Abstract:Animals achieve camouflage through a variety of mechanisms, of which background matching and disruptive coloration are likely the most common. Although many studies have investigated camouflage mechanisms using artificial stimuli and in lab experiments, less work has addressed camouflage in the wild. Here we examine egg camouflage in clutches laid by ground-nesting Snowy Plovers Charadrius nivosus and Least Terns Sternula antillarum breeding in mixed aggregations at Bahía de Ceuta, Sinaloa, Mexico. We obtained… Show more
“…For example, Stoddard et al. () developed edge detection algorithms to evaluate the relative camouflage of nesting shorebird species as compared to their nesting substrate (Figure b).…”
Section: Descriptionmentioning
confidence: 99%
“…(2) From Stoddard et al. (), snowy plover ( Charadrius nivosus ) nest clutch (2a) segmented into egg and background regions (2b), edge detection was used to quantify edges (2c), in order to calculate the degree of egg camouflage compared to the background substrate (2d). See for credits and permissions [Colour figure can be viewed at wileyonlinelibrary.com]…”
Section: Descriptionmentioning
confidence: 99%
“…() and Stoddard et al. () were used under the PlosOne Creative Commons License. Thanks to Shanis Barnard, Drew Weber, Will Pearse, Margaret Kosmala, Tanya Berger‐Wolf, Chuck Stewart, J. J. Valletta and Oscar Beijboom for their helpful input.…”
Section: Acknowledgementsmentioning
confidence: 99%
“…By comparing image features, computer vision can be used to study animal camouflage (Tankus & Yeshurun, 2009) and biomimicry (Yang, Wang, Liang, & Møller, 2016). For example, Stoddard et al (2016) developed edge detection algorithms to evaluate the relative camouflage of nesting shorebird species as compared to their nesting substrate ( Figure 3b).…”
A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in time and space. However, the ability to process these images remains a bottleneck. Computer vision can greatly increase the efficiency, repeatability and accuracy of image review. Computer vision uses image features, such as colour, shape and texture to infer image content. I provide a brief primer on ecological computer vision to outline its goals, tools and applications to animal ecology. I reviewed 187 existing applications of computer vision and divided articles into ecological description, counting and identity tasks. I discuss recommendations for enhancing the collaboration between ecologists and computer scientists and highlight areas for future growth of automated image analysis.
“…For example, Stoddard et al. () developed edge detection algorithms to evaluate the relative camouflage of nesting shorebird species as compared to their nesting substrate (Figure b).…”
Section: Descriptionmentioning
confidence: 99%
“…(2) From Stoddard et al. (), snowy plover ( Charadrius nivosus ) nest clutch (2a) segmented into egg and background regions (2b), edge detection was used to quantify edges (2c), in order to calculate the degree of egg camouflage compared to the background substrate (2d). See for credits and permissions [Colour figure can be viewed at wileyonlinelibrary.com]…”
Section: Descriptionmentioning
confidence: 99%
“…() and Stoddard et al. () were used under the PlosOne Creative Commons License. Thanks to Shanis Barnard, Drew Weber, Will Pearse, Margaret Kosmala, Tanya Berger‐Wolf, Chuck Stewart, J. J. Valletta and Oscar Beijboom for their helpful input.…”
Section: Acknowledgementsmentioning
confidence: 99%
“…By comparing image features, computer vision can be used to study animal camouflage (Tankus & Yeshurun, 2009) and biomimicry (Yang, Wang, Liang, & Møller, 2016). For example, Stoddard et al (2016) developed edge detection algorithms to evaluate the relative camouflage of nesting shorebird species as compared to their nesting substrate ( Figure 3b).…”
A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in time and space. However, the ability to process these images remains a bottleneck. Computer vision can greatly increase the efficiency, repeatability and accuracy of image review. Computer vision uses image features, such as colour, shape and texture to infer image content. I provide a brief primer on ecological computer vision to outline its goals, tools and applications to animal ecology. I reviewed 187 existing applications of computer vision and divided articles into ecological description, counting and identity tasks. I discuss recommendations for enhancing the collaboration between ecologists and computer scientists and highlight areas for future growth of automated image analysis.
“…1). Previously, we have used subsets of these data to report on a wide variety of topics in organismal biology, including sex ratio variation 12 , population viability 13 , courtship behaviour 14 , incubation behaviour 15 , parental care 16 , ontogeny 17 , chronobiology 18 , camouflage mechanisms 19 , offspring desertion 20 and mating system dynamics 21 . The motivation for making our database open is to provide evolutionary ecologists with an accessible resource that will serve as an important repository for addressing overarching questions in organismal biology and conservation.…”
Shorebirds (partim members of order Charadriiformes) have a global distribution and exhibit remarkable variation in ecological and behavioural traits that are pertinent to many core questions in the fields of evolutionary ecology and conservation biology. Shorebirds are also relatively convenient to study in the wild as they are ground nesting and often occupy open habitats that are tractable to monitor. Here we present a database documenting the reproductive ecology of 1,600 individually marked snowy plovers (Charadrius nivosus) monitored between 2006 and 2016 at Bahía de Ceuta (23°54 N, 106°57 W) – an important breeding site in north-western Mexico. The database encompasses various morphological, behavioural, and fitness-related traits of males and females along with spatial and temporal population dynamics. This open resource will serve as an important data repository for addressing overarching questions in avian ecology and wetland conservation during an era of big data and global collaborative science.
Over the past few decades, there has been a growing interest in the pigmentation of avian eggshells. Many functions have been proposed to explain the vast diversity of this feature. Among them,
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