One of our main activities is monitor the coast of Zamboanguita and parts of Dauin and Siaton. We do this to show the changes is the amount of species and amount of animals/plants along the coast, which gives us an idea of the effectiveness of the protection that is put in place, and shows us possible threats as well. This will help policy makers more effectively manage the protected areas reduce those threats.

As regulating fisheries and over-fishing is the most important factor in protecting the ecosystems here, we first focused on monitoring fish species. But as there are over 300 fish species in the Philippines, we cannot look at all the fish species at the same time, especially since many of our volunteers are not trained scientists. We would therefore only like to look at a subset of species, which are ecologically or commercially important, or are indicative of a specific threat. This way, we can make the monitoring less complicated. This selection of species is our set of “indicator species”.

In order to select these species we first needed to know which species are present, and how many individuals of each species we see at the different locations. This is what we did in our “baseline” study of all species.

Aside from giving us information on all the fish species present at the different locations, and the differences between those locations in the amount of fish for each species, this baseline study also allows us to compare later results for these species with the data we gather now, allowing us to show changes over time. To keep the method as simple as possible, and to make it less sensitive to differences between researchers and observation distance, we used the Rapid Visual Census method as described in Hill and Wilkinson (2004)¹. To simplify it further, we only monitored a few families at a time, making teaching the species of these families to volunteers a lot easier.

The disadvantage of this method was that it took a long time to monitor all the sites thoroughly, especially since we want to analyse the data statistically, requiring multiple surveys per site. The advantage though is that it allowed us to survey at a high level of detail, while still making it manageable for volunteers to be trained in a relatively short period of time.

MCP was invited to help out the local governmental monitoring team in Bias, Negros Oriental to assess their biggest Marine Protected Area (MPA), encompassing an area of 55 hectares of coral reefs and seagrasses. The assessment was conducted in order to determine if their MPA showed signs of improvement over the 3 years since the last assessment in 2015 by Silliman University. Located approximately 2 hours north of the MCP base, Bais was an adventure which required our first ever expedition team of volunteers to stay at a remote location to complete the assessments.

The expedition team had three days to complete the surveys inside and outside of the MPA, collecting the data needed to assess and compare the health of the ecosystems. The team consisted of six volunteers and one staff member. Together, they created a strategy that would ensure that all the surveys to be completed in the most efficient manner. By the time the dust settled, the team had completed 72 surveys in the three days, including replicates for fish, substrate and invertebrates.

MCP’s staff will interpret the data and return a completed report to the Bais LGU along with information they can present in their annual fiesta. In late September, four members from the Bais MPA Bantay Dagat (MPA guards) will join MCP to get certified in scuba diving and trained in monitoring methods. The overall goal of the project is to create a local monitoring team from the Bantay Dagat members to complete the same assessments on a regular basis.

In June 2018, MCP’s conservation team set off to Cebu to present at the Asia Pacific Coral Reef Symposium,  a symposium that occurs every four years and brings together coral reef scientists from around the world. The topics presented by MCP were based on recent research: first, using technical diver based monitoring methods to assess mesophotic reefs; and second, assessing the accuracy of the data MCP collects, and how data collected using similar techniques can be made more accurate.

Mesophotic Monitoring

Mesophotic reefs are coral reef ecosystems found between 30-150 meters deep, and are often thought to be a refuge to their shallower reef counterparts. MCP is interested in monitoring these mesophotic reefs to determine the overall health of these reefs and determine if they are also in need of protection from anthropogenic effects.

To accurately asses these mesophotic reefs, team members from MCP worked hard to figure out a reliable monitoring strategy, testing methods using a varying combination of divers and cameras to collect data. The project leader presented the findings, concluding that divers seemed to be more accurate when monitoring fish and substrate than when using a camera to collect the data. In the future, we hope to build on this project and create a technical diver based monitoring team able to conduct continuous monitoring of mesophotic reefs.

Citizen science programs, and monitoring methods using a similar level of training, are rapidly becoming more common in the world. These approaches are spreading so fast because they are often a very effective way to make sure that data is readily available to governmental environmental managers that may not have the skills or time to collect the data otherwise. This is especially true in the developing world where there is often little funding available to ensure that all of the governmental staff are trained to collect and analyse this data.

To collect the data, our staff conducted surveys alongside volunteers, recoding exactly the same life forms as the volunteers. In this way, we collected a data set that could be compared, in which any differences between the volunteer data and the staff data was a measurable level of error.

We used a version of a group of analysis methods known as Percentage Agreement. Basically, this gave us a number between 0 and 1 that told us how accurate our data was, the closer to 1 the better. We found that, on average, our data is 92% accurate, and that most of the errors are concentrated into relatively tricky areas like the recording of species that are thoroughly camouflaged, and counting very large numbers of small organisms. In knowing this, we can make sure that our monitoring is designed to solve these problems, adding count ranges, and extra in-water training for identifying camouflaged species for example , always moving toward better accuracy and therefore better management of the marine ecosystem.