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PRODID:-//University of Iceland//AI Centre//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
UID:cd739add-c845-48c4-b99b-a788ee9f3afd@ai.hi.is
DTSTAMP:20261025T155645Z
DTSTART:20260922T090000Z
DTEND:20260922T100000Z
SUMMARY:Modelling the spatiotemporal growth dynamics of Haddock in Icelandi
 c waters in RTMB
DESCRIPTION:Growth is central to stock productivity and as such reliable es
 timates of growth are essential for assessing fish stocks\, modelling ecos
 ystems and developing science-based management plans. This thesis develops
  a hierarchical spatio-temporal von Bertalanffy growth model (VBGF) for Ic
 elandic haddock (Melanogrammus aeglefinus)\, implemented in RTMB. Asymptot
 ic length (L∞)\, growth rate (k)\, and theoretical age at zero length (t
 ₀) are estimated jointly as correlated latent Gaussian random fields\, w
 ith a non-stationary barrier SPDE constraining spatial correlation across 
 Iceland's fragmented coastline\, natural cubic splines for bottom temperat
 ure and depth\, and a covariate for early-life nursery density. Individual
  length-at-age observations from the MFRI spring and autumn groundfish sur
 veys (1985–2025) were used for fitting and validation.\n\nNine candidate
  models were compared sequentially by AIC. The best-fitting model combined
  correlated AR(1) spatio-temporal fields on L∞ and k. Spatial and inter-
 annual structure accounted for larger improvements in fit than the measure
 d environmental and density covariates combined. Estimated mean asymptotic
  length was 76.0 cm (spring) and 77.1 cm (autumn)\, with growth rates of 0
 .247 yr⁻¹ and 0.235 yr⁻¹. Nursery density was negatively associated 
 with growth rate\, reducing it by up to 15% across its observed range\, an
 d bottom temperature was positively associated with growth rate across the
  full range sampled. L∞ and k were strongly negatively correlated at bot
 h the baseline spatial scale (−0.932) and the inter-annual scale (−0.9
 62)\, describing faster growth to a smaller asymptotic size inshore and sl
 ower growth to a larger asymptotic size offshore.\n\nThe model predicted l
 ength-at-age accurately under spatial interpolation (R² = 0.913–0.937) 
 and temporal forecasting beyond the training period (R² = 0.920–0.942).
  Forecast accuracy varied by year and declined over the later forecast hor
 izon\, consistent with the estimated two-to-three-year temporal persistenc
 e. The results show that haddock growth in Icelandic waters is spatially a
 nd temporally varying but predictable.\n\nhttps://ai.hi.is/is/events/collo
 quium-in-statistics-and-ai-22/
LOCATION:Íslensk erfðagreining\, Tjarnarsalur
URL:https://ai.hi.is/is/events/colloquium-in-statistics-and-ai-22/
STATUS:CONFIRMED
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