Abstract:Se analizaron 96 puntos de muestreo realizados a bordo del B/O Miguel Oliver, desde el 3 de enero hasta el 3 de febrero del 2011. En cada punto se llevaron a cabo faenas de pesca de arrastre utilizando una red Lofoten. Los arrastres de 30 minutos de duración cada uno se efectuaron en 25 transectos equidistantes y divididos en estratos según la profundidad local, hasta un máximo de 1500 m. Se encontraron y analizaron un total de 142 especies de peces óseos y cartilaginosos (n = 28 074) pertenecientes a 73 famil… Show more
“…Luminous Hake is a gadiform codfish found in the Gulf of Mexico and Caribbean Sea (Cohen et al, 1990) and is a diurnal vertical migrant. Daytime surveys have recorded Luminous Hakes at depths from ~200 to ~1300 m (Benavides‐Morera & Campos‐Calderón, 2018); nighttime surveys have recorded Luminous Hakes at depths from ~30 to ~190 m (Love et al, 2004). We downloaded occurrence data via R OBIS (http://obis.org, 24 September 2020 via robis, Provoost & Bosch, 2019) and GBIF (http://gbif.org, 24 September 2020 via rGBIF, Chamberlain et al, 2021) via occCite (Owens et al, 2021).…”
Section: Example: Potential Distribution Of Luminous Hakementioning
Ecological niche modelling (ENM), species distribution modelling and related spatial analytical methods were first developed in two‐dimensional (2‐D) terrestrial systems; many common ENM workflows organize and analyse geographically structured occurrence and environmental data based on 2‐D latitude and longitude coordinates. This may be suitable for most terrestrial organisms, but pelagic marine species are distributed not only horizontally but also vertically. Extracting environmental data for marine species based only on latitude and longitude coordinates may result in poorly trained ENMs and inaccurate prediction of species' geographical distributions, as water conditions may vary strikingly with depth.
We developed the voluModel R package to efficiently extract three‐dimensional (3‐D) environmental data for training ENMs (i.e. presences and absences/pseudoabsences/background). voluModel also provides tools for 3‐D ENM projection visualization and estimation of model extrapolation risk.
We present the main features of the voluModel R package and provide a simple modelling workflow for Luminous Hake, Steindachneria argentea, as an example. We also compare results from 2‐D and 3‐D spatial models to demonstrate differences in how the modelling methods perform.
The use of 3‐D environmental data generates more precise estimates of environmental conditions for training ENMs. This method also improves inference of species' suitable abiotic ecological niches and potential geographic ranges. 3‐D niche modelling is important step forward for marine macroecology and biogeography, as it will yield more accurate estimates of ocean species richness and potential past and future changes in the horizontal and vertical dimensions of species' geographic ranges. The latter is particularly relevant considering ongoing climate change that may cause redistribution of species in environmental space (both in latitude and depth) over time.
“…Luminous Hake is a gadiform codfish found in the Gulf of Mexico and Caribbean Sea (Cohen et al, 1990) and is a diurnal vertical migrant. Daytime surveys have recorded Luminous Hakes at depths from ~200 to ~1300 m (Benavides‐Morera & Campos‐Calderón, 2018); nighttime surveys have recorded Luminous Hakes at depths from ~30 to ~190 m (Love et al, 2004). We downloaded occurrence data via R OBIS (http://obis.org, 24 September 2020 via robis, Provoost & Bosch, 2019) and GBIF (http://gbif.org, 24 September 2020 via rGBIF, Chamberlain et al, 2021) via occCite (Owens et al, 2021).…”
Section: Example: Potential Distribution Of Luminous Hakementioning
Ecological niche modelling (ENM), species distribution modelling and related spatial analytical methods were first developed in two‐dimensional (2‐D) terrestrial systems; many common ENM workflows organize and analyse geographically structured occurrence and environmental data based on 2‐D latitude and longitude coordinates. This may be suitable for most terrestrial organisms, but pelagic marine species are distributed not only horizontally but also vertically. Extracting environmental data for marine species based only on latitude and longitude coordinates may result in poorly trained ENMs and inaccurate prediction of species' geographical distributions, as water conditions may vary strikingly with depth.
We developed the voluModel R package to efficiently extract three‐dimensional (3‐D) environmental data for training ENMs (i.e. presences and absences/pseudoabsences/background). voluModel also provides tools for 3‐D ENM projection visualization and estimation of model extrapolation risk.
We present the main features of the voluModel R package and provide a simple modelling workflow for Luminous Hake, Steindachneria argentea, as an example. We also compare results from 2‐D and 3‐D spatial models to demonstrate differences in how the modelling methods perform.
The use of 3‐D environmental data generates more precise estimates of environmental conditions for training ENMs. This method also improves inference of species' suitable abiotic ecological niches and potential geographic ranges. 3‐D niche modelling is important step forward for marine macroecology and biogeography, as it will yield more accurate estimates of ocean species richness and potential past and future changes in the horizontal and vertical dimensions of species' geographic ranges. The latter is particularly relevant considering ongoing climate change that may cause redistribution of species in environmental space (both in latitude and depth) over time.
Corales de Profundidad National Natural Park (CPNNP), at the central Colombian Caribbean margin, has an extension of 142.195 ha with depths ranging from 34 to 1,234 m. The CPNNP’s essential ecological value is Madracis spp. as potential structure-forming deep-water coral; this work represents the first footages of these unique habitats for the Colombian Caribbean. In 11 sectors, remote video surveys are conducted, based on a detailed digital elevation model. From these sectors, four cover mesophotic zones (46–169m depth), and seven cover aphotic zones (up to 354m depth). After still images’ description and interpretation, a guide was generated with nine types of macrohabitats surrounding the coral formations of the CPNNP: soft substrate (mud/sand), soft substrate/rubble/rock with solitary corals, coral and shell rubble, rock/ledges with attached fauna, rugged stones with attached fauna, hard substrate with attached fauna, sandstone with attached fauna, soft substrate with burrows, and pockmark with attached fauna. Video transect analysis confirms the occurrence of Madracis spp., with coral patches as the main framework builder of the CPNNP. These patches comprise many clumped 50 to 80 cm high coral colonies that developed over slow slopes, with seafloor elevations between 107 and 233 m and textured soils of soft and not very compact ridges, associated with the macrohabitat sandstone with attached fauna. This information is being used for the management and monitoring of this unique protected area.
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