Data from: Sampling from commercial vessel routes can capture marine biodiversity distributions effectively

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.