Seasonal monitoring of forage C:N:ADF ratio in natural rangeland using remote sensing data

IF 3 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Monde Rapiya, Abel Ramoelo, Wayne Truter
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Abstract

In recent decades, natural rangelands have emerged as vital sources of livelihood and ecological services, particularly in Southern Africa, supporting communities in developing regions. However, the escalating global demand for food, driven by a growing human population, has led to the extensive expansion of cultivated areas, resulting in continuous nutrient leaching in rangelands. To ensure the long-term viability of these ecosystems, there is a need to develop effective approaches for managing and monitoring the seasonality of forage quality. This study aims to achieve this by utilizing multispectral Sentinel-1 (S1) and Sentinel-2 (S2) data to monitor the seasonal distribution and occurrence of carbon (C), nitrogen (N), acid detergent fiber (ADF), and the (C:N:ADF) ratio in mesic rangelands. Six sites were randomly selected from Welgevonden and Hoogland private game reserves in Limpopo, South Africa, representing varying vegetation cover and standing biomass. Transects, each with ten fixed sample sites (30 × 30 m) characterized by homogeneous vegetation, were established. The grass samples and aboveground biomass were collected during each season and analyzed for biochemical parameters using a near-infrared spectroscopy (NIRS) machine. S1 and S2 data from Google Earth Engine (GEE) were employed, and the random forest (RF) modelling algorithm revealed significant seasonality impacts on the distribution of forage C:N:ADF ratios. The study demonstrates that integrating S1 and S2 data enhances the estimation of forage nutrients. This study offers valuable insights for a diverse range of stakeholders, including ecologists, resource managers, farmers, and park managers. By giving an understanding of nutrient limitations and facilitating a deeper understanding of resource availability and animal distribution in rangelands, this research serves as a crucial tool for informed decision-making and sustainable management practices.

基于遥感数据的自然放牧区牧草C:N:ADF比值的季节监测
近几十年来,自然牧场已成为生计和生态服务的重要来源,特别是在南部非洲,支持发展中地区的社区。然而,在人口增长的推动下,全球对粮食的需求不断上升,导致耕地面积的广泛扩张,导致牧场的养分不断流失。为了确保这些生态系统的长期生存能力,需要制定有效的方法来管理和监测饲料质量的季节性。本研究利用多光谱Sentinel-1 (S1)和Sentinel-2 (S2)数据,监测中牧地碳(C)、氮(N)、酸性洗涤纤维(ADF)和(C:N:ADF)比值的季节分布和发生情况。从南非林波波的Welgevonden和Hoogland私人野生动物保护区中随机选择了6个地点,代表了不同的植被覆盖和直立生物量。建立样带,每个样带有10个固定样点(30 × 30 m),以均匀植被为特征。利用近红外光谱仪(NIRS)分析了不同季节牧草和地上生物量的生化参数。利用谷歌Earth Engine (GEE)的S1和S2数据,随机森林(RF)建模算法发现,季节对牧草C:N:ADF比的分布有显著影响。研究表明,整合S1和S2数据可以提高对饲料营养成分的估计。这项研究为不同的利益相关者提供了有价值的见解,包括生态学家、资源管理者、农民和公园管理者。通过了解营养限制和促进对牧场资源可用性和动物分布的更深入了解,本研究可作为知情决策和可持续管理实践的重要工具。
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来源期刊
Environmental Monitoring and Assessment
Environmental Monitoring and Assessment 环境科学-环境科学
CiteScore
4.70
自引率
6.70%
发文量
1000
审稿时长
7.3 months
期刊介绍: Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.
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