نوع مقاله : مقاله واکاوی
عنوان مقاله English
نویسنده English
Sampling in the environmental sciences is recognized as a fundamental basis for collecting reliable data and for analyzing ecological phenomena. This review, with an emphasis on vegetation and associated ecological factors, examines the principles, methods, and challenges of sampling in natural environments. Primary sampling approaches include non-probability (non-random), probability (random), stratified, cluster, spatial, and integrated (hybrid) designs, each is selected according to the conditions and complexity of natural ecosystems, the practical challenges of field data collection, the study’s spatiotemporal scale and objectives, and the types of variables under investigation. For the assessment of ecological drivers in plant communities, correct selection of sampling units and instruments, appropriate sampling protocols, and the incorporation of modern technologies such as geographic information systems (GIS) and remote sensing play a central role in reducing measurement error and uncertainty and in increasing data accuracy and precision. Moreover, explicit consideration of spatial heterogeneity and species distributions, temporal replication of sampling, and the determination of optimal sample size and sampling intensity ensure data quality and the generalizability of findings. This review presents an integrated framework for selecting sampling methods that leverages remote sensing and GIS data in vegetation studies of heterogeneous ecosystems, thereby enabling error and uncertainty reduction and cost optimization. The findings indicated that combining traditional field methods with advanced technologies (e.g., GIS and remote sensing), together with adherence to statistical principles and objective-driven study design, not only improves data accuracy but also strengthens the capacity to provide practical management recommendations for the conservation and sustainable management of rangeland ecosystems.
کلیدواژهها English
