Seasonal Variation in the Thermoregulation Pattern of an Insular Agamid Lizard

Karameta, Emmanouela; Gavriilidi, Ioanna; Sfenthourakis, Spyros; Pafilis, Panayiotis

doi:10.3390/ani13203195

Cited by 2 publications

(1 citation statement)

References 67 publications

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“…This system allows biologists to easily obtain valuable data on the body temperature of lizards to use in their research without causing pain or stress to the animal. Karameta et al [33] obtained the body temperature of insular agamid lizards by inserting a type K thermocouple directly into the animal's cloaca to study how seasonality impacts the thermal biology of an island population of lizards, providing insights into their survival strategies and potential adaptations to future environmental changes. The use of a non-invasive (contactless) and automatic system to extract these temperature values, such as the one developed in this paper, would have been a huge advantage in this study.…”

Section: Current Research Statusmentioning

confidence: 99%

Lizard Body Temperature Acquisition and Lizard Recognition Using Artificial Intelligence

Afonso,

Lopes,

Ribeiro

2024

Sensors

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The acquisition of the body temperature of animals kept in captivity in biology laboratories is crucial for several studies in the field of animal biology. Traditionally, the acquisition process was carried out manually, which does not guarantee much accuracy or consistency in the acquired data and was painful for the animal. The process was then switched to a semi-manual process using a thermal camera, but it still involved manually clicking on each part of the animal’s body every 20 s of the video to obtain temperature values, making it a time-consuming, non-automatic, and difficult process. This project aims to automate this acquisition process through the automatic recognition of parts of a lizard’s body, reading the temperature in these parts based on a video taken with two cameras simultaneously: an RGB camera and a thermal camera. The first camera detects the location of the lizard’s various body parts using artificial intelligence techniques, and the second camera allows reading of the respective temperature of each part. Due to the lack of lizard datasets, either in the biology laboratory or online, a dataset had to be created from scratch, containing the identification of the lizard and six of its body parts. YOLOv5 was used to detect the lizard and its body parts in RGB images, achieving a precision of 90.00% and a recall of 98.80%. After initial calibration, the RGB and thermal camera images are properly localised, making it possible to know the lizard’s position, even when the lizard is at the same temperature as its surrounding environment, through a coordinate conversion from the RGB image to the thermal image. The thermal image has a colour temperature scale with the respective maximum and minimum temperature values, which is used to read each pixel of the thermal image, thus allowing the correct temperature to be read in each part of the lizard.

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Section: Current Research Statusmentioning

confidence: 99%

Lizard Body Temperature Acquisition and Lizard Recognition Using Artificial Intelligence

Afonso,

Lopes,

Ribeiro

2024

Sensors

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Surviving on a Rock, but for How Long? Deviations in the Thermoregulatory Strategy of the Milos Wall Lizard (Podarcis milensis)

Pafilis,

Adamopoulou,

Antonopoulos

et al. 2024

Animals

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Reptiles are unable to generate metabolic heat and regulate body temperature behaviorally depending on environmental conditions. The thermal quality of their habitat is therefore of pivotal importance for their survival. Lizards render themselves as ideal ectothermic models, and their thermal biology has been extensively studied. In this work, we focused on the thermoregulatory performance of the endemic Milos wall lizard (Podarcis milensis) (Milos Archipelago, Aegean Sea, Greece). Applying the same standard methodology, we estimated the effectiveness of thermoregulation (E) taking into account the three main thermal parameters: body (Tb, the temperature of active animals in the field), environmental (Te, the temperature that animals would achieve in the field if passively conform to the environment) and preferred temperatures (Tpref, the temperatures an animal achieves in a laboratory thermal gradient). Here, we compare the thermoregulatory profile of two remote rocky islet populations, Falconera and Velopoula, with the Milos Island population. We collected Tb values from active lizards as well as Te from specially designed copper models, which were appropriately placed in the field so as to cover all possible microhabitats. Lizards were then transported to the laboratory where we assessed their Tprefs. Falconera and Velopoula populations showed the same high thermoregulatory effectiveness as that of Milos Island (EFalconera = 0.97, EVelopoula = 0.95, EMilos = 0.89). However, when we used an alternative evaluation of the thermoregulatory strategy, the E values outlined a much more effective thermoregulation for the islets: de-dbFalconera = 6.97, de-dbVelopoula = 11.54, de-dbMilos = 4.27. The adverse conditions on the islets outline a demanding habitat of low thermal quality that dictates effective thermoregulation. However, the trend of increasing temperatures depicts an even harsher environment for the years to come. Could lizards that have already achieved the highest thermoregulatory effectiveness and cannot escape from the isolated islets they dwell cope with these new conditions? This is the kind of questions to which conservation biology will be called upon to respond.

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Seasonal Variation in the Thermoregulation Pattern of an Insular Agamid Lizard

Cited by 2 publications

References 67 publications

Lizard Body Temperature Acquisition and Lizard Recognition Using Artificial Intelligence

Lizard Body Temperature Acquisition and Lizard Recognition Using Artificial Intelligence

Surviving on a Rock, but for How Long? Deviations in the Thermoregulatory Strategy of the Milos Wall Lizard (Podarcis milensis)

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