Bay watch: Using unmanned aerial vehicles (UAV's) to survey the box jellyfish Chironex fleckeri

Evaluating Thermal Infrared Drone Flight Parameters on Spider Monkey Detection in Tropical Forests

Geoffroy's spider monkeys, an endangered, fast-moving arboreal primate species with a large home range and a high degree of fission-fusion dynamics, are challenging to survey in their natural habitats. Our objective was to evaluate how different flight parameters affect the detectability of spider monkeys in videos recorded by a drone equipped with a thermal infrared camera and examine the level of agreement between coders. We used generalized linear mixed models to evaluate the impact of flight speed (2, 4, 6 m/s), flight height (40, 50 m above ground level), and camera angle (-45°, -90°) on spider monkey counts in a closed-canopy forest in the Yucatan Peninsula, Mexico. Our results indicate that none of the three flight parameters affected the number of detected spider monkeys. Agreement between coders was "substantial" (Fleiss' kappa coefficient = 0.61-0.80) in most cases for high thermal-contrast zones. Our study contributes to the development of standardized flight protocols, which are essential to obtain accurate data on the presence and abundance of wild populations. Based on our results, we recommend performing drone surveys for spider monkeys and other medium-sized arboreal mammals with a small commercial drone at a 4 m/s speed, 15 m above canopy height, and with a -90° camera angle. However, these recommendations may vary depending on the size and noise level produced by the drone model.

Monitoring jellyfish outbreaks along Israel's Mediterranean coast using digital footprints

With mounting global concerns about jellyfish outbreaks, monitoring their occurrence remains challenging. Tapping into the wealth of digital data that internet users share online, which includes reports of jellyfish sightings, may provide an alternative or complement to more conventional expert-based or citizen science monitoring. Here, we explore digital footprints as a data source to monitor jellyfish outbreaks along the Israeli Mediterranean coast. We compiled jellyfish sighting data for the period 2011-2022 from multiple platforms, including leading social media platforms, searches in the Google search engine, and Wikipedia page views. Employing time series analysis, cross-correlation, and various evaluation metrics for presence/absence data, we compared weekly data from three sources: digital footprints, citizen science, and traditional expert-based field monitoring. Consistent seasonal patterns emerge across datasets, with notable correlations, particularly in jellyfish abundance. The cross-correlation between digital footprint and citizen science data exceeds >0.7, with Twitter and Instagram showing the highest correlation. Citizen science data often precedes digital footprints by up to one week. Correlation with traditional, expert-based field monitoring is limited as a result of limited data availability. Digital footprints demonstrate substantial agreement with the other data sources regarding jellyfish presence/absence and major outbreaks, especially for data from Wikipedia, Twitter, and Instagram. Overall, we highlight digital footprint data as a reliable, cost-effective tool for passive monitoring of jellyfish outbreaks, which can aid characterization in data-scarce coastal regions, including retrospective assessment. Transferring and scaling up the proposed approach should consider data accessibility as well as platform relative popularity and usage in the regions under investigation.

Genetic Detection and a Method to Study the Ecology of Deadly Cubozoan Jellyfish

Cubozoan jellyfish pose a risk of envenomation to humans and a threat to many businesses, yet crucial gaps exist in determining threats to stakeholders and understanding their ecology. Environmental DNA (eDNA) provides a cost-effective method for detection that is less labour intensive and provides a higher probability of detection. The objective of this study was to develop, optimise and trial the use of eDNA to detect the Australian box jellyfish, Chironex fleckeri. This species was the focus of this study as it is known to have the strongest venom of any cubozoan; it is responsible for more than 200 recorded deaths in the Indo-Pacific region. Further, its ecology is poorly known. Herein, a specific and sensitive probe-based assay, multiplexed with an endogenous control assay, was developed, and successfully utilised to detect the deadly jellyfish species and differentiate them from closely related taxa. A rapid eDNA decay rate of greater than 99% within 27 h was found with no detectable influence from temperature. The robustness of the technique indicates that it will be of high utility for detection and to address knowledge gaps in the ecology of C. fleckeri; further, it has broad applicability to other types of zooplankton.

