Marianne Nyegaard

Taxonomic confusion and limited data have impeded species-level biogeographic analyses of the world’s largest bony fishes, ocean sunfishes (Molidae; ‘molids’), in many ecosystems. However, recent advances in molid taxonomy and the emergence of photo-based community-science platforms provide an opportunity to revisit species-level biogeography. In this study, we use crowd-sourced images of 1,213 ocean sunfishes to determine if molid morphology visible in citizen-science images permits reliable species determination. From the ensuing data, we describe patterns in molid size structure and species composition from 1,178 molids observed in the Alaska and California Current Systems (ACS and CCS, respectively). Molids 1 m TL were more commonly observed in both the CCS and cooler ACS, which suggests larger molids occupy a larger thermal range (ontogenetic habitat expansion) than smaller individuals. Overall, Mola mola was the most frequently observed species in both the ACS and CCS; however, the persistent occurrence of Mola tecta in both current systems suggests a range extension for this otherwise Southern Hemisphere species. The species identity of six M. tecta specimens from California and Alaska were verified with genetic analysis. Finally, two Mola alexandrini confirmed in the southern portion of the CCS represent the first records of this species in the Northeast Pacific Ocean.

The small family of ocean sunfishes has a long and complicated taxonomic and nomenclatorial history dating back several centuries. Most recently, Britz (2022) questioned the validity of Mola alexandrini (Ranzani, 1839) as the valid name for Mola sp. A sensu Yoshita et al. (2009). Specifically, he questioned the authenticity of the purported Orthragoriscus alexandrini holotype rediscovered by Sawai et al. (2018) due to uncertainties regarding the original units of measurement, along with discrepancies between the original illustration and the purported holotype. He also questioned the reliability of the illustration to reflect the fresh morphology, and the adequacy of the species description (sans illustration and holotype) to link it to any of the currently recognized Mola species. In summary, Britz (2022) opined that M. alexandrini is a species inquirenda. Here we respond to Britz’s concerns with the findings from an additional literature review. Firstly, the original species description appears to give measurements in ‘Parisian units’, yielding a discrepancy in length with the purported holotype within human error. However, due to various uncertainties, length does not appear to be a robust piece of evidence to neither confirm nor refute the specimen’s authenticity. Secondly, the morphological differences between the original illustration and the purported holotype were found to be within the expected level of accuracy for Mola illustrations at the time, by both Ranzani and others. Thirdly, a contemporaneous publication describes how Ranzani himself bought the specimen which became the Or. alexandrini holotype, suggesting he would likely have seen it in its fresh state, rendering it unlikely he would have produced a species description and illustration incongruent with this. Fourthly, re-examining the original species description suggests this provides adequate and sufficient information to link Or. alexandrini to Mola sp. A, even in the absence of a holotype. Finally, during this review, we came upon an even older paper describing Or. alexandrini, and we conclude that the currently valid name for Mola sp. A sensu Yoshita et al. (2009) is Mola alexandrini (Ranzani, 1834).

The ocean sunfishes Mola spp. (Family Molidae) are charismatic marine megafauna that are difficult for nature-based tourism operators to target due to their sporadic occurrence. However, the giant sunfish M. alexandrini is seasonally important for the SCUBA tourism industry in Bali, Indonesia, where these molids seek cleaner-fish interactions on the reefs of the local Nusa Penida Marine Protected Area (MPA) in the Lombok Strait. Little is known of their movements, including their apparent seasonal affinity to the Nusa Penida MPA. We tagged 8 fish with Fastloc GPS tags; however, intermittent surface visits and crepuscular diving habits, combined with early tag dislodgment and tag transmission failures, yielded a challenging data set to analyze. We overcame this difficulty with a geolocation model (HMMoce) that was parameterized to leverage the complex topography of the study region, be robust to data sparsity, and accommodate switching between distinct resident and migrant behaviour states. The results revealed small-scale movements whereby the fish exhibited particular affinity to bathymetrically complex, intense upwelling areas around Nusa Penida, the east coast of Bali, and an inter-basin trough to the north. Dive patterns suggested that the molids were foraging in these oceanographically dynamic areas. Our findings suggest that the Lombok Strait is at least of seasonal importance to this species, and the local SCUBA tourism industry likely relies on individual fish that re-visit the reefs of the Nusa Penida MPA multiple times during the sunfish season.

