Kevin C. Weng

Electronic tagging and population structure of Atlantic bluefin tuna

Electronic tags that archive or transmit stored data to satellites have advanced the mapping of habitats used by highly migratory fish in pelagic ecosystems. Here we report on the electronic tagging of 772 Atlantic bluefin tuna in the western Atlantic Ocean in an effort to identify population structure. Reporting electronic tags provided accurate location data that show the extensive migrations of individual fish (n = 330). Geoposition data delineate two populations, one using spawning grounds in the Gulf of Mexico and another from the Mediterranean Sea. Transatlantic movements of western-tagged bluefin tuna reveal site fidelity to known spawning areas in the Mediterranean Sea. Bluefin tuna that occupy western spawning grounds move to central and eastern Atlantic foraging grounds. Our results are consistent with two populations of bluefin tuna with distinct spawning areas that overlap on North Atlantic foraging grounds. Electronic tagging locations, when combined with US pelagic longline observer and logbook catch data, identify hot spots for spawning bluefin tuna in the northern slope waters of the Gulf of Mexico. Restrictions on the time and area where longlining occurs would reduce incidental catch mortalities on western spawning grounds.

Climate impacts and oceanic top predators: moving from impacts to adaptation in oceanic systems

Climate impacts are now widely reported from coastal marine systems, but less is known for the open ocean. Here we review progress in understanding impacts on large pelagic species presented at an international workshop for the Climate Impacts on Oceanic Top Predators programme, and discuss the future with regard to the next phase of adaptation-focused research. Recent highlights include a plan to map the distribution of key species in the foodweb using both acoustics and biochemical techniques, and development of a new data sharing and access tool for fisheries and associated data, including socio-economic information. A common research focus in pelagic ecosystems is on understanding climate variability and climate change impacts on marine species, but a greater emphasis on developing future scenarios and adaptation options is needed. Workshop participants also concluded that engagement with and provision of science support to regional fisheries management organisations are critical elements for ensuring successful uptake of research. This uptake will be required for future management of fisheries as global warming continues such that some open ocean top predators can be sustainably harvested, impacts on conservation-dependent species can be avoided, and ecosystem function is not compromised.

Drivers of daily routines in an ectothermic marine predator : hunt warm, rest warmer?

Animal daily routines represent a compromise between maximizing foraging success and optimizing physiological performance, while minimizing the risk of predation. For ectothermic predators, ambient temperature may also influence daily routines through its effects on physiological performance. Temperatures can fluctuate significantly over the diel cycle and ectotherms may synchronize behaviour to match thermal regimes in order to optimize fitness. We used bio-logging to quantify activity and body temperature of blacktip reef sharks (Carcharhinus melanopterus) at a tropical atoll. Behavioural observations were used to concurrently measure bite rates in herbivorous reef fishes, as an index of activity for potential diurnal prey. Sharks showed early evening peaks in activity, particularly during ebbing high tides, while body temperatures peaked several hours prior to the period of maximal activity. Herbivores also displayed peaks in activity several hours earlier than the peaks in shark activity. Sharks appeared to be least active while their body temperatures were highest and most active while temperatures were cooling, although we hypothesize that due to thermal inertia they were still warmer than their smaller prey during this period. Sharks may be most active during early evening periods as they have a sensory advantage under low light conditions and/or a thermal advantage over cooler prey. Sharks swam into shallow water during daytime low tide periods potentially to warm up and increase rates of digestion before the nocturnal activity period, which may be a strategy to maximize ingestion rates. “Hunt warm, rest warmer” may help explain the early evening activity seen in other ectothermic predators.

Estimating individual animal movement from observation networks

Summary Observation network data comprise animal presences detected by observer stations at fixed spatial locations. Statistical analysis of these data is complicated by spatial bias in sampling and temporal variability in detection conditions. Advanced methods for analysis of these data are required but are currently underdeveloped. We propose a state-space model (SSM) for observation network data to estimate detailed movements of individual animals. The underlying movement model is an Ornstein–Uhlenbeck (OU) process, which is stationary, and therefore has an inherent mechanism that models home range behaviour. An integral part of the approach is the detection function, which models the probability of logging animal presences. The detection function is also used to provide absence information when animals are undetected. Since the ability to detect an animal often depends on time-varying external factors such as environmental conditions, we use covariate information about detection efficiency as control variables. Via simulation, we found that movement estimation error scales log-linearly with network sparsity. This result can be used to indicate the number of stations necessary to achieve a desired upper bound on estimation error. Furthermore, we found that the SSM outperforms existing techniques in terms of estimating detailed movements and that estimates are robust towards mis-specification of the detection function. We also tested the importance of accounting for time-varying detection conditions and found that the probability of making wrong conclusions decreases substantially when covariate information is exploited. The model is used to estimate movements and home range of a humphead wrasse (Cheilinus undulatus) at Palmyra Atoll in the central Pacific Ocean. Here, detection conditions have a strong diel component, which is controlled for using detection efficiency information from a reference device. The presented approach enhances the toolbox for analysis of observation network data as collected by acoustic telemetry or potentially other aspiring methods such as camera trapping and mobile phone tagging. By explicitly modelling movement and observation processes, the model integrates all sources of uncertainty and provides a sound statistical basis for making well-informed management decisions from imperfect information.

