Small-scale spatial and temporal variation in the demographic processes underlying the large-scale decline of eiders in the Baltic Sea

2015 ◽  
Vol 58 (1) ◽  
pp. 121-133 ◽  
Author(s):  
Markus Öst ◽  
Satu Ramula ◽  
Andreas Lindén ◽  
Patrik Karell ◽  
Mikael Kilpi
Keyword(s):  
Baltic Sea ◽  
Temporal Variation ◽  
Large Scale ◽  
Spatial And Temporal Variation ◽  
Small Scale ◽  
The Baltic Sea ◽  
Demographic Processes ◽  
The Baltic

scholarly journals Deficiency syndromes in top predators associated with large-scale changes in the Baltic Sea ecosystem

PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0227714 ◽  
Author(s):  
Sanna Majaneva ◽  
Emil Fridolfsson ◽  
Michele Casini ◽  
Catherine Legrand ◽  
Elin Lindehoff ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Large Scale ◽  
The Baltic Sea ◽  
Top Predators ◽  
The Baltic

scholarly journals Effect of ocean acidification and elevated <i>f</i>CO<sub>2</sub> on trace gas production by a Baltic Sea summer phytoplankton community

2016 ◽  
Vol 13 (15) ◽  
pp. 4595-4613 ◽  
Author(s):  
Alison L. Webb ◽  
Emma Leedham-Elvidge ◽  
Claire Hughes ◽  
Frances E. Hopkins ◽  
Gill Malin ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Large Scale ◽  
Gas Production ◽  
Trace Gas ◽  
Research Station ◽  
The Baltic Sea ◽  
Chl A ◽  
The Baltic ◽  
Upwelling Event ◽  
Ambient Co2

Abstract. The Baltic Sea is a unique environment as the largest body of brackish water in the world. Acidification of the surface oceans due to absorption of anthropogenic CO2 emissions is an additional stressor facing the pelagic community of the already challenging Baltic Sea. To investigate its impact on trace gas biogeochemistry, a large-scale mesocosm experiment was performed off Tvärminne Research Station, Finland, in summer 2012. During the second half of the experiment, dimethylsulfide (DMS) concentrations in the highest-fCO2 mesocosms (1075–1333 µatm) were 34 % lower than at ambient CO2 (350 µatm). However, the net production (as measured by concentration change) of seven halocarbons analysed was not significantly affected by even the highest CO2 levels after 5 weeks' exposure. Methyl iodide (CH3I) and diiodomethane (CH2I2) showed 15 and 57 % increases in mean mesocosm concentration (3.8 ± 0.6 increasing to 4.3 ± 0.4 pmol L−1 and 87.4 ± 14.9 increasing to 134.4 ± 24.1 pmol L−1 respectively) during Phase II of the experiment, which were unrelated to CO2 and corresponded to 30 % lower Chl a concentrations compared to Phase I. No other iodocarbons increased or showed a peak, with mean chloroiodomethane (CH2ClI) concentrations measured at 5.3 (±0.9) pmol L−1 and iodoethane (C2H5I) at 0.5 (±0.1) pmol L−1. Of the concentrations of bromoform (CHBr3; mean 88.1 ± 13.2 pmol L−1), dibromomethane (CH2Br2; mean 5.3 ± 0.8 pmol L−1), and dibromochloromethane (CHBr2Cl, mean 3.0 ± 0.5 pmol L−1), only CH2Br2 showed a decrease of 17 % between Phases I and II, with CHBr3 and CHBr2Cl showing similar mean concentrations in both phases. Outside the mesocosms, an upwelling event was responsible for bringing colder, high-CO2, low-pH water to the surface starting on day t16 of the experiment; this variable CO2 system with frequent upwelling events implies that the community of the Baltic Sea is acclimated to regular significant declines in pH caused by up to 800 µatm fCO2. After this upwelling, DMS concentrations declined, but halocarbon concentrations remained similar or increased compared to measurements prior to the change in conditions. Based on our findings, with future acidification of Baltic Sea waters, biogenic halocarbon emissions are likely to remain at similar values to today; however, emissions of biogenic sulfur could significantly decrease in this region.

scholarly journals A century of genetic homogenization in Baltic salmon—evidence from archival DNA

2021 ◽  
Vol 288 (1949) ◽  
Author(s):  
Johan Östergren ◽  
Stefan Palm ◽  
John Gilbey ◽  
Göran Spong ◽  
Johan Dannewitz ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Large Scale ◽  
Isolation By Distance ◽  
Anthropogenic Impacts ◽  
Genetic Change ◽  
Past Century ◽  
The Baltic Sea ◽  
The Baltic ◽  
Archival Dna

