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>
本说明适用于数据集的原始下载版本，有关数据集修订（更新）版本的详细信息如下。当Figshare平台上存在多个文件版本时，原始DOI会将用户导向最新版本，但每个版本实际上均拥有独立的DOI。
本数据集包含两份全球树木密度栅格地图，用以展现全球范围内树木数量的分布差异。其中一份地图基于生物群系（biome）尺度的树木密度模型生成，并在生物群系尺度上应用；另一份则基于生态区（ecoregion）尺度的树木密度模型生成，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边界过渡可能会出现不切实际的生硬感，但大尺度的估算结果仍具备稳健性（详见Crowther等人2015年与Glick等人2016年的研究）。本研究最初旨在生成大空间尺度下的可靠估算值，这不可避免地以牺牲精细尺度的精度为代价。因此，国家尺度（或更大尺度）的估算结果通常比单个像元级别的估算结果更为稳健。此外，受限于数据可得性，红树林（Mangroves）与热带针叶林（Tropical coniferous forest，由世界自然基金会WWF和大自然保护协会TNC界定）的估算值，分别基于热带湿润阔叶林与温带针叶林的数据构建的模型生成。由于采用了生态类比法，这两个生物群系的估算结果可靠性应低于其他生物群系。

这两份地图最初发表于Crowther等人2015年的研究中，其中基于生物群系的地图得到了更为广泛的展示。本数据集的正式出版关联于Glick等人2016年的研究。随着数据集的更新版本以及其他格式版本的推出，相关内容将在“附加版本”栏目下发布（详见下文）。

研究方法：我们从全球范围内收集了超过42万份实地观测的树木密度估算数据。随后，我们利用植被、气候、地形以及人为活动相关变量构建线性回归模型，以生成全球所有区域的森林树木密度估算值。所有建模工作均在R语言环境中完成，地图绘制则通过R与ArcGIS 10.1实现。

查看说明：将文件导入合适的地理信息系统（Geographic Information System, GIS）即可查看。对于原始下载的ArcGIS文件地理数据库文件，可将其导入ArcGIS以查看数据，或导出为其他格式。由于本数据集体积较大，且采用了许多GIS软件无法直接读取的专属坐标系，我们建议将其导入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格式文件（详见“附加版本”），可将其导入任意兼容的GIS或图像管理程序中查看。

补充说明：原始下载文件为压缩文件夹，内含以下内容：(1) 一个ArcGIS文件地理数据库（.gdb），包含两份全球树木密度模型各自对应的一份栅格文件——一份基于生物群系，另一份基于生态区；(2) 两份全球树木密度模型对应的图层文件（.lyr），包含Crowther等人2015年研究中各模型所使用的符号体系；以及一份ArcGIS地图文档（.mxd），内含论文中两张地图对应的图层与符号体系。本数据采用古德霍莫洛辛间断投影坐标系（Goode homolosine interrupted projected coordinate system），该坐标系被用于计算Crowther等人2015年研究中提出的生物群系、生态区以及全球尺度的树木数量与密度估算值。若要生成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（Eckert III）投影坐标系。后续修订版本与其他文件格式的详细信息将在下文“附加版本”栏目中列出。----------
附加版本：
<b>Crowther_Nature_Files_Revision_01.zip</b> 包含原始数据集中未纳入的小型岛屿树木密度预测值。除补充表2中的数值外，这些预测值未被纳入Crowther等人2015年研究中的地图与图表制作流程。该文件的结构与原始数据一致，同时包含基于生物群系与生态区尺度的模型。
<b>Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip</b> 包含修订版01的生物群系尺度模型，采用WGS84坐标系与GeoTiff格式存储。该文件通过ArcMap中最近邻重采样法，将原始古德霍莫洛辛间断投影文件重投影至WGS84坐标系生成。论文中所有面积计算均采用古德霍莫洛辛间断投影坐标系完成，因此使用该WGS84格式数据进行的可比计算结果可能存在差异（在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., and Bradford, M. A. 2015. Mapping tree density at a global scale. *Nature*, 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., and Crowther, T. W. 2016. Spatially explicit models of global tree density. *Scientific Data*, 3(160069), doi:10.1038/sdata.2016.69.