2021 > 02
The lakes in SITES AquaNet and SITES Water

After a mild autumn, the real winter has arrived at Lönnstorp Research Station. Over the last two weeks, temperatures have been below zero, with a minimum of -12ºC, according to the automatic weather station. These low temperatures have caused ice to form on the sea surface, which is just 3 km away from the station, and the fields around the station are covered in snow.
Despite the winter conditions, the station staff are already thinking about the spring season, as there is less than two months until the first crops should be sown and therefore time to check and calibrate the spectral equipment.
Text: Ana Barreiro.
Normalized difference vegetation index
Normalized difference vegetation index (NDVI) is an index that describes the greenness of the vegetation. Through SITES Spectral, SITES monitors NDVI at Lönnstorp Research Station and six other stations.
The data from SITES Spectral is available through SITES Data Portal.
The monitoring program IM - Integrated monitoring - follows both physical and chemical processes and their impact on the biological system in four small catchments dominated by coniferous forest, located in different parts of Sweden’s climate and air pollution gradients. One of the areas, Aneboda IM, is through SITES associated with Asa Research Station. A severe storm hit Aneboda sixteen years ago, and the effects are still impacting the biogeochemical status and field work in the area.
After the storm, the fallen Norway spruce trees (Picea abies) attracted bark beetles (Ips typographus), which caused a massive insect outbreak. The beetles infested a large proportion of the Norway spruce trees that survived the storm. In the 2011 survey, almost half of all Norway spruce trees with diameters larger than 20 cm were dead.
The Aneboda IM site and the nearby forest and bog are part of a nature reserve. Long-term monitoring in Aneboda IM was initiated in the mid-1990s in semi-natural coniferous forests, where atmospheric deposition of pollutants and anthropogenically induced climate change are the main human disturbances.
Aneboda IM is one of four Swedish IM catchments within the program Long-Term Ecosystem Research in Europe (eLTER). These programs provide infrastructure, data and management for research at reference conditions on hydrological and biogeochemical processes, including interactions with the biota.
Issues of special interest are soil and surface water acidification, weathering, carbon sequestration, leaching of nutrients, DOC and trace metals, including Hg, as well as the biological effects on organic matter decomposition, bioelement uptake by vegetation and changes in the microbial and vegetation communities down to species level. The semi-natural state at these sites defines the limits for what could be expected without forest management, e.g. defining background conditions and elemental dynamics at reference conditions.

Snow situation at Röbäcksdalen
Röbäcksdalen Field Research Station is measuring snow depth since 2010. So far this season, 75 cm of snow have accumulated at the station, which is the deepest snow cover since the recording started. Usually, the highest snow depths are measured later in the season which shows the magnitude of the current situation and that there is a possibility for more snow to come before this winter is over.
At Svartberget research station, about an hour drive inland from Umeå, the snow depth increased with over 60 cm during the period with several snowstorms in January, which added onto the already existing snow cover.
The local newspaper refers to old farmer’s traditions, which says that half of winter’s snow should have arrived by now. However, data from previous years at Svartberget show that half the amount of snow usually has arrived by Christmas time and that the maximum snow depth is in the beginning of March. The same data supports the likelihood that another 10-20 cm of snow will fall before the winter is over. However, the variation between years is large and climate change makes it difficult to predict the weather, especially in the past years.

During the autumn 2020, an initial sediment investigation was conducted at Lake Erssjön and Lake Feresjön (see SITES December Newsletter for more information). To determine the sediment depth a sub-bottom profiler (Innomar SES-2000) was used. The profiler uses acoustic signals of different wavelengths to produce images showing bottom surface, sediment layers and underlying bedrock. However, gas bubbles in the sediment layers can make it difficult to interpret the bottom profile images and the bubbles can mask the bedrock transition zone. To counteract these issues, during the initial campaign, surface sediment was collected from many locations and deep sediment sampling was carried out at the deepest point of the lake.

Thus, additional data from Erssjön is needed to interpret the data. Fortunately, the ice-cover that formed in January 2021 on Erssjön made further investigations possible, as a stable platform is required for working with deep sediment cores.