UAV remote sensing applications in marine monitoring: Knowledge visualization and review

With the booming development of information technology and the growing demand for remote sensing data, unmanned aerial vehicle (UAV) remote sensing technology has emerged. In recent years, UAV remote sensing technology has developed rapidly and has been widely used in the fields of military defense, agricultural monitoring, surveying and mapping management, and disaster and emergency response and management. Currently, increasingly serious marine biological and environmental problems are raising the need for effective and timely monitoring. Compared with traditional marine monitoring technologies, UAV remote sensing is becoming an important means for marine monitoring thanks to its flexibility, efficiency and low cost, while still producing systematic data with high spatial and temporal resolutions. This study visualizes the knowledge domain of the application and research advances of UAV remote sensing in marine monitoring by analyzing 1130 articles (from 1993 to early 2022) using a bibliometric approach and provides a review of the application of UAVs in marine management mapping, marine disaster and environmental monitoring, and marine wildlife monitoring. It aims to promote the extensive application of UAV remote sensing in the field of marine research.

Evaluating the effectiveness of drones for quantifying invasive upside-down jellyfish (Cassiopea sp.) in Lake Macquarie, Australia

Upside-down jellyfish (Cassiopea sp.) are mostly sedentary, benthic jellyfish that have invaded estuarine ecosystems around the world. Monitoring the spread of this invasive jellyfish must contend with high spatial and temporal variability in abundance of individuals, especially around their invasion front. Here, we evaluated the utility of drones to survey invasive Cassiopea in a coastal lake on the east coast of Australia. To assess the efficacy of a drone-based methodology, we compared the densities and counts of Cassiopea from drone observations to conventional boat-based observations and evaluated cost and time efficiency of these methods. We showed that there was no significant difference in Cassiopea density measured by drones compared to boat-based methods along the same transects. However, abundance estimates of Cassiopea derived from scaling-up transect densities were over-inflated by 319% for drones and 178% for boats, compared to drone-based counts of the whole site. Although conventional boat-based survey techniques were cost-efficient in the short-term, we recommend doing whole-of-site counts using drones. This is because it provides a time-saving and precise technique for long-term monitoring of the spatio-temporally dynamic invasion front of Cassiopea in coastal lakes and other sheltered marine habitats with relatively clear water.

Using Drones to Measure Jellyfish Density in Shallow Estuaries

Understanding jellyfish ecology and roles in coastal ecosystems is challenging due to their patchy distribution. While standard net sampling or manned aircraft surveys are inefficient, Unmanned Aerial Vehicles (UAVs) or drones represent a promising alternative for data collection. In this technical report, we used pictures taken from a small drone to estimate the density of Aurelia sp. in a shallow fjord with a narrow entrance, where the population dynamic is well-known. We investigated the ability of an image processing software to count small and translucent jellyfish from the drone pictures at three locations with different environmental conditions (sun glare, waves or seagrass). Densities of Aurelia sp. estimated from semiautomated and manual counts from drone images were similar to densities estimated by netting. The semiautomated program was able to highlight the medusae from the background in order to discard false detections of items unlikely to be jellyfish. In spite of this, some objects (e.g., seagrass) were hardly distinguishable from jellyfish and resulted in a small number of false positives. This report presents a preview of the possible applications of drones to observe small and fragile jellyfishes, for which in situ sampling remains delicate. Drones may represent a noninvasive approach to monitoring jellyfish abundance over time, enabling the collection of a large amount of data in a short time. Software development may be useful for automatically measuring jellyfish size and even population biomass.

Rapid and Accurate Species-Specific PCR for the Identification of Lethal Chironex Box Jellyfish in Thailand

Box jellyfish are extremely potent venom-producing marine organisms. While they have been found worldwide, the highest health burden has been anticipated to be the tropical Indo-Pacific of Southeast Asia (SEA). At least 12 Cubozoan species have now been documented in Thai waters, and many of them inflict acutely lethal strings, especially those under the order Chirodropida. Our previous study has successfully differentiated species of box jellyfish using DNA sequencing to support the morphological study. In this study, we specifically designed polymerase chain reaction (PCR) primers for the 16S ribosomal RNA (rRNA) gene and the mitochondrial DNA cytochrome oxidase subunit I (COI) gene of lethal Thai Chironex species. The SYBR green-based real-time PCR panel was performed for rapid species identification. The sensitivity and specificity of the panel were determined by testing samples of different species. Moreover, we applied the panel to the tentacle sample from a real patient, which helped confirm the animal-of-cause of envenomation. Our results show a success for species identification of box jellyfish using 16S rRNA and COI PCR panel, which revealed congruence between molecular and morphological identification. Furthermore, the panel worked very well with the unknown samples and jellyfish tissue from the real envenomation case. The results demonstrated that molecular panels were able to identify three species of Chironex box jellyfish both rapidly and accurately, and can be performed without having a complete specimen or morphological study.