Final Technical Report: - Southwest Fisheries Science Center - NOAA

5.0 Conclusion
The field of predictive modeling of cetacean density has advanced considerably during
the past few years, in part as a result of our research presented in this report and associated
publications (Appendix C). Several new lines of research on model methodology, effects of
scale, inclusion of mid-trophic data, comparison of remotely sensed vs. in situ data, and seasonal
predictive capabilities have provided a robust set of predictive models for cetaceans within a
broad region of the eastern Pacific Ocean, spanning both temperate and tropical waters. Our
research has confirmed that generalized additive models offer a robust framework for predictive
modeling of cetacean density, as long as sufficient observations of each species are available and
the surveys adequately characterize the full range of oceanographic variability. Models derived
from either in situ or remotely sensed environmental data (or a combination thereof) were able to
predict cetacean occurrence patterns within the highly dynamic California Current Ecosystem,
although a few species were clearly better characterized by one type of data or the other (e.g.
striped dolphins in the CCE were better modeled using the remotely sensed data). The use of
remotely sensed data will be important for expanding models to include seasonal predictive
capabilities as additional years of data become available. Our studies also confirmed that the
inclusion of variables related to the abundance of mid-trophic species from net-tow and acoustic
backscatter data can improve habitat models for several species in both the ETP and CCE.
As with all research, there is continued room for improvement and expansion of
predictive cetacean density models. The Spatial Decision Support Software (SDSS) produced
through our research provides users with long-term seasonal average cetacean densities (and
uncertainty therein) within any user-specified polygon, based on the range of environmental
conditions and species occurrence patterns observed during nearly two decades of SWFSC
surveys. While this represents a significant improvement over the previous, constant-density
estimates from broad-scale line-transect surveys, a logical next step in model development will
be to identify methods of near real-time density prediction based on current or projected
oceanographic conditions.
This 'next-generation' of models will likely build upon recent advances in processing and
integrating remotely sensed data, ship reports, and buoy data to create new habitat indices and
ocean circulation models. Such synoptic measures may improve accuracy of models, allow
forecasting based on modeled oceanographic conditions, or allow prediction of oceanographic
variables on finer temporal and spatial scales. It may also be possible to develop analytical
methods of incorporating alternative data types, such as small-scale line-transect survey, tagging,
opportunistic, and acoustic data, into the building and validation of cetacean-habitat models.
Currently, the models are based on large-scale line-transect surveys that are limited by weather,
funding, and logistics. Expansion of the models to include alternative data types would help
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