First record of the southern ocean sunfish, Mola ramsayi , in the Galápagos Marine Reserve

tierney m. thys, jonathan whitney, alex hearn, kevin c. weng, cesar pen~aherrera, l. jawad, j. alfaro-shigueto, j.c. mangel and stephen a. karl Ocean Sunfish Research and Tagging Program, 25517 Hacienda Place, Suite C Carmel, CA, 93923, Hawai’i Institute of Marine Biology, University of Hawai’i, Mānoa, PO Box 1346, Kāne’ohe, HI, 96744, Department of Wildlife, Fish, and Conservation Biology, 1088 Academic Surge, University of California, Davis, One Shields Avenue, Davis, CA, 95616-5270, Oceanography Department, Pelagic Fisheries Research Program, University of Hawai’i, Mānoa, Honolulu, HI 96822, Charles Darwin Foundation, Puerto Ayora, Santa Cruz Island, Galapagos, Ecuador, Natural Sciences, Auckland War Memorial Museum, Tamaki Paenga Hira, The Domain, Private Bag 92018, Victoria Street West, Auckland 1142, New Zealand, Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Cornwall Campus, TR10 9EZ, UK

Satellite Tracking and Site Fidelity of Short Ocean Sunfish, Mola ramsayi, in the Galapagos Islands

Ocean sunfishes, with their peculiar morphology, large size, and surface habits, are valuable assets in ecotourism destinations worldwide. This study investigates site fidelity and long-range movements of short ocean sunfish, Mola ramsayi (Giglioli 1883), at Punta Vicente Roca (PVR) off Isabela Island in the Galapagos Islands. Five individuals were tracked between 32 and 733 days using ultrasonic receivers and transmitters. Two of the 5 were also tracked with towed pop-off satellite tags. One travelled to the equatorial front covering 2700 km in 53 days, with dive depths in the upper 360 m at temperatures between 9.2°C and 22°C. During its westward travel, dives extended to 1112 m (the deepest depth yet recorded for Molidae) into temperatures ranging between 4.5°C and 23.2°C. The remaining four individuals demonstrated site fidelity to PVR and were detected at the site between 128–1361 times for a total of 3557 reports. Forty-eight percent of the reports occurred during daytime hours and 52% after dark. Presumed cleaning session durations had a median of 15 minutes and a maximum of nearly 100 minutes. No other ultrasonic arrays around Galapagos or in the Eastern Pacific regional network recorded the presence of tagged individuals. These data are combined with tourist vessel sightings and submersible observations to confirm Punta Vicente Roca as an important sunfish hotspot.

Tracking a Marine Ecotourism Star: Movements of the Short Ocean Sunfish Mola ramsayi in Nusa Penida, Bali, Indonesia

Ocean sunfishes, Molidae, comprise the world’s heaviest bony fishes. They include the short mola, Mola ramsayi (Giglioli 1883), an important tourist draw at Nusa Penida and Nusa Lembongan, Bali, where SCUBA divers can observe ectoparasite-laden individuals being cleaned by smaller reef fishes. Despite widespread appeal, little is known about these fishes relative to regional oceanography. We present the first behavioral information for this species anywhere in the world. Satellite tag data indicate a wide thermal range (10–27.5°C) with depth occupation mostly (95%) in the upper 250 m and habitat preference near the bottom of the warm surface layer. One tag popped off as scheduled after 6 months off Nusa Penida, <10 km from its original deployment. The 3 other tags popped off prematurely: 747 km southeast 89 days after deployment; 142 km south after 7 days of deployment; and 162 km south after 24 days of deployment. Amid mounting tourist pressures and bycatch of M. ramsayi in eastern regions of Indonesia, such as Alor, behavioral information of this species is essential for effective management and conservation of this valuable marine ecotourism asset.

