RESUMEN
Body coloration in ectotherms serves multiple biological functions, including avoiding predators, communicating with conspecific individuals, and involvement in thermoregulation. As ectotherms rely on environmental sources of heat to regulate their internal body temperature, stable melanistic body coloration or color change can be used to increase or decrease heat absorption and heat exchange with the environment. While melanistic coloration for thermoregulation functions to increase solar radiation absorption and consequently heating in many diurnal ectotherms, research on crepuscular and nocturnal ectotherms is lacking. Since crepuscular and nocturnal ectotherms generally absorb heat from the substrate, in these organisms melanistic coloration may have other primary functions beside thermoregulation. As such, in this work we hypothesized that the proportion of dorsal melanistic body coloration would not influence heating and cooling rates in the crepuscular gecko, Eublepharis macularius, and that changes in environmental temperature would not trigger color changes in this species. Temperature measurements of the geckos and of the environment were taken using infrared thermography and temperature loggers. Color data were obtained using objective photography and a newly developed custom software package. We found that body temperature reflected substrate temperatures, and that the proportion of melanistic coloration has no influence on heating or cooling rates or on color changes. These findings support that melanistic coloration in E. macularius may not be used for thermoregulation and strengthen the hypothesis that in animals active in low light conditions, melanistic coloration may be used instead for camouflage or other functions.
Asunto(s)
Regulación de la Temperatura Corporal , Lagartos , Animales , Lagartos/fisiología , Temperatura Corporal , Temperatura , CalorRESUMEN
The evaluation of geometric defects is necessary in order to maintain the integrity of structures over time. These assessments are designed to detect damages of structures and ideally help inspectors to estimate the remaining life of structures. Current methodologies for monitoring structural systems, while providing useful information about the current state of a structure, are limited in the monitoring of defects over time and in linking them to predictive simulation. This paper presents a new approach to the predictive modeling of geometric defects. A combination of segments from point clouds are parametrized using the convex hull algorithm to extract features from detected defects, and a stochastic dynamic model is then adapted to these features to model the evolution of the hull over time. Describing a defect in terms of its parameterized hull enables consistent temporal tracking for predictive purposes, while implicitly reducing data dimensionality and complexity as well. In this study, two-dimensional (2D) point clouds analogous to information derived from point clouds were firstly generated over simulated life cycles. The evolutions of point cloud hull parameterizations were modeled as stochastic dynamical processes via autoregressive integrated moving average (ARIMA) and vectorized autoregression (VAR) and compared against ground truth. The results indicate that this convex hull approach provides consistent and accurate representations of defect evolution across a range of defect topologies and is reasonably robust to noisy measurements; however, assumptions regarding the underlying dynamical process play a significant the role in predictive accuracy. The results were then validated on experimental data from fatigue testing with high accuracy. Longer term, the results of this work will support finite element model updating for predictive analysis of structural capacity.