Using dung densities to assess the ecological effectiveness of a protected area network

Given recent global endeavors to increase protected area coverage, it is crucial to comprehensively evaluate the efficacy of various area-based conservation strategies in effectively reducing biodiversity loss. Here, we investigated responses of wildlife populations to different protection levels and environmental variables at the landscape scale in the Katavi-Rukwa Ecosystem, western Tanzania. To this end, we conducted line distance sampling surveys and counted dung of six target mammal species (elephant, giraffe, buffalo, zebra, topi, hartebeest) along foot transects within areas differing in protection levels (from strict to less-strictly protected: national park, game reserve, forest reserve, game-controlled area, and unprotected areas). Based on these dung counts, we modelled the spatial distribution of these six mammal species using a species-specific density surface modelling framework. We, found consistent effects of protection level and land-use variables on the spatial distrib..., We established a 35 km buffer around the boundary of the KNP to include areas with different protection levels, ranging from unprotected to strictly protected. To capture an even coverage of transects across different protection levels, we divided the study area into 5 km by 5 km grids, so that transects were separated by 5 km to minimize spatial autocorrelation of the data. We randomly selected 105 grids (21 grids within each protection level) and placed triangular-shaped transects of 3 km total length in the centre of each selected grid. To ease logistics in the field, we opted for 1 km segment length. We surveyed each transect once during the dry season between July and September 2021. Three people (one each primarily responsible for navigating, observing, and recording) walked along the transect. We used a handheld GPS and compass to navigate between segments (i.e. we moved towards 90° E in the first segment, 330° NW in the second segment, and 210° SW in the third segment). In each ..., Microsoft office excel and R, # Title of Dataset:

Dung densities to assess the ecological effectiveness of a protected area network

## Description of the Data and file structure

We conducted line distance sampling surveys and counted dung of six target mammal species (elephant, giraffe, buffalo, zebra, topi, hartebeest) along foot transects within areas differing in protection levels (from strict to less strictly protected: national park, game reserve, forest reserve, game-controlled area, and unprotected areas).There is single data files contains the following varibles column wise:
1. Column 1 presents Transect Label indicating transect identification number
2. Column 2 presents Sample Label indicating identification number for individual dung
3. Column 3 presents Transect Length indicating the length of transect in kilometers (km)
4. Column 4 presents perpendicular distance indicating the perpendicular distance in meters (m) from the transect line to dung piles.
5. Column 5 presents size indicating number of du...

鉴于当前全球范围内提升保护区覆盖范围的各项举措，全面评估各类基于区域的保护策略在有效减缓生物多样性丧失方面的成效至关重要。本研究聚焦坦桑尼亚西部的卡塔维-鲁夸生态系统（Katavi-Rukwa Ecosystem），于景观尺度下探究野生动物种群对不同保护等级及环境变量的响应。为此，我们开展了样线距离抽样（line distance sampling）调查，沿步行样线计数6种目标哺乳动物（大象、长颈鹿、水牛、斑马、转角牛羚、狷羚）的粪便，这些样线分布于保护等级各异的区域（从严格保护至较低保护等级依次为：国家公园、禁猎区、森林保护区、狩猎管控区及未保护区域）。基于上述粪便计数数据，我们采用物种专属的密度表面模型（density surface modelling）框架，对这6种哺乳动物的空间分布进行建模。我们发现保护等级与土地利用变量对空间分布具有一致的影响……我们在卡塔维国家公园（KNP）边界周边设置了35千米的缓冲区，以涵盖从未保护到严格保护的各类保护等级区域。为确保样线在不同保护等级区域内均匀分布，我们将研究区划分为5千米×5千米的网格，使样线间距保持5千米，以最大限度降低数据的空间自相关性（spatial autocorrelation）。我们随机选取了105个网格（每个保护等级对应21个网格），并在每个选中网格的中心布设总长度为3千米的三角形样线。为简化野外作业流程，我们将样线划分为1千米的分段。我们于2021年7月至9月的旱季对每条样线开展一次调查。每一条样线由3人组队完成：分别负责导航、观测与记录。我们使用手持全球定位系统（GPS）与罗盘进行分段间的导航：第一段朝向东经90°方向行进，第二段朝向西北330°方向行进，第三段朝向西南210°方向行进。在每个……
# 数据集标题：用于评估保护区网络生态成效的粪便密度数据
## 数据与文件结构说明
我们沿步行样线对6种目标哺乳动物（大象、长颈鹿、水牛、斑马、转角牛羚、狷羚）的粪便进行计数，开展样线距离抽样（line distance sampling）调查，样线分布于保护等级各异的区域（从严格保护至较低保护等级依次为：国家公园、禁猎区、森林保护区、狩猎管控区及未保护区域）。本数据集仅包含单个数据文件，各列变量说明如下：
1. 第1列：样线编号（Transect Label），用于标识样线的唯一识别号
2. 第2列：样本编号（Sample Label），用于标识单份粪便样本的唯一识别号
3. 第3列：样线长度（Transect Length），单位为千米（km），表示样线的总长度
4. 第4列：垂直距离（perpendicular distance），单位为米（m），表示从样线到粪便堆的垂直距离
5. 第5列：规模（size），表示粪便堆的数量（原文表述未完整）
本研究使用Microsoft Office Excel与R进行数据处理与分析。