2021 > 02
The lakes in SITES AquaNet and SITES Water

After a mild autumn, the real winter has arrived at Lönnstorp Research Station. Over the last two weeks, temperatures have been below zero, with a minimum of -12ºC, according to the automatic weather station. These low temperatures have caused ice to form on the sea surface, which is just 3 km away from the station, and the fields around the station are covered in snow.
Despite the winter conditions, the station staff are already thinking about the spring season, as there is less than two months until the first crops should be sown and therefore time to check and calibrate the spectral equipment.
Text: Ana Barreiro.
Normalized difference vegetation index
Normalized difference vegetation index (NDVI) is an index that describes the greenness of the vegetation. Through SITES Spectral, SITES monitors NDVI at Lönnstorp Research Station and six other stations.
The data from SITES Spectral is available through SITES Data Portal.
The monitoring program IM - Integrated monitoring - follows both physical and chemical processes and their impact on the biological system in four small catchments dominated by coniferous forest, located in different parts of Sweden’s climate and air pollution gradients. One of the areas, Aneboda IM, is through SITES associated with Asa Research Station. A severe storm hit Aneboda sixteen years ago, and the effects are still impacting the biogeochemical status and field work in the area.
After the storm, the fallen Norway spruce trees (Picea abies) attracted bark beetles (Ips typographus), which caused a massive insect outbreak. The beetles infested a large proportion of the Norway spruce trees that survived the storm. In the 2011 survey, almost half of all Norway spruce trees with diameters larger than 20 cm were dead.
The Aneboda IM site and the nearby forest and bog are part of a nature reserve. Long-term monitoring in Aneboda IM was initiated in the mid-1990s in semi-natural coniferous forests, where atmospheric deposition of pollutants and anthropogenically induced climate change are the main human disturbances.
Aneboda IM is one of four Swedish IM catchments within the program Long-Term Ecosystem Research in Europe (eLTER). These programs provide infrastructure, data and management for research at reference conditions on hydrological and biogeochemical processes, including interactions with the biota.
Issues of special interest are soil and surface water acidification, weathering, carbon sequestration, leaching of nutrients, DOC and trace metals, including Hg, as well as the biological effects on organic matter decomposition, bioelement uptake by vegetation and changes in the microbial and vegetation communities down to species level. The semi-natural state at these sites defines the limits for what could be expected without forest management, e.g. defining background conditions and elemental dynamics at reference conditions.

Snow situation at Röbäcksdalen
Röbäcksdalen Field Research Station is measuring snow depth since 2010. So far this season, 75 cm of snow have accumulated at the station, which is the deepest snow cover since the recording started. Usually, the highest snow depths are measured later in the season which shows the magnitude of the current situation and that there is a possibility for more snow to come before this winter is over.
At Svartberget research station, about an hour drive inland from Umeå, the snow depth increased with over 60 cm during the period with several snowstorms in January, which added onto the already existing snow cover.
The local newspaper refers to old farmer’s traditions, which says that half of winter’s snow should have arrived by now. However, data from previous years at Svartberget show that half the amount of snow usually has arrived by Christmas time and that the maximum snow depth is in the beginning of March. The same data supports the likelihood that another 10-20 cm of snow will fall before the winter is over. However, the variation between years is large and climate change makes it difficult to predict the weather, especially in the past years.

During the autumn 2020, an initial sediment investigation was conducted at Lake Erssjön and Lake Feresjön (see SITES December Newsletter for more information). To determine the sediment depth a sub-bottom profiler (Innomar SES-2000) was used. The profiler uses acoustic signals of different wavelengths to produce images showing bottom surface, sediment layers and underlying bedrock. However, gas bubbles in the sediment layers can make it difficult to interpret the bottom profile images and the bubbles can mask the bedrock transition zone. To counteract these issues, during the initial campaign, surface sediment was collected from many locations and deep sediment sampling was carried out at the deepest point of the lake.

Thus, additional data from Erssjön is needed to interpret the data. Fortunately, the ice-cover that formed in January 2021 on Erssjön made further investigations possible, as a stable platform is required for working with deep sediment cores.

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