Global map of tree density

<b>Crowther_Nature_Files.zip</b> This description pertains to the original download. Details on revised (newer) versions of the datasets are listed below. When more than one version of a file exists in Figshare, the original DOI will take users to the latest version, though each version technically has its own DOI. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al 2015 and Glick et al 2016). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. Additionally, due to data limitations, estimates for Mangroves and Tropical coniferous forest (as identified by WWF and TNC) were generated using models constructed from Topical moist broadleaf forest data and Temperate coniferous forest data, respectively. Because we used ecological analogy, the estimates for these two biomes should be considered less reliable than those of other biomes .<br> These two maps initially appeared in Crowther et al (2015), with the biome map being featured more prominently. Explicit publication of the data is associated with Glick et al (2016). As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Versions (see below).<br> <br> Methods: We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally. All modeling was done in R. Mapping was done using R and ArcGIS 10.1.<br> <br> Viewing Instructions: Load the files into an appropriate geographic information system (GIS). For the original download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files (see Additional Versions), load them into any compatible GIS or image management program.<br> <br> Comments: The original download provides a zipped folder that contains (1) an ArcGIS File Geodatabase (.gdb) containing one raster file for each of the two global models of tree density – one based on biomes and one based on ecoregions; (2) a layer file (.lyr) for each of the global models with the symbology used for each respective model in Crowther et al (2015); and an ArcGIS Map Document (.mxd) that contains the layers and symbology for each map in the paper. The data is delivered in the Goode homolosine interrupted projected coordinate system that was used to compute biome, ecoregion, and global estimates of the number and density of trees presented in Crowther et al (2015). To obtain maps like those presented in the official publication, raster files will need to be reprojected to the Eckert III projected coordinate system. Details on subsequent revisions and alternative file formats are list below under Additional Versions.----------<br> Additional Versions:<br> <b>Crowther_Nature_Files_Revision_01.zip</b> contains tree density predictions for small islands that are not included in the data available in the original dataset. These predictions were not taken into consideration in production of maps and figures presented in Crowther et al (2015), with the exception of the values presented in Supplemental Table 2. The file structure follows that of the original data and includes both biome- and ecoregion-level models. <b>Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip</b> contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ (substantially at greater latitudes) as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files. <br>References: Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A. 2015. Mapping tree density at a global scale. <i>Nature</i>, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., and Crowther, T. W. 2016. Spatially explicit models of global tree density. <i>Scientific Data</i>, 3(160069), doi:10.1038/sdata.2016.69.<br> <br> <br> <br>

<b>Crowther_Nature_Files.zip</b> 本说明针对原始下载包。数据集修订（更新）版本的详情见下文。若Figshare平台中存在多个文件版本，原始DOI将引导用户访问最新版本，但每个版本严格来说拥有独立的DOI。

本数据集包含两幅全球树木密度栅格地图，用以展示全球树木数量的分布差异。其中一幅地图基于生物群系（biome）尺度的树木密度模型构建，并在生物群系尺度上应用；另一幅则基于生态区（ecoregion）尺度的树木密度模型构建，并在生态区尺度上应用。正因如此，生物群系或生态区之间的过渡可能显得极不自然，但大尺度估算结果具备稳健性（详见Crowther等人2015年及Glick等人2016年研究）。本研究初衷为生成大空间尺度下的可靠估算值，这必然以牺牲精细尺度的精度为代价。因此，国家尺度及更大尺度的估算通常比单个像素级估算更为稳健。此外，受限于数据可得性，红树林与热带针叶林（由世界自然基金会(WWF)和大自然保护协会(TNC)定义）的估算值分别采用热带湿润阔叶林数据与温带针叶林数据构建模型得到。由于采用了生态类比方法，这两类生物群系的估算值可靠性应低于其他生物群系。

这两幅地图最初发表于Crowther等人2015年的研究中，其中基于生物群系的地图得到了更广泛的展示。本数据集的正式发表关联于Glick等人2016年的研究。后续更新的数据集版本及其他格式的数据将在“附加版本”板块发布（详见下文）。

研究方法：我们收集了全球范围内超过42万份地面实测的树木密度估算数据。随后，我们利用植被、气候、地形及人为活动变量构建线性回归模型，以生成全球所有区域的林木密度估算值。所有建模工作均在R语言环境中完成，制图则使用R与ArcGIS 10.1。

查看说明：将文件加载至合适的地理信息系统（Geographic Information System, GIS）中。对于原始下载的ArcGIS地理数据库文件，需将其加载至ArcGIS中以查看数据，或导出为其他格式。由于本数据集体量较大且采用了多数地理信息系统无法识别的专属坐标系，我们建议将其加载至坐标系与数据匹配的ArcGIS数据框中（详见“文件格式”说明）。对于GeoTiff(GeoTiff)格式文件（详见附加版本），可将其加载至任意兼容的地理信息系统或图像管理程序中。

补充说明：原始下载包为压缩文件夹，内含以下内容：(1) 一个ArcGIS文件地理数据库(.gdb)，包含两个全球树木密度模型对应的栅格文件——分别基于生物群系与生态区；(2) 两个全球模型各自的图层文件(.lyr)，带有Crowther等人2015年研究中对应模型使用的符号系统；以及一份ArcGIS地图文档(.mxd)，包含论文中两幅地图的图层与符号系统。本数据采用古德homolosine中断投影坐标系，该坐标系用于计算Crowther等人2015年研究中提出的全球树木数量与密度的生物群系、生态区及全球尺度估算值。若要获取与正式出版物中一致的地图，需将栅格文件重投影至埃克特三世投影坐标系。后续修订版本与替代文件格式的详情见下文“附加版本”板块。----------

附加版本：
<b>Crowther_Nature_Files_Revision_01.zip</b> 包含原始数据集未涵盖的小岛树木密度预测值。除补充表2中的数值外，这些预测值未被纳入Crowther等人2015年研究的地图与图表制作流程。该文件的结构与原始数据一致，包含生物群系与生态区尺度的模型数据。<b>Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip</b> 包含修订版01的生物群系模型数据，存储为WGS84坐标系下的GeoTiff格式。该文件通过在ArcMap中使用最近邻重采样方法，将原始古德homolosine文件重投影至WGS84坐标系得到。论文中所有面积计算均采用古德homolosine投影坐标系，因此使用该WGS84版本数据进行的可比计算可能存在差异（高纬度地区差异尤为显著），这是重采样过程导致的结果。该压缩包内含主.tif文件及其可视化辅助文件。

参考文献：
Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., & Bradford, M. A. 2015. Mapping tree density at a global scale. <i>Nature</i>, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967
Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., & Crowther, T. W. 2016. Spatially explicit models of global tree density. <i>Scientific Data</i>, 3(160069), doi:10.1038/sdata.2016.69.