southern elephant seal : a method using swim speed and stomach temperature , 2008 .

[31]  P. Koubbi,et al.  Day and night mesopelagic fish assemblages off the Kerguelen Islands (Southern Ocean) , 2000, Polar Biology.

[32]  S. Bograd,et al.  Vertical and horizontal habitat preferences of post-nesting leatherback turtles in the South Pacific Ocean. , 2011 .

[33]  C. A. Bosta,et al.  Changes in dive profiles as an indicator of feeding success in king and Adélie penguins , 2007 .

[34]  G. J. Marshall,et al.  Crittercam : An animal-borne imaging and data logging system , 1998 .

[35]  I. Boyd,et al.  Swimming speed and allocation of time during the dive cycle in Antarctic fur seals , 1995, Animal Behaviour.

[36]  C. Guinet,et al.  Fish prey of Antarctic fur seals Arctocephalus gazella at Ile de Croy, Kerguelen , 1997, Polar Biology.

[37]  Henri Weimerskirch,et al.  Does Prey Capture Induce Area‐Restricted Search? A Fine‐Scale Study Using GPS in a Marine Predator, the Wandering Albatross , 2007, The American Naturalist.

[38]  P. Knoppien,et al.  Predators with two modes of searching: A mathematical model* , 1985 .

[39]  Y. Naito,et al.  A comparison of prey richness estimates for Weddell seals using diving profiles and image data , 2005 .

[40]  Y. Naito,et al.  Time/depth usage of Adélie penguins: an approach based on dive angles , 2001, Polar Biology.

[41]  F. Harrell,et al.  Regression modelling strategies for improved prognostic prediction. , 1984, Statistics in medicine.

[42]  Ian D. Jonsen,et al.  Identifying leatherback turtle foraging behaviour from satellite telemetry using a switching state-space model , 2007 .

[43]  H. Weimerskirch,et al.  Conserving pelagic habitats: seascape modelling of an oceanic top predator , 2011 .

[44]  David R. Anderson,et al.  Multimodel Inference , 2004 .

[45]  Paul M. Thompson,et al.  Using marine mammal habitat modelling to identify priority conservation zones within a marine protected area , 2009 .

[46]  Yasuhiko Naito,et al.  Dive depths of Weddell seals in relation to vertical prey distribution as estimated by image data , 2003 .

[47]  Yasuhiko Naito,et al.  Validation of a device for accurate timing of feeding events in marine animals , 2009, Polar Biology.

[48]  C. Guinet,et al.  Antarctic fur seals foraging in the Polar Frontal Zone: inter-annual shifts in diet as shown from fecal and fatty acid analyses , 2002 .

[49]  D. Oro,et al.  Oceanographic habitat of an endangered Mediterranean procellariiform: implications for marine protected areas. , 2006, Ecological applications : a publication of the Ecological Society of America.

[50]  Michael A. Fedak,et al.  TWO APPROACHES TO COMPRESSING AND INTERPRETING TIME‐DEPTH INFORMATION AS AS COLLECTED BY TIME‐DEPTH RECORDERS AND SATELLITE‐LINKED DATA RECORDERS , 2001 .

[51]  M. Hindell,et al.  Variability in the diving activity of Antarctic fur seals, Arctocephalus gazella, at Iles Kerguelen , 2002, Polar Biology.

[52]  A Behavioral Indicator of Prey Patch Richness Derived From Diving Behavior: the Proportion of Residence Time to the Standard Time , 2007 .

[53]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[54]  Joachim Plötz,et al.  SHORT COMMUNICATION CAN WE DETERMINE WHEN MARINE ENDOTHERMS FEED? A CASE STUDY WITH SEABIRDS , 1992 .

[55]  Y. Mori.  The Optimal Patch Use in Divers: Optimal Time Budget and the Number of Dive Cycles During Bout , 1998 .

[56]  Weiqi Luo,et al.  Analysing ecological data , 2009 .

[57]  Yan Ropert-Coudert,et al.  Foraging strategies and prey encounter rate of free-ranging Little Penguins , 2006 .

[58]  Pascal Monestiez,et al.  Prey capture attempts can be detected in Steller sea lions and other marine predators using accelerometers , 2010, Polar Biology.