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. 2022 Oct 18;194(Suppl 1):741.
doi: 10.1007/s10661-022-10018-7.

Benthic studies adjacent to Sakhalin Island, Russia 2015 III: benthic energy density spatial models in the nearshore gray whale feeding area

Arny L Blanchard  1 , Laurie Ainsworth  2 , Glenn Gailey  3 , Natalia L Demchenko  4 , Ilya A Shcherbakov  4
Affiliations

Benthic studies adjacent to Sakhalin Island, Russia 2015 III: benthic energy density spatial models in the nearshore gray whale feeding area

Arny L Blanchard et al. Environ Monit Assess. .

Abstract

Energy densities of six dominant benthic groups (Actinopterygii, Amphipoda, Bivalvia, Cumacea, Isopoda, and Polychaeta) and total prey energy were modeled for the nearshore western gray whale feeding area, Sakhalin Island, Russia, as part of a multi-disciplinary research program in the summer of 2015. Energy was modeled using generalized additive mixed models (GAMM) with accommodations for zero-inflation (logistic regression and hurdle models) and regression predictions combined with kriging to interpolate energy densities across the nearshore feeding area. Amphipoda energy density was the highest nearshore and in the south whereas Bivalvia energy density was the highest offshore and in the northern portion of the study area. Total energy was the highest in mid-range distances from shore and in the north. Amphipoda energy density was higher than minimum energy estimates defining gray whale feeding habitats (312-442 kJ/m2) in 13% of the nearshore feeding area whereas total prey energy density was higher than the minimum energy requirement in 49% of the habitat. Inverse distance-weighted interpolations of Amphipoda energy provided a broader scale representation of the data whereas kriging estimates were spatially limited but more representative of higher density in the southern portion of the study area. Both methods represented the general trend of higher Amphipoda energy density nearshore but with significant differences that highlight the value of using multiple methods to model patterns in highly complex environments.

Keywords: Benthic ecology; Ecosystem variability; Macrobenthos; Marine ecology; Sea of Okhotsk.

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Figures

Fig. 1
Fig. 1
The 2015 benthic nearshore study area in the Sakhalin Island gray whale feeding area, Russia. The inset presents the geographic reference of the gray whale feeding area. See Aerts et al. (2022) for further details of the 2015 seismic mitigation and monitoring plan. The * marks the mouth of Piltun Bay
Fig. 2
Fig. 2
Amphipoda energy (kJ/m2) for the nearshore feeding area, Sakhalin Island Russia, 2015. Observed energy density is presented by a sampling period and zone, b densities by northing with a smoothed regression, and c densities by distance to shore with a smoothed regression. d Presents kriging predicted energy density by sampling period. Northing (m north) and latitude (degrees north) are presented on the vertical scale
Fig. 3
Fig. 3
Average energy density (kJ/m2) by period and zone and scatterplots of northing (km) and distance from shore (km) for Actinopterygii, Cumacea, and Polychaeta for the nearshore feeding area, Sakhalin Island, Russia, 2015. Smoothed regressions are presented on scatterplots
Fig. 4
Fig. 4
Total energy (kJ/m2) for the nearshore feeding area, Sakhalin Island, Russia, 2015. Observed energy density is presented by a sampling period and zone, b northing with a smoothed regression, and c distance to shore with a smoothed regression. d Presents kriging predicted energy density by sampling period. Northing (m north) and latitude (degrees north) are presented on the vertical scale
Fig. 5
Fig. 5
Bivalvia energy (kJ/m2) for the nearshore feeding area, Sakhalin Island Russia, 2015. Observed energy density is presented by a sampling period and zone, b northing with a smoothed regression, and c depth with a smoothed regression. d Presents kriging predicted energy density by sampling period. Northing (m north) and latitude (degrees north) are presented on the vertical scale
Fig. 6
Fig. 6
Isopoda energy (kJ/m2) for the nearshore feeding area, Sakhalin Island Russia, 2015. Observed energy density is presented by a northing and sampling period with smoothed regressions. b Presents kriging predicted energy density by sampling period. Northing (m north) and latitude (degrees north) are presented on the vertical scale
Fig. 7
Fig. 7
Amphipoda energy density (kJ/m2) in the 2015 nearshore study area, Sakhalin Island, Russia. Bubble plots of energy density by sampling period represent replicate values at individual sampling points. The shoreline is added for geographic context and is not an accurate representation of distance from shore
Fig. 8
Fig. 8
Inverse distance weighting predictions of Amphipoda energy density for the nearshore feeding area Sakhalin Island Russia, 2015
See this image and copyright information in PMC

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