Influence of altitude on tropical marine habitat classification using imagery from fixed‐wing, water‐landing UAVs

Unmanned aerial vehicles (UAVs) are cost‐effective remote sensing tools useful for generating very high‐resolution (VHR) aerial imagery. Habitat maps generated from UAV imagery are a fundamental component of marine spatial planning, essential for the designation and governance of marine protected areas (MPAs). We investigated whether UAV survey altitude affects habitat classification performance and the classification accuracy of thematic maps from a tropical shallow water environment. We conducted repeated UAV flights at 75, 85, and 110 m, using a fixed‐wing UAV on the Turneffe Atoll, Belize. Flights were ground truthed with snorkel surveys. Images were mosaiced to form orthomosaics and transformed into thematic maps through semi‐automatic object‐based image analysis (OBIA). Three subset areas (4000 m2, 17 000 m2 and 17 000 m2) from two cayes on the atoll were selected to investigate the effect of survey altitude. A linear regression demonstrated that for every 1 m increase in survey altitude, there was a ~1% decrease in the overall classification accuracy. A low survey altitude of 75 m produced a higher classification accuracy for thematic maps and increased the representation of mangrove, seagrass and sand. The variability in classified cover was driven by altitude, although the direction and extent of this relationship was specific to each class. For coral and sea, classified cover decreased with increased altitude. Mangrove classified cover was non‐sensitive to altitude changes, demonstrating a lesser need for a consistent survey altitude. Sand and seagrass had a greater sensitivity to altitude, due to classified cover variability between altitudes. Our findings suggest that survey altitude should be minimized when classifying tropical marine environments (coral, seagrass) and, given that most fixed‐wing UAVs are restricted to a minimum altitude of 70 m, we recommend an altitude of 75 m. Survey altitude should be a major consideration when targeting habitats with greater sensitivity to altitude variability

Enhanced pelagic biomass around coral atolls

Understanding the processes driving the distribution of mid-water prey such as euphausiids and lanternfish is important for effective management and conservation. In the vicinity of abrupt topographic features such as banks, seamounts and shelf-breaks, mid-water faunal biomass is often elevated, making these sites candidates for special protection. We investigated the spatial distribution of water column acoustic backscatter—a proxy for macrozooplankton and fish biomass—in the 9 km transition zone between the pelagos and coral atolls in the Chagos Archipelago (6° N, 72° E). The purpose was to determine the magnitude and distance over which bathymetry may enhance biomass in the mid-water, and thereby identify the scale over which static topographic features could influence the open ocean. Two distinct sound scattering layers were identified, from the surface to 180 m and from 300 to 600 m, during daytime. Both layers exhibited significant increases in backscatter near features. Close to features, the shallow layer backscatter was ca. 100 times higher and was driven partly by increasing numbers of larger individuals, evident as single target echoes. We determine the regional scale of influence of features on pelagic biomass enhancement to be ca. 1.8 km in the Chagos Archipelago, and suggest possible ecological explanations that may support it. Our approach determining the scale of influence of bathymetry should be applied during the process of marine reserve design, in order to improve protection of mid-water fauna associated with topographical features, such as seamounts and coral reefs

Climate oscillation and the invasion of alien species influence the oceanic distribution of seabirds

Spatial and temporal distribution of seabird transiting and foraging at sea is an important consideration for marine conservation planning. Using at-sea observations of seabirds (n = 317), collected during the breeding season from 2012 to 2016, we built boosted regression tree (BRT) models to identify relationships between numerically dominant seabird species (red-footed booby, brown noddy, white tern, and wedge-tailed shearwater), geomorphology, oceanographic variability, and climate oscillation in the Chagos Archipelago. We documented positive relationships between red-footed booby and wedge-tailed shearwater abundance with the strength in the Indian Ocean Dipole, as represented by the Dipole Mode Index (6.7% and 23.7% contribution, respectively). The abundance of red-footed boobies, brown noddies, and white terns declined abruptly with greater distance to island (17.6%, 34.1%, and 41.1% contribution, respectively). We further quantified the effects of proximity to rat-free and rat-invaded islands on seabird distribution at sea and identified breaking point distribution thresholds. We detected areas of increased abundance at sea and habitat use-age under a scenario where rats are eradicated from invaded nearby islands and recolonized by seabirds. Following rat eradication, abundance at sea of red-footed booby, brown noddy, and white terns increased by 14%, 17%, and 3%, respectively, with no important increase detected for shearwaters. Our results have implication for seabird conservation and island restoration. Climate oscillations may cause shifts in seabird distribution, possibly through changes in regional productivity and prey distribution. Invasive species eradications and subsequent island recolonization can lead to greater access for seabirds to areas at sea, due to increased foraging or transiting through, potentially leading to distribution gains and increased competition. Our approach predicting distribution after successful eradications enables anticipatory threat mitigation in these areas, minimizing competition between colonies and thereby maximizing the risk of success and the conservation impact of eradication programs

Significant range extensions for two fish species at Pitcairn Island, South Pacific

