Biology subjects

Papafitsoros, K.

Publications and source records attributed to Papafitsoros, K..

6 recordsLinked to original sources

bioRxiv2024

Exploiting facial side similarities to improve AI-driven sea turtle photo-identification systems

AO_SCPLOWBSTRACTC_SCPLOWAnimal Photo-identification (photo-ID) denotes the process of identifying individual animals based on their unique and stable morphological characteristics. It has been proven to be a particularly useful tool for a variety of studies on sea turtles increasing the knowledge of their ecology and informing conservation efforts. The photo-ID process in sea turtles is predominantly based on the geometric patterns of the scales of their two head sides which are unique to every individual, and also different from side to side. As such, both manual and automated photo-ID techniques are performed under a side-specific image retrieval setting. There, a query image showing a single profile of an unknown individual, either left or right, is only compared to images of previously identified individuals showing the same side. Here, by employing the recently introduced state-of-the-art deep feature extractor MegaDescriptor, we show for the first time an inherit deep visual similarity between left and right facial profiles of the same individuals in three sea turtle species. We show that the similarity between the left and right profiles of the same individual with respect to geometry, coloration and pigmentation, is on average higher than the similarity between profiles of different individuals. The similarity is detectable even when images are taken years apart and under diverse settings and conditions. We perform several image retrieval experiments under scenarios which mimic realistic sea turtle photo-ID matching processes, where we also allow comparisons of opposite sides in the matching process which have no spatial overlap. We show that the detection and exploitation of this similarity is translated to improved accuracies when compared to the traditional side-specific image retrieval setting. Notably this similarity cannot be detected and thus neither explored by the so-far state-of-the-art sea turtle photo-ID automated methods such as those based on SIFT. Our work leads to a change of paradigm for the sea turtle photo-ID workflows which will be further facilitated by the constant improvement of deep feature-based re-identification methods and paves the path for adopting similar workflows in other animal species as well.

ecology↗

bioRxiv2023

Underreported in-water behaviours of the loggerhead sea turtle: Foraging on sea cucumbers

In this article, we report on four observations of loggerhead sea turtles (Caretta caretta) foraging on sea cucumbers (Holothuria spp.), on Zakynthos Island, Greece. Direct observations of this behaviour are underreported in the literature. Foraging on such prey was in general a challenging process as the turtles used their flippers and their beak to cut the sea cucumbers albeit without success. They ended up shallowing the sea cucumbers most likely in one intact piece. Even though this behaviour is rare in this site, two out of four observations involved the same male sea turtle, indicating potentially specific dietary preferences for this individual.

animal behavior and cognition↗

bioRxiv2022

Underreported in-water behaviours of the loggerhead sea turtle: Getting buried in the sand

In this short report, we provide a direct evidence that loggerhead sea turtles Caretta caretta are capable of partially burying themselves in the sand by actively moving their front flippers and stirring the sea bottom sediment. In particular, we report the cases of three male loggerhead sea turtles from Zakynthos island, Greece, which, after obtaining a resting position on a sandy spot at the sea bottom, they actively performed digging and stirring movements with their front flippers, resulting to the sand getting raised at the sea column. When the sand settled back, the turtles ended up half-buried and camouflaged. To our current knowledge, this self-burying behaviour has not been described in the literature.

animal behavior and cognition↗

bioRxiv2022

A social media-based framework for quantifying temporal changes to wildlife viewing intensity: Case study of sea turtles before and during COVID-19

