DOI: 10.5061/dryad.280gb5ms5
title: Data from: Sampling from commercial vessel routes can capture marine biodiversity distributions effectively

description: 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. Optimising 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 under-sampled 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 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
 to 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 minimise 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, including for eDNA analyses. 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.
description: This dataset includes binary species distribution models for 43
 species of marine predators (9 mammals, 13 elasmobranchs, 20 fishes, and
 one turtle) from the Mediterranean Sea, and a binary stacked species
 distribution model showing the species richness of all marine predators.
 Models are available at 0.083° x 0.083° resolution in a WGS84 projection.
 Species distribution models were made with occurrence data collated from
 publically available data sources GBIF, OBIS, EurOBIS, and ACCOBAMS, and
 the Medlem database which is available upon request from its authors, as
 well as environmental predictors from Bio-Oracle and Marspec. Quality
 checking of occurrence records prior to modelling has been carried out
 including removal of records with GPS coordinates with fewer than three
 decimal places and duplicates between records based on the species,
 coordinates, year and month. Records were manually filtered further to
 identify records with the same species, year and month but different
 coordinates as a result of potential rounding between the different
 datasets. 
description: .tiff files can be opened with GIS software or in R using the
 raster package.