Margaret F. J. Wilson

Bio: Margaret F. J. Wilson is an academic researcher from National University of Ireland, Galway. The author has contributed to research in topics: Terrain & Bathymetry. The author has an hindex of 1, co-authored 1 publications receiving 605 citations.

Multiscale Terrain Analysis of Multibeam Bathymetry Data for Habitat Mapping on the Continental Slope

Abstract: Multibeam surveys can provide detailed bathymetry data for the continental slope from which quantitative descriptors of the seabed terrain (e.g., slope) may be obtained. We illustrate the value of these descriptors for benthic habitat mapping, and highlight the advantages of multiscale analysis. We examine the application of these descriptors as predictor variables for species distribution models, which are particularly valuable in the deep sea where opportunities to directly survey the benthic fauna remain limited. Our initial models are encouraging and suggest that wider adoption of these methods may assist the delivery of ecologically relevant information to marine resource managers.

Benthic habitat mapping: A review of progress towards improved understanding of the spatial ecology of the seafloor using acoustic techniques

Abstract: This review examines the various strategies and methods used to produce benthic habitat maps using acoustic remote sensing techniques, coupled with in situ sampling. The applications of three acoustic survey techniques are examined in detail: single-beam acoustic ground discrimination systems, sidescan sonar systems, and multi-beam echo sounders. Over the past decade we have witnessed the nascence of the field of benthic habitat mapping and, on the evidence of the literature reviewed in this paper, have seen a rapid evolution in the level of sophistication in our ability to image and thus map seafloor habitats. As acoustic survey tools have become ever more complex, new methods have been tested to segment, classify and combine these data with biological ground truth sample data. Although the specific methods used to derive habitat maps vary considerably, the review indicates that studies can generally be categorized into one of three over-arching strategies; 1) Abiotic surrogate mapping; 2) Assemble first, predict later (unsupervised classification); 3) Predict first, assemble later (supervised classification). Whilst there is still no widely accepted agreement on the best way to produce benthic habitat maps, all three strategies provide valuable map resources to support management objectives. Whilst there is still considerable work to be done before we can answer many of the outstanding technological, methodological, ecological and theoretical questions that have been raised here, the review concludes that the advent of spatial ecological studies founded on high-resolution environmental data sets will undoubtedly help us to examine patterns in community and species distributions. This is a vital first step in unraveling ecological complexities and thus providing improved spatial information for management of marine systems.

Statistical Characterization of Altitude Matrices by Computer. Report 6. An Integrated System of Terrain Analysis and Slope Mapping.

Abstract: : A system is described which: (a) replaces existing sets of diverse terrain indices with a group of statistics for point-characteristics; (b) calculates all of these statistics in a single computer run from a single data set; and (c) utilizes available altitude matrix data The procedures are applicable to Altitude matrix data at any grid mesh From altitudes in each 3 x 3 submatrix, a quadratic surface is fitted and solved for its first and second horizontal and vertical derivatives at the central point This yields the slope gradient, slope aspect, profile convexity, and plan convexity at every point in the original matrix, except for the peripheral rows and columns These 'point' descriptors are presented as: (1) line-printer shaded maps; (2) histograms; (3) scatter plots of each pair; (4) matrix of pair-wise correlations, plus circular regressions on aspect, and several multiple regressions, and (5) summary (moment-based) statistics In general, the five basic descriptors have little relation to each other, except that gradient is usually a quadratic function of altitude A comparison is made with other approaches, such as spectral analysis and fractal modelling The long-distance persistence properties of terrain mean that considerable extra variance at long wavelengths is usually incorporated when the study area is extended Hence the auto correlation function varies with the length of series or size of area Variance of derivatives are also affected, but means, skews, and kurtoses are not

ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling

Abstract: Species distribution modeling is a valuable tool with many applications across ecology and evolutionary biology. The selection of biologically meaningful environmental variables that determine relative habitat suitability is a crucial aspect of the modeling pipeline. The 19 bioclimatic variables from WorldClim are frequently employed, primarily because they are easily accessible and available globally for past, present and future climate scenarios. Yet, the availability of relatively few other comparable environmental datasets potentially limits our ability to select appropriate variables that will most successfully characterize a species’ distribution. We identified a set of 16 climatic and two topographic variables in the literature, which we call the ENVIREM dataset, many of which are likely to have direct relevance to ecological or physiological processes determining species distributions. We generated this set of variables at the same resolutions as WorldClim, for the present, mid-Holocene, and Last Glacial Maximum (LGM). For 20 North American vertebrate species, we then assessed whether including the ENVIREM variables led to improved species distribution models compared to models using only the existing WorldClim variables. We found that including the ENVIREM dataset in the pool of variables to select from led to substantial improvements in niche modeling performance in 13 out of 20 species. We also show that, when comparing models constructed with different environmental variables, differences in projected distributions were often greater in the LGM than in the present. These variables are worth consideration in species distribution modeling applications, especially as many of the variables have direct links to processes important for species ecology. We provide these variables for download at multiple resolutions and for several time periods at envirem.github.io. Furthermore, we have written the ‘envirem’ R package to facilitate the generation of these variables from other input datasets.

Global habitat suitability for framework-forming cold-water corals.

Abstract: Predictive habitat models are increasingly being used by conservationists, researchers and governmental bodies to identify vulnerable ecosystems and species' distributions in areas that have not been sampled. However, in the deep sea, several limitations have restricted the widespread utilisation of this approach. These range from issues with the accuracy of species presences, the lack of reliable absence data and the limited spatial resolution of environmental factors known or thought to control deep-sea species' distributions. To address these problems, global habitat suitability models have been generated for five species of framework-forming scleractinian corals by taking the best available data and using a novel approach to generate high resolution maps of seafloor conditions. High-resolution global bathymetry was used to resample gridded data from sources such as World Ocean Atlas to produce continuous 30-arc second (∼1 km2) global grids for environmental, chemical and physical data of the world's oceans. The increased area and resolution of the environmental variables resulted in a greater number of coral presence records being incorporated into habitat models and higher accuracy of model predictions. The most important factors in determining cold-water coral habitat suitability were depth, temperature, aragonite saturation state and salinity. Model outputs indicated the majority of suitable coral habitat is likely to occur on the continental shelves and slopes of the Atlantic, South Pacific and Indian Oceans. The North Pacific has very little suitable scleractinian coral habitat. Numerous small scale features (i.e., seamounts), which have not been sampled or identified as having a high probability of supporting cold-water coral habitat were identified in all ocean basins. Field validation of newly identified areas is needed to determine the accuracy of model results, assess the utility of modelling efforts to identify vulnerable marine ecosystems for inclusion in future marine protected areas and reduce coral bycatch by commercial fisheries.