Parameter affecting the I3S algorithm reliability: how does correcting for body curvature affect individual recognition?
Giacomo Rosa
A , Fanny Guillaud A , Pauline Priol B and Julien Renet A C
A Conservatoire d’espaces naturels de Provence-Alpes-Côte d’Azur, Pôle Biodiversité Régionale, Appartement n°5, 96 Rue Droite, 04200 Sisteron, France.
B StatiPop Scientific Consulting, 4 Avenue de Nîmes, 34190 Ganges, France.
C Corresponding author. Email: julien.renet@cen-paca.org
Wildlife Research - https://doi.org/10.1071/WR19238
Submitted: 11 December 2019 Accepted: 9 June 2020 Published online: 8 September 2020
Abstract
Context: In recent years, multiple computer algorithms, which allow us to perform photographic capture–recapture analysis, have been developed. Their massive application, also in wildlife demographic and ecological studies, is largely due to the fact that these tools are non-invasive and non-expensive. To maximise the performance of these programs, it is essential to have a good photo-standardisation so as to avoid bias in the results. A lot of ‘non-standardised’ photos are not usable for capture–mark–recapture (CMR) analysis, entailing the loss of potentially exploitable data.
Aims: No study has accurately investigated the effect of the corporal bending of an animal on the performance of the interactive individual identification system (I3S) algorithm. For this reason, we assessed the effect of this photographic standardisation parameter (PSP) on the reliability of this algorithm.
Methods: We assessed the effect of the body position of Triturus cristatus between capture and recapture photos on the error rates of a group of standardised pictures, performing a generalised linear model analysis. We have also evaluated the effect of image correction (i.e. straightening of newts’ bodies) on the error rates (expressed by false rejection rates, FRRs) of the first (standardised) photo-group (G1) and of a non-standardised photo-group (G2). To perform this, we used I3S-Pattern+ for the photo-matching analysis and I3S-Straighten for the correction of the pictures.
Key results: The difference of body angles between capture and recapture pictures had a significantly increased error rates in G1. Digital correction of body bending reduced the error rates. For the pictures where corporal bending was not digitally corrected, the top 20 FRRs were 0.38 and 0.33 for G1 and G2 respectively. For corrected (straightened) pictures, the top 20 FRRs were 0.026 and 0.15.
Conclusions: Our findings showed a high impact of newt corporal bending and photographic treatment on the I3S algorithm reliability.
Implications: We provide some recommendations to avoid or minimise the effects of this PSP and improve photo-standardisation during and after CMR studies of species of Urodela. In this way, pictures that would be unusable in photo-matching software under current practice could become usable, increasing the available data to conduct a survey.
Additional keywords: corporal bending, false rejection rate, I3S-Pattern+, I3S-Straighten, photographic standardisation, Triturus cristatus.
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