A matter of scale: Identifying the best spatial and temporal scale of environmental variables to model the distribution of a small cetacean

The importance of scale when investigating ecological patterns and
processes is recognised across many species. In marine ecosystems, the
processes that drive species distribution have a hierarchical structure
over multiple nested spatial and temporal scales. Hence, multi-scale
approaches should be considered when developing accurate distribution
models to identify key habitats, particularly for populations of
conservation concern. Here, we propose a modelling procedure to identify
the best spatial and temporal scale for each modelled and remotely sensed
oceanographic variable to model harbour porpoise (Phocoena phocoena)
distribution. Harbour porpoise sightings were recorded during dedicated
line-transect aerial surveys conducted in the summer of 2016, 2021 and
2022 in the Northeast Atlantic. Binary generalised additive models were
used to assess the relationships between porpoise presence and
oceanographic variables at different spatial (5, 20 and 40 km) and
temporal (daily, monthly and across survey period) scales. Selected
variables included sea surface temperature, thermal fronts, chlorophyll-a,
sea surface height, mixed layer depth and salinity. A total of 30,514 km
was covered on-effort with 216 harbour porpoise sightings recorded.
Overall, the best spatial scale corresponded to the coarsest resolution
considered in this study (40 km), while porpoise presence showed stronger
association with oceanographic variables summarised at a longer temporal
scale (monthly and averaged over survey period). Habitat models
including covariates at coarse spatial and temporal scales may better
reflect the processes driving availability and abundance of prey resources
at the large scales covered during the surveys. These findings support the
hypothesis that a multi-scale approach should be applied when
investigating species distribution. Identifying suitable spatial and
temporal scale would improve the functional interpretation of the
underlying relationships, particularly when studying how a small marine
predator interacts with its environment and responds to climate and
ecosystem changes.