Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?

Abstract

Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered "measured data"), but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS) to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE), observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.

Habitat-Based Density Models for Three Cetacean Species off Southern California Illustrate Pronounced Seasonal Differences

“…Also shown is the approximate 238,495 km 2 southern portion of the CalCOFI study area (hashed area encompassed by the dashed blue line) used by Douglas et al (2014) and Campbell et al (2015) to develop line-transect density estimates. The southern boundary roughly follows the Unites States/Mexico border and is consistent with that used by Becker et al (2016) to develop the summer/fall estimates used for comparison in this study.…”

“…Methods largely followed those described in Becker et al (2016), but pertinent aspects are summarized here. Restricted maximum likelihood (REML) was used to optimize the parameter estimates as Marra and Wood (2011) found REML to perform better than generalized cross validation.…”

“…The dynamic predictors are served at 10 km spatial resolution (i.e., 100 km 2 ). We used 8-day running average composites centered on the date of each survey segment to provide consistent representation of average survey-day conditions and to ensure consistency with the Becker et al (2016) summer/fall habitat models. Both the "UCSC ROMS reanalysis" and the "UCSC ROMS near-real-time" (2011)(2012)(2013)(2014)(2015) outputs were used.…”

“…Using a well-established Generalized Additive Modeling (GAM) framework, models were fit for three taxonomically diverse species with sufficient sample sizes for modeling: shortbeaked common dolphin (Delphinus delphis delphis), Dall's porpoise (Phocoenoides dalli), and humpback whale (Megaptera novaeangliae). Habitat variables included both static and dynamic predictors shown to be important in previous SDMs (e.g., Becker et al, 2014Becker et al, , 2016Hazen et al, 2016). Modelpredicted density surface plots captured observed distribution patterns for all three species and revealed unique areas of high density within the study area.…”

“…As part of marine mammal and ecosystem assessments, systematic surveys have been conducted in the California Current since 1991, and these data have been used to develop SDMs for many of the cetacean species known to occur in this region (Forney, 2000;Barlow et al, 2009;Becker et al, 2010Becker et al, , 2012Becker et al, , 2014Becker et al, , 2016Forney et al, 2012;Redfern et al, 2013). Density predictions from these models have been used by the U.S. Navy to assist in the evaluation of potential impacts on cetaceans (U.S. Department of the Navy, 2015), to assess overlap between fisheries and cetaceans (Saez et al, 2013;Feist et al, 2015), and to evaluate potential ship-strike risk to large whales in waters off Southern California (Redfern et al, 2013).…”