Dataset Information

Coupling instantaneous energy-budget models and behavioural mode analysis to estimate optimal foraging strategy: an example with wandering albatrosses.

ABSTRACT:

Background

How foragers move across the landscape to search for resources and obtain energy is a central issue in ecology. Direct energetic quantification of animal movements allows for testing optimal foraging theory predictions which assumes that animals forage so as to maximise net energy gain. Thanks to biologging advances, we coupled instantaneous energy-budget models and behavioural mode analysis to test optimal foraging theory predictions on wandering albatross Diomedea exulans during the brooding period. Specifically, the instantaneous energy-budget model considered the energetic balance (i.e., the difference between empirical energy gain data and modelled energy expenditure via heart rate values) along the trajectory of a given individual. Four stereotypic instantaneous behavioural modes were identified based on trajectory properties (e.g., speed and turning angle) by applying a new algorithm called Expectation Maximization Binary Clustering. Previous studies on this species have shown that foraging-in-flight is the optimal foraging strategy during the incubation period when albatrosses undertake long-distance movements but no specific foraging strategy has been determined for shorter foraging movements (e.g., brooding period).

Results

The output of our energy-budget model (measured as net energy gain) highlighted the potential optimality of alternative search strategies (e.g., sit-and-wait) during brooding, when birds may be subjected to specific energetic trade-offs and have to adapt their foraging strategies accordingly. However, not all birds showed this pattern, revealing the importance of considering individual variability in foraging strategies, as well as any switching among strategies, before drawing population-level generalizations. Finally, our study unveils the importance of considering fine scale activities to make realistic estimates of trip energy expenditure for flying birds at sea.

Conclusions

The up-scaling of accurately measured fine-scale energy patterns is essential to quantify energy balances, and their fluctuations by season of different activities among individuals or populations. In particular, we offer new insights for the energetic quantification of the effect of changing oceanic winds on the biology of pelagic predators in the southern oceans.

SUBMITTER: Louzao M

PROVIDER: S-EPMC4267543 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Coupling instantaneous energy-budget models and behavioural mode analysis to estimate optimal foraging strategy: an example with wandering albatrosses.

Louzao Maite M Wiegand Thorsten T Bartumeus Frederic F Weimerskirch Henri H

Movement ecology 20140423 1

<h4>Background</h4>How foragers move across the landscape to search for resources and obtain energy is a central issue in ecology. Direct energetic quantification of animal movements allows for testing optimal foraging theory predictions which assumes that animals forage so as to maximise net energy gain. Thanks to biologging advances, we coupled instantaneous energy-budget models and behavioural mode analysis to test optimal foraging theory predictions on wandering albatross Diomedea exulans du ...[more]

PMID: 25520818

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Project description:Allocation decisions depend on an organism's condition which can change with age. Two opposite changes in life-history traits are predicted in the presence of senescence: either an increase in breeding performance in late age associated with terminal investment or a decrease due to either life-history trade-offs between current breeding and future survival or decreased efficiency at old age. Age variation in several life-history traits has been detected in a number of species, and demographic performances of individuals in a given year are influenced by their reproductive state the previous year. Few studies have, however, examined state-dependent variation in life-history traits with aging, and they focused mainly on a dichotomy of successful versus failed breeding and non-breeding birds. Using a 50-year dataset on the long-lived quasi-biennial breeding wandering albatross, we investigated variations in life-history traits with aging according to a gradient of states corresponding to potential costs of reproduction the previous year (in ascending order): non-breeding birds staying at sea or present at breeding grounds, breeding birds that failed early, late or were successful. We used multistate models to study survival and decompose reproduction into four components (probabilities of return, breeding, hatching, and fledging), while accounting for imperfect detection. Our results suggest the possible existence of two strategies in the population: strict biennial breeders that exhibited almost no reproductive senescence and quasi-biennial breeders that showed an increased breeding frequency with a strong and moderate senescence on hatching and fledging probabilities, respectively. The patterns observed on survival were contrary to our predictions, suggesting an influence of individual quality rather than trade-offs between reproduction and survival at late ages. This work represents a step further into understanding the evolutionary ecology of senescence and its relationship with costs of reproduction at the population level. It paves the way for individual-based studies that could show the importance of intra-population heterogeneity in those processes.

Project description:BackgroundIn highly seasonal environments, animals face critical decisions regarding time allocation, diet optimisation, and habitat use. In the Arctic, the short summers are crucial for replenishing body reserves, while low food availability and increased energetic demands characterise the long winters (9-10 months). Under such extreme seasonal variability, even small deviations from optimal time allocation can markedly impact individuals' condition, reproductive success and survival. We investigated which environmental conditions influenced daily, seasonal, and interannual variation in time allocation in high-arctic muskoxen (Ovibos moschatus) and evaluated whether results support qualitative predictions derived from upscaled optimal foraging theory.MethodsUsing hidden Markov models (HMMs), we inferred behavioural states (foraging, resting, relocating) from hourly positions of GPS-collared females tracked in northeast Greenland (28 muskox-years). To relate behavioural variation to environmental conditions, we considered a wide range of spatially and/or temporally explicit covariates in the HMMs.ResultsWhile we found little interannual variation, daily and seasonal time allocation varied markedly. Scheduling of daily activities was distinct throughout the year except for the period of continuous daylight. During summer, muskoxen spent about 69% of time foraging and 19% resting, without environmental constraints on foraging activity. During winter, time spent foraging decreased to 45%, whereas about 43% of time was spent resting, mediated by longer resting bouts than during summer.ConclusionsOur results clearly indicate that female muskoxen follow an energy intake maximisation strategy during the arctic summer. During winter, our results were not easily reconcilable with just one dominant foraging strategy. The overall reduction in activity likely reflects higher time requirements for rumination in response to the reduction of forage quality (supporting an energy intake maximisation strategy). However, deep snow and low temperatures were apparent constraints to winter foraging, hence also suggesting attempts to conserve energy (net energy maximisation strategy). Our approach provides new insights into the year-round behavioural strategies of the largest Arctic herbivore and outlines a practical example of how to approximate qualitative predictions of upscaled optimal foraging theory using multi-year GPS tracking data.

Dataset Information

Coupling instantaneous energy-budget models and behavioural mode analysis to estimate optimal foraging strategy: an example with wandering albatrosses.

Background

Results

Conclusions

Publications

Coupling instantaneous energy-budget models and behavioural mode analysis to estimate optimal foraging strategy: an example with wandering albatrosses.

Similar Datasets

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