The Global Autonomous Reef Monitoring Structures (ARMS) Program is a Smithsonian Institution initiative hosted at the National Museum of Natural History in Washington DC. The program centralizes and makes available information and documentation on the ARMS and standardized processing protocols.


The ARMS were developed during the Census of Marine Life (CoML) international initiative. In an attempt to enhance global understanding of reef biodiversity. Since the Census of Marine Life, the ARMS project has expanded on a global scale and the ARMS have been adopted as a key biodiversity assessment tool by NOAA’s National Coral Reef Monitoring Program (NCRMP) and Ocean Acidification Program’s climate monitoring stations in the Pacific. NOAA has played a central role in developing ARMS deployment and processing protocols and training material.
The ARMS program has created very detailed protocols for sampling, sample processing, vouchering, imaging, and molecular analysis (barcoding and metabarcoding) of sessile and motile organisms on hard substrates. The key innovation of the ARMS is their ability to sample marine communities over precisely the same area and in the exact same manner providing a standardized and quantifiable biodiversity measure. This sampling repeatability is a great asset to answer varied research questions: monitoring of diversity over time, exploring the effects of marine protected areas on the recovery of biodiversity, or quantifying human impacts. Combined with today’s powerful molecular methods such as high throughput sequencing, they enable the study of microbial, prokaryotic and eukaryotic whole communities.

The PacMAN project will build upon existing monitoring schemes and protocols such as the one from ARMS, and as such the director of the global ARMS program will participate in the advisory board to advise on the design of the monitoring plan as well as the decision-support tool. The ARMS Program also looks forward to a streamlined bioinformatics pipelines in order to improve the availability of omics data to global data infrastructures such as OBIS.