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Sampling from commercial vessel routes can capture marine biodiversity distributions effectively
by
Beger, Maria
, Boyse, Elizabeth
, Valsecchi, Elena
, Goodman, Simon J.
in
Accuracy
/ Bias
/ biased sampling frames
/ Biodiversity
/ Biogeography
/ cetaceans
/ Conservation Ecology
/ Datasets
/ Environmental DNA
/ Ferries
/ Geographical distribution
/ marine megafauna
/ Megafauna
/ Protected areas
/ Sampling
/ Spatial Ecology
/ Species composition
/ species distribution models
/ Species richness
/ Surveys
/ Taxonomy
/ Variability
/ Vessels
/ Workflow
2023
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Sampling from commercial vessel routes can capture marine biodiversity distributions effectively
by
Beger, Maria
, Boyse, Elizabeth
, Valsecchi, Elena
, Goodman, Simon J.
in
Accuracy
/ Bias
/ biased sampling frames
/ Biodiversity
/ Biogeography
/ cetaceans
/ Conservation Ecology
/ Datasets
/ Environmental DNA
/ Ferries
/ Geographical distribution
/ marine megafauna
/ Megafauna
/ Protected areas
/ Sampling
/ Spatial Ecology
/ Species composition
/ species distribution models
/ Species richness
/ Surveys
/ Taxonomy
/ Variability
/ Vessels
/ Workflow
2023
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Do you wish to request the book?
Sampling from commercial vessel routes can capture marine biodiversity distributions effectively
by
Beger, Maria
, Boyse, Elizabeth
, Valsecchi, Elena
, Goodman, Simon J.
in
Accuracy
/ Bias
/ biased sampling frames
/ Biodiversity
/ Biogeography
/ cetaceans
/ Conservation Ecology
/ Datasets
/ Environmental DNA
/ Ferries
/ Geographical distribution
/ marine megafauna
/ Megafauna
/ Protected areas
/ Sampling
/ Spatial Ecology
/ Species composition
/ species distribution models
/ Species richness
/ Surveys
/ Taxonomy
/ Variability
/ Vessels
/ Workflow
2023
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Sampling from commercial vessel routes can capture marine biodiversity distributions effectively
Journal Article
Sampling from commercial vessel routes can capture marine biodiversity distributions effectively
2023
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Overview
Collecting fine‐scale occurrence data for marine species across large spatial scales is logistically challenging but is important to determine species distributions and for conservation planning. Inaccurate descriptions of species ranges could result in designating protected areas with inappropriate locations or boundaries. Optimizing sampling strategies therefore is a priority for scaling up survey approaches using tools such as environmental DNA (eDNA) to capture species distributions. In a marine context, commercial vessels, such as ferries, could provide sampling platforms allowing access to undersampled areas and repeatable sampling over time to track community changes. However, sample collection from commercial vessels could be biased and may not represent biological and environmental variability. Here, we evaluate whether sampling along Mediterranean ferry routes can yield unbiased biodiversity survey outcomes, based on perfect knowledge from a stacked species distribution model (SSDM) of marine megafauna derived from online data repositories. Simulations to allocate sampling point locations were carried out representing different sampling strategies (random vs regular), frames (ferry routes vs unconstrained), and number of sampling points. SSDMs were remade from different sampling simulations and compared with the “perfect knowledge” SSDM to quantify the bias associated with different sampling strategies. Ferry routes detected more species and were able to recover known patterns in species richness at smaller sample sizes better than unconstrained sampling points. However, to minimize potential bias, ferry routes should be chosen to cover the variability in species composition and its environmental predictors in the SSDMs. The workflow presented here can be used to design effective sampling strategies using commercial vessel routes globally for eDNA and other biodiversity survey techniques. This approach has potential to provide a cost‐effective method to access remote oceanic areas on a regular basis and can recover meaningful data on spatiotemporal biodiversity patterns.
Commercial vessels as sampling platforms can accurately capture species distribution patterns, despite inherent biases associated with constrained spatial coverage. Our workflow can be applied across the global shipping network to upscale sampling using techniques such as environmental DNA to reduce gaps in marine biodiversity knowledge.
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