Local Hotspots In The Gulf Of Maine: Spatial Overlap Between Dynamic Aggregations Of Primary Productivity And Fish Abundance

Identification of biological hotspots may be a necessary step toward ecosystem-based management goals, as these often signal underlying processes that aggregate or stimulate resources in a particular location. However, previously used metrics to locate these hotspots are not easily adapted to local marine datasets, in part due to the high spatial and temporal variability of phytoplankton populations. While most fish species in temperate regions are well adapted to the seasonal variability of phytoplankton abundance, it is the variability beyond this predictable pattern (i.e. anomalies) that may heavily impact the abundance and spatial distribution of organisms higher up the food chain. The objective of this study was to identify local-scale biological hotspots in a region in the western side of the Gulf of Maine using remote sensing chlorophyll-a data (from MERIS sensor), and to study the spatial overlap between these hotspots and high concentrations of fish abundance (derived from VTR dataset). For this reason, we defined a new hotspot metric that identified as a hotspot any area that consistently exhibited high-magnitude anomalies through time, a sign of highly dynamic communities. We improved on previous indices by minimizing the effect that different means and variances across space may have on the results, a situation that often occurs when comparing coastal and offshore systems. Results show a significant spatial correlation between pelagic fish abundance and aggregations of primary productivity. Spatial correlations were also significant between benthic fish abundance and primary productivity hotspots, but only during spring months. We argue that this new hotspot index compliments existing global measures as it helps managers understand the dynamic characteristics of a complex marine system. It also provides a unique metric that is easily compared across space and between different trophic levels, which may facilitate future ecosystem-wide studies.