Proximate and evolutionary sources of variation in offspring energy expenditure in songbirds
Mitchell, Adam; Wolf, Blair; Martin, Thomas (2022), Proximate and evolutionary sources of variation in offspring energy expenditure in songbirds, Dryad, Dataset, https://doi.org/10.5061/dryad.gb5mkkwr0
Aim: Understanding variation in offspring energy expenditure is important because energy is critical for growth and development. Weather may exert proximate effects on offspring energy expenditure, but in altricial species these might be masked by parental care and huddling with siblings. Such effects are particularly important to understand given changing global weather patterns, yet studies of wild offspring in the presence of parental care are lacking. Offspring energy expenditure may also vary among species due to evolved responses to environmental selection pressures, requiring studies at both proximate and ultimate levels.
Location: USA, South Africa, Malaysia.
Time period: 2016-2019.
Major taxa studied: Songbirds.
Methods: We used the doubly-labeled water technique to estimate nestling daily energy expenditure of 54 songbird species across three continents. We used Bayesian phylogenetic mixed models to test proximate and evolutionary causes of variation in offspring energy expenditure while accounting for phylogeny and phylogenetic uncertainty.
Results: Offspring energy expenditure increased with more rainfall and colder air temperatures, but decreased among offspring in broods with more siblings. Across species, nestling and adult mortality, but not growth rate, were positively associated with offspring energy use.
Main conclusions: Weather had clear proximate effects on offspring energy expenditure and parents were either unable or unwilling to fully offset these effects. However, the decrease in offspring energy use when huddling with more siblings demonstrated a modulating effect of life history traits. For example, high nest predation rates favor reduced parental care and can force offspring to spend more energy coping with environmental conditions. Furthermore, reduced energy expenditure is thought to facilitate increased longevity, which is increasingly realized with lower extrinsic mortality rates, providing an explanation for the positive association between adult mortality and offspring energy expenditure. Ultimately, both proximate and evolutionary influences need to be considered to better understand causes of offspring energetics.
We used the two-sample doubly-labeled water technique administered on nestling songbirds of 54 species across 3 continents. Nestlings were sampled on pin break, the day the 8th primary feathers broke from their sheaths. Blood samples were spun to separate plasma, and flame-sealed in the field. At the end of each season, samples were microdistilled to pure water for laboratory analyses. Isotope concentrations were analyzed using a Picarro L1102-I or a LGR DLT-100 liquid water isotope analyzer (Picarro Inc., Santa Clara, CA, USA) at the University of New Mexico. Data were normalized to the IAEA water standard VSMOW. We estimated CO2 production using the equation by Nagy (1983, Eqn. 1). CO2 production was then converted to DEE using conversion factors based 26.3 J/ml CO2 for Arizona, and 26.7 J/ml CO2 for South Africa and Malaysia. Air temperature and rainfall were collected in Arizona and South Africa using an Onset data logging rain gauge with a tipping bucket and air temperature logger. Weather variables in South Africa were provided by Eskom Holdings from a meteorological station at the field site. To account for the linear decrease in temperature with increasing elevation, we used a predicted temperature value at the Malaysia site based on the elevation of each nest and the lapse rate of 0.55°C*100 m-1. Growth rate constant K estimates came from Martin 2015, nest predation rates were modeled using the logistic exposure method from Martin 2015. Adult mortality estimates came from Martin et al. 2015a and Martin et al. 2017. We removed far outliers that were ± 3*IQR for each species following Tukey’s boxplot rule for far outliers.
Data file shows each data point for daily energy expenditure of nestling songbirds. Sites are AZ (Arizona), SA (South Africa), and MY (Malaysia). Nest-ID is the unique nest identifier. DEE and nestling body mass are log10-transformed. Brood_Size is the number of nestlings in the nest during the 24 or 48-hour sampling interval. Min_Temp is the lowest temperature over the 24 or 48 hour sampling period in °C. Sum_Rain is the total rainfall over the 24 or 48-hour sampling period in mm. nstl_pred is the daily nest predation rate estimated per species. k_mass is the growth rate constant K for body mass estimated per species. Mort is the annual mortality rate estimated per species. Animal is the latin binomial name used for phylogenetic analyses. All variables with an underscore_s (e.g., L_Mass_s) have been mean-centered and scaled to units of standard deviation.
National Geographic Society, Award: 9875-16
National Science Foundation, Award: DEB-1241041, DEB-1651283, IOS-1656120, IOS-1656273