DOI: 10.5061/dryad.2ngf1vhw1
title: Heritable variation in thermal profiles is associated with reproductive success in the world’s largest bird

description: Organisms inhabiting extreme thermal environments, such as desert birds,
 have evolved spectacular adaptations to thermoregulate during hot and cold
 conditions. However, our knowledge of selection for thermoregulation and
 the potential for evolutionary responses is limited, particularly for
 large organisms experiencing extreme temperature fluctuations. Here we use
 thermal imaging to quantify selection and genetic variation in
 thermoregulation in ostriches (Struthio camelus), the world’s largest bird
 species that is experiencing increasingly volatile temperatures. We found
 that females that are better at regulating their head temperatures
 (‘thermoregulatory capacity’) had higher egg-laying rates under hotter
 conditions. Thermoregulatory capacity was both heritable and showed
 signatures of local adaptation: females originating from more
 unpredictable climates were better at regulating their head temperatures
 in response to temperature fluctuations. Together these results reveal
 that past and present evolutionary processes have shaped genetic variation
 in thermoregulatory capacity, which appears to protect critical organs,
 such as the brain, from extreme temperatures during reproduction.
description: General information and field setting 
 Data on head and neck surface
 temperatures of ostriches. For several years, we took repeated thermal
 images of individually marked ostriches in a pedigreed population at a
 research farm in the Western Cape Province in South Africa. We also
 recorded ambient temperatures at the time of each picture, allowing us to
 relate surface temperatures to ambient air temperatures.   Each year, from 2012 to 2017 and
 during October to December, we took 2744 pictures of 423 females between 5
 am and 6 pm (average number of images per female = 6.5). This dataset was
 designed to maximize the number of individuals with repeated measures
 across years, in order to characterize individual thermal profiles across
 different thermal environments. Consequently, there was little repeated
 sampling within days (8 % of the pictures). 
description: # Heritable variation in thermal profiles is associated with reproductive
 success in the world’s largest bird
 [https://doi.org/10.5061/dryad.2ngf1vhw1](https://doi.org/10.5061/dryad.2ngf1vhw1) Data on head and neck surface temperatures of ostriches using thermal image cameras. For several years, we took repeated thermal images of individually marked ostriches in a pedigreed population at a research farm in the Western Cape Province in South Africa. We also recorded ambient temperatures at the time of each picture, allowing us to relate surface temperatures to ambient air temperatures. From 2012 to 2017 during October to December, we took 2744 pictures of 423 females between 5 am and 6 pm (average number of images per female = 6.5). This dataset was designed to maximize the number of individuals with repeated measures across years, in order to characterize individual thermal profiles across different thermal environments. Consequently, there was little repeated sampling within days (8 % of the pictures). Images of the ostriches in the enclosures were taken using an infrared thermography camera (H2640, NEC Avio Infrared Technologies; purchased from the company Senso-Test in Sweden). Pictures were taken in the field, usually from distances between 2 m and 25 m. We regularly calibrated the thermal camera against a black body during our field sessions, following the instructions from the camera supplier, which also provided regular recalibration services of our equipment. Images that were out of focus were discarded prior to analysis, and we used the software InfRec Analyzer to draw separate polygons within the head and neck regions of the ostrich in each image. The average temperature of these polygons was extracted as individual head and neck surface temperatures, respectively. We used the same procedures and default software settings as in our previous work (Svensson & Waller, 2013; Svensson *et al.*, 2020), which assumes an emissivity of 1. Biological structures, such as bird skin and feathers, typically have emissivity values ranging between 0.94 -1.0 (Gerken *et al.