From Echosounders to Ecosystems: Seafloor Habitat Mapping in a Shifting Ocean Climate
Bibliographic record
Abstract
In the Northwest Atlantic (NWA), marine ecosystems have been identified as particularly vulnerable to climate change impacts, due to the region’s important effect on the Atlantic Meridional Overturning Circulation (AMOC) and to its significant role in ocean uptake of anthropogenic carbon dioxide. Climate-induced change on the distribution patterns and ranges of benthic fauna are expected, but precise prediction on how these changes will occur, or the underlying abiotic and biotic drivers of change, are mostly unknown. When faced with warming temperatures, studies have shown that many species are likely to exhibit poleward range shifts. However, the role that availability of suitable benthic habitat plays in this process is largely unknown due to a scarcity of seafloor mapping data at appropriate resolutions. This is a critical gap across studies to date examining climate impacts on benthic faunal distributions. To address this knowledge gap, a major, multi-year research program commenced in 2020, funded through the Ocean Frontier Institute (OFI): the BEcoME project – Benthic Ecosystem Mapping and Engagement (www.ofibecome.org). Through a series of inter-connected, cross-disciplinary work-packages, the BEcoME project is addressing what role benthic habitat plays in controlling shifting patterns in species and biodiversity caused by a changing ocean climate. This overarching question is being examined across spatial scales, from broad-scale geomorphology mapping over the entire NWA, to fine-scale surficial geology and benthic habitat mapping using emerging seafloor mapping technologies (e.g. multispectral multibeam) over local case study areas. This seminar will present an overview of some early results from this, and other associated projects, undertaken by the Seascape Ecology and Mapping (SEAM) Lab at Dalhousie University. Presenter Bio Dr. Craig J. Brown is an Associate Professor in the Department of Oceanography at Dalhousie University. Over the past two decades, his research has focused on studying benthic ecosystems from a geospatial perspective utilizing the latest seafloor habitat mapping methods and technologies – primarily focusing on marine acoustic remote sensing techniques. His main areas of research interest include the study of biophysical interactions in seafloor ecosystems to facilitate the development of effective fisheries and conservation management strategies. This interdisciplinary research involves spatial analysis of ecological, geological, geophysical, and oceanographic data sets to understand spatial and temporal patterns in benthic biodiversity and habitat characteristics for effective and sustainable ocean stewardship. Dr. Brown holds B.Sc. Hons in Zoology from the University of Reading (1993), and a Ph.D. in Marine Ecology from the University of Portsmouth (1998) in the UK. He held government, academic and industry positions in both the UK and Canada before joining Dalhousie University in 2019, where he now leads the Seascape Ecology and Mapping (SEAM) laboratory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".