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Dynamic occupancy modeling of temperate marine fish in area-based closures
Jay Calvert1, Chris McGonigle1, Suresh Andrew Sethi2,3
1School of Geography & Environmental Science University of Ulster Coleraine UK.
Species distribution models often underestimate marine species occupancy by ignoring detectability. This study developed a dynamic occupancy model for cusk, accounting for environmental factors like current speed and algae cover, revealing higher occupancy than previously observed.
Area of Science:
- Marine Ecology
- Population Modeling
- Conservation Biology
Background:
- Species distribution models (SDMs) are widely used for marine species but often fail to account for detectability, leading to underestimated occupancy.
- Site occupancy models (SOMs) address this by modeling occupancy as a latent variable and incorporating detection submodels.
- Dynamic occupancy models (DOMs) are rarely applied to marine fish, and never for multiseason analyses.
Purpose of the Study:
- To develop and apply a multiseason dynamic occupancy model (DOM) for the cusk (Brosme brosme), a species of conservation concern.
- To incorporate detectability as a function of environmental variables, specifically current speed and algae cover, into the DOM.
- To compare model-estimated occupancy with direct observations to highlight the impact of detectability on occupancy estimates.
Main Methods:
- A dynamic occupancy model (DOM) was developed for cusk over a four-season period.
- A high-resolution 3D hydrodynamic model was used to estimate current speed.
- Seabed video surveys quantified algae cover, categorizing the study area into regions with and without canopy-forming algae.
Main Results:
- Modeled estimates of cusk site occupancy were significantly higher (0.88, 0.45, 0.74, 0.83) than those from video observations (0.57, 0.28, 0.43, 0.57) across seasons.
- Cusk detection probability varied with current speed and bottom type: higher detection with increased current in non-canopy areas, lower detection in canopy areas.
- Hydrodynamic modeling and habitat data improved occupancy estimates by accounting for detection probability.
Conclusions:
- Incorporating detectability into species distribution models is crucial for accurate marine species occupancy estimation.
- Dynamic occupancy models, utilizing environmental data like hydrodynamics, can correct for underestimation bias in traditional methods.
- This approach is vital for effective conservation and management of marine species, especially when using low-impact sampling methods.
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