Variation in benthic long-term data of transitional waters: Is interpretation more than speculation?

Abstract

Biological long-term data series in marine habitats are often used to identify anthropogenic impacts on the environment or climate induced regime shifts. However, particularly in transitional waters, environmental properties like water mass dynamics, salinity variability and the occurrence of oxygen minima not necessarily caused by either human activities or climate change can attenuate or mask apparent signals. At first glance it very often seems impossible to interpret the strong fluctuations of e.g. abundances or species richness, since abiotic variables like salinity and oxygen content vary simultaneously as well as in apparently erratic ways. The long-term development of major macrozoobenthic parameters (abundance, biomass, species numbers) and derivative macrozoobenthic indices (Shannon diversity, Margalef, Pilou's evenness and Hurlbert) has been successfully interpreted and related to the long-term fluctuations of salinity and oxygen, incorporation of the North Atlantic Oscillation index (NAO index), relying on the statistical analysis of modelled and measured data during 35 years of observation at three stations in the south-western Baltic Sea. Our results suggest that even at a restricted spatial scale the benthic system does not appear to be tightly controlled by any single environmental driver and highlight the complexity of spatially varying temporal response.

Fig 1. Bathymetry (water depth in m) of the southern Baltic Sea with three selected long-term monitoring stations.

Fig 2. Median of bottom salinity calculated from model simulations covering the last 15 years.

Fig 3. Difference of 10th-and 90th-percentile of simulated bottom salinity calculated over the last 35 years.

Fig 4. Estimated number of days per year with oxygen concentration below 1 ml/l covering the last 35 years.

Fig 5. Estimated number of days per year and station with below 10th- and above 90th-percentile of bottom salinity.

Simulations covering the last 35 years [stn. 012: p10th (18.41 psu), p90th (25.94 psu); stn. 030: p10th (9.45 psu), p90th (19.29 psu); stn. 109: p10th (12.73 psu), p90th (17.74 psu)].

Fig 6. Estimated number of days per year and station with oxygen concentration below 1 ml/l.

Simulations covering the last 35 years.

Fig 7. Median anomaly of abundance, biomass and species number at station 012.

Logarithm to base 10 of ratio between annual and median value of the long-term data (left axis). Negative anomaly means annual value is smaller than median value and vice versa. Multiples of the median are indicated by dotted lines. Solid line = Oxygen minimum value per year (right axis).

Fig 8. Median anomaly of diversity indices at station 012.

Logarithm to base 10 of ratio between annual and median value of the long-term data (left axis). Negative anomaly means annual value is smaller than median value and vice versa. Multiples of the median are indicated by dotted lines. Solid line = Oxygen minimum value per year (right axis).

Fig 9. Median anomaly of abundance, biomass and species number at station 030.

Logarithm to base 10 of ratio between annual and median value of the long-term data (left axis). Negative anomaly means annual value is smaller than median value and vice versa. Solid line = North Atlantic Oscillation Index (NAOI) for winter (DJFM) (right axis).

Fig 10. Median anomaly of diversity indices at station 030.

Logarithm to base 10 of ratio between annual and median value of the long-term data (left axis). Negative anomaly means annual value is smaller than median value and vice versa. Solid line = North Atlantic Oscillation Index (NAOI) for winter (DJFM) (right axis).

Fig 11. Median anomaly of abundance, biomass and species number at station 109.

Logarithm to base 10 of ratio between annual and median value of the long-term data (left axis). Negative anomaly means annual value is smaller than median value and vice versa. Solid line = North Atlantic Oscillation Index (NAOI) for winter (DJFM) (right axis).

Fig 12. Median anomaly of diversity indices at station 109.

Logarithm to base 10 of ratio between annual and median value of the long-term data (left axis). Negative anomaly means annual value is smaller than median value and vice versa. Solid line = North Atlantic Oscillation Index (NAOI) for winter (DJFM) (right axis).

Fig 13. Ordination of Bray-Curtis similarities in species composition and abundance of the station 030 from 1980 to 2015.

Arrows indicate strong changes and might be seen as “regime shifts”.