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Polygons of BS benthos

16. Polygons of BS benthos. 58. 8. Spec. Bio 50. Data background per polygon. Is the number of communities depended on number of stations in each of the polygons. Is the number of species depended on the number of stations within each polygon ?.

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Polygons of BS benthos

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  1. 16 Polygons of BS benthos 58 8

  2. Spec. Bio 50

  3. Data background per polygon

  4. Is the number of communities depended on number of stations in each of the polygons

  5. Is the number of species depended on the number of stations within each polygon ?

  6. Is the mean biomass depended on number of stations within each polygon

  7. Is the mean abundance depended on the number of stations in each polygon

  8. Is the number of species depended on number of communities in each polygon

  9. Does coastal polygons have more communities than bank and open-sea polygons ?

  10. Does the number of communities depends on the depth ?

  11. Where do we find the largest “bodies”

  12. Where do we find the largest biomass

  13. Where do we find the highest abundances

  14. What to do Polygon (within and between comparisons) Species history (within and between species)

  15. Gradients (within and between polygons) • Trawl impact on community structure and complexity • Snow-King crab impact on community structure and complexity • Temperature impact on community structure and complexity

  16. Social-ecological system delivering ecosystem goods and services Disturbed end-member community High stability and low lifespan turnover Low stability and high lifespan turnover Key sp. w. important functions Resilience of an degraded community often makes it difficult for the system to return to its previous, non-degraded state limiting the potential for restoration. Deep-burrowing and bioturbating taxa What's the indicator species Dying out Regime shift Along a gradient or in time Basin of attraction depth ? Basin of attraction depth? Threshold, step-trends, critically rapid transition, tipping point Recovery (engineering resilience)

  17. Teories • Large organisms represent “k-selective” specimens (biomass is important) • Many, small organisms represent “r-selective” specimens (A and B is important) • Cumulative species history represent the “status” (Species number is important) Hypothesis: stations with high degree of trawl impact has low “1”, high “2” and low “3” and visa versa (another history for king/snow crab)

  18. How to present the results ? • Colour polygons according to results • Is there any consistence or pattern ? • Does the species history tell why ? • Temperature “impact” • Impact from invasive top predators • Fishing impact .......

  19. VMS and fishing impact • Vessel Monitoring System • Introduced in Norway in 2000 • All fishing vessels > 15 m (since 2010) • Date, time, vessel, position, speed, heading • Hourly resolution • VMS data = proxy for trawling impact?

  20. The ATLANTIS polygons

  21. VMS data from one year: 2006

  22. Filtered by vessel speed: 2-5 knots

  23. Red dots: assumption of trawling

  24. VMS data joined to polygons

  25. Symbolised by vms position counts, ≈ for total no. of hrs trawled

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