Determining population status to inform mitigation of anthropogenic threats requires statistical approaches that investigate spatial and temporal variation. In the face of climate change it is increasingly important to differentiate between changes in population size and redistributions of populations. This is especially true for wide-ranging species such as the blue whale. Abundance of eastern North Pacific blue whales has previously been estimated using (non-spatial) closed capture–recapture and distance sampling methods, but the estimates show opposite and diverging trends over the last 30 years. Evidence that the distribution has been expanding could explain the apparent disparity, due to the confounding effects of spatial variation in sampling and the changing distribution. To investigate this, we apply, for the first time, spatial capture–recapture (SCR) methods to blue whale photo-identification data from small boat surveys to estimate abundance. The study area was defined as the length of the continental USA coastline, extending approximately 100 km offshore. Average annual effort from 1991 to 2023 was 97 days, resulting in 7358 sightings of 1488 unique individuals. We find significant support for non-linear spatiotemporal variation. In all years, there were higher densities at lower latitudes but there were notable decadal cyclical fluctuations in the number of animals using the study area. This large variation in the numbers of animals using these waters motivates further study into the relationship with environmental changes. Our results are an important step in spatially explicit modelling of observational blue whale data, which highlight the value of including spatial and temporal data and are relevant to any marine mammal species monitored using photo-identification.
Citation:
Whittome, G., J. Calambokidis, P.S. Hammond, S. Smout, and C. Sutherland. 2025. Using Spatial Capture-Recapture Methods to Estimate Long-Term Spatiotemporal Variation of a Wide-Ranging Marine Species. Ecography 2025: e07878. doi: 10.1002/ecog.07878
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