A global map to aid the identification and screening of critical habitat for marine industries

Marine industries face a number of risks that necessitate careful analysis prior to making decisions on the siting of operations and facilities. An important emerging regulatory framework on environmental sustainability for business operations is the International Finance Corporation’s Performance Standard 6 (IFC PS6). Within PS6, identification of biodiversity significance is articulated through the concept of “Critical Habitat”, a definition developed by the IFC and detailed through criteria aligned with those that support internationally accepted biodiversity designations. No publicly available tools have been developed in either the marine or terrestrial realm to assess the likelihood of sites or operations being located within PS6-defined Critical Habitat. This paper presents a starting point towards filling this gap in the form of a preliminary global map that classifies more than 13 million km2 of marine and coastal areas of importance for biodiversity (protected areas, Key Biodiversity Areas [KBA], sea turtle nesting sites, cold- and warm-water corals, seamounts, seagrass beds, mangroves, saltmarshes, hydrothermal vents and cold seeps) based on their overlap with Critical Habitat criteria, as defined by IFC. In total, 5798×103 km2 (1.6%) of the analysis area (global ocean plus coastal land strip) were classed as Likely Critical Habitat, and 7526×103 km2 (2.1%) as Potential Critical Habitat; the remainder (96.3%) were Unclassified. The latter was primarily due to the paucity of biodiversity data in marine areas beyond national jurisdiction and/or in deep waters, and the comparatively fewer protected areas and KBAs in these regions. Globally, protected areas constituted 65.9% of the combined Likely and Potential Critical Habitat extent, and KBAs 29.3%, not accounting for the overlap between these two features. Relative Critical Habitat extent in Exclusive Economic Zones varied dramatically between countries. This work is likely to be of particular use for industries operating in the marine and coastal realms as an early screening aid prior to in situ Critical Habitat assessment; to financial institutions making investment decisions; and to those wishing to implement good practice policies relevant to biodiversity management. Supplementary material (available online) includes other global datasets considered, documentation and justification of biodiversity feature classification, detail of IFC PS6 criteria/scenarios, and coverage calculations

Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel

This paper describes the design, implementation and testing of a suite of algorithms to enable depth constrained autonomous bathymetric (underwater topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth and a bounding polygon, the ASV will find and follow the intersection of the bounding polygon and the depth contour as modeled online with a Gaussian Process (GP). This intersection, once mapped, will then be used as a boundary within which a path will be planned for coverage to build a map of the Bathymetry. Methods for sequential updates to GP's are described allowing online fitting, prediction and hyper-parameter optimisation on a small embedded PC. New algorithms are introduced for the partitioning of convex polygons to allow efficient path planning for coverage. These algorithms are tested both in simulation and in the field with a small twin hull differential thrust vessel built for the task.Comment: 21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field Robotic

Errors in particle tracking velocimetry with high-speed cameras

Velocity errors in particle tracking velocimetry (PTV) are studied. When using high-speed video cameras, the velocity error may increase at a high camera frame rate. This increase in velocity error is due to particle-position uncertainty, which is one of two sources of velocity errors studied here. The other source of error is particle acceleration, which has the opposite trend of diminishing at higher frame rates. Both kinds of errors can propagate into quantities calculated from velocity, such as the kinetic temperature of particles or correlation functions. As demonstrated in a dusty plasma experiment, the kinetic temperature of particles has no unique value when measured using PTV, but depends on the sampling time interval or frame rate. It is also shown that an artifact appears in an autocorrelation function computed from particle positions and velocities, and it becomes more severe when a small sampling-time interval is used. Schemes to reduce these errors are demonstrated.Comment: 6 pages, 5 figures, Review of Scientific Instruments, 2011 (In Press

Parametric inference of recombination in HIV genomes

Recombination is an important event in the evolution of HIV. It affects the global spread of the pandemic as well as evolutionary escape from host immune response and from drug therapy within single patients. Comprehensive computational methods are needed for detecting recombinant sequences in large databases, and for inferring the parental sequences. We present a hidden Markov model to annotate a query sequence as a recombinant of a given set of aligned sequences. Parametric inference is used to determine all optimal annotations for all parameters of the model. We show that the inferred annotations recover most features of established hand-curated annotations. Thus, parametric analysis of the hidden Markov model is feasible for HIV full-length genomes, and it improves the detection and annotation of recombinant forms. All computational results, reference alignments, and C++ source code are available at http://bio.math.berkeley.edu/recombination/.Comment: 20 pages, 5 figure