Modeling Bowhead Whale Habitat Integration of Ocean Models

Modeling Bowhead Whale Habitat: Integration of Ocean Models with Satellite, Biological Survey and Oceanographic Data Dan Pendleton, NOAA / NEAq Jinlun Zhang, Univ. Washington Elizabeth Holmes & Megan Ferguson, NOAA

Western Arctic Bowhead Whales Photo: Hopcroft Photo: Brenda K. Rone, NOAA/AFSC/NMML

Research Goals • Map bowhead whale potential habitat suitability throughout their summer range • 25 years aerial survey data • Arctic ocean model output • Satellite data: Pathfinder, NSIDC-0051: MODIS, Sea. Wi. FS • P-PA species distribution models • Phase 1: Hindcast from 1988 – 2012 • Phase 2: Forecast by forcing ocean model with future climate scenarios Photo: Brenda K. Rone, NOAA/AFSC/NMML

Hypotheses & Questions • Proof of concept: Can we provide reasonable representations of bowhead whale habitat? • Is the spatial resolution of satellite and modeled data sufficient? • Measure relative importance of biotic vs abiotic environmental variables • Spatial & temporal model transferability: – yes or no • SDM comparison: – Max. Ent vs BRT

BIOMAS Arctic Ocean Model • Biology/Ice/Ocean Modeling Assimilation System • 3 D, Pan-Arctic • Highest resolution in Beaufort and Chukchi seas • Hourly estimates from 19882013, forecast to 2050 • Estimates zooplankton concentrations • Provides a good representation of inter-annual variability in ice, chl and temperature Model spatial resolution Zhang et al. , 2010, JGR V 115, C 10015

Study region CHUKCHI BEAUFORT Clarke, J. T. et al. (2013) OCS Study BOEM 2013 -00117. NMML

Data layers Bowhead whale sightings Week 1 t 1 Week 2 Max. Ent & BRT Habitat Map 1 Habitat Map 2 Time t 2 Week N Models t. N Habitat Map N Overlay whale sightings and evaluate habitat maps

Aug 21 -28 Aug 29 -Sep 5 Sep 6 -13 Sep 14 -21 • Train with years 19881994 & 1996 -2012 • Tested with independent data from 1995 • Based upon • Depth • Zooplankton • Temperature • Ice Maximum Entropy Sep 22 -29 Modeled Potential Habitat with Max. Ent and BRT Boosted Regression Tree

Max. Ent and BRT model performance Max. Ent AUC = 0. 81 BRT AUC = 0. 82

Percent Contribution Variable Importance for models trained with all years Depth Ice Temperature Zooplankton

Variable importance changes Boosted Regression Tree Percent Contribution Maximum Entropy Year

Spatial Transferability: 2008 - 2012 TEST TRAIN Beaufort Sea Chukchi Sea ALASKA TRAIN TEST Chukchi Sea Beaufort Sea ALASKA

BIOMAS Futurecast: anomalies relative to 1988 -2012 2015 2020 2025 2030 2035 2040 2045 2050

Forecasted Potential Whale Habitat Anomalies in the Beaufort Sea Boosted Regression Tree Early year model (1988 -1996) Late year model (1997 -2012) Maximum Entropy Month

Summary • Reasonable representations of hindcasted bowhead whale habitat suitability • Variable importance changes with time • Models are not transferable in space • SDM forecasts suggest that the Beaufort Sea will become a more habitable place for bowhead whales

What’s left? • Incorporate acoustic detections • Analysis of forecasted spatial patterns • Marine Model Mapper results outlet

Carl Buell Art