Piazzolla Daniele, Scanu Sergio, Mancuso Francesco Paolo, Bosch-Belmar Mar, Bonamano Simone, Madonia Alice, Scagnoli Elena, Tantillo Mario Francesco, Russi Martina, Savini Alessandra, Fersini Giorgio, Sarà Gianluca, Coppini Giovanni, Marcelli Marco, Piermattei Viviana
CMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy.
Laboratory of Ecology, Department of Earth and Marine Sciences (DiSTeM), University of Palermo, 90123, Palermo, Italy.
Sci Rep. 2024 Mar 11;14(1):5888. doi: 10.1038/s41598-024-56662-6.
Among marine ecosystems globally, those in the Mediterranean Sea, are facing many threats. New technologies are crucial for enhancing our understanding of marine habitats and ecosystems, which can be complex and resource-intensive to analyse using traditional techniques. We tested, for the first time, an integrated multi-platform approach for mapping the coastal benthic habitat in the Civitavecchia (northern Latium, Italy) coastal area. This approach includes the use of an Unmanned Surface Vehicle (USV), a Remote Operated Vehicle (ROV), and in situ measurements of ecosystem functionality. The echosounder data allowed us to reconstruct the distribution of bottom types, as well as the canopy height and coverage of the seagrass Posidonia oceanica. Our study further involved assessing the respiration (Rd) and net primary production (NCP) rates of P. oceanica and its associated community through in situ benthic chamber incubation. By combining these findings with the results of USV surveys, we were able to develop a preliminary spatial distribution model for P. oceanica primary production (PP-SDM). The P. oceanica PP-SDM was applied between the depths of 8 and 10 m in the studied area and the obtained results showed similarities with other sites in the Mediterranean Sea. Though in the early stages, our results highlight the significance of multi-platform observation data for a thorough exploration of marine ecosystems, emphasizing their utility in forecasting biogeochemical processes in the marine environment.
在全球的海洋生态系统中，地中海的那些生态系统正面临诸多威胁。新技术对于增进我们对海洋栖息地和生态系统的理解至关重要，因为使用传统技术分析这些可能既复杂又耗费资源。我们首次测试了一种综合多平台方法，用于绘制奇维塔韦基亚（意大利拉齐奥北部）沿海地区的沿海底栖生境图。这种方法包括使用无人水面航行器（USV）、遥控潜水器（ROV）以及对生态系统功能进行原位测量。回声测深仪数据使我们能够重建海底类型的分布，以及海草波喜荡草的冠层高度和覆盖范围。我们的研究还通过原位底栖室培养评估了波喜荡草及其相关群落的呼吸（Rd）和净初级生产力（NCP）速率。通过将这些发现与无人水面航行器调查结果相结合，我们能够为波喜荡草初级生产力建立一个初步的空间分布模型（PP - SDM）。在研究区域8至10米深度之间应用了波喜荡草PP - SDM，所得结果与地中海其他地点的结果相似。尽管尚处于早期阶段，但我们的结果凸显了多平台观测数据对于全面探索海洋生态系统的重要性，强调了它们在预测海洋环境中生物地球化学过程方面的效用。
