Estimating enhanced fish production on restored shellfish reefs using automated data collection from underwater videos

Shellfish reefs across the world have been heavily degraded by mechanical harvesting, disease, and declining water quality. In southern Australia, where substantial losses have occurred, Government and non-government efforts to restore functioning reefs are now underway with a strong focus on enhancing fish productivity. However, the capacity of these restored reefs to enhance fish production remains unknown, hampering estimates of return on investment.
We quantify the density differences of newly-recruited juvenile fish and other nekton on these restored reefs, relative to those on unrestored, unstructured habitat. Fish were surveyed at three paired reef-unstructured locations using 169 unbaited stereo video deployments during three periods over 12 months (2022–2023). We used automation software, FishID, to automatically identify, size, and count fish in videos. We subsequently applied known growth and mortality parameters to model enhancement of fish productivity. 
Sixteen species occ...,
Stereo underwater cameras in two habitats: restored oyster reefs and unrestored, unstructured control habitat
Three survey periods over 12 months
FishID software automatically extracts data from videos to identify all fish (and cephalopods and crabs)
Fish sizes measured from synchronised stereo imagery, only juvenile fish counted
Area of camera field of view calculated
Counts of juvenile fish converted to densities per unit area, for each habitat for each survey period, for each species
, , # Estimating enhanced fish production on restored shellfish reefs using automated data collection from underwater videos

Experimental purpose

These data were collected to determine the difference in density of juvenile fish on restored oyster reefs relative to unrestored, unstructured control habitat at three locations in southern Australia. Stereo underwater cameras in two habitats: restored oyster reefs and unrestored, unstructured control habitat

1. Three survey periods over 12 months
2. Data automatically extracted using FishID software
3. Fish identified, sized, and counts of juvenile fish made
4. Area of camera field of view calculated, counts converted to densities per unit area

Dataset contents

* Density of juvenile fish per survey period per habitat per location for every species

## Description of the data and file structure

1. Species name (names as per Table 3 in associated published paper)
2. Survey period (first, second, third)
3. Location (Dromana, Glene...