Documenting how human pressure on wildlife changes over time is important to minimise potential adverse effects through implementing appropriate management and policy actions; however, obtaining objective measures of these changes and their potential impacts is often logistically challenging, particularly in the natural environment. Here, we developed a modular stochastic model that infers the ratio of actual viewing pressure on wildlife in consecutive time periods (years) using social media, as this medium is widespread and easily accessible. Pressure was calculated from the number of times individual animals appeared in social media in pre-defined time windows, accounting for time-dependent variables that influence them (e.g. number of people with access to social media). Formulas for the confidence intervals of viewing pressure ratios were rigorously developed and validated, and corresponding uncertainty was quantified. We applied the developed framework to calculate changes to wildlife viewing pressure on loggerhead sea turtles (Caretta caretta) at Zakynthos island (Greece) before and during the COVID-19 pandemic (2019-2021) based on 2646 social media entries. Our model ensured temporal comparability across years of social media data grouped in time window sizes, by correcting for the interannual increase of social media use. Optimal sizes for these windows were delineated, reducing uncertainty while maintaining high time-scale resolution. The optimal time window was around 7-days during the peak tourist season when more data were available in all three years, and >15 days during the low season. In contrast, raw social media data exhibited clear bias when quantifying changes to viewing pressure, with unknown uncertainty. The framework developed here allows widely-available social media data to be used objectively when quantifying temporal changes to wildlife viewing pressure. Its modularity allowed viewing pressure to be quantified for all data combined, or subsets of data (different groups, situations or locations), and could be applied to any site supporting wildlife exposed to tourism.

ecology↗

bioRxiv2022

Social media mining and photo-identification detects the shift of long-term seasonal foraging habitat for a juvenile loggerhead sea turtle

Animal imagery uploaded on social media has been identified as an important tool in wildlife research and conservation and has been used in a variety of recent studies. Here a case study is presented, where a detailed analysis of social media content revealed a shift of a long-term foraging habitat for a juvenile loggerhead sea turtle (Caretta caretta) in Greece. In particular, this individual was a long term resident of Zakynthos island, Greece, from 2016 until 2020 (5 consecutive summer seasons), regularly foraging on a nearshore reef, with no observations of it being made during the 2021 season. However regular social media image mining combined with photo-identification, detected this individual foraging in the Gulf of Corinth in August 2021, more that 200km away from his previous foraging habitat. This case study (i) shows the possibility for juvenile loggerheads to shift their foraging site even after long term use, with implications in capture-mark-recapture studies and (ii) once more highlights the usefulness of social media mining and citizen science in diverse aspects of sea turtle studies.

ecology↗

bioRxiv2020

Social media reveals consistently disproportionate tourism pressure on a threatened marine vertebrate

Establishing how wildlife viewing pressure is distributed across individual animals within a population can inform the management of this activity, and ensure targeted individuals or groups are sufficiently protected. Here, we used social media data to quantify whether tourism pressure varies in a loggerhead sea turtle (Caretta caretta) population and elucidate potential implications. Laganas Bay (Zakynthos, Greece) supports both breeding (migratory, and hence transient) and foraging (resident) turtles, with turtle viewing representing a major component of the tourism industry. Social media entries spanning two seasons (April to November, 2018 and 2019) were evaluated, and turtles were identified via photo-identification. For both years, 1684 and 2105 entries of 139 and 122 unique turtles were obtained from viewings, respectively (boats and underwater combined). However, while residents represented less than one-third of uniquely identified turtles, they represented 81.9% and 87.9% of all entries. Even when the seasonal breeding population was present (May to July), residents represented more than 60% entries. Of note, the same small number of resident turtles (<10), mostly males, were consistently viewed in both years; however, different individuals were targeted by boats versus underwater. Thus, turtles appear to use and remain in the area despite high viewing intensity, possibly indicating low disturbance. However, photo-identification records revealed a high risk of propeller and boat strike to residents (30%) leading to trauma and mortality. To reduce this threat and ease viewing pressure, we recommend the compulsory use of propeller guards for all boats and the creation of temporary "refuge" zones for resident animals at viewing hotspots, with these suggestions likely being relevant for other wildlife with similar population dynamics. In conclusion, social media represents a useful tool for monitoring individuals at a population scale, evaluating the pressure under which they are placed, and providing sufficient data to refine wildlife viewing guidelines and/or zoning.

ecology↗