Predictive mapping of tree species assemblages in an African montane rainforest

Conservation of mountain ecosystems can benefit from knowledge of habitats and their distribution patterns. This benefit is particularly true for diverse ecosystems with high conservation values such as the “Afromontane” rainforests. We mapped the vegetation of one such forest: the rugged Bwindi Impenetrable Forest, Uganda—a World Heritage Site known for its many restricted-range plants and animal taxa including several iconic species. Given variation in elevation, terrain and human impacts across Bwindi, we hypothesised that these factors influence the composition and distribution of tree species. To test this, detailed surveys were carried out using stratified random sampling. We established 289 georeferenced sample sites (each with 15 trees ≥20 cm dbh) ranging from 1,320 to 2,467 m a.s.l. and measured 4,335 trees comprising 89 species that occurred in four or more sample sites. These data were analysed against twenty-one digitally mapped biophysical variables using various analytical..., Study design
To account for the different environmental conditions, we employed a stratified random sampling approach. The park was divided into five strata based on geological formations visible on the Digital Elevation Model (DEM) of Bwindi and the starting points on the boundary of the DEM in each stratum were selected randomly with the random point function within ArcGIS (version 10.5; ESRI, Redlands, CA, USA). Line transects were drawn on the DEM in each stratum from the random starting points to traverse the topographic positions of the ridges (Figure 1; Table 1). The number and length of the transects selected varied with area, accessibility and shape of the strata. We then superimposed the transect drawings on high-resolution (0.5m) true color, digital aerial photographs of Bwindi. The aerial photos were visually interpreted along the transects by drawing polygons around areas perceived to be of uniform tree community structure based on differences in tone and texture. This allo..., , # Predictive mapping of tree species assemblages in an African montane rainforest

Predictive mapping of tree species assemblages in an African montane rainforest

Babaasa, Dennis, Mbarara University,
Finn, John T., University of Massachusetts
Schweik, Charles M., University of Massachusetts
Fuller, Todd K., University of Massachusetts
Sheil, Douglas, Wageningen University

Research facility: Institute of Tropical Forest Conservation
Published January …., 2024 on Dryad.

Cite this dataset:
Babaasa, Dennis, Finn, John T., Schweik, Charles M., Fuller, Todd K., Sheil, Douglas (2024). Predictive mapping of tree species assemblages in an African montane rainforest. [Dataset] Dryad.

### Abstract

In this study, Bwindi Impenetrable National Park, Uganda, was divided into five strata based on geological formations visible on the Digital Elevation Model (DEM) of the study area. Random transects were established with the starting points on the boundary of the DEM in each stratum. The aeri...

山地生态系统的保护可依托对栖息地及其分布格局的认知，这一认知对于如"非洲山地（Afromontane）"雨林这类兼具高保护价值与丰富生物多样性的生态系统而言，意义尤为突出。我们对其中一处典型代表——乌干达崎岖的布温迪禁猎国家公园的植被开展了制图工作。该区域为世界遗产地，以众多狭域分布的动植物类群（含多种标志性物种）而享誉学界。
鉴于布温迪地区在海拔、地形与人类活动影响方面存在显著异质性，我们提出假设：上述因素会对树木物种的组成与分布产生调控作用。为验证该假设，我们采用分层随机抽样法开展了详尽的野外调查。本次调查共设置289个带有地理坐标的样地，每个样地内调查15株胸径≥20cm的树木，样地海拔跨度为1320至2467米；累计记录树木4335株，隶属于89个物种，且每个物种至少在4个样地中出现。我们针对21个数字化生成的生物物理变量，结合多种分析方法对上述数据开展了研究……

## 研究设计
为充分兼顾研究区域内不同的环境条件，我们采用分层随机抽样方案。本研究基于布温迪地区数字高程模型（Digital Elevation Model, DEM）上可识别的地质构造，将研究区域划分为5个抽样分层；随后利用ArcGIS（10.5版本；ESRI，美国加利福尼亚州雷德兰兹市）的随机点工具，在每个分层的DEM边界上随机选取样线起始点。在每个分层的DEM上，从随机选取的起始点出发布设样线，以穿越山脊的地形位置（相关信息见图1、表1）。所布设样线的数量与长度，会根据各分层的面积、可达性及形状进行调整。随后，我们将样线图层叠加至布温迪地区0.5米分辨率的高分辨率真彩色数字航空影像上。研究人员沿布设的样线对航空影像开展目视解译，依据影像色调与纹理差异，在具有统一树木群落结构的区域外围绘制多边形斑块。该流程……

# 非洲山地雨林树木物种组合的预测制图

## 非洲山地雨林树木物种组合的预测制图
Babaasa, Dennis，姆巴拉拉大学
Finn, John T.，马萨诸塞大学
Schweik, Charles M.，马萨诸塞大学
Fuller, Todd K.，马萨诸塞大学
Sheil, Douglas，瓦赫宁根大学

研究依托机构：热带森林保护研究所
2024年1月发表于Dryad数据平台。

引用本数据集：
Babaasa, Dennis, Finn, John T., Schweik, Charles M., Fuller, Todd K., Sheil, Douglas (2024). 非洲山地雨林树木物种组合的预测制图. [数据集] Dryad.

### 摘要
本研究以乌干达布温迪禁猎国家公园为研究对象，基于研究区域数字高程模型（DEM）上可识别的地质构造将其划分为5个抽样分层。研究人员在每个分层的DEM边界上选取起始点，布设随机样线。航空影像……