Pre‐screening acoustic and other natural signatures for use in noninvasive individual identification

Abstract

Summary1. Common ecological tasks, such as wildlife monitoring, adaptive management, and behavioural study, often make use of natural signatures (e.g. animal calls or visual markings) to identify individual animals noninvasively. However, there is no accepted method for pre-screening candidate natural signatures to select which signatures are the best-suited for this purpose. In this paper, we suggest a pre-screening checklist and focus on the challenge of assessing a candidate signature's individuality. 2. Individuality is critical, as the use of low-individuality natural signatures can lead to misidentification of individuals and therefore bias estimation of population parameters and population response to management actions. An information-based metric of individuality could assist researchers with selecting suitable signatures by allowing comparison among candidate signatures and providing an estimate of how many individuals may be reliably discriminated using a particular signature. 3. Before an individuality metric can be used to pre-screen natural signatures, the metric must first be calculated from preliminary sampling and must be robust to typical sampling concerns. We used field-collected animal vocalizations as well as simulations to test how robust the metric is to variation in sampling design. 4. We found that the metric is fairly robust to the number of animals sampled and the number of sessions (e.g. calling bouts) analysed, but that it is sensitive to the number of observations per session. 5. Synthesis and applications. Managers and researchers could save time and energy and improve the accuracy of estimates (such as abundance, survival, or population response) based on individual identification by first pre-screening candidate natural signatures for their individuality. As long as the number of observations per session is controlled, the relative values of the individuality metric can be meaningfully compared. The metric can thus be used as a tool to estimate relative individuality and so facilitates a difficult step in choosing a natural signature for noninvasive individual identification. We include instructions on how to calculate and interpret the individuality metric.

Differences in alarm calls of juvenile and adult European ground squirrels (Spermophilus citellus): Findings on permanently marked animals from a semi‐natural enclosure

“…Figure 1 shows a representative spectrogram of several alarm calls typical for the European ground squirrel. Similar to that in other ground-dwelling sciurids [Nikol'skii and Suchanova, 1994;McCowan and Hooper, 2002;Blumstein and Munos, 2005;Volodin, 2005;Pollard et al, 2010;Matrosova et al, 2011;Pollard and Blumstein, 2011], the alarm call of this species manifests with high short-term individuality, such that calls recorded from one individual are highly similar within one recording session but differ significantly from calls produced by different individuals [Schneiderov a and Policht, 2010]. It was previously demonstrated that the first and the second element do not differ in this respect [Schneiderov a, 2012].…”

The assessment of biases in the acoustic discrimination of individuals

“…We show that discrimination improves with the number of calls available per individual which is in accordance with a previous study [34]. The previous and this study (Fig 5c) both agree that relatively small number of calls is sufficient to assess the amount of individual information in the calls.…”

“…The effect of the number of individuals on H S , though small, has also been found previously [34], suggesting that comparisons of H S values from different studies might be problematic. In the original study, there was not apparent effect of number of individuals on H S [33].…”

Evolving communicative complexity: insights from rodents and beyond

“…Because studies quantifying vocal individuality are not common, this analysis required novel data, and eight species of ground-dwelling sciurid were thus captured, individually marked and recorded on multiple occasions. Individuality was calculated from acoustic traits using an information-theory metric developed by Beecher [5,73] and used in previous studies [25,27,52,74]. The individuality information statistic quantifies, in bits, the amount of individually specific information content present in a species' vocalizations.…”