Data from: Abiotic and biotic predictors of macroecological patterns in bird and butterfly coloration

Animal color phenotypes are invariably influenced by both their biotic community and the abiotic environments. A host of hypotheses have been proposed for how variables such as solar radiation, habitat shadiness, primary productivity, temperature, rainfall and community diversity might affect animal color traits. However, while individual factors have been linked to coloration in specific contexts, little is known about which factors are most important across broad taxonomic and geographic scales. Using data collected from 570 species of birds and 424 species of butterflies from Australia which inhabit an area spanning a latitudinal range of 35 degrees and covering deserts, tropical and temperate forests, savannas and heathlands, we test multiple hypotheses from the coloration literature and assess their relative importance. We show that bird and butterfly species exhibit more reflective and less saturated colors in better-lit environments, a pattern that is robust across an array of variables expected to influence the intensity or quality of ambient light in an environment. Both taxa display more diverse colors in regions with greater net primary production and longer growing seasons. Models that included variables related to energy inputs and resources in ecosystems have better explanatory power for bird and butterfly coloration overall than do models that included community diversity metrics. However, the diversity of the bird community in an environment was the single most powerful predictor of color pattern variation in both birds and butterflies. We observed strong similarities across taxa in the covariance between color and environmental factors, suggesting the presence of fundamental macro-ecological drivers of visual appearance across disparate taxa.

Usage Notes
Dalrymple_etal_EM2018Data from Dalrymple. et al. Abiotic and biotic predictors of macroecological patterns in bird and butterfly coloration. Ecological Monographs

Data for each grid cell in the study range is presented, including bird and butterfly colour (response) variables and environmental (predictor) variables. Predictor variables relate to the community diversity and averages of the data available for the energy and resources in the environment and the habitat conditions in the grid cells. See manuscript for details on data sourcing and units on environmental variables. see Dalrymple et al 2015 Birds, butterflies and flowers in the tropics are not more colourful than those at higher latitudes. Global Ecology and Biogeography, 24(12), 1424-1432. DOI: 10.1111/geb.12368 for information on bird and butterfly color data and methodology. .csv fileDalrymple_etal_EM2018_scriptforanalysesR script for application to Dalrymple_etal_EM2018.CSV data file - produces analyses and some figures. .txt fileDalrymple_etal_EM2018_Rcode.txt

动物的色彩表型始终受生物群落（biotic community）与非生物环境（abiotic environments）共同影响。学界已提出诸多假说，用以阐释太阳辐射、生境遮光度、初级生产力（primary productivity）、温度、降雨量以及群落多样性等变量如何作用于动物色彩性状。然而，尽管已有单个因素在特定情境下与动物色彩形成建立关联的研究，但目前学界对在宽泛的分类学与地理尺度下哪些因素最为关键仍知之甚少。

本研究利用采集自澳大利亚570种鸟类与424种蝴蝶的相关数据展开分析，这些物种的分布范围横跨35个纬度的跨度，涵盖沙漠、热带与温带森林、稀树草原以及灌丛多种生境。我们检验了色彩研究领域的多项假说，并评估了各假说的相对重要性。

研究结果显示，在光照更充足的环境中，鸟类与蝴蝶物种的色彩反射性更强、饱和度更低，这一模式在一系列可影响环境光强度与质量的变量中均表现出稳健性。两类群的色彩多样性均在净初级生产力（net primary production）更高、生长季更长的区域更为显著。相较于纳入群落多样性指标的模型，纳入生态系统能量输入与资源相关变量的模型，整体上对鸟类与蝴蝶色彩的解释力更强。然而，某一区域的鸟类群落多样性，是同时预测鸟类与蝴蝶色彩模式变异的最具效力的单一变量。我们观察到两类群在色彩与环境因子的协变关系上存在高度相似性，这表明在不同类群的视觉外观背后，存在普适性的宏观生态驱动因子（macro-ecological drivers）。

使用说明
本数据集源自Dalrymple等人的研究：《Abiotic and biotic predictors of macroecological patterns in bird and butterfly coloration》，发表于《Ecological Monographs》。
本数据集包含研究范围内每个网格单元的数据，涵盖鸟类与蝴蝶色彩（响应变量，response variable）以及环境（预测变量，predictor variable）两类数据。预测变量涉及群落多样性、环境中可获取的能量与资源的平均值，以及网格单元内的生境条件。有关环境变量的数据来源与量纲的详细信息，请参阅研究原文。
关于鸟类与蝴蝶色彩数据及研究方法的相关信息，可参考Dalrymple等人2015年的研究：《Birds, butterflies and flowers in the tropics are not more colourful than those at higher latitudes》，发表于《Global Ecology and Biogeography》，24(12), 1424-1432，DOI: 10.1111/geb.12368。
Dalrymple_etal_EM2018.csv：数据文件
Dalrymple_etal_EM2018_scriptforanalyses.R：用于处理Dalrymple_etal_EM2018.csv数据文件的R脚本，可生成分析结果与部分图表。
Dalrymple_etal_EM2018_Rcode.txt：R代码文本文件。