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Temporal Distribution and Multi-scale Habitat Preference Analyses for Azorean Blue Whales

Authors:

Abstract

Blue whales are sighted every year around the Azores islands, which apparently provide an important seasonal foraging area. In this study we aim to characterize habitat preferences and analyse the temporal distribution of blue whales around São Miguel Island. To do so, we applied Generalized Additive Models to a seven-year opportunistic cetacean occurrence dataset (2008-2014) and remotely sensed environmental data on bathymetry, sea surface temperature, chlorophyll concentration and altimetry (MSLA). Oceanographic dynamism in the Azores has been recently studied at a regional scale. However, detailed information at a more local scale is still scarce. As our study area is well limited and relatively small, here we provide a high-resolution description of the oceanographic conditions around São Miguel Island based on the environmental variables previously cited. We emphasize its high spatio-temporal variability. In order to capture this dynamism, we used environmental data with two different spatial resolutions (low and high) and three different temporal resolutions (daily, weekly and monthly), thus accounting for both long-term oceanographic events such as the spring bloom, and shorter-term features such as eddies or fronts. Blue whales' temporal distribution was analysed for sightings recorded between 2008 and 2018, accounting for a total of 188 records. Interannual differences in the number of blue whale sightings are apparent. Our results show that blue whales have a well-defined ecological niche around the Azores. They usually cross the archipelago from March to June, every year, and habitat suitability is highest in dynamic areas (with high Eddy Kinetic Energy) characterized by convergence or aggregation zones where productivity is enhanced. Multi-scale studies are useful to understand the ecological niche and habitat requirements of highly mobile species that can easily react to short-term changes in the environment.
Laura González García*1,2, Graham J. Pierce3, Emmanuelle Autret4, Jesús M. Torres-Palenzuela 1
ID 623
Why a MULTI-SCALE approach?
Migrations may be linked with persistent
oceanographic events usually quite predictable
in time and space (e.g. spring bloom).
Reduces data loss.
To capture the short-term mesoscale
oceanographic events such as eddies, filaments
or fronts (Fig.2), which are abundant in dynamic
areas like the Azores.
COARSE SCALES FINER SCALES
1. Applied Physics Department, Universidade de Vigo (Vigo, Spain); 2. Futurismo Azores Adventures, Ponta Delgada (Azores, Portugal);
3. Instituto de Investigaciones Marinas (IIM), CSIC, (Vigo, Spain); 4. Laboratoire d'Océanographie Physique et Spatiale, IFREMER (Brest, France)
lauragonzalez@uvigo.es
ENDANGERED species 70% - 90%
of the population
in the last century
Sighted EVERY YEAR in São Miguel (Azores) (Fig.1).
AIM
Why BLUE WHALES?
González García L, Pierce GJ, Autret E,
Torres-Palenzuela JM (2018) Multi-scale habitat
preference analyses for Azorean blue whales.
PLoS ONE 13(9): e0201786. https://doi.org/10.1371/
journal.pone.0201786
Too many variables for each dataset
to run the models. Therefore, run a
VARIABLE SELECTION PROCESS:
correlation distance in dendrograms > 0.8
& Variance Inflation Factor < 5
vars / dataset DAILY WEEKLY MONTHLY
LOW RESOLUTION 60 -> 19 58 -> 17 49 -> 17
HIGH RESOLTUION 61 -> 22 61 -> 20 43 -> 15
SÃO MIGUEL (AZORES), a dynamic oceanographic area HABITAT PREFERENCE. Generalized Additive Models (GAMs)
ENVIRONMENTAL VARIABLES (multi-scale)
BLUE WHALE SPATIAL & TEMPORAL DISTRIBUTION
Fig.1. Study area. SST and Chl variables were calculated
for the three areas shown: Azores, São Miguel and
south São Miguel.
* OSTIA gridded at 0.05º (~6km); ECMWF gridded at 0,5º (~54km)
DEPTH SEA SURFACE
TEMPERATURE CHLOROPHYLL-A
ALTIMETRY (MSLA
-
UV)
WIND
DERIVED
VARIABLES
Slope
[Dist. Coast]
Mean, gradient, SD and
anomaly per area.
FRONTS (sst, grad, dist)
WEEKLY DELAYS (1-17 wk
).
Mean and SD per area.
Chl Index
EKE
(Eddy Kinetic Energy
)
7-years, seasonal,
monthly
Wind
speed, u, v
SPATIAL
& TEMPORAL
RESOLUTION
1km, static
LOW HIGH LOW HIGH
0.25º, daily
79km
effective*,
6h
10-100km
effective*,
daily
1km, 3-5
images/day
1km, 8-
days,
monthly 1km, daily
SOURCE GEBCO-08
[HidrofráficoPortugal] OSTIA MetOp GlobColour AVISO ECMWF
WHAT DO BLUE WHALES PREFER?
Fig.2. High resolution images showing the dynamic oceanographic conditions
around São Miguel. A) Effect of the bathymetry on the SW of the island shown
by Sea Surface Temperature. B) Small eddies on the S-SE of the island and strong
chlorophyll concentration on the N shown by weekly chlorophyll concentration.
Week of 07-Apr-2011 log(chl)
SST (ºC)
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Binomial distribution: PRESENCE/PSEUDO-ABSENCE, using as pseudo-absence sightings of
the other species (P=89/ PA=7632) // Backwards selection // AIC (Akaike)
K-FOLD CROSS-VALIDATION (6 years training, 1 evaluation. AUC & SD(AUC)
LOW RESOLUTION DAILY, WEEKLY AND MONTHLY
HIGH RESOLUTION DAILY, WEEKLY AND MONTHLY
6 FINAL MODELS
(one per dataset) {
Fig.5. GAM plots of the two variables present in all the final models.
A. Distance to the coast. B. Seasonal EKE in Azores.
FURTHER THAN 10 KM
Distance to the coast.
DYNAMIC AREAS
Seasonal Eddy Kinetic Energy.
Intermediate EKE values in the
Azores = high EKE in São Miguel.
Telling the story
DYNAMIC AREAS
High SST gradients.
CHLOROPHYLL
Intermediate concentrations
in Azores > time to develop
krill (food) from
phytoplankton.
High chl SD -> PATCHED,
aggregation areas.
DEVIANCE
31-41%
AUC
0,82-0,93
In all models:
Fig.4. Temporal distribution of blue whales around São Miguel between 2008 and 2019. Effort
measured as number of hours registered at sea per month shown as background. Total number of
sightings: 204. From those,82% recorded in April and May, and only 2 in autumn.
0
100
200
300
400
500
600
700
800
900
1000
EFFORT (hours)
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
2019 (16)
2018 (36)
2017 (32)
2016 (8)
2015 (11)
2014 (25)
2013 (6)
2012 (32)
2011 (7)
2010 (23)
2009 (6)
2008 (2)
N (2008-2019) = 204
82%
of the sightings in
April-May
Fig.3. Spatial distribution of blue whales
sightings 2008-2014.
OPEN ACCESS
Fig.6. GAM plots of the more representative variables (low resolution models) to
understand blue whale preference off São Miguel. A. Strong SST gradients in São Miguel.
B. Intermediate chlorophyll in the Azores. C. High SD chlorophyll.
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