five

Cabrillo National Monument Rocky Intertidal Long-Term Monitoring (LTM) Data Package

收藏
DataCite Commons2025-09-06 更新2026-05-04 收录
下载链接:
https://irma.nps.gov/DataStore/Reference/Profile/2314797
下载链接
链接失效反馈
官方服务:
资源简介:
The rocky intertidal zone at Cabrillo National Monument (CABR) is a valued and rare natural resource in southern California. It has been monitored since 1990 and was incorporated into the “Vital Signs” monitoring program of the Mediterranean Coast Network (MEDN) of the National Park Service (NPS) Inventory and Monitoring Program in 2011. Specific monitoring objectives are 1) to determine the long-term trends in percent cover of key sessile organisms in the rocky intertidal ecosystem (Table 1), and 2) to determine population dynamics of Lottia gigantea, sea stars, and abalone. Target species are monitored using core Multi-Agency Rocky Intertidal Network (MARINe) protocols (Engle 2008), which consist of: (1) permanently marked photo-plots (50 x 75 cm) to monitor percent cover of sessile invertebrates and rockweed (Chthamalus/Balanus, Tetraclita, Mytilus, Pollicipes, and Silvetia), (2) 10-meter line transects to assess percent cover of dominant algae and seagrass (red algal turf, Egregia and Phyllospadix), (3) 1-meter radius circular plots to monitor the size and abundance of Lottia gigantea, and (4) 30-minute timed searches to record presence of rare species (Pisaster spp. and Haliotis spp.). These surveys are conducted across three sites within CABR and five sites outside of CABR across southern California which encompass a gradient of human use. This data package includes sessile rocky intertidal species percent cover data, abundance data for giant owl limpets, and abundance and size data for sea stars and abalone. These data were collected throughout the duration of the program, which began at CABR in 1990. The package will be updated annually with newly collected data.
提供机构:
National Park Service
创建时间:
2025-09-06
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作