Intra-species genetic homogenization arising from anthropogenic impacts is a major threat to biodiversity. However, few taxa have sufficient historical material to systematically quantify long-term genetic changes. Using archival DNA collected over approximately 100 years, we assessed spatio-temporal genetic change in Atlantic salmon populations across the Baltic Sea, an area heavily impacted by hydropower exploitation and associated with large-scale mitigation stocking. Analysis was carried out by screening 82 SNPs in 1680 individuals from 13 Swedish rivers. We found an overall decrease in genetic divergence and diminished isolation by distance among populations, strongly indicating genetic homogenization over the past century. We further observed an increase in genetic diversity within populations consistent with increased gene flow. The temporal genetic change was lower in larger wild populations than in smaller wild and hatchery-reared ones, indicating that larger populations have been able to support a high number of native spawners in relation to immigrants. Our results demonstrate that stocking practices of salmon in the Baltic Sea have led to the homogenization of populations over the last century, potentially compromising their ability to adapt to environmental change. Stocking of reared fish is common worldwide, and our study is a cautionary example of the potentially long-term negative effects of such activities.

Nemo-Nordic 2.0: Updated Baltic Sea model based on NEMO 4.0

2021 ◽  
Author(s):  
Tuomas Kärnä ◽  
Ida Ringgaard ◽  
Vasily Korabel ◽  
Adam Nord ◽  
Patrik Ljungemyr ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Horizontal Resolution ◽  
Sea Surface ◽  
Small Scale ◽  
The Baltic Sea ◽  
Inflow Event ◽  
Arkona Basin ◽  
The Baltic ◽  
Marine Environment Monitoring ◽  
Monitoring Service

&lt;p&gt;We present Nemo-Nordic 2.0, the latest version of the operational marine forecasting model for the Baltic Sea used and developed in the Baltic Monitoring Forecasting Centre (BAL MFC) under the Copernicus Marine Environment Monitoring Service (CMEMS). The most notable differences between Nemo-Nordic 2.0 and its predecessor Nemo-Nordic 1.0 are the switch from NEMO 3.6 to NEMO 4.0 and an increase in horizontal resolution from 2 to 1 nautical mile. In addition, the model's bathymetry and bottom friction formulation have been updated. The model configuration was specially tuned to represent Major Baltic Inflow events. Focusing on a 2-year validation period from October 1, 2014, covering one Major Baltic Inflow event, Nemo-Nordic 2.0 simulates Sea Surface Height (SSH) well: centralized Root-Mean-Square Deviation (CRMSD) is within 10 cm for most stations outside the Inner Danish Waters. CRMSD is higher at some stations where small-scale topographical features cannot be correctly resolved. SSH variability tends to be overestimated in the Baltic Sea and underestimated in the Inner Danish Waters. Nemo-Nordic 2.0 represents Sea Surface Temperature (SST) and Salinity (SSS) well, although there is a negative bias around -0.5&amp;#176;C in SST. The 2014 Major Baltic Inflow event is well reproduced. The simulated salt pulse agrees well with observations in the Arkona basin and progresses into the Gotland basin in 3 to 4 months.&lt;/p&gt;

Statistical Downscaling of daily extreme Sea Level with Random Forest: Examples from South-East Asia and the Baltic Sea

2020 ◽  
Author(s):  
Svenja Bierstedt ◽  
Eduardo Zorita ◽  
Birgit Hünicke
Keyword(s):  
Random Forest ◽  
Baltic Sea ◽  
East Asia ◽  
Sea Level ◽  
Large Scale ◽  
South East Asia ◽  
The Baltic Sea ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
The Baltic

&lt;p&gt;The coastlines of the Baltic Sea and Indonesia are both relatively complex, so that the estimation of extreme sea levels caused by the atmospheric forcing becomes complex with conventional methods. Here, we explore whether Machine Learning methods can provide a model surrogate to compute more rapidly daily extremes in sea level from large-scale atmosphere-ocean fields. We investigate the connections between the atmospheric and ocean drivers of local extreme sea level in South East Asia and along the Baltic Sea based on statistical analysis by Random Forest Models, driven by large-scale meteorological predictors and daily extreme sea level measured by tide-gauge records over the last few decades.&lt;/p&gt;&lt;p&gt;First results show that in some Indonesian areas extremes are driven by large-scale climate fields; in other areas they are incoherently driven by local processes. An area where random forest predicted extremes show good correspondence to observed extremes is found to be the Malaysian coastline. For the Indonesian coasts, the Random Forest Algorithm was unable to predict extreme sea levels in line with observations. Along the Baltic Sea, in contrast, the Random Forest model is able to produce reasonable estimations of extreme sea levels based on the large-scale atmospheric fields. An analysis of the interrelations of extreme sea levels in the South Asia regions suggests that either the data quality may be compromised in some regions or that other forcing factors, distinct from the large-scale atmospheric fields, may also be involved.&lt;/p&gt;

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