A quantitative approach to static sensor network design

Summary Static sensor networks to observe animals are widely used in ecological, management and conservation research, but quantitative methods for designing these networks are underdeveloped. In the context of aquatic systems, we present a method for quasi-optimal network design, which accounts for blocking of detections by obstacles, horizontal and vertical movement behaviour of the target animals, and type of research question (is the network intended for estimation of detailed movement or home range?). Optimal design is defined as the sensor configuration that maximizes the expected number of unique animal detections. As finding the global optimum is generally time consuming, we use a greedy algorithm instead, which places sensors optimally relative to already placed sensors. The design method requires access to topographic data of the study site and knowledge of the sensor detection range. We illustrate the method with real topographic data from a rugose coral reef where network performance is highly influenced by detection shadowing. Network performance is visualized by a coverage map indicating the probability of detection at any location in the study area. The reported unique recovery rate summarizes the expected ability of the network to collect data given the design constraints. Because sensors are placed sequentially, the information gain per sensor can be evaluated and used as a proxy for sensor value. The presented method formalizes important considerations, when designing sensor networks, that were previously often based on heuristics and intuition. The method provides a guide to maximizing the information potential of future monitoring studies as well as a means to improve existing networks. The method is available as an R package and can be tested via an online web tool.

Depth- and range-dependent variation in the performance of aquatic telemetry systems: understanding and predicting the susceptibility of acoustic tag–receiver pairs to close proximity detection interference

Background Passive acoustic telemetry using coded transmitter tags and stationary receivers is a popular method for tracking movements of aquatic animals. Understanding the performance of these systems is important in array design and in analysis. Close proximity detection interference (CPDI) is a condition where receivers fail to reliably detect tag transmissions. CPDI generally occurs when the tag and receiver are near one another in acoustically reverberant settings. Here we confirm transmission multipaths reflected off the environment arriving at a receiver with sufficient delay relative to the direct signal cause CPDI. We propose a ray-propagation based model to estimate the arrival of energy via multipaths to predict CPDI occurrence, and we show how deeper deployments are particularly susceptible. Methods A series of experiments were designed to develop and validate our model. Deep (300 m) and shallow (25 m) ranging experiments were conducted using Vemco V13 acoustic tags and VR2-W receivers. Probabilistic modeling of hourly detections was used to estimate the average distance a tag could be detected. A mechanistic model for predicting the arrival time of multipaths was developed using parameters from these experiments to calculate the direct and multipath path lengths. This model was retroactively applied to the previous ranging experiments to validate CPDI observations. Two additional experiments were designed to validate predictions of CPDI with respect to combinations of deployment depth and distance. Playback of recorded tags in a tank environment was used to confirm multipaths arriving after the receiver’s blanking interval cause CPDI effects. Results Analysis of empirical data estimated the average maximum detection radius (AMDR), the farthest distance at which 95% of tag transmissions went undetected by receivers, was between 840 and 846 m for the deep ranging experiment across all factor permutations. From these results, CPDI was estimated within a 276.5 m radius of the receiver. These empirical estimations were consistent with mechanistic model predictions. CPDI affected detection at distances closer than 259–326 m from receivers. AMDR determined from the shallow ranging experiment was between 278 and 290 m with CPDI neither predicted nor observed. Results of validation experiments were consistent with mechanistic model predictions. Finally, we were able to predict detection/nondetection with 95.7% accuracy using the mechanistic model’s criterion when simulating transmissions with and without multipaths. Discussion Close proximity detection interference results from combinations of depth and distance that produce reflected signals arriving after a receiver’s blanking interval has ended. Deployment scenarios resulting in CPDI can be predicted with the proposed mechanistic model. For deeper deployments, sea-surface reflections can produce CPDI conditions, resulting in transmission rejection, regardless of the reflective properties of the seafloor.

The political biogeography of migratory marine predators

During their migrations, marine predators experience varying levels of protection and face many threats as they travel through multiple countries’ jurisdictions and across ocean basins. Some populations are declining rapidly. Contributing to such declines is a failure of some international agreements to ensure effective cooperation by the stakeholders responsible for managing species throughout their ranges, including in the high seas, a global commons. Here we use biologging data from marine predators to provide quantitative measures with great potential to inform local, national and international management efforts in the Pacific Ocean. We synthesized a large tracking data set to show how the movements and migratory phenology of 1,648 individuals representing 14 species—from leatherback turtles to white sharks—relate to the geopolitical boundaries of the Pacific Ocean throughout species’ annual cycles. Cumulatively, these species visited 86% of Pacific Ocean countries and some spent three-quarters of their annual cycles in the high seas. With our results, we offer answers to questions posed when designing international strategies for managing migratory species.Daily location data on the individuals of 14 migratory marine species from 2000 to 2009 allow annual migratory cycles to be mapped to the time spent in the high seas and the exclusive economic zones of specific countries, providing a basis for international management strategies for these species.