Data from: A challenge of warmer temperate winters: Long-term exposure to rain in cold temperatures drives higher thermogenic investment in a captive songbird
Data files
Nov 24, 2025 version files 69.39 KB
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Msum_and_BMR_w_food_and_activity.csv
13.43 KB
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README.md
5.50 KB
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Weekly_Data__Activity__Food_intake__Fat__Muscle__Mass.csv
41.02 KB
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Wet_Tissue_Mass__Enzyme_Activity.csv
9.44 KB
Abstract
Long-term cold exposure induces many endotherms to invest in metabolic heat production, but how precipitation impacts thermogenic capacity in the context of different thermal conditions is largely undescribed in animals. In this study, songbirds (red crossbills; Loxia curvirostra) were held in warm (21 °C) or cold (6 °C) temperatures and either dry or rain precipitation treatments while experiencing a more northern or southern latitude photoperiod. We hypothesized that individuals experiencing winter rain would increase investment in thermogenic capacity, metabolic machinery, and catabolic enzymes to cope with increased thermogenic demands. Food intake and activity were monitored weekly, summit (Msum) and basal metabolic rates were measured in November, January, and February, and tissues were collected at the end of the study. Individuals held in cold rain treatments achieved the highest summit metabolic rate and had higher food intake, subcutaneous fat, heart mass, and metabolic enzyme activities. Further, birds in dry conditions showed slight disinvestment of Msum in late winter, while birds in rain treatments maintained thermogenic investment. Our results suggest that cold rain induces increased investment in thermogenic capacity across the winter season. Thus, rain may offset the potential thermal benefits that warming winters would otherwise provide to small-bodied endotherms.
Dataset DOI: 10.5061/dryad.6wwpzgncf
Description of the data and file structure
In this experiment data was collected over the course of four months on 48 individual birds to determine how cold rain impacts thermogenic capacity and avian physiology. Birds were randomly assigned treatments of cold rain, cold dry, warm rain, and warm dry, and were assigned an ID number for the course of the experiment. Metabolic measurements were measured three times throughout the experiment, food intake & activity rates were measured daily and then averaged weekly, and morphometric data were collected once per week.
Files and variables
File: Msum_and_BMR_w_food_and_activity.csv
Description: Month and its interaction with weather variables were included as fixed effects to detect seasonal changes in Msum and BMR. We include log transformed mass in all metabolic models.
Variables
* Date: Date of metabolic measurement
* Month: Month of metabolic measurement (Measurements in late december and early january were combined as January measurements)
* Bird ID: Individual ID
* Temperature: Temperature treatment of Cold or Warm
* Precipitation: Precipitation treatment of Rain or Dry
* Daylength: Daylength treatment of Short or Long
* Gonadal Sex: Sex of Individual
* Mass: Mass of individual (g)
* Abdominal Fat: Abdominal fat score (scale of 0-5)
* Furnicular Fat: Furnicular fat score (scale of 0-5)
* Bairlein Muscle Size: Muscle size (scale of 0-3)
* MSUM: Summit metabolic rate (mL O2 min -1)
* BMR: Basal metabolic rate (mL O2 min -1)
* Food Intake: Average daily food intake (g)
* Activity: Average daily activity rate (total number of movements per day)
File: Weekly_Data__Activity__Food_intake__Fat__Muscle__Mass.csv
Description: Experiment week and its interaction with weather variables were included to detect changes across time. Individual ID was included as a random effect. GAMMs were used to account for nonlinearity in food intake and daily activity across weeks.
Variables
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Week: Week of the experiment
* Temperature: Temperature treatment of Cold or Warm
* Precipitation: Precipitation treatment of Rain or Dry
* Daylength: Daylength treatment of Short or Long
* Bird ID: Individual ID
* Gonadal Sex: Sex of Individual
* Food Intake: Average daily food intake (g)
* Activity: Average daily activity rate (total number of movements per day)
* Abdominal Fat: Abdominal fat score (scale of 0-5)
* Furnicular Fat: Furnicular fat score (scale of 0-5)
* Subcutaneous Fat: Subcutaneous fat score. Sum of Abdominal fat and furnicular fat (scale of 0-10)
* Bairlein Muscle Size: Muscle size (scale of 0-3)
File: Wet_Tissue_Mass__Enzyme_Activity.csv
Description: We included BMR and Msum measurements from the February sampling date to determine if metabolic traits were associated with wet mass of heart, pectoralis, liver, intestine, kidney, gastrocnemius, brain and lung. Body size (keel and tarsus measurements) determined by a PCA was used to control for size differences amongst individuals in the categorical fixed effects models.
Variables:
* Month: Month of metabolic measurement (Measurements in late december and early january were combined as January measurements)
* Bird ID: Individual ID
* Temperature: Temperature treatment of Cold or Warm
* Precipitation: Precipitation treatment of Rain or Dry
* Daylength: Daylength treatment of Short or Long
* Gonadal Sex: Sex of Individual
* Body Size: PCA values from keel and tarsus measurements upon capture
* Mass: Mass of individual (g)
* Abdominal Fat: Abdominal fat score (scale of 0-5)
* Furnicular Fat: Furnicular fat score (scale of 0-5)
* Bairlein Muscle Size: Muscle size (scale of 0-3)
* MSUM: Summit metabolic rate (mL O2 min -1)
* BMR: Basal metabolic rate (mL O2 min -1)
* Heart Mass: Wet heart mass (g)
* PM Mass: Wet pectoralis muscle mass (g)
* Liver Mass: Wet liver tissue mass (g)
* Intestine Mass: Wet intestine mass (g)
* Lung Mass: Wet lung mass (g)
* Liver CS Activity: Liver tissue citrate synthase activity (units min -1)
* Heart CS Activity: Heart tissue citrate synthase activity (units min -1)
* Pect CS Activity: Pectoralis muscle citrate synthase activity (units min -1)
* Pect HOAD Activity: Pectoralis muscle HOAD activity (units min -1)
* Heart HOAD Activity: Heart tissue HOAD activity (units min -1)
* Liver HOAD Activity: Liver tissue HOAD activity (units min -1)
* Brain Mass: Wet brain mass (g)
* Kidney Mass: Wet kidney mass (g)
* Thigh Mass: Wet thigh mass (g)
Note: "NA" means data are not available.
Code/software
All statistical analyses were conducted in R (version 2023.10.31). Linear models, linear mixed models (“lme4” R package) and general additive mixed models (“mgcv” R package) fit by restricted maximum likelihood were used to evaluate dependent variables. Plots of dependent variables and model residuals were visually checked and verified to be normally distributed using skewness and kurtosis. We used a = 0.05 for assessing significance and the top models were selected based on the lowest AIC values when comparing between full and reduced models.