9-second gridded continental Australia potential degree of ecological change for Mammals 1990:2050 CanESM2 RCP 8.5 (CMIP5) (GDM: MAM_R2)
收藏资源简介：
Potential degree of ecological change in Mammals as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CanESM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the change in long term average environmental conditions at a single location (9s grid square) from the present (1990 centred) to a 2050 centred future, scaled in terms of its expected effects on the turnover of species. Compositional turnover patterns in amphibian species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracted from the Atlas of Living Australia (ALA) in 2013, and spatial environmental predictor data compiled at 9 second resolution. GDM-scaled environmental grids were used as the basis for pairwise cell comparisons across space and time using the highly parallel CSIRO Muru software to derive the potential degree of ecological change. Each location is compared with its future state. The difference in environment is presented as an expected ecological similarity, ranging from 1 (completely similar) to 0, for which we would expect no species in common. If this environmental difference was observed in a different spatial location within the present, we would expect to observe such a difference if we visited both sites. This 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. Data are provided in two forms:1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file.2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend.Additionally a short methods summary is provided in the file 9sMethodsSummary.pdf for further information.Tom HALayers in this 9s series use a consistent naming convention:BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSISe.g. A_90_CAN85_S or R_90_MIR85_Lwhere BIOLOGICAL GROUP is A: Mammals, M: mammals, R: reptiles and V: vascular plantsLineage: Potential degree of ecological change was calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. The similarity of each cell in the present to its future state was calculated. More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download. GDM Model:
基于物种组成更替的广义相异性建模（Generalised Dissimilarity Modelling, GDM），本数据集展示了以1990年为中心时段的当前气候，与基于CanESM2模型（RCP 8.5情景）预测的以2050年为中心时段的未来气候之间的长期（30年平均）气候变化为函数的哺乳动物潜在生态变化程度。 该指标描述了单个位点（9秒网格单元）内，从以1990年为基准的当前长期平均环境条件，到以2050年为基准的未来长期平均环境条件的变化，并基于其对物种更替的预期效应进行了标准化。基于广义相异性建模（GDM），研究推导了澳大利亚大陆范围内两栖动物的物种组成更替模式。本模型采用2013年从澳大利亚生物图鉴（Atlas of Living Australia, ALA）中获取的最优生物数据，以及分辨率为9秒的空间环境预测变量数据。研究采用高度并行化的CSIRO Muru软件，以经GDM标准化后的环境栅格为基础，开展空间与时间维度上的成对栅格单元对比，从而计算得到潜在生态变化程度。每个位点均与其未来状态进行对比，环境差异以预期生态相似性表示，取值范围为1（完全相似）至0（无共有物种）。若在当前的不同空间位点间观测到该类环境差异，则当同时造访这两个位点时，可观测到一致的物种组成差异。 该指标与其他指标一同被开发，用于在大陆与全球尺度上评估气候变化背景下保护区系统对生物多样性的保护效能，相关成果曾在2014年世界自然保护联盟（IUCN）世界公园大会上展示。该指标的详细说明见于AdaptNRM指南"Implications of Climate Change for Biodiversity: a community-level modelling approach"，可通过网址www.adaptnrm.org在线获取。 本数据集提供两种格式的数据： 1. 压缩版ESRI浮点栅格数据：二进制浮点栅格文件（*.flt），配套关联的ESRI头文件（*.hdr）与投影文件（*.prj）。从压缩包中解压后，这些文件可导入绝大多数GIS软件中，通过替换对应头文件的方式，也可作为其他二进制文件格式使用。 2. ArcGIS图层包（*.lpk）：此类数据包可通过ArcGIS解压为带有配套图例的栅格数据。 此外，数据集中附带的9sMethodsSummary.pdf文件提供了简短的方法概述，以供进一步查阅。（作者：Tom HA） 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_情景_分析类型 示例：A_90_CAN85_S 或 R_90_MIR85_L 其中生物类群的取值含义为：A代表哺乳动物（Mammals），M代表哺乳动物（mammals），R代表爬行动物，V代表维管植物。 数据溯源：潜在生态变化程度通过运行于Linux高性能计算集群的高度并行化定制化CSIRO Muru软件计算得到，输入数据为经GDM模型转换后的环境栅格。研究计算了当前时段每个栅格单元与其未来状态的相似性。计算与方法的更多细节可参见数据下载包中附带的9sMethodsSummary.pdf文件。 广义相异性建模（GDM）模型：