A baited videographic survey at Pitcairn Island has significantly extended the known range for two reef-fish species: blue-lined triggerfish Xanthichthys caeruleolineatus and greater amberjack Seriola dumerili, with an additional minor extension noted for giant trevally Caranx ignobilis. This highlights the importance of further research in this remote, poorly studied island group and provides evidence supplementing the understanding of oceanographic patterns in the South Pacific

Isolation and no-entry marine reserves mitigate anthropogenic impacts on grey reef shark behavior

Reef sharks are vulnerable predators experiencing severe population declines mainly due to overexploitation. However, beyond direct exploitation, human activities can produce indirect or sub-lethal effects such as behavioral alterations. Such alterations are well known for terrestrial fauna but poorly documented for marine species. Using an extensive sampling of 367 stereo baited underwater videos systems, we show modifications in grey reef shark (Carcharhinus amblyrhynchos) occurrence and feeding behavior along a marked gradient of isolation from humans across the New Caledonian archipelago (South-Western Pacific). The probability of occurrence decreased by 68.9% between wilderness areas (more than 25 hours travel time from the capital city) and impacted areas while the few individuals occurring in impacted areas exhibited cautious behavior. We also show that only large no-entry reserves (above 150 km²) can protect the behavior of grey reef sharks found in the wilderness. Influencing the fitness, human linked behavioral alterations should be taken into account for management strategies to ensure the persistence of populations

Improved bathymetry leads to >4000 new seamount predictions in the global ocean – but beware of phantom seamounts!

Seamounts are important marine habitats that are hotspots of species diversity. Relatively shallow peaks, increased productivity and offshore locations make seamounts vulnerable to human impact and difficult to protect. Present estimates of seamount numbers vary from anywhere between 10,000 to more than 60,000. Seamount locations can be estimated by extracting large, cone-like features from bathymetry grids (based on criteria of size and shape). These predicted seamounts are a useful reference for marine researchers and can help direct exploratory surveys. However, these predictions are dependent on the quality of the surveys underpinning the bathymetry. Historically, quality has been patchy, but is improving as mapping efforts step up towards the target of complete seabed coverage by 2030. This study presents an update of seamount predictions based on SRTM30 PLUS global bathymetry version 11 and examines a potential source of error in these predictions. This update was prompted by a seamount survey in the British Indian Ocean Territory in 2016, where locations of two putative seamounts were visited. These ‘seamounts’ were targeted based on previous predictions, but these features were not detected during echosounder surveys. An examination of UK hydrographic office navigational (Admiralty) charts for the area showed that the summits of these putative features had soundings reporting ‘no bottom detected at this depth’ where ‘this depth’ was similar to the seabed reported from the bathymetry grids: we suspect that these features likely resulted from an initial misreading of the charts. We show that 15 ‘phantom seamount’ features, derived from a misinterpretation of no bottom sounding data, persist in current global bathymetry grids and updated seamount predictions. Overall, we predict 37,889 seamounts, an increase of 4437 from the previous predictions derived from an older global bathymetry grid (SRTM30 PLUS v6). This increase is due to greater detail in newer bathymetry grids as acoustic mapping of the seabed expands. The new seamount predictions are available at https://doi.pangaea.de/10.1594/PANGAEA.921688.</jats:p

Wasp-Waist Interactions in the North Sea Ecosystem

Background In a “wasp-waist” ecosystem, an intermediate trophic level is expected to control the abundance of predators through a bottom-up interaction and the abundance of prey through a top-down interaction. Previous studies suggest that the North Sea is mainly governed by bottom-up interactions driven by climate perturbations. However, few studies have investigated the importance of the intermediate trophic level occupied by small pelagic fishes. Methodology/Principal Findings We investigated the numeric interactions among 10 species of seabirds, two species of pelagic fish and four groups of zooplankton in the North Sea using decadal-scale databases. Linear models were used to relate the time series of zooplankton and seabirds to the time series of pelagic fish. Seabirds were positively related to herring (Clupea harengus), suggesting a bottom-up interaction. Two groups of zooplankton; Calanus helgolandicus and krill were negatively related to sprat (Sprattus sprattus) and herring respectively, suggesting top-down interactions. In addition, we found positive relationships among the zooplankton groups. Para/pseudocalanus was positively related to C. helgolandicus and C. finmarchicus was positively related to krill. Conclusion/Significance Our results indicate that herring was important in regulating the abundance of seabirds through a bottom-up interaction and that herring and sprat were important in regulating zooplankton through top-down interactions. We suggest that the positive relationships among zooplankton groups were due to selective foraging and switching in the two clupeid fishes. Our results suggest that “wasp-waist” interactions might be more important in the North Sea than previously anticipated. Fluctuations in the populations of pelagic fish due to harvesting and depletion of their predators might accordingly have profound consequences for ecosystem dynamics through trophic cascades

Models of marine fish biodiversity : assessing predictors from three habitat classification schemes

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modeling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modeling metrics of fish biodiversity that are not fully captured by remotely sensed data. As such, the use of remotely sensed data to model biodiversity represents a compromise between model performance and data availability

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta