Heat stress reduces growth rate of red deer calf: Climate warming implications

Heat stress indices and physical environment data The most reliable method of assessing heat stress is by calorimetry techniques. Calorimetry measures the heat produced from metabolic activity, using direct or indirect methods [30]. The most extensively used indirect methods are those based on respirometry, which estimates metabolic activity by determining rates of O2 consumption and/or CO2 production of animals caged in respiration chambers. Respirometry techniques enable measuring changes in meta- bolic rate related to animal physiology, intake, diet composition, and experimental changes in the respiration chamber physical environment [31]. To overcome the logistic problems of using calorimetry techniques to simulate outdoor physical environment and assessing how they affect body condition, reproduction and animal production [4, 32], many indices and proxies of thermal stress that have been developed. Some proxies of thermal stress rely on changes in physiological behaviour, such as breath frequency and panting behaviour [33, 34, 35]. Other methods use indirect measurements of the energy expenditure and heat flux neces- sary to maintain homeothermy, based on operative temperature mechanical models [7, 8]. Among the thermal stress indices widely used are those that combine air temperature, air humidity and wind speed, on the basis that homeothermic species offset the exposure to high temperature by sweating, as when water evaporation occurs on the skin surface, the energy removed from the vaporized water reduces body temperature. Evaporation is highly reduced

when atmospheric water vapour is close to saturation, and increases with wind, as it facilitates the removal of water vapour from the air layer surrounding the skin, preventing the creation of insulating epiclimatic conditions on the skin surface [5]. We used meteorological data from the Spanish Ministry of Agriculture, Food and Environ- ment, supplied by SIAR regional service of Castilla-La Mancha (available at http://crea.uclm. es/siar/datmeteo/). Data came from the meteorological station of Albacete (38˚56’56.5"N 1˚ 53’53.3"W), only 2 km from the UCLM experimental deer farm and located at the same alti- tude. We used daily mean records across the study period of air temperature, relative humidity and wind speed, and global solar radiation accumulated per day (Eqs 1 and 2, below). There are many indices that attempt to express heat stress experienced by animals [5]. The most commonly used, with satisfactory results in a variety of conditions, is the temperature- humidity index (THI, Eq 1) that combines temperature and humidity [36, 37]. Among some of THI variants there is one (THIWS, Eq 2) that incorporates the convection effect of wind speed, and solar radiation [38, 36], which might be worth considering in outdoors conditions, THI ¼ 0:8 � T þ 0:01 � Hr � ðT 14:4Þ þ 46:4 Eq 1 THIWS ¼ 4:51 þ THI ð1:992 � WÞ þ 1:887 � SR Eq 2 where T is the daily mean temperature (˚C), Hr is the mean relative humidity (%), W is the mean wind speed (m�s-1) and SR is the accumulated solar radiation across a 24 h circadian period (MJ�m-2). Statistical analysis

We used two different statistical approaches, (i) non-linear mixed regression models to assess the effects of heat stress on calf body weight [39], and (ii) generalised additive mixed linear models GAM on mother weight [40]. This was justified because it is well accepted that calf growth fits an exponential asymptotic curve (Eq 3) [24, 41, 25], which can be efficiently para- meterised using non-linear mixed regression models implemented with the R software pack- age nlme [39]. On the other hand, there is not a defined model that represents the change in mother body weight through lactation. Consequently, we applied GAM regression models that PLOS ONE Heat stress and calf growth in red deer PLOS ONE | https://doi.org/10.1371/journal.pone.0233809 June 1, 2020 4 / 26