###### Abstract  
Commonly, when studies deal with the effects of climate change on biodiversity, mean value is used more than other parameters. However, climate change also leads to greater temperature variability, and many papers have demonstrated its importance in the implementation of biodiversity response strategies. We studied the spatio-temporal variability of activity time and persistence index, calculated from operative temperatures measured at three sites over three years, for a mountain endemic species. Temperatures were recorded with biomimetic loggers, an original remote sensing technology, which has the same advantages as these tools but is suitable for recording biological organisms data. Among the 42 tests conducted, 71% were significant for spatial variability and 28% for temporal variability. The differences in daily activity times and in persistence indices demonstrated the effects of the micro-habitat, habitat, slope, altitude, hydrography, and year. These observations have highlighted the great variability existence in the environmental temperatures experienced by lizard populations. Thus, our study underlines the importance to implement multi-year and multi-site studies to quantify the variability and produce more representative results. These studies can be facilitated by the use of biomimetic loggers, for which a user guide is provided in the last part of this paper.  
activity time; biomimetic model; biomimetic logger; data logger; operative temperature; persistence; remote sensors; spatio-temporal variability 2020 IEEE/RSJ International Conference on  
often in terms of the mean and ignores variability in time and/or in space [8; 9; 10]. Many studies acknowledge spatial variability and use spatial replication but eventually average the results from the different study sites (see in [11] for discussion). Very few address temporal variability; experiments are very often conducted over only one year (see, for example, in [12]). Absence of true temporal and/or spatial replication to address explicitly variability issues is often linked to budget limitations but it still raises the crucial issue of the representativeness of the results. Many other studies demonstrate indeed the important role of variability in explaining species responses to climate change [13; 14; 15] as responses appear to be favored by thermal regimes more than by the mean temperature itself [16; 17]. Moreover, several studies have shown that there are interactions between mean and variability. For example, these two parameters better explain thermal performance when considered together in the model rather than separately as they act in synergy [10]. Temperature variability has different impacts depending on the mean temperature and the thermal performance curve. If the mean is low, the temperature variability increase may lead to temperatures allowing a better performance; otherwise, if the average is already close to the optimum temperature, it will lead to a decrease in performance [8; 18]. Furthermore, increased variability may cause heat stress leading to higher energy costs for the maintenance of individuals, which may consequently reduce reproductive performance [9; 19]. Climate variability appears to play a major role in species persistence, so it is crucial to integrate it into studies dealing with climate change effects on biodiversity [20; 21].