m_90mir85_snd: 9-second gridded continental Australia composite ecological change for Mammals 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: MAM_R2)

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 mammals (MAM_R2). \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 Mammals 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: MAM_R2)\n2. N, novel: 9-second gridded continental Australia novel ecological environments for Mammals 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: MAM_R2)\n3. D, dissimilarity: 9-second gridded continental Australia disappearing ecological environments for Mammals 1990:2050 MIROC5 RCP 8.5 (CMIP5) (GDM: MAM_R2)\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 mammal species for continental Australia at 9 second resolution using ANHAT data extracted 4 April 2013 (GDM: MAM_R2)\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\n

复合生态变化作为三个指标（潜在生态变化程度、消失生态环境及新生生态环境）的函数，基于哺乳动物组成周转的广义差异模型（Generalised Dissimilarity Modelling, GDM）（MAM_R2），利用MIROC5全球气候模型（RCP 8.5）下当前（1990：1976-2005）与未来预测（2050：2036-2065）两个时期的30年气候平均值，揭示了变化可能最显著的区域及不同类型的脆弱性。

当潜在生态变化程度得分较低时，生态环境既不会成为新生环境也不会消失，预期变化极小；而当潜在生态变化程度得分较高时，变化的可能类型则取决于新生和/或消失生态环境的得分是否同样较高。

为构建复合视图，我们将三个组分指标分别分配至复合波段栅格的一个颜色通道：局部相似性对应绿色色调（反转后，1-0重标度至0-255）；新生环境对应蓝色色调（0-1重标度至0-255）；消失环境对应红色色调（0-1重标度至0-255）。随后可将这三个波段同时映射（红：波段3；绿：波段1；蓝：波段2），各波段均缩放至0-255，以呈现相似、新生及消失生态环境的不同程度及其组合。

该指标与其他指标共同开发，用于在大陆及全球尺度评估气候变化下保护区系统对生物多样性的有效性，并在2014年世界自然保护联盟（IUCN）世界公园大会上展示。其详细描述见《AdaptNRM指南：气候变化对生物多样性的影响——群落水平建模方法》，可在线获取：www.adaptnrm.org。

数据以压缩的ESRI TIFF网格形式提供，包含栅格图像（*.tif）及关联的头文件（*.tfw）和投影文件（*.xml）。从压缩包中提取后，这些文件可导入大多数地理信息系统（GIS）软件包。自述文件（readme）描述了如何正确复现颜色图例。在ArcGIS中，可使用符号统计文件："SND_display.stat.XML"。

在ArcGIS中为3波段栅格复现RGB复合颜色：
1. 在ArcGIS的文件属性中，切换至符号学（Symbology）选项卡，加载XML文件"SND_display.stat.XML"；
2. 红色 = 波段3（消失环境）；
3. 绿色 = 波段1（相似性）；
4. 蓝色 = 波段2（新生环境）；
5. 始终使用最小-最大图例；
6. 将每个波段的自定义范围设为0-255，均值=126，标准差=0。

本9秒系列中的图层采用一致的命名规则：生物类群_基准至情景_分析类型，例如A_90CAN85_SND或R_90MIR85_SND。其中生物类群：A=两栖动物、M=哺乳动物、R=爬行动物、V=维管植物；情景：CAN=CanESM2、MIR=MIROC5；分析类型SND指相似性（similarity）、新生（novel）、消失（disappearing）。

谱系（Lineage）：生态相似性取值范围为0至1：越接近0，生物多样性组成变化的潜力越大。三个生态相似性指标均被重标度为0至255的整数以匹配RGB颜色尺度，但潜在生态变化程度指标需先反转（1-0重标度至0-255）。

使用ArcGIS 10.2.2中的复合波段工具，创建三波段栅格：波段1=相似性（S）、波段2=新生（N）、波段3=消失（D）。

在ArcGIS映射符号学中，三个组分指标分别分配至以下颜色通道：红色通道=波段3（消失环境）、绿色通道=波段1（相似性）、蓝色通道=波段2（新生环境）。

未使用伽马拉伸图例缩放，而是应用最小-最大图例拉伸，各波段的统计量由相同自定义设置定义：最小值=0、最大值=255、均值=126、标准差=0。这些设置可正确复现颜色。

复合生态变化指数源自以下三个别处详述的指标：
1. S（相似性）：澳大利亚大陆9秒网格哺乳动物潜在生态变化程度（当前1990：1976-2005至未来2050：2036-2065，MIROC5 RCP 8.5（CMIP5），GDM：MAM_R2）；
2. N（新生）：澳大利亚大陆9秒网格哺乳动物新生生态环境（同上情景，GDM：MAM_R2）；
3. D（差异）：澳大利亚大陆9秒网格哺乳动物消失生态环境（同上情景，GDM：MAM_R2）。

各指标计算及方法的更多细节见数据下载包中的文档"9sMethodsSummary.pdf"。

这三个指标均使用广义差异模型（GDM），其别处描述如下：基于2013年4月4日提取的ANHAT数据，澳大利亚大陆9秒分辨率下哺乳动物物种组成周转的广义差异模型（GDM：MAM_R2）。

气候数据：广义差异模型的构建与投影使用以下别处描述的气候数据：
a) 澳大利亚大陆1976-2005年9秒网格气候学：含海拔及辐射调整的汇总变量；
b) 澳大利亚大陆2036-2065年9秒网格气候学（MIROC5 RCP 8.5（CMIP5））：含海拔及辐射调整的汇总变量。

气候降尺度方法的简要概述见数据下载包中的文档"9sMethodsSummary.pdf"。

MIROC5全球气候模型的更多细节：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及Kimoto M（2010）《MIROC5对气候模拟的改进：平均状态、变率及气候敏感性》，《气候杂志》23(23)：6312-6335，DOI:10.1173/2010JCLI3679.1。