Other language confidence: 0.9409438725840299
This raster dataset shows forest canopy cover loss (FCCL) in Germany at a monthly resolution from September 2017 to September 2024. It is similar to the product developed by Thonfeld et l. (2022) but was fully reprocessed and updated to reveal the most recent forest disturbance dynamics. The combination of Sentinel-2A/B and Landsat-8/9 data allows for a high temporal resolution while the pixel size of the product is 10 m. The results are clipped to the stocked area 2018 mapped by the Johann-Heinrich-von-Thünen Institute (Langner et al. 2022, https://doi.org/10.3220/DATA20221205151218). The dataset contains predominantly larger canopy openings resulting from different drivers but also larger clusters of standing deadwood. FCCL can result from abiotic (e.g. wind, fire, drought, hail) drivers, biotic (e.g. insects, funghi) drivers or a combination of both as well as from sanitary and salvage logging and planned harvest. The first version with canopy cover losses from January 2018 - April 2021 (Thonfeld et al. 2022) can be accessed here: https://geoservice.dlr.de/web/datasets/tccl.
We simulated an experimental summer storm in large-volume (~1200 m³, ~16m depth) enclosures in Lake Stechlin (https://www.lake-lab.de) by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Size-fractionated (0.2-3 µm and >3.0 µm) chlorophyll a (Chla) development was monitored for 42 days after the experimental disturbance event. Mixing disrupted the thermal stratification, increased concentrations of dissolved nutrients and CO2 and changed light conditions in the epilimnion. Thereby, mixing increased the concentration of Chla of the small size fraction 0.2-3.0 within one week after mixing. After 2-3 weeks, mixing resulted in increased concentrations of Chla also in the large size fraction, which was associated to a bloom of Dolichospermums sp.
We simulated an experimental summer storm in large-volume (~1200 m³, ~16m depth) enclosures in Lake Stechlin by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Water physical variables and water chemistry was monitored for 42 days after the experimental disturbance event. Mixing disrupted the thermal stratification, increasing concentrations of dissolved nutrients and CO2 and changing light conditions in the epilimnion. Mixing, thus, stimulated phytoplankton growth, resulting in higher particulate matter concentrations of carbon, nitrogen and phosphorous.
We simulated an experimental summer storm in large-volume (~1200 m³, ~16m depth) enclosures in Lake Stechlin by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Copepod and Cladocera biomass was monitored for 42 days after the experimental disturbance event (Utermöhl counting at 60x magnification and biomass calculation from length-dry mass relationships). Sampling was performed using a 90 µm mesh size Apstein-cone.
We simulated an experimental summer storm in large-volume (~1200 m³, ~16m depth) enclosures in Lake Stechlin (https://www.lake-lab.de) by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Phytoplankton community composition and biomass of phytoplankton functional groups were monitored for 42 days after the experimental disturbance event in addition to water physical variables and water chemistry. Mixing disrupted the thermal stratification, increased concentrations of dissolved nutrients and CO2 and changed light conditions in the epilimnion. Mixing stimulated phytoplankton growth and changes phytoplankton community composition, resulting in higher biomass of Cryptophyceae (within one week after mixing), Nostocales (mainly Dolichospermum sp.; 2-3 weeks after mixing) and thereafter Bacillariophyceae (mainly Asterionella sp.).
We simulated an experimental summer storm in large-volume (~1200 m³, ~16m depth) enclosures in Lake Stechlin (https://www.lake-lab.de) by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Water physical variables and water chemistry was monitored for 42 days after the experimental disturbance event. Mixing disrupted the thermal stratification, increased concentrations of dissolved nutrients and CO2 and changed light conditions in the epilimnion. Mixing stimulated phytoplankton growth, thus, resulting in a bloom of Dolichospermum sp. and thereafter increased biomass of Bacillariophyceae. Subsequent, break down of both phytoplankton groups resulted in higher particulate matter sinking fluxes of particulate organic carbon (POC), total particulate nitrogen (TPN) and total particulate phosphorous (TPP) 4-5 weeks after the disturbance event. Mixing resulted in average increases in elemental downward fluxes of 9% POC, 14% total particulate Nitrogen (TPN) and 19% TPP by the end of the experiment (42 days) (n.control=4, n.mixed=4).
We simulated an experimental summer storm in large-volume (~1200 m³, ~16m depth) enclosures in Lake Stechlin (https://www.lake-lab.de) by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Primary production rates as well as exoenzyme activities (alkaline phosphatase, beta-glucosidase, leucine aminopeptidase) were monitored for 42 days after the experimental disturbance event by incubation of size-fractionated sample with H14CO3- and MUF substrate analogue assays, respectively. Mixing disrupted the thermal stratification, increased concentrations of dissolved nutrients and CO2 and changed light conditions in the epilimnion. Thus, mixing stimulated phytoplankton production, resulting in higher primary production rates within one week after mixing.
We simulated an experimental summer storm in large-volume (~1200 m³, ~16m depth) enclosures in Lake Stechlin (https://www.lake-lab.de) by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Size-fractionated Bacterial Protein Production (BPP) of particle associated (PA, >3.0 µm) and free-living bacteria (FL, 0.2-3.0 µm) (14C-Leu incorporation) as well as abundances of PA (microscopy of DAPI stained cells on 3.0 µm polycarbonate filters) and FL heterotrophic prokaryotes and picocyanobacteria (flow cytometry of SYBR green I stained cells) were monitored for 42 days after the experimental disturbance event. Mixing increased bacterial abundance and production about 3 weeks after mixing, which was associated to a mixing-induced stimulation of phytoplankton growth in the mixed enclosures compared to the controls. Simultaneously, decreased abundances of picocyanobacteria could be observed in mixed enclosures.
This vector dataset is based on a 10 m resolution raster dataset that shows forest canopy cover loss (FCCL) in Germany at a monthly resolution from September 2017 to September 2024. Results at pixel level were aggregated at municipality, district, and federal state level. For the results at administrative level we differentiate between deciduous and coniferous forests. We use the stocked area map 2018 (Langner et al. 2022, https://doi.org/10.3220/DATA20221205151218 ) as a reference forest mask. We differentiate between deciduous and coniferous forests by intersecting the stocked area map with a tree species map (Blickensdoerfer et al. 2024). Pixels of the classes birch, beech, oak, alder, deciduous trees with long lifespan and deciduous trees with short lifespan were classified as deciduous forest and pixels of the classes Douglas fir, spruce, pine, larch and fir as coniferous forest. The coverage of the two datasets is not identical, which is why a few areas of the forest reference map remained unclassified. These were filled with the dominant leaf type map of the Copernicus Land Monitoring Service (CLMS 2025). Therefore, the vector data at administrative level contains information about unclassified forest areas and the total forest area as the sum of deciduous, coniferous, and unclassified forests. The FCCL confidence at pixel level is lowest at the end of the time series because the number of repeated threshold exceedance is used as a criterion to record forest canopy cover losses. Therefore, we excluded July 2024 through September 2024 from the annual and overall statistics and summarized the respective FCCL as additional attribute. The dataset is a fully reprocessed continuation of the assessment in Thonfeld et al. (2022).
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