The influence of environmental parameters on the distribution of Dolly Varden in the Beaufort Sea A remote sensing approach, using Landsat 8 and Sentinel 2 data from 2013 to 2019
Bibliographic record
Abstract
The spatial and temporal heterogeneity of ecosystems plays an important role in species distribution and ecosystem dynamics (Kovalenko et al., 2012). The physical and biochemical properties of the waters of the Mackenzie Shelf in the Beaufort Sea are strongly influenced by the eponymous river and its discharge plume, occasionally causing strong salinity, temperature, and turbidity gradients (Brenkman et al., 2007; Swanson & Kidd, 2009; Jensen et al., 2014), thus affecting the distribution of economically and culturally important organisms, among others. Clarifying how the physical characteristics of marine habitats influence the relative abundance and demographic characteristics of anadromous fishes has an important bearing on management and conservation objectives. The objective of this study was to examine how the timing and catch of Dolly Varden in the nearshore summer subsistence fishery are affected by environmental conditions in the Beaufort Sea. In addition, we examined whether there is a relationship between environmental parameters and the demographic and somatic characteristics of the Dolly Varden caught. \nThe study analysed fisheries-dependent data from two different study sites (Herschel Island and Shingle Point, Yukon Territory, Canada) from 2013 to 2019. Remotely sensed environmental parameters of temperature, chlorophyll-a, turbidity, and sea ice were derived from Landsat-8 and Sentinel-2 imagery and examined along with wind vectors. To provide information on how Dolly Varden abundances respond to stochastic environmental events in marine waters. \nMeasured environmental parameters show that aggregation of Dolly Varden on Herschel Island is spatially correlated with increased chlorophyll-a as well as SST. Stochastic turbidity events showed a negative influence, causing specimens to seek spatial refuge in better water conditions. Results showed similar correlations for SPT, although the parameters here are much more difficult to differentiate due to the high suspended sediment concentration (CDOM). \nData obtained from this study indicate that the geographic distribution of Dolly Varden in the Beaufort Sea is dependent on condition and osmoregulation (age/length). In marine waters, adult individuals are clearly influenced by stochastic environmental events (temperature and turbidity), opportunistically seeking out production hotspots for feeding (sea ice and chlorophyll-a).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".