Completed projects

Please note that the entries below are archival. This page has not been updated since 2020. As MCP has grown considerably in size and operational scope since 2018, the reporting format below became too cumbersome and is no longer used. For a better overview of current developments and results, please visit our achievements page.

One of our main activities is monitoring the coast of Zamboanguita and parts of Dauin and Siaton. We do this to show changes in the number of species and the abundance of animals and plants along the coast. This tells us how effective the protection in place is, and shows us possible threats as well. It also helps policy makers manage the protected areas more effectively and reduce those threats.

As regulating fisheries and overfishing is the most important factor in protecting the ecosystems here, we first focused on monitoring fish species. But with over 300 fish species in the Philippines, we cannot look at all of them at the same time, especially since many of our volunteers are not trained scientists. We therefore look at a subset of species that are ecologically or commercially important, or that indicate a specific threat. This makes the monitoring less complicated. This selection of species is our set of “indicator species”.

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.

Besides telling us which fish species are present at each location, and how the numbers of each species differ between locations, the baseline study lets us compare later results for these species with the data we gather now, so we can show changes over time. To keep the method as simple as possible, and less sensitive to differences between observers and observation distances, we used the Rapid Visual Census method described by Hill and Wilkinson (2004).¹ To simplify it further, we only monitored a few fish families at a time, which made it much easier to teach volunteers the species in those families.

The disadvantage of this method was that it took a long time to monitor all the sites thoroughly, especially as we wanted to analyse the data statistically, which requires multiple surveys per site. The advantage, though, was that it allowed us to survey in great detail while still training volunteers in a relatively short time.

¹ Hill, J. and Wilkinson, C. (2004). Methods for Ecological Monitoring of Coral Reefs: A Resource for Managers. Australian Institute of Marine Science, Townsville.

MCP was invited to help the local government monitoring team in Bais, Negros Oriental, assess their largest marine protected area (MPA), which covers 55 hectares of coral reef and seagrass. The aim was to find out whether the MPA had improved in the three years since its last assessment by Silliman University in 2015. Bais lies about two hours north of the MCP base, and the trip was an adventure: our first ever expedition, with a team of volunteers staying at a remote location to complete the assessments.

The expedition team had three days to complete the surveys inside and outside the MPA, collecting the data needed to assess and compare the health of the ecosystems. The team was made up of six volunteers and one staff member, who worked out a plan to complete all the surveys as efficiently as possible. By the time the dust settled, they had completed 72 surveys in three days, including replicates for fish, substrate and invertebrates.

MCP’s staff will analyse the data and return a full report to the Bais LGU, along with information they can present at their annual fiesta. In late September, four members of the Bais MPA’s Bantay Dagat (MPA guards) will join MCP to get certified in scuba diving and trained in our monitoring methods. The overall goal of the project is to build a local monitoring team from the Bantay Dagat members, who can carry out the same assessments regularly.

In June 2018, MCP’s conservation team travelled to Cebu to present at the Asia Pacific Coral Reef Symposium, which takes place every four years and brings together coral reef scientists from around the world. MCP presented two pieces of recent research: first, using technical diving to monitor mesophotic reefs; and second, assessing the accuracy of the data MCP collects, and how data collected with similar techniques can be made more accurate.

Mesophotic monitoring

Mesophotic reefs are coral reef ecosystems found between 30 and 150 metres deep, and are often thought to act as a refuge for shallower reefs. MCP wants to monitor these mesophotic reefs to assess their overall health and find out whether they, too, need protection from human impacts.

To assess these reefs accurately, MCP’s team worked hard to develop a reliable monitoring strategy, testing different combinations of divers and cameras to collect the data. The project leader presented the findings, concluding that divers seemed to be more accurate than cameras when monitoring fish and substrate. In future, we hope to build on this project and create a team of technical divers able to monitor mesophotic reefs continuously.

Data accuracy

Citizen science programmes, and monitoring methods using a similar level of training, are quickly becoming more common around the world. They spread so fast because they are often a very effective way to make data available to government environmental managers who may not have the skills or time to collect it themselves. This is especially true in developing countries, where there is often little funding to train all government staff to collect and analyse such data.

To test our data, our staff carried out surveys alongside volunteers, recording exactly the same life forms. This gave us a dataset we could compare, in which any difference 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. Put simply, this gave us a number between 0 and 1 showing how accurate our data was: the closer to 1, the better. We found that, on average, our data was 92% accurate, and that most errors were concentrated in a few tricky areas, such as recording well-camouflaged species and counting very large numbers of small organisms. Knowing this, we can design our monitoring to solve these problems, for example by adding count ranges and extra in-water training for identifying camouflaged species, always moving towards better accuracy and therefore better management of the marine ecosystem.