Department of Biology, Faculty of Science, University of Zagreb, Rooseveltov trg 6, HR-10000 Zagreb, Croatia.
Department of Maritime Studies, University of Zadar, M. Pavlinovica bb, HR-23000 Zadar, Croatia.
Sci Total Environ. 2014 Feb 1;470-471:364-78. doi: 10.1016/j.scitotenv.2013.09.103. Epub 2013 Oct 22.
In the context of current global environmental changes, mapping and monitoring seagrass meadows have become highly important for management and preservation of coastal zone ecosystems. The purpose of this research was to determine the numerical precision of various cost-effective benthic habitat mapping techniques and their suitability for mapping and monitoring of Posidonia oceanica meadows in the Croatian Adriatic. We selected ultra-high resolution aerial imagery, single-beam echo sounder (SBES) seabed classification system from Quester Tangent Co. (QTC), and surface based underwater videography as affordable, non-destructive and simple to use systems for data acquisition. The ultra-high resolution digital imagery was capable of detecting P. oceanica meadows up to 4m depth with 94% accuracy, from 4m to 12.5m depth the accuracy dropped to app. 76%, and from 12.5 to 20 m the system was only capable of distinguishing seabed biota from substrata, though with 97% accuracy. The results of the QTC system showed over 90% detection accuracy for Cymodocea nodosa covered seabed, excellent separation capabilities (>92%) of different sediment types (slightly gravelly sand, gravelly muddy sand and slightly gravelly muddy sand) and reasonable accuracy for mapping underwater vegetation regardless of the bathymetric span. The system proved incapable of separating P. oceanica from dense macroalgae on the same type of substratum. Surface-based underwater videography demonstrated great potential for estimating P. oceanica cover in a sampled region using either a single human rater or a computer estimate. The consistency between two human scorers in evaluating P. oceanica bottom coverage was near perfect (>98%) and high between digital and human scorers (80%). The results indicate that although the selected systems are suitable for mapping seagrasses, they all display limitations in either detection accuracy or spatial coverage, which leads to a conclusion that suitable system integration is essential for producing high quality seagrass spatial distribution maps.
在当前全球环境变化的背景下，对海草床进行测绘和监测对于沿海生态系统的管理和保护变得至关重要。本研究的目的是确定各种具有成本效益的海底栖息地测绘技术的数值精度及其在克罗地亚亚得里亚海波西多尼亚海草床测绘和监测中的适用性。我们选择了超高分辨率航空影像、来自 Quester Tangent Co.（QTC）的单波束回声测深仪（SBES）海底分类系统以及基于水面的水下摄影作为经济实惠、无损且易于使用的数据采集系统。超高分辨率数字图像能够以 94%的准确率检测到 4 米深的 P. oceanica 海草床，从 4 米到 12.5 米深度的准确率下降到约 76%，而从 12.5 米到 20 米深度，该系统只能以 97%的准确率区分海底生物群落与基质。QTC 系统的结果表明，Cymodocea nodosa 覆盖的海底的检测准确率超过 90%，对不同沉积物类型（稍含砾石的砂、含砾石的泥砂和稍含砾石的泥砂）具有出色的分离能力（>92%），并且无论水深范围如何，对水下植被的测绘都具有合理的准确性。该系统无法将 P. oceanica 与同一基质上的密集大型藻类区分开来。基于水面的水下摄影证明，使用单个人工评分员或计算机估算，对采样区域中的 P. oceanica 覆盖范围进行估计具有很大的潜力。两名人工评分员在评估 P. oceanica 底部覆盖范围时的一致性近乎完美（>98%），数字评分员和人工评分员之间的一致性也很高（80%）。结果表明，虽然所选系统适用于绘制海草，但它们在检测精度或空间覆盖范围方面都存在局限性，因此得出的结论是，合适的系统集成对于生成高质量的海草空间分布图至关重要。
