Paper
25 October 2016 Remote sensing as a tool to analyse lizards behaviour
Remi Dos Santos, Ana C. Teodoro, Miguel Carretero, Neftalí Sillero
Author Affiliations +
Abstract
Although the spatial context is expected to be a major influence in the interactions among organisms and their environment, it is commonly ignored in ecological studies. This study is part of an investigation on home ranges and their influence in the escape behaviour of Iberian lizards. Fieldwork was conducted inside a 400 m2 mesocosm, using three acclimatized adult male individuals. In order to perform analyses at this local scale, tools with high spatial accuracy are needed. A total of 3016 GPS points were recorded and processed into a Digital Elevation Model (DEM), with a pixel resolution of 2 cm. Then, 1156 aerial photos were taken and processed to create an orthophoto. A refuge map, containing possible locations for retreats was generated with supervised image classification algorithms, obtaining four classes (refuges, vegetation, bare soil and organic soil). Furthermore, 50 data-loggers were randomly placed, recording evenly through the area temperature and humidity every 15'. After a month of recording, all environmental variables were interpolated using Kriging. The study area presented an irregular elevation. The humidity varied according to the topography and the temperature presented a West-East pattern. Both variables are of paramount importance for lizard activity and performance. In a predation risk scenario, a lizard located in a temperature close to its thermal optimum will be able to escape more efficiently. Integration of such ecologically relevant elements in a spatial context exemplifies how remote sensing tools can contribute to improve inference in behavioural ecology.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Remi Dos Santos, Ana C. Teodoro, Miguel Carretero, and Neftalí Sillero "Remote sensing as a tool to analyse lizards behaviour", Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99981Z (25 October 2016); https://doi.org/10.1117/12.2241093
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KEYWORDS
Remote sensing

Humidity

Orthophoto maps

Vegetation

Global Positioning System

Cameras

Ecology

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