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April 2024
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MAPPING QUEEN SNAPPER
(ETELIS OCULATUS) SUITABLE HABITAT
IN PUERTO RICO USING ENSEMBLE SPECIES DISTRIBUTION MODELING
By Kate Overly, Fishery Biologist
This work tackles the challenge of predicting areas of suitable habitat for queen snapper, and by extension, mapping their potential distribution around Puerto Rico. Queen snapper are vital to Puerto Rico's marine ecosystems, supporting both commercial and recreational fisheries and the ecological balance in the ocean.
This article is a summary of the research titled “Mapping queen snapper (Etelis oculatus) suitable habitat in Puerto Rico using ensemble species distribution modeling”.
Fig 1 Queen snapper, Etelis oculatus
A queen snapper near a rocky outcrop off the coast of Puerto Rico.
Photo credit: NOAA Ocean Exploration
Habitat suitability refers to the degree to which a particular area provides the environmental conditions necessary for a species to survive, grow, and reproduce. It is a measure of how well a habitat meets the needs of a species. Information such as this is necessary for determining essential fish habitat or EFH, which is defined by Magnuson-Stevens Fishery Conservation and Management Act as waters and substrate necessary for fish spawning, breeding, feeding or growth to maturity. The first step of determining EFH for a species requires knowledge of their basic distribution for at least some of its geographic range.
The current understanding of queen snapper suitable habitat and distribution in Puerto Rico is limited, which hinders the development of informed management plans, determination of EFH, and thus long-term biological and economic sustainability of the fishery in the region. The limited data stems from the high cost and extensive time it would take to sample every possible location
queen snapper might be. Species distribution modeling has emerged as a powerful tool to predict where fish are likely to live based on factors like depth, type of habitat (such as reef or sandy bottom), and the attributes that make a habitat important such as steepness of terrain, size and complexity.
In this study, we utilized locations where queen snapper were caught, depth, and other habitat attributes derived from seafloor mapping. We then created computer models that depict where suitable habitat for queen snapper is likely to be found based on the environmental conditions they may prefer. We used a more advanced approach called ensemble species distribution modeling, which combines multiple different models rather than a single model to create even more accurate maps and generate a measure of uncertainty in the predictions. Our main goal through the
Fig 2 Deepwater finfish landings in Puerto Rico
Total Puerto Rico commercial landings, in pounds (lbs), by year for the top five reef-associated finfishes, spiny lobster, and queen conch
modeling was exploratory in nature as we sought to identify areas where queen snapper habitat suitability is predicted to be high (≥ 85% probability) and which habitat attributes may influence the species presence and potential distribution.
Depth was the most important predictor of queen snapper suitable habitat. Our models predicted ≥ 85% suitable habitat presence probability in depths ranging from 160–429 m (87–235 ftm) island-wide in Puerto Rico, with the average depth of 326–333 m (178–182 ftm), depending on region.
3. Region-specific binary habitat maps.
A binary index of habitat suitability for queen snapper on the A) west, B) northeast, and C) southeast region of Puerto Rico, where habitat suitability >85% = 1 and <85% = 0. Red points denote habitat suitability = 1, and the black outline denotes the sampling area explored. Total suitable habitat area (km2) out of total sampling frame area (km2), and percentage of total suitable habitat in lower left corner of each figure.
With limited direct environmental variables such as salinity and benthic water temperature available, we used surrogate terrain attributes to assist with better understanding the distribution and complexity of marine habitats around Puerto Rico. Surrogate terrain attributes included variables such as rugosity, slope,
Fig
curvature, raspect and benthic position index. These variables are derived from bathymetry, or depth data, collected via seafloor mapping and can serve as indicators to potentially describe overall benthic habitat conditions such as optimal food availability, refuge for juveniles, appropriate temperatures, favorable currents or salinity levels.
Variable
Rugosity
Slope
Curvature
Aspect
Benthic Position Index (BPI)
Explanation
A measure of how bumpy or rough the surface of the ocean floor is
The angle at which the ocean floor rises or falls.
How the shape of the ocean floor changes over short distances, this tells us whether the seafloor is bending upwards (like a hill) or downwards (like a valley).
The direction that a slope on the ocean floor faces (north, south, etc.).
The relative position of a point on the seafloor compared to its surrounding area, which helps us understand if a point is located at the top of a broad underwater feature (like a ridge or plateau), at the bottom of a larger depression (like a basin), or somewhere in between.
Several of the terrain attributes derived from bathymetry were found to be important in determining whether or not habitat was suitable. Queen snapper suitable habitat was positively associated with areas of moderate to high slope, with low to moderate rugosity habitat, and adjacent to features that are higher than the surrounding area (e.g., ridge-like features) and seamounts. These areas likely retain dense zooplankton populations due to upwelling from deeper depths, which in turn attracts larger predators such as the queen snapper. When combined, terrain attributes can be linked to an environmental parameter such as food availability,
Table 1. Terrain attributes derived from bathymetry data.
which is difficult to directly calculate. The resulting models depicted localized hot spots adjacent to Desecheo, Bajo de Sico, and Whiting and Grappler seamount, all areas of moderate to steep slope and rugosity often associated with harder substrates. Queen snappers were also predicted to be present in close proximity to elevated ridge features throughout the west and northeast coast and were specifically predicted to be on areas lower than the surrounding area, such as depressions and valleys on the northeast and southeast coast.
Fig 4. Region-specific presence probability maps. Queen snapper habitat suitability maps for the A) west, B) northeast, and C) southeast region of Puerto Rico
Our results demonstrate that seafloor characteristics function as effective predictors for queen snapper distribution across deepwater habitats. Our goal was to develop models and corresponding maps to be used as a tool to identify potential areas where queen snapper, a commercially and ecologically important species in the study regions, may reside when intensive field sampling may be cost-prohibitive. Our results complement the limited knowledge that queen snapper can be found near oceanic islands and reefs on the continental shelf and upper slope, and also serve to broaden our understanding of the spatial extent of queen snapper and highlight hotspots for potential management concerns such as EFH for the species.
The author is a Fisheries Biologist in the Gulf and Caribbean Reef Fish Branch in the Population and Ecosystem Monitoring Division at NOAA Fisheries. You can visit https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0298755 to access the full study.
GLOSSARY
bathymetry - The study of the "beds" or "floors" of water bodies, including the ocean, rivers, streams, and lakes.
benthic - Occurring at the marine bottom.
essential fish habitats - These are the areas necessary for the reproduction, growth, feeding and shelter of fish. This includes: estuaries and river mouths, sandy bottoms, mangroves, seagrass beds, and coral reefs, both shallow and mesophotic.
zooplankton - A group of tiny animal organisms that drift and live on the surface and in the water column.
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