v_90mir85_snd: 9-second gridded continental Australia composite ecological change for Vascular Plants 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: VAS_v5_r11)

Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and different types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the MIROC5 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for vascular plants (VAS_v5_r11). \n\nWherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. \n\nTo create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. \n\nThis metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Implications of Climate Change for Biodiversity: a community-level modelling approach”, available online at: www.adaptnrm.org. \n\nData are provided as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". \n\nReproducing RGB composite colours for 3-band raster in ArcGIS: \n1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML"\n2. RED = BAND_3 (Disappearing)\n3. GREEN = BAND_1 (Similarity )\n4. BLUE = BAND_2 (Novel)\n5. Always use min-max legend\n6. Set each band in the custom range 0-255, mean = 126, std = 0\n\nLayers in this 9s series use a consistent naming convention:\nBIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS\ne.g. A_90CAN85_SND or R_90MIR85_SND\nwhere BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants\nand scenario is CAN: CanESM2; MIR: MIROC5\nanalysis, SND refers to – similarity, novel, disappearing\n\nLineage: Ecological similarity ranges between 0 and 1: the closer to zero, the greater the potential for compositional change in biodiversity. Each of the three ecological similarity measures were rescaled between 0 and 255 as integers to match the RGB colour scale, but the Potential degree of ecological change measure was inverted first (1-0 rescaled 0-255). \n\nUsing the Composite Bands tool in ArcGIS 10.2.2, a three-band raster was created with band1 = similarity, S; band 2 = novel, N; and band 3 = disappearing, D. \n\nIn ArcGIS mapping symbology, each of the three component measures are then assigned to a colour band:\nRED channel = BAND_3 (Disappearing)\nGREEN channel = BAND_1 (Similarity)\nBLUE channel = BAND_2 (Novel)\n\nThe gamma stretch legend scaling is not used and the min-max legend stretch is applied with statistics defined from the same custom settings for each band: minimum = 0; maximum= 255, mean = 126, std = 0. \n\nThese settings correctly reproduce the colours. \n\nThe composite ecological change index derives from the following three measures that are elsewhere described: \n\n1. S, similarity: 9-second gridded continental Australia potential degree of ecological change for Vascular Plants 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: VAS_v5_r11)\n2. N, novel: 9-second gridded continental Australia novel ecological environments for Vascular Plants 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: VAS_v5_r11)\n3. D, dissimilarity: 9-second gridded continental Australia disappearing ecological environments for Vascular Plants 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: VAS_v5_r11)\n\nMore detail of the calculations and methods used to derive the individual measures are given in the document “9sMethodsSummary.pdf” provided with the data download.\n\nEach of these three measures use the GDM model that is elsewhere described: Generalised dissimilarity model of compositional turnover in vascular plant species for continental Australia at 9 second resolution using ANHAT data extracted 4 April 2013 (GDM: VAS_v5_r11)\n\nClimate data. Generalised dissimilarity models were built and projected using climate data that are elsewhere described:\na) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment\nb) 9-second gridded climatology for continental Australia 2036-2065 MIROC5 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment\n\nA brief summary of the climate downscaling method is given in the document “9sMethodsSummary.pdf” provided with the data download. \n\nFurther details about the MIROC5 global climate model: \nWatanabe M, Suzuki T, O'ishi R, Komuro Y, Watanabe S, Emori S, Takemura T, Chikira M, Ogura T, Sekiguchi M, Takata K, Yamazaki D, Yokohata T, Nozawa T, Hasumi H, Tatebe H and Kimoto M (2010) ‘Improved Climate Simulation by MIROC5. Mean States, Variability, and Climate Sensitivity’, JOURNAL of CLIMATE 23(23), 6312-6335, doi:10.1173/2010JCLI3679.1

本复合生态变化指标以三项量化指标为基础（生态变化潜在程度、消失型生态环境与新型生态环境），基于维管植物（vascular plants）物种组成周转的广义相异模型（Generalised Dissimilarity Modelling, GDM，VAS_v5_r11），利用当前时段（1990年：1976-2005年）与未来预测时段（2050年：2036-2065年）的30年气候平均值，结合MIROC5全球气候模型（RCP 8.5）情景，用以识别生态变化最剧烈的区域以及不同类型的生态脆弱性。

当生态变化潜在程度得分较低时，区域内既不会出现新型生态环境，也不会有生态环境消失，仅会发生极小幅度的变化；而当生态变化潜在程度得分较高时，则会依据新型与/或消失型生态环境的得分高低，出现多种不同类型的生态变化。

为生成复合可视化结果，我们将三项组分指标分别对应至复合波段栅格（composite-band raster）的色彩通道：以绿色调表示局地相似性（local similarity）（经反转处理，将1-0区间重映射至0-255）；以蓝色调表示新型生态环境（0-1区间重映射至0-255）；以红色调表示消失型生态环境（0-1区间重映射至0-255）。随后可同时映射三层数据（红色对应波段3，绿色对应波段1，蓝色对应波段2），所有波段均缩放至0-255区间，用以展示相似、新型与消失型生态环境的不同程度及其组合模式。

