Climate-driven changes in functional biogeography of Arctic marine fish communities

Abstract

Climate change triggers poleward shifts in species distribution leading to changes in biogeography. In the marine environment, fish respond quickly to warming, causing community-wide reorganizations, which result in profound changes in ecosystem functioning. Functional biogeography provides a framework to address how ecosystem functioning may be affected by climate change over large spatial scales. However, there are few studies on functional biogeography in the marine environment, and none in the Arctic, where climate-driven changes are most rapid and extensive. We investigated the impact of climate warming on the functional biogeography of the Barents Sea, which is characterized by a sharp zoogeographic divide separating boreal from Arctic species. Our unique dataset covered 52 fish species, 15 functional traits, and 3,660 stations sampled during the recent warming period. We found that the functional traits characterizing Arctic fish communities, mainly composed of small-sized bottom-dwelling benthivores, are being rapidly replaced by traits of incoming boreal species, particularly the larger, longer lived, and more piscivorous species. The changes in functional traits detected in the Arctic can be predicted based on the characteristics of species expected to undergo quick poleward shifts in response to warming. These are the large, generalist, motile species, such as cod and haddock. We show how functional biogeography can provide important insights into the relationship between species composition, diversity, ecosystem functioning, and environmental drivers. This represents invaluable knowledge in a period when communities and ecosystems experience rapid climate-driven changes across biogeographical regions.

Keywords: Barents Sea; climate warming; functional traits; marine ecosystems; trait-based ecology.

Fig. S1.

Multivariate analysis of species functional traits. Cod (GaM), haddock (MeA), Norway pout (TrE), blue whiting (MiP), and long rough dab (HiP) are characterized by boreal-like traits (left side of PC1), whereas several other less-abundant species are characterized by Arctic-like traits (right side of PC1). Species are colored according to their position on the functional multivariate space, from yellow (left side) to red (right side). Full names of the fish species are given in Table S1.

Fig. S2.

Principal component analysis of the community-weighted mean trait values from 2004 to 2012 across the Barents Sea. This analysis contains data on all 3,660 sampling sites, which are colored by their positioning along PC axis 1 (CWM PC1). We used information from the PC1 to assess the functional characteristics of fish communities in subsequent analyses.

Fig. 1.

Spatial distribution of functional traits in the Barents Sea fish communities in 2004 and 2012. Colors indicate the dominant trait characteristics of each community as obtained from PC1 of abundance-weighted trait values and range from red (boreal-like) to blue (Arctic-like). Boreal-like trait values indicate communities dominated by large body-sized, generalist, piscivorous, and semipelagic species. Arctic-like trait values indicate dominance of small body-sized, benthivorous, and more strictly demersal species.

Fig. S3.

Community-weighted mean trait values of demersal fish species in the Barents Sea from 2004 to 2012. Colors indicate the dominant trait characteristics at each community and were obtained from CWM PC1 (Fig. S2); they range from red (boreal-like) to blue (Arctic-like).

Fig. 2.

(A) Boreal (red) and Arctic (blue) regions used for assessing trends (from 2004 to 2012) in (B) CWM trait values for all traits (PC1), (C) benthivory, and (D) piscivory (Fig. S4 for all traits). Data points are the average within each region, and the trend lines are estimated by linear regression. The 95% confidence bands are shown in gray.

Fig. S4.

Variation of community-weighted mean trait values across 9 y (2004–2012) of sampling in the boreal (red) and Arctic (blue) regions. Data points are the average within each region. The 95% CI is shown. Traits that have significant interaction between time and region (P < 0.05) are indicative of convergence or divergence between the Arctic and boreal regions and are marked with an asterisk.

Fig. 3.

Distribution of fish functional traits in the Barents Sea along two environmental variables affected by warming in 2004 and 2012. Colors code the dominant trait characteristics from red (boreal-like) to blue (Arctic-like) as in Fig. 1. The two environmental variables displayed were the most important explanatory variables in the regression tree analyses. Lines indicate the threshold values for the environmental variables obtained by the regression tree (solid lines, first threshold values; dotted lines, second threshold values). Numbers indicate the mean CWM PC1 value (and number of stations) for stations found within ranges of environmental characteristics specified by the environmental threshold values.

Fig. S5.

Results of the random forest analyses for each year from 2004 to 2012. Higher %IncMSE indicate higher amount of variation explained by the predictor variable.

Fig. S6.

Regression tree analyses on the CWM of Barents Sea demersal fish species and the environmental predictors Sea ice coverage (d), water bottom temperature (°C), depth (m), and salinity (‰). Regression trees were applied to each year independently, from 2004 to 2012.

Fig. S7.

Scatterplot showing the relationship between demersal fish CWM PC1 and environmental predictors (A) water bottom temperature (°C), (B) sea ice coverage (d), (C) salinity (‰), and (D) depth (m) in the Barents Sea. Data points are pooled across all years between 2004 and 2012.