Quantifying pigment content in crustose coralline algae using hyperspectral imaging: A case study with Tethysphytum antarcticum (Ross Sea, Antarctica).

Crustose coralline algae (CCA) are a highly diverse group of habitat-forming, calcifying red macroalgae (Rhodophyta) with unique adaptations to diverse irradiance regimes. A distinctive CCA phenotype adaptation, which allows them to maximize photosynthetic performance in low light, is their content of a specific group of light-harvesting pigments called phycobilins. In this study, we assessed the potential of noninvasive hyperspectral imaging (HSI) in the visible spectrum (400-800 nm) to describe the phenotypic variability in phycobilin content of an Antarctic coralline, Tethysphytum antarcticum (Hapalidiales), from two distinct locations. We validated our measurements with pigment extractions and spectrophotometry analysis, in addition to DNA barcoding using the psbA marker. Targeted spectral indices were developed and correlated with phycobilin content using linear mixed models (R2 = 0.64-0.7). Once applied to the HSI, the models revealed the distinct phycoerythrin spatial distribution in the two site-specific CCA phenotypes, with thin and thick crusts, respectively. This study advances the capabilities of hyperspectral imaging as a tool to quantitatively study CCA pigmentation in relation to their phenotypic plasticity, which can be applied in laboratory studies and potentially in situ surveys using underwater hyperspectral imaging systems.

Mapping the in situ microspatial distribution of ice algal biomass through hyperspectral imaging of sea-ice cores.

Ice-associated microalgae make a significant seasonal contribution to primary production and biogeochemical cycling in polar regions. However, the distribution of algal cells is driven by strong physicochemical gradients which lead to a degree of microspatial variability in the microbial biomass that is significant, but difficult to quantify. We address this methodological gap by employing a field-deployable hyperspectral scanning and photogrammetric approach to study sea-ice cores. The optical set-up facilitated unsupervised mapping of the vertical and horizontal distribution of phototrophic biomass in sea-ice cores at mm-scale resolution (using chlorophyll a [Chl a] as proxy), and enabled the development of novel spectral indices to be tested against extracted Chl a (R2 ≤ 0.84). The modelled bio-optical relationships were applied to hyperspectral imagery captured both in situ (using an under-ice sliding platform) and ex situ (on the extracted cores) to quantitatively map Chl a in mg m-2 at high-resolution (≤ 2.4 mm). The optical quantification of Chl a on a per-pixel basis represents a step-change in characterising microspatial variation in the distribution of ice-associated algae. This study highlights the need to increase the resolution at which we monitor under-ice biophysical systems, and the emerging capability of hyperspectral imaging technologies to deliver on this research goal.

A seafloor habitat map for the Australian continental shelf.

Here we outline the genesis of Seamap Australia, which integrates spatial data of the seabed of Australia's continental shelf (0-200 m depth) from multiple sources to provide a single national map layer of marine habitat. It is underpinned by a hierarchical classification scheme with registered vocabulary, enabling presentation of nationally consistent information at the highest resolution available for any point in space. The Seamap Australia website enables users to delineate particular areas of interest, overlay habitat maps with many other marine data layers, and to directly access the data and metadata underlying the maps they produce. This unique resource represents a step-change in capacity to access and integrate large and diverse marine data holdings and to readily derive information and products to underpin decision making around marine spatial planning and conservation prioritisation, state-of-environment reporting, and research. It is a world first fully integrated national-scale marine mapping and data service.

An evaluation of the error and uncertainty in epibenthos cover estimates from AUV images collected with an efficient, spatially-balanced design.

Efficient monitoring of organisms is at the foundation of protected area and biodiversity management. Such monitoring programs are based on a systematically selected set of survey locations that, while able to track trends at those locations through time, lack inference for the overall region being "monitored". Advances in spatially-balanced sampling approaches offer alternatives but remain largely untested in marine ecosystems. This study evaluated the merit of using a two-stage, spatially-balanced survey framework, in conjunction with generalized additive models, to estimate epifauna cover at a reef-wide scale for mesophotic reefs within a large, cross-shelf marine park. Imagery acquired by an autonomous underwater vehicle was classified using a hierarchical scheme developed under the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI). At a realistic image subsampling intensity, the two-stage, spatially-balanced framework provided accurate and precise estimates of reef-wide cover for a select number of epifaunal classes at the coarsest CATAMI levels, in particular bryozoan and porifera classes. However, at finer hierarchical levels, accuracy and/or precision of cover estimates declined, primarily because of the natural rarity of even the most common of these classes/morphospecies. Ranked predictor importance suggested that bathymetry, backscatter and derivative terrain variables calculated at their smallest analysis window scales (i.e. 81 m2) were generally the most important variables in the modeling of reef-wide cover. This study makes an important step in identifying the constraints and limitations that can be identified through a robust statistical approach to design and analysis. The two-stage, spatially-balanced framework has great potential for effective quantification of epifaunal cover in cross-shelf mesophotic reefs. However, greater image subsampling intensity than traditionally applied is required to ensure adequate observations for finer-level CATAMI classes and associated morphospecies.

