This study explores the application of small, commercially available drones to determine morphometric the measurements and record key demographic parameters of reef manta rays (Mobula alfredi) in Raja Ampat, Indonesia. DJI Mavic 2 Pro drones were used to obtain videos of surface-feeding M. alfredi with a floating, known-length PVC pipe as a reference scale—thus avoiding the need to utilize altitude readings, which are known to be unreliable in small drones, in our photogrammetry approach. Three dimensions (disc length (DL), disc width (DW), and cranial width (CW)) from 86 different individuals were measured. A hierarchical multivariate model was used to estimate the true measurements of these three dimensions and their population-level multivariate distributions. The estimated true measurements of these dimensions were highly accurate and precise, with the measurement of CW more accurate than that of DL and, especially, of DW. Each pairing of these dimensions exhibited strong linear relationships, with estimated correlation coefficients ranging from 0.98–0.99. Given these, our model allows us to accurately calculate DW (as the standard measure of body size for mobulid rays) using the more accurate CW and DL measurements. We estimate that the smallest mature M. alfredi of each sex we measured were 274.8 cm (males, n = 30) and 323.5 cm DW (females, n = 8). We conclude that small drones are useful for providing an accurate “snapshot” of the size distribution of surface-feeding M. alfredi aggregations and for determining the sex and maturity of larger individuals, all with minimal impact on this vulnerable species.
The 6.7-million-hectare Raja Ampat archipelago is home to Indonesia’s largest reef manta ray (Mobula alfredi) population and a representative network of nine marine protected areas (MPAs). However, the population dynamics of M. alfredi in the region are still largely unknown. Using our photo-identification database, we fitted modified POPAN mark-recapture models with transience and per capita recruitment parameters to estimate key demographic characteristics of M. alfredi from two of Raja Ampat’s largest MPAs: Dampier Strait and South East (SE) Misool. A total of 1,041 unique individuals were photo-identified over an 11-year period (2009–2019) from Dampier Strait (n = 515) and SE Misool (n = 536). In our models, apparent survival probabilities and per capita recruitment rates were strongly linked with El Niño–Southern Oscillation (ENSO) events. Our models also estimated high apparent survival probabilities and significant increases in (sub)population sizes in both MPAs over a decade. In Dampier Strait, the estimated population size increased significantly (p = 0.018) from 226 (95% CI: 161, 283) to 317 (280, 355) individuals. Likewise, the estimated population size in SE Misool increased significantly (p = 0.008) from 210 (137, 308) to 511 (393, 618) individuals. Regardless of variation in the percentage change in population size between years throughout the study, the estimated overall population change shows a compound growth of 3.9% (0.7, 8.6) per annum in Dampier Strait and 10.7% (4.3, 16.1) per annum in SE Misool. Despite the global decline in oceanic sharks and rays due to fishing pressure in the last five decades, our study demonstrates the positive impact of a suite of long-term conservation efforts, coupled with the influence of ENSO events, on increasing M. alfredi abundance in Raja Ampat MPAs. Our study also underscores the importance of long-term monitoring to evaluate the effectiveness of conservation management measures on manta ray populations. Our modification of the standard POPAN model by incorporating per capita recruitment and transience parameters represents an important advance in mark-recapture modelling that should prove useful when examining other manta ray populations and other highly migratory species that are likely to have a substantial percentage of transient individuals.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.