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The normalized segment classification model: A new tool to compare spectral reflectance curves

ABSTRACT: Abstract Color patterns are complex traits under selective pressures from conspecifics, mutualists, and antagonists. To evaluate the salience of a pattern or the similarity between colors, several visual models are available. Color discrimination models estimate the perceptual difference between any two colors. Their application to a diversity of taxonomic groups has become common in the literature to answer behavioral, ecological, and evolutionary questions. To use these models, we need information about the visual system of our beholder species. However, many color patterns are simultaneously subject to selective pressures from different species, often from different taxonomic groups, with different visual systems. Furthermore, we lack information about the visual system of many species, leading ecologists to use surrogate values or theoretical estimates for model parameters. Here, we present a modification of the segment classification method proposed by Endler (Biological Journal of the Linnean Society, 1990 41, 315–352): the normalized segment classification model (NSC). We explain its logic and use, exploring how NSC differs from other visual models. We also compare its predictions with available experimental data. Even though the NSC model includes no information about the visual system of the receiver species, it performed better than traditional color discrimination models when predicting the output of some behavioral tasks. Although vision scientists define color as independent of stimulus brightness, a likely explanation for the goodness of fit of the NSC model is that its distance measure depends on brightness differences, and achromatic information can influence the decision?making process of animals when chromatic information is missing. Species?specific models may be insufficient for the study of color patterns in a community context. The NSC model offers a species?independent solution for color analyses, allowing us to calculate color differences when we ignore the intended viewer of a signal or when different species impose selective pressures on the signal. Color patterns are complex traits under a variety of biotic and abiotic selective pressures. In a community context, species?specific models may be insufficient for the study of colour patterns. The NSC model offers a species?independent solution for colour analyses, allowing ecologists to calculate colour differences when we ignore the intended viewer of a signal, or when different species impose selective pressures on the signal.

SUBMITTER: Rodriguez?Girones M

PROVIDER: S-EPMC7771133 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Project description:As coral bleaching events become more frequent and intense, our ability to predict and mitigate future events depends upon our capacity to interpret patterns within previous episodes. Responses to thermal stress vary among coral species; however the diversity of coral assemblages, environmental conditions, assessment protocols, and severity criteria applied in the global effort to document bleaching patterns creates challenges for the development of a systemic metric of taxon-specific response. Here, we describe and validate a novel framework to standardize bleaching response records and estimate their measurement uncertainties. Taxon-specific bleaching and mortality records (2036) of 374 coral taxa (during 1982-2006) at 316 sites were standardized to average percent tissue area affected and a taxon-specific bleaching response index (taxon-BRI) was calculated by averaging taxon-specific response over all sites where a taxon was present. Differential bleaching among corals was widely variable (mean taxon-BRI = 25.06 ± 18.44%, ±SE). Coral response may differ because holobionts are biologically different (intrinsic factors), they were exposed to different environmental conditions (extrinsic factors), or inconsistencies in reporting (measurement uncertainty). We found that both extrinsic and intrinsic factors have comparable influence within a given site and event (60% and 40% of bleaching response variance of all records explained, respectively). However, when responses of individual taxa are averaged across sites to obtain taxon-BRI, differential response was primarily driven by intrinsic differences among taxa (65% of taxon-BRI variance explained), not conditions across sites (6% explained), nor measurement uncertainty (29% explained). Thus, taxon-BRI is a robust metric of intrinsic susceptibility of coral taxa. Taxon-BRI provides a broadly applicable framework for standardization and error estimation for disparate historical records and collection of novel data, allowing for unprecedented accuracy in parameterization of mechanistic and predictive models and conservation plans.

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The normalized segment classification model: A new tool to compare spectral reflectance curves

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