Plunge-diving into dynamic body acceleration and energy expenditure in the Peruvian booby

Abstract

Daily energy expenditure (DEE) is the result of decisions on how to allocate time among activities (resting, commuting and foraging) and the energy costs of those activities. Dynamic body acceleration (DBA), which measures acceleration associated with movement, can be used to estimate DEE. Previous studies of DBA-DEE correlations in birds were carried out on species foraging below their thermoneutral zone, potentially decoupling the DBA-DEE relationship. We used doubly labelled water (DLW) to validate the use of DBA on plunge-diving seabirds, Peruvian boobies (Sula variegata), foraging in waters above their thermoneutral zone (>19°C). Mass-specific DEEDLW in boobies was 1.12 kJ day-1 g-1, and higher in males than in females. DBA alone provided the best fitting model to estimate mass-specific DEEDLW compared with models partitioned per activity and time budget models. Nonetheless, the model parametrizing activity at and away from their onshore breeding colony was the most parsimonious (r=0.6). This r value, although high, is lower than that of all other avian studies, implying that temperature is not the main cause of DBA-DEE decoupling in birds. Time at the colony (∼80% of the day) was the largest contributor to DEE as it was the most time-consuming activity and involved nest defence. However, foraging was the most power-consuming activity (4.6 times higher activity-specific metabolic rate than resting at the colony), and commuting flight was higher than in other gliding seabirds. In short, DBA alone can act as a proxy for DEE, opening avenues to measure the conservation energetics of this seabird in the rapidly changing Peruvian Humboldt Current system.

Keywords: Accelerometry; Daily activity patterns; Doubly labelled water; Field metabolic rate; Flight costs.

Fig. 1.

Behavioural classification of Peruvian boobies. (A) Sample full track of one bird with the Hidden Markov Model (HMM) behavioural classifications showing ‘colony’ (grey), ‘commuting’ (yellow), ‘foraging’ (blue) and ‘resting’ (green) for the respective values (from top to bottom) of diving depth, distance to the colony, step length and wingbeat frequency. (B) Mapped track with HMM behavioural classifications, where black lines represent ‘commuting’. HMM parameters for each behavioural class are shown in Table 1.

Fig. 2.

Relationship between measured and predicted daily energy expenditure for the top three best models from the AICc ranking with the full dataset. Daily energy expenditure from the doubly labelled water method (DEE_DLW) and (A) predicted DEE from the model for daily dynamic body acceleration (DBA), (B) predicted DEE from the model parametrizing mean daily DBA of activity in the colony (DBA_col) and mean daily DBA activity away from the colony (commuting, foraging and resting: DBA_com,for,rest) and (C) predicted DEE from the model parametrizing mean daily DBA at the colony and resting and mean daily DBA commuting and foraging (n=20). Mass-specific DEE_DLW data for males and females were combined. Dashed blue line represents equal distribution of values for both axes.

Fig. 3.

Mean daily proportion of time spent in each activity by Peruvian boobies in Guañape Norte Island in 2019. Filled circles represent means and semi-transparent circles (females) and triangle (males) are the individual values. Error bars represent s.e.m. (n=20).

Fig. 4.

Multispecies comparison of flight costs of 22 primarily gliding bird species. Gliding birds were as defined in Guigueno et al. (2019). The metabolic cost of flight was expressed in watts (kJ h⁻¹/3.6) and was calculated from activity-specific time budgets, and plotted against body mass (g). Peruvian boobies are indicated as a green diamond. All data were log₁₀-transformed. Shaded area represents the confidence intervals.