Photo ID is a common tool in ecology, but has not previously been attempted for the ocean sunfishes (Mola spp., Molidae; ‘molids’). The technique, based on body patterns, could potentially be informative for studying the seasonal occurrence of giant sunfish (Mola alexandrini) on the Bali reefs (Indonesia), where this species is an important drawcard for the local SCUBA diving tourism. However, molids are capable of rapid physiological colouration change, which may complicate the application of the method. Our study aimed to determine if photo ID is nevertheless achievable and informative. To test this, we created the citizen-science platform ‘Match My Mola’ for crowd-sourcing imagery (photos and video) of M. alexandrini in Bali, and undertook trial matching (n=1,098 submissions). The submitted imagery revealed a wide range of pattern clarity, from fish with no pattern to bold displays. Video confirmed physiological colouration change can occur in seconds in this species from low to high contrast, and cause individuals to look very different between moments. However, individual patterns appear to be stable although at least some parts can become inconspicuous during low contrast displays. Despite of this, photo ID is possible, including in some instances, where only partial patterns are visible on one image compared with another. However, true negatives (confirming two fish are not the same) can be challenging. Most identified matches were of fish photographed by different divers on the same day. Only a small number (n=9) were found with resighting durations ≥1 day (1 – 2,652 days). These matches demonstrate that at least some individuals return to the same reefs both within and between seasons, with the resighting duration of 7.2 years constituting the longest known example of molid site fidelity. Comparing body morphology between resightings of > 1 year (n=6) revealed limited indications of growth, contradicting the current understanding of rapid growth in captive molids (Mola mola), and highlighting the knowledge gap regarding growth in the wild. Continued photo ID in the Bali area could provide valuable complementary information to future growth studies using other methods as well as provide further insights into molid site fidelity.

The Giant Sunfish (Mola alexandrini) has unique patterns on its body, which allow for individual identification. By continuously gathering and matching images, it is possible to monitor and track individuals across location and time. However, matching images manually is a tedious and time-consuming task. To automate the process, we propose a pipeline based on finding and matching keypoints between image pairs. We evaluate our pipeline with four different keypoint descriptors, namely ORB, SIFT, RootSIFT, and SuperPoint, and demonstrate that the number of matching keypoints between a pair of images is a strong indicator for the likelihood that they contain the same individual. The best results are obtained with RootSIFT, which achieves an mAP of 75.91% on our test dataset (TinyMola+) without training or fine-tuning any parts of the pipeline. Furthermore, we show that the pipeline generalizes to other domains, such as re-identification of seals and cows. Lastly, we discuss the impracticality of a ranking-based output for real-life tasks and propose an alternative approach by viewing re-identification as a binary classification. We show that the pipeline can be easily modified with minimal fine-tuning to provide a binary output with a precision of 98% and recall of 44% on the TinyMola+ dataset, which basically eliminates the need for time-consuming manual verification on nearly half the dataset.

The world's heaviest extant bony fish has long been considered the ocean sunfish Mola mola (family Molidae). However, recent taxonomic research suggests the world record specimen (2300 kg) was actually a misidentified giant sunfish M. alexandrini. Moreover, the history of taxonomic confusion in the genus Mola, combined with anecdotal size information perpetuated in both media and literature, has resulted in uncertainty in regard to species identity and actual weights of very large Mola specimens. In this study, we searched for records of molid specimens with reported body mass over 2000 kg, with a focus on the north‐west and south‐west Pacific. For each specimen, we reviewed the species identification and assessed the reliability of the information, including if the specimen had actually been weighed. Of the 15 specimens uncovered, we identified one M. mola and 14 M. alexandrini, and found that only five had actually been weighed (one with the viscera removed). Furthermore, we collected length–weight data for verified M. alexandrini specimens from the literature and museum specimens, and established the first length–weight relationship for this species [body mass (kg) = 1.1 × 10⁻⁵ × total length (cm)^3.3248 (29–330 cm total length, n = 20)]. These findings are discussed in the context of other extant bony fish species, which allegedly also exceed 2000 kg in body mass, i.e., other Molidae species and the beluga sturgeon Huso huso. Overall, we conclude that M. alexandrini is the only extant bony fish species we could confirm that exceeds 2000 kg, and that basic biological information is generally not collected when very large molid specimens occasionally are stranded or are caught. Finally, we confirm that the world's heaviest extant bony fish specimen actually weighed was a female M. alexandrini (2300 kg, 272 cm total length) captured from Kamogawa, Chiba Prefecture, Japan, on August 16, 1996.

We present the first work where re-identification ofthe Giant Sunfish (Mola alexandrini) is automated using computer vision and deep learning. We propose a pipeline that scores an mAP of 60.34% on a full rank of the novel TinyMola dataset which includes 31 IDs and 91 images. The method requires no domain-adaptation or training which makes it especially suited for low-budget or volunteer-based projects, like Match My Mola, as part of a human-in-the-loop model. The pipeline includes segmentation, keypoint detection and description, keypoint matching, and ranking. The choice of feature descriptor has the largest impact on the performance and we show that the deep learning based SuperPoint descriptor greatly outperforms handcrafted descriptors like SIFT and RootSIFT independent of the segmentation level and matching method. Combining SuperPoint and the graph neural network based SuperGlue matching method produces the best results.