Proposed in 1849 by Charles Morren to depict periodical phenomena governed by seasons, the term "phenology" has spread in many fields of biology. With the wide adoption of the concept of phenology flourished a large number of metrics with different meaning and interpretation. Here, we first a priori classified 52 previously published metrics used to characterise the phenology of births in large herbivores according to four biological characteristics of interest: timing, synchrony, rhythmicity and regularity of births. We then applied each metric retrieved on simulation data, considering normal and non-normal distributions of births, and varying distributions of births in time. We then evaluated the ability of each metric to capture the variation of the four phenology characteristics via a sensitivity analysis. Finally, we scored each metric according to eight criteria we considered important to describe phenology correctly. The high correlation we found among the many metrics we retrieved suggests that such diversity of metrics is unnecessary. We further show that the best metrics are not the most commonly used, and that simpler is often better.Circular statistics with the mean vector orientation and mean vector length seems, respectively, particularly suitable to describe the timing and synchrony of births in a wide range of phenology patterns. Tests designed to compare statistical distributions, like Mood and Kolmogorov-Smirnov tests, allow a first and easy quantification of rhythmicity and regularity of birth phenology respectively. By identifying the most relevant metrics our study should facilitate comparative studies of phenology of births or of any other life-history event.For instance, comparative studies of the phenology of mating or migration dates are particularly important in the context of climate change.
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Proposed in 1849 by Charles Morren to depict periodical phenomena governed by seasons, the term ″phenology″ has spread in many fields, from evolutionary to molecular biology. The adoption of the concept of phenology in such diverse fields has been associated with the creation of a wide diversity of metrics, and we believe, some confusion about what they measure. Here, as an example and to offer some perspective, we studied phenology of births in large herbivores and we identified 52 metrics that were previously used to quantify phenology. We conducted a quantitative analysis of these metrics based on simulations. We compared and classified the metrics using a correlation matrix, and we evaluated the ability of each metric to capture the variation of a set of phenological characteristics via a sensitivity analysis. We finally scored each metric according to eight criteria we thought were important to describe phenology well. We highlight the fact that four characteristics of phenology are important and can be clearly defined: timing, synchrony, rhythmicity and regularity. We also report on the high correlations that can usually be observed among the metrics corresponding to each of the four characteristics of phenology, suggesting that such diversity of metrics is not useful. Additionally, we show that the best metrics are not necessarily the most commonly used and that simpler is often better: easy to implement metrics often got the best scores. We give some guidelines and advice, in order to facilitate repeatability and comparison of phenology between studies. We also discuss some pitfalls to avoid when choosing a metric. We trust our study can facilitate the use of well-defined and robust concepts and metrics in studies of phenology, for instance in the context of global change effects on populations.
Though non–lethal, recreational activities often result in a spatial and/or temporal shift of activity in a large range of species because they are perceived as a risk. With the concurrent development of outdoors activities and the increase of temperatures due to climate change in mountainous ecosystems, mountain species face an increasing pressure in terms of managing their activity pattern to both limit risk exposure and reduce thermal stress. In this context, we investigated how female northern chamois adjust their summer circadian activity to spatio–temporal variations of both temperature and hikers disturbance. We found that chamois behaviour was more affected by high temperatures than by hikers disturbance. During the hottest days, they shifted their activity peak earlier in the morning (50 minutes earlier; and to a lesser extent, later in the evening), and were more active at night (+ 21.5% approx.) than during daytime (− 10.10% approx.). Their global daily activity was higher (+ 4.54% approx.) during the hottest than coldest days owing to a significant increase of activity level during the activity peaks. Conversely, hikers disturbance had almost no effect on activity peaks of chamois most likely due to a temporal mismatch with hikers arrival and departure. Spatial and temporal disturbance had also a weak effect on chamois activity level, except when considered together and during the hottest days (i.e. the most disturbed conditions) exacerbating the temporal report of activity at night those days. Low tolerance of chamois to hikers presence might have led to the pattern reported with a similar response whatever the intensity of encounter risk. These results might also suggest that behavioural changes buffering animals from high temperature (relocation into refuge areas) and/or from hikers presence (moving away temporarily from trails) allow them to marginally modify their activity pattern. In the context of ongoing socio–environmental changes, these findings stress the importance of conserving habitats providing both shelter against summer heat and human disturbance to mitigate their potential detrimental consequences.
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