Comparing Selections of Environmental Variables for Ecological Studies: A Focus on Terrain Attributes.

Selecting appropriate environmental variables is a key step in ecology. Terrain attributes (e.g. slope, rugosity) are routinely used as abiotic surrogates of species distribution and to produce habitat maps that can be used in decision-making for conservation or management. Selecting appropriate terrain attributes for ecological studies may be a challenging process that can lead users to select a subjective, potentially sub-optimal combination of attributes for their applications. The objective of this paper is to assess the impacts of subjectively selecting terrain attributes for ecological applications by comparing the performance of different combinations of terrain attributes in the production of habitat maps and species distribution models. Seven different selections of terrain attributes, alone or in combination with other environmental variables, were used to map benthic habitats of German Bank (off Nova Scotia, Canada). 29 maps of potential habitats based on unsupervised classifications of biophysical characteristics of German Bank were produced, and 29 species distribution models of sea scallops were generated using MaxEnt. The performances of the 58 maps were quantified and compared to evaluate the effectiveness of the various combinations of environmental variables. One of the combinations of terrain attributes-recommended in a related study and that includes a measure of relative position, slope, two measures of orientation, topographic mean and a measure of rugosity-yielded better results than the other selections for both methodologies, confirming that they together best describe terrain properties. Important differences in performance (up to 47% in accuracy measurement) and spatial outputs (up to 58% in spatial distribution of habitats) highlighted the importance of carefully selecting variables for ecological applications. This paper demonstrates that making a subjective choice of variables may reduce map accuracy and produce maps that do not adequately represent habitats and species distributions, thus having important implications when these maps are used for decision-making.

Mapping Habitats and Developing Baselines in Offshore Marine Reserves with Little Prior Knowledge: A Critical Evaluation of a New Approach.

The recently declared Australian Commonwealth Marine Reserve (CMR) Network covers a total of 3.1 million km2 of continental shelf, slope, and abyssal habitat. Managing and conserving the biodiversity values within this network requires knowledge of the physical and biological assets that lie within its boundaries. Unfortunately very little is known about the habitats and biological assemblages of the continental shelf within the network, where diversity is richest and anthropogenic pressures are greatest. Effective management of the CMR estate into the future requires this knowledge gap to be filled efficiently and quantitatively. The challenge is particularly great for the shelf as multibeam echosounder (MBES) mapping, a key tool for identifying and quantifying habitat distribution, is time consuming in shallow depths, so full coverage mapping of the CMR shelf assets is unrealistic in the medium-term. Here we report on the results of a study undertaken in the Flinders Commonwealth Marine Reserve (southeast Australia) designed to test the benefits of two approaches to characterising shelf habitats: (i) MBES mapping of a continuous (~30 km2) area selected on the basis of its potential to include a range of seabed habitats that are potentially representative of the wider area, versus; (ii) a novel approach that uses targeted mapping of a greater number of smaller, but spatially balanced, locations using a Generalized Random Tessellation Stratified sample design. We present the first quantitative estimates of habitat type and sessile biological communities on the shelf of the Flinders reserve, the former based on three MBES analysis techniques. We contrast the quality of information that both survey approaches offer in combination with the three MBES analysis methods. The GRTS approach enables design based estimates of habitat types and sessile communities and also identifies potential biodiversity hotspots in the northwest corner of the reserve's IUCN zone IV, and in locations close to shelf incising canyon heads. Design based estimates of habitats, however, vary substantially depending on the MBES analysis technique, highlighting the challenging nature of the reserve's low profile reefs, and improvements that are needed when acquiring MBES data for small GRTS locations. We conclude that the two survey approaches are complementary and both have their place in a successful and flexible monitoring strategy; the emphasis on one method over the other should be considered on a case by case basis, taking into account the survey objectives and limitations imposed by the type of vessel, time available, size and location of the region where knowledge is required.