本指标与其他相关指标一同开发，用于评估大陆及全球尺度下气候变化对生物多样性保护地系统有效性，相关成果发表于2014年世界自然保护联盟（International Union for Conservation of Nature, IUCN）世界公园大会。其详细说明载于AdaptNRM指南《气候变化对生物多样性的影响：群落级建模方法》，可通过网址www.adaptnrm.org在线获取。

数据集以压缩的ESRI TIFF栅格包形式提供，内含栅格图像文件（*.tif）及相关的头文件（*.tfw）与投影文件（*.xml）。解压压缩包后，这些文件可导入绝大多数地理信息系统（Geographic Information System, GIS）软件。自述文件（readme file）说明了如何正确复现色彩图例；在ArcGIS中，可直接使用符号系统统计文件"SND_display.stat.XML"。

在ArcGIS中复现三波段栅格的RGB复合色彩步骤如下：
1. 打开ArcGIS中的文件属性窗口，切换至符号系统（Symbology）标签页，加载XML文件"SND_display.stat.XML"
2. 红色通道对应波段3（消失型生态环境）
3. 绿色通道对应波段1（相似性）
4. 蓝色通道对应波段2（新型生态环境）
5. 始终使用最小-最大图例（min-max legend）
6. 将每个波段的自定义范围设为0-255，均值设为126，标准差设为0

本9秒分辨率系列数据集的图层采用统一命名规则：
[生物类群] _ [基准时段至情景时段] _ [分析类型]
示例：A_90CAN85_SND 或 R_90MIR85_SND
其中，生物类群代码含义为：A=两栖类（amphibians），M=哺乳类（mammals），R=爬行类（reptiles），V=维管植物（vascular plants）；情景代码含义为：CAN=CanESM2模型，MIR=MIROC5模型；分析类型代码SND分别对应相似性（similarity）、新型（novel）与消失型（disappearing）

指标溯源：生态相似性取值范围为0至1，数值越接近0，生物群落组成发生变化的潜在幅度越大。三项生态相似性指标均被转换为0-255区间的整数，以匹配RGB色彩刻度；其中生态变化潜在程度指标需先进行反转处理（将1-0区间重映射至0-255）。

使用ArcGIS 10.2.2中的复合波段工具（Composite Bands tool），可生成三波段栅格：波段1对应相似性指标S，波段2对应新型生态环境指标N，波段3对应消失型生态环境指标D。

在ArcGIS制图符号系统中，需将三项组分指标分别对应至色彩通道：
红色通道对应波段3（消失型生态环境）
绿色通道对应波段1（相似性）
蓝色通道对应波段2（新型生态环境）
无需使用伽马拉伸图例缩放方式，而是采用最小-最大图例拉伸，并为每个波段设置统一的自定义统计参数：最小值=0，最大值=255，均值=126，标准差=0。
该设置可正确复现目标色彩。

本复合生态变化指数源自如下三项已在其他文献中详述的指标：
1. S（相似性）：澳大利亚大陆9秒分辨率栅格数据，维管植物1990-2050年MIROC5模型RCP 8.5（CMIP5）情景下的生态变化潜在程度（GDM: VAS_v5_r11）
2. N（新型生态环境）：澳大利亚大陆9秒分辨率栅格数据，维管植物1990-2050年MIROC5模型RCP 8.5（CMIP5）情景下的新型生态环境（GDM: VAS_v5_r11）
3. D（消失型生态环境）：澳大利亚大陆9秒分辨率栅格数据，维管植物1990-2050年MIROC5模型RCP 8.5（CMIP5）情景下的消失型生态环境（GDM: VAS_v5_r11）

各项指标的具体计算方法与技术细节可参见数据下载包中附带的文档"9sMethodsSummary.pdf"。

三项指标均采用已在其他文献中详述的广义相异模型（Generalised Dissimilarity Modelling, GDM）方法：基于2013年4月4日提取的ANHAT数据，以9秒分辨率对澳大利亚大陆维管植物物种组成周转进行建模（GDM: VAS_v5_r11）

气候数据。本研究的广义相异模型构建与投影均采用已在其他文献中详述的气候数据：
a) 澳大利亚大陆1976-2005年9秒分辨率气候学数据：包含高程与辐射校正的汇总变量
b) 澳大利亚大陆2036-2065年MIROC5模型RCP 8.5（CMIP5）情景下9秒分辨率气候学数据：包含高程与辐射校正的汇总变量
气候降尺度方法的简要概述可参见数据下载包中附带的文档"9sMethodsSummary.pdf"。

关于MIROC5全球气候模型的更多细节可参见如下文献：
Watanabe M, Suzuki T, O'ishi R, Komuro Y, Watanabe S, Emori S, Takemura T, Chikira M, Ogura T, Sekiguchi M, Takata K, Yamazaki D, Yokohata T, Nozawa T, Hasumi H, Tatebe H, Kimoto M. 2010. MIROC5对气候模拟的改进：平均状态、变异性与气候敏感性. 气候学报（JOURNAL of CLIMATE）, 23(23): 6312-6335. doi:10.1173/2010JCLI3679.1