Results
Demersal fish biomass was highest in the northern regions of the
Northeast Pacific (Gulf of Alaska, Eastern Bering Sea and Aleutian
Islands) and Northeast Atlantic (Barents Sea and Norwegian Sea) (Figure
1a). Conversely, demersal fish biomass was lowest in the Gulf of Mexico
and temperate regions of the North Atlantic (Baltic Sea, southern North
Sea, Gulf of Saint Lawrence).
At the ecoregion scale, Pearson correlations between demersal fish
biomass and temperature (Figure 1b, r = -0.54), fishing
exploitation (Figure 1c, r = -0.34), net primary production
(Figure 1d, r = -0.40) and detrital bottom flux (r =
-0.33) were negative, while depth correlated positively with biomass
(r = 0.23). Demersal fish biomass had no correlation with
zooplankton production (r = 0.04) and mean trophic level
(r = -0.04). Whether the correlations with biomass were direct
effects of the predictor variable or indirect effects governed by other
predictor variables were examined with the SEM.
Including all predictors resulted in a SEM that
was too complex for the available
number of observations at the ecoregion scale to assess goodness-of-fit
(Figure S2.2). Hence, we
simplified the full model by removing the detrital bottom flux, which
had an insignificant relation with biomass in 6 out of 6 runs (2 spatial
scales × 3 time periods). We also removed depth, which became irrelevant
for the SEM network after removing the detrital bottom flux. The final
model, including the remaining five predictors, had a meanΧ 2 of 6.02 (standard deviation from the 6 runs
is 2.4) with 6 degrees of freedom, and p-values ranging between 0.21 and
0.88, indicating that our hypothesized causal structure is supported by
the data (an insignificant result indicates good model fit).
Among the individual pathways, demersal fish biomass at the ecoregion
and subdivision scale was negatively related to temperature, fishing
exploitation and mean trophic level and positively related to
zooplankton production (Figure 2). The pronounced spatial variation in
demersal fish biomass was reasonably well explained (mean
R2 = 0.59) with no clear spatial pattern in the
residuals (Figure S2.3). The effects of temperature and fishing were
almost equally strong (Figure S2.4). For most other pathways, the
directionality conformed with the initial expectations (Figure 2 vs
Figure S2.2). A partial effect size plot showed that demersal fish
biomass is approximately twice as high with a decline in temperature
from 15 to 5°C and a decline in exploitation rate from 0.3 to 0.03,
whereas the effect of mean trophic level and zooplankton production on
biomass were more variable (Figure 3).
Similar to the SEM analyses, the grid-cell analysis using
wavelet-revised model regression showed a negative relationship between
demersal fish biomass and fishing exploitation and temperature, while
zooplankton had a positive relationship with biomass for all three time
periods (Table 2). In contrast to the previous analysis, the detrital
bottom flux, which was excluded in the SEM, had a mixed effect on
biomass (positive in one period and negative in the two others). Mean
trophic level was not part of the best candidate model in any of the
time periods.
The best fit between observed and predicted demersal fish biomass with
the trophodynamic model (i.e., eq. 1) was obtained with a trophic
transfer efficiency of 0.075 and a Q 10temperature scaling of trophic transfer efficiency between 0.4 and 0.7
(Figure 4, S2.5), implying that trophic transfer declines with
increasing temperature. Replacing the temperature dependent trophic
transfer efficiency with a single mean value sharply reduced the
R2 of the trophodynamic model from 0.66 to 0.42.
Furthermore, replacing the exploitation rate in eq. 1 with a single mean
value and refitting led to an R2 of 0.55. The results
of the trophodynamic model are thus consistent with the SEM in
suggesting temperature-linked trophodynamic effects, i.e., a trophic
transfer efficiency decrease with increasing temperature, and
exploitation rates as the primary drivers of demersal fish biomass
across the range of systems considered.
Finally, we found no evidence
that temporal changes in temperature have impacted demersal community
biomass within ecoregions during the period 1980-2015 (Table 1).
All models with and without a
temperature term differed less than 2 AIC units. The models without the
temperature term were therefore selected as best candidate as they have
the fewest parameters.