*, 2006; Yahav & Giloh, 2012). However, the exact emissivity value used does not change our results as we focused on relative temperature measures that are independent of emissivity values. Hourly air temperatures were measured at a weather station positioned 600 m from the study populations. We fitted a cubic spline to the hourly temperature estimates of each day using the R-package *mgcv* v.1.8 (Wood, 2004), from which we extracted the predicted air temperature at the time-points when thermal images were taken. **References** Gerken, M., Afnan, R. & Dörl, J. (2006) Adaptive behaviour in chickens in relation to thermoregulation. *Poultry Science*, **70**, 199–207. Svensson, E.I. & Waller, J.T. (2013) Ecology and sexual selection: evolution of wing pigmentation in calopterygid damselflies in relation to latitude, sexual dimorphism and speciation. *American Naturalist*, **182**, E174–E195. Svensson, E.I., Gomez-Llano, M.A. & Waller, J.T. (2020) Selection on phenotypic plasticity favors thermal canalization. *Proceedings of the National Academy of Sciences of the United States of America*, **117**, 29767–29774. Yahav, S. & Giloh, M. (2012) Infrared Thermography - Applications in Poultry Biological Research. In *Infrared Thermography* (ed. by Prakash, R.V.). InTech. Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation for generalized additive models. *Journal of the American Statistical Association*, **99**, 673–686. ## Description of the data and file structure The dataset is a CSV file with individual ostrich records (thermal image information on a given date), with the following columns and variables: * **ID:** a variable denoting individual ID (unique) * **animal:** a variable denoting individual ID for the link to the pedigree (unique; identical to ID) * **sex:** a categorical variable denoting if the individual was male or female (F) or male (M)) * **date:** date when the individual was photographed (format: DD/MM/YY) * **year:** year when the individual was photographed (2012-2017; format 1Year) * **Pop:** a categorical variable denoting which population the individual belongs to (ZB, SAB, Hybrid, KR) * **NeckTemp:** neck temperature of the individual (measured in °C) * **HeadTemp:** head temperature of the individual (measured in °C) * **Temp:** ambient air temperature at the local weather station when the individual was photographed (measured in °C) * **Daytime:** day-time when the picture was taken (continuous in hours) * **enclosure:** a categorical variable denoting the enclosure where the individual was photographed * **TempCat:** air temperature category used for character state models (factorial: Benign, Cold or Hot) * **TempDir:** direction of air temperature change from optimum temperature (factorial: increasing or decreasing) * **TempCon:** absolute air temperature change from optimum temperature. Values are standardized to be between 0 and 1. * **Direction:** identical to TempDir but with different naming, increasing = hot and decreasing = cold * **Image:** the thermal image from which the data was extracted Detailed explanations for all these variables and how they are analyzed are given in our article and in our Supporting Material. **ID** and **animal** are identical and are unique to each individual; **sex** refers to if the animal was a male or female and year (2012-2017) is the year of measurement. **Pop** refers to population (3 categories), also called subspecies, from different parts of Africa. **NeckTemp** and **HeadTemp** refer to neck and head temperatures, respectively, whereas **Temp** refers to ambient (air) temperature at a nearby weather station, and **enclosure** refers to the specific fenced area where a given individual was when its thermal profile was recorded by us on a given day. The remaining pedigree data used to support the findings of this study are available from the Western Cape Department of Agriculture in South Africa (WCDA). Restrictions apply to the use of some of these data, which are thus not publicly available. These data are however available from the WCDA upon reasonable request. ## Sharing/Access information Links to other publicly accessible locations of the data: https://osf.io/p94ce ## Code/Software We used the software InfRec Analyzer to draw separate polygons within the head and neck regions of the ostrich in each image and to obtain estimates of surface temperatures of the head and the neck. For the analyses of individual thermal image data, we combined these individual thermal profiles with pedigree information, constructed and ran generalized linear mixed models (GLMMs) in R v.3.6.0 (R Core Team, 2020) using the Bayesian framework implemented in the R-package MCMCglmm v.2.29 (Hadfield, 2010). Code for analyses is available on Github: [www.github.com/abumadsen/thermal-images-ostrich/tree/main](http://www.github.com/abumadsen/thermal-images-ostrich/tree/main) **References** Hadfield, J.D. (2010) MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm *R* Package. *Journal of Statistical Software*, **33**, 1–22. R Core Team. (2020) *R: A language and environment for statistical computing*. R foundation for statistical computing, Vienna, Austria.