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1.
PeerJ Comput Sci ; 10: e2003, 2024.
Article in English | MEDLINE | ID: mdl-38855218

ABSTRACT

Land use and land cover (LULC) classification is becoming faster and more accurate thanks to new deep learning algorithms. Moreover, new high spectral- and spatial-resolution datasets offer opportunities to classify land cover with greater accuracy and class specificity. However, deploying deep learning algorithms to characterize present-day, modern land cover based on state-of-the-art data is insufficient for understanding trends in land cover change and identifying changes in and drivers of ecological and social variables of interest. These identifications require characterizing past land cover, for which imagery is often lower-quality. We applied a deep learning pipeline to classify land cover from historical, low-quality RGB aerial imagery, using a case study of Vancouver, Canada. We deployed an atrous convolutional neural network from DeepLabv3+ (which has previously shown to outperform other networks) and trained it on modern Maxar satellite imagery using a modern land cover classification. We fine-tuned the resultant model using a small dataset of manually annotated and augmented historical imagery. This final model accurately predicted historical land cover classification at rates similar to other studies that used high-quality imagery. These predictions indicate that Vancouver has lost vegetative cover from 1995-2021, including a decrease in conifer cover, an increase in pavement cover, and an overall decrease in tree and grass cover. Our workflow may be harnessed to understand historical land cover and identify land cover change in other regions and at other times.

2.
Proc Natl Acad Sci U S A ; 117(26): 15112-15122, 2020 06 30.
Article in English | MEDLINE | ID: mdl-32541035

ABSTRACT

Many animals have the potential to discriminate nonspectral colors. For humans, purple is the clearest example of a nonspectral color. It is perceived when two color cone types in the retina (blue and red) with nonadjacent spectral sensitivity curves are predominantly stimulated. Purple is considered nonspectral because no monochromatic light (such as from a rainbow) can evoke this simultaneous stimulation. Except in primates and bees, few behavioral experiments have directly examined nonspectral color discrimination, and little is known about nonspectral color perception in animals with more than three types of color photoreceptors. Birds have four color cone types (compared to three in humans) and might perceive additional nonspectral colors such as UV+red and UV+green. Can birds discriminate nonspectral colors, and are these colors behaviorally and ecologically relevant? Here, using comprehensive behavioral experiments, we show that wild hummingbirds can discriminate a variety of nonspectral colors. We also show that hummingbirds, relative to humans, likely perceive a greater proportion of natural colors as nonspectral. Our analysis of plumage and plant spectra reveals many colors that would be perceived as nonspectral by birds but not by humans: Birds' extra cone type allows them not just to see UV light but also to discriminate additional nonspectral colors. Our results support the idea that birds can distinguish colors throughout tetrachromatic color space and indicate that nonspectral color perception is vital for signaling and foraging. Since tetrachromacy appears to have evolved early in vertebrates, this capacity for rich nonspectral color perception is likely widespread.


Subject(s)
Birds/physiology , Color Perception/physiology , Color Vision/physiology , Animals , Photic Stimulation , Retina
3.
Interface Focus ; 9(1): 20180053, 2019 Feb 06.
Article in English | MEDLINE | ID: mdl-30603072

ABSTRACT

The use of artificially coloured stimuli, especially to test hypotheses about sexual selection and anti-predator defence, has been common in behavioural ecology since the pioneering work of Tinbergen. To investigate the effects of colour on animal behaviour, many researchers use paints, markers and dyes to modify existing colours or to add colour to synthetic models. Because colour perception varies widely across species, it is critical to account for the signal receiver's vision when performing colour manipulations. To explore this, we applied 26 typical coloration products to different types of avian feathers. Next, we measured the artificially coloured feathers using two complementary techniques-spectrophotometry and digital ultraviolet--visible photography-and modelled their appearance to mammalian dichromats (ferret, dog), trichromats (honeybee, human) and avian tetrachromats (hummingbird, blue tit). Overall, artificial colours can have dramatic and sometimes unexpected effects on the reflectance properties of feathers, often differing based on feather type. The degree to which an artificial colour differs from the original colour greatly depends on an animal's visual system. 'White' paint to a human is not 'white' to a honeybee or blue tit. Based on our analysis, we offer practical guidelines for reducing the risk of introducing unintended effects when using artificial colours in behavioural experiments.

4.
Sci Rep ; 6: 32059, 2016 09 12.
Article in English | MEDLINE | ID: mdl-27616020

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 digital images of clutches laid by both species. We then calibrated the images and used custom computer software and edge detection algorithms to quantify measures related to three potential camouflage mechanisms: pattern complexity matching, disruptive effects and background color matching. Based on our image analyses, Snowy Plover clutches, in general, appeared to be more camouflaged than Least Tern clutches. Snowy Plover clutches also survived better than Least Tern clutches. Unexpectedly, variation in clutch survival was not explained by any measure of egg camouflage in either species. We conclude that measures of egg camouflage are poor predictors of clutch survival in this population. The behavior of the incubating parents may also affect clutch predation. Determining the significance of egg camouflage requires further testing using visual models and behavioral experiments.


Subject(s)
Biological Mimicry , Charadriiformes/physiology , Animals , Image Processing, Computer-Assisted , Species Specificity , Survival Analysis
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