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Influenza A viruses (IAV) are zoonotic pathogens relevant to human, domestic animal and wildlife health. Many avian IAVs are transmitted among waterfowl via a faecal-oral-route. Therefore, environmental water where waterfowl congregate may play an important role in the ecology and epidemiology of avian IAV. Water and sediment may sustain and transmit virus among individuals or species. It is unclear at what concentrations waterborne viruses are infectious or remain detectable. To address this, we performed lake water and sediment dilution experiments with varying concentrations or infectious doses of four IAV strains from seal, turkey, duck and gull. To test for infectivity of the IAV strains in a concentration dependent manner, we applied cultivation to specific pathogen free (SPF) embryonated chicken eggs and Madin-Darby Canine Kidney (MDCK) cells. IAV recovery was more effective from embryonated chicken eggs than MDCK cells for freshwater lake dilutions, whereas, MDCK cells were more effective for viral recovery from sediment samples. Low infectious dose (1 PFU/200 μL) was sufficient in most cases to detect and recover IAV from lake water dilutions. Sediment required higher initial infectious doses (≥ 100 PFU/200 μL).

Torpor is a state of controlled reduction of metabolic rate (M) in endotherms. Assigning measurements of M to torpor or euthermy can be challenging, especially when the difference between euthermic M and torpid M is small, in species defending a high minimal body temperature in torpor, in thermolabile species, and slightly below the thermoneutral zone (TNZ). Here, we propose a novel method for distinguishing torpor from euthermy. We use the variation in M measured during euthermic rest and torpor at varying ambient temperatures (Ta) to objectively estimate the lower critical temperature (Tlc) of the TNZ and to assign measurements to torpor, euthermic rest or rest within TNZ. In addition, this method allows the prediction of M during euthermic rest and torpor at varying Ta, including resting M within the TNZ. The present method has shown highly satisfactory results using 28 published sets of metabolic data obtained by respirometry on 26 species of mammals. Ultimately, this novel method aims to facilitate analysis of respirometry data in heterothermic endotherms. Finally, the development of the associated R-package (torpor) will enable widespread use of the method amongst biologists.

23 24 1.Torpor is a state of controlled reduction of metabolic rate (M) and body 25 temperature in endotherms. Assigning measurements of M to torpor or euthermia 26 can be challenging. All current techniques available to distinguish between those two 27 states have their limitations and are at least partly arbitrary. 28 2.Here, we firstly propose a new R package (torpor) enabling distinction of torpid 29 versus euthermic M measured in stable environmental conditions. Functions are 30 based on the variation in M measured along varying ambient temperatures (T a ). This 31 model determines physiological state membership using a binary mixture model, and 32 further allows prediction of M along T a . Secondly, we challenge this method by 33 applying it to previously published data (N=28) on the M of various mammals 34 covering a diversity of metabolic and thermal strategies. 35 3.The fractions of values for which the original assignment matched that of the 36 model ranged between 0.78 and 1 (median=0.99). Most of the conflicts concerned M 37 measured at temperatures close to the thermoneutral zone. Parameters describing 38 torpid M could not always be identified accurately with some smaller data sets. 39 4.The package "torpor" provides an objective method to assign measurements 40 of M to euthermia and/or torpor, and to predict M values at any given T a below the 41 thermoneutral zone. Necessary considerations for a lucid application of this method 42 are further discussed. Ultimately, the use of this package should improve the 43 standardization of respirometry analyses in heterotherms. 44 45 Table 1: Abbreviations used in the present paper and descriptions of the functions of the package "torpor". M metabolic rate BMR basal metabolic rate TMR minimal metabolic rate in torpor T a ambient temperature T b body temperature T lc lower critical temperature (i.e., lower limit of the thermoneutral zone) T m extrapolated modelled temperature where the conforming torpor function reaches BMR T t threshold ambient temperature below which thermoregulation occurs in torpor tor_fit () fits a binomial mixture model using Bayesian inference. tor_plot () provides a plot of the M values over the respective T a . Raw data and predictions are presented in different colors depending on the metabolic state. Predicted values are represented by continuous and stripped lines for the estimates' median and 95% credible interval bounds of the posterior distribution, respectively. The function is a wrapper function around the tor_fit () and tor_predict (). For more flexibility, output of tor_fit () can be directly included as argument. tor_predict () provides the predicted M and 95% credible interval bounds at a given T a , for the normothermic and torpid states. tor_summary() provides a comprehensive summary of the output returned by tor_fit (). Reported are the mean, 95% credible interval bounds, median and Brooks-Gelman-Rubin criterion (i.e., chain convergence 46