French Associates Institute for Agriculture and Biotechnology of Dryland, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, 8499000, Israel.
Department of Natural Resources, Institute of Plant Sciences, Agricultural Research Organization (ARO), Volcani Center, 68 HaMaccabim Road, P.O.B 15159, Rishon LeZion 7505101, Israel.
Sci Total Environ. 2023 Oct 15;895:164830. doi: 10.1016/j.scitotenv.2023.164830. Epub 2023 Jun 23.
The frequency and severity of Mediterranean forest fires are expected to worsen as climate change progresses, heightening the need to evaluate understory fuel management strategies as rigorously as possible. Prescribed small-ruminant foraging is considered a sustainable, cost-effective strategy, but demonstrating a link between animal presence and vegetation change is challenging. This study tested whether the effect of small-ruminant herd presence in Mediterranean woodlands can be detected by integrating remote sensing and herd tracking at the landscape scale. The daily foraging routes of seven shepherded goat herds that exploited a 100-km forested area of the Judean Hills, Israel, were tracked over six years using GPS (Global Positioning System) collars. Herd locations were converted to stocking rates, with units of animal-presence-days per unit area per defined time period, and mapped at a spatial resolution of 10 m. We estimated pixel-level vegetation cover change based on a time series of 63 monthly Landsat-8 images expressed as the normalized soil-adjusted vegetation index (SAVI). Spatiotemporal trend analysis assessed the magnitude and direction of change, and a random forest machine-learning algorithm estimated the relative impact on vegetation cover change of environmental factors as well as the herd-related factors of stocking rate that accrued over six years and distance to the closest corral. The last two factors were among the most influential factors determining vegetation cover change in the regional and individual-herd analyses. In some respects, the permanent herds differed in their spatial pattern of stocking rate from the mobile herds that periodically relocated their night corral throughout the year, but stocking rate scaled logarithmically for all herds individually and combined. The combination of multi-season GPS tracking, remote sensing, and machine-learning techniques, applied at a regional scale, detected herd impacts on vegetation cover trends, consistent with livestock foraging being an effective tool for fuel reduction in Mediterranean woodlands.
随着气候变化的推进，预计地中海森林火灾的频率和严重程度将加剧，因此需要尽可能严格地评估林下燃料管理策略。规定的小反刍动物觅食被认为是一种可持续且具有成本效益的策略，但证明动物存在与植被变化之间的联系具有挑战性。本研究通过在景观尺度上整合遥感和畜群跟踪，测试了地中海林地中小反刍动物畜群存在的影响是否可以被检测到。六年来，使用 GPS（全球定位系统）项圈跟踪了七群放牧山羊在以色列朱迪亚山 100 公里森林地区的日常觅食路线。畜群的位置被转换为放养率，单位为动物存在天数/单位面积/定义时间段，并以 10 米的空间分辨率进行映射。我们根据 63 个月的 Landsat-8 图像时间序列估算了像素级植被覆盖变化，该序列表示为归一化土壤调整植被指数 (SAVI)。时空趋势分析评估了变化的幅度和方向，随机森林机器学习算法估计了环境因素以及在六年期间积累的放养率和到最近畜栏的距离等畜群相关因素对植被覆盖变化的相对影响。最后两个因素是确定区域和个别畜群分析中植被覆盖变化的最具影响力的因素之一。在某些方面，永久性畜群的放养率空间模式与全年定期重新安置夜间畜栏的移动畜群不同，但所有畜群的放养率均按对数比例单独和组合。多季节 GPS 跟踪、遥感和机器学习技术的组合，在区域尺度上应用，检测到畜群对植被覆盖趋势的影响，这与牲畜觅食是减少地中海林地燃料的有效工具一致。
