en:
The available lichen data consists of detection/nondetection data (1/0) of 373 tree-inhabiting (*corticolous*) lichen species from 416 plots surveyed 1-2 times. The lichen data were originally collected for the purpose of the Red List of epiphytic lichen species in Switzerland ([Scheidegger *et al.* 2002](https://www.bafu.admin.ch/bafu/de/home/themen/biodiversitaet/publikationen-studien/publikationen/rote-liste-gefaehrdete-arten-baum-erdbewohnende-flechten.html)), but updated to recent nomenclature for the purpose of this study.
This repository contains all the supporting data and R code for the paper:
von Hirschheydt, G., Kéry, M., Ekman, S., Stofer, S., Dietrich, M., Keller, C., Scheidegger, C. (2024) **Occupancy model reveals limited detectability of lichens in a standardised large-scale monitoring**. *Journal of Vegetation Science*.
Results and figures presented in the manuscript should be reproducible (with small differences in the latter digits due to stochasticity of the MCMC sampler) with the provided data and code.
The downloadable `.zip` folder has the following structure:
* `0_data/`
* `1_code/`
* `2_output/`
* `lichen_detectability.Rproj`
* `README.txt`
* `workflow.html`
- `workflow.Rmd`

The main folder and the three subordinate folders each have their own `README*.txt` file. These describe each available file in detail and should be consulted prior to using the data or running any code. The file `lichen_detectability.Rproj` stores the information about the R project. The user can open the project by clicking/double-clicking on this file which will automatically define the repository as working directory for the R session. If the user does not use RStudio/Posit, they may have to set the working directory manually to the stored location in the R files. The files `workflow.*` guide the user through the analysis (`1_code/*.R`) in the correct order so that they can:
- bundle the cleaned data into a data list readable for JAGS
- fit the multi-species occupancy model to the data and store the output
- assess the goodness-of-fit of the model to the data
- conduct a prior sensitivity analysis with 2 additional sets of priors
- extract the summary statistics reported in the manuscript and supplementary materials
- generate the figures shown in the manuscript and supplementary materials

en: detectability detection-probability bayesian-inference swisslichens inter-observer-difference lichens sessile-species cryptogams biodiversity monitoring observer-error occupancy-model

en: Repeated detection-nondetection data of corticolous lichens from a standardised monitoring across Switzerland

bayesian-inference

display_name: bayesian-inference

biodiversity

display_name: biodiversity

cryptogams

display_name: cryptogams

detectability

display_name: detectability

detection-probability

display_name: detection-probability

inter-observer-difference

display_name: inter-observer-difference

lichens

display_name: lichens

observer-error

display_name: observer-error

occupancy-model

display_name: occupancy-model

sessile-species

display_name: sessile-species

swisslichens

display_name: swisslichens


$oid: OBSOLETE

en:
In the associated study [1], two time-lapse temperature gradient metamorphism series of three-dimensional micro-computed tomography images of snow (obtained by [2]) have been used to model the decrease of specific surface area (SSA) over time based on the pore-scale physics. We conducted finite element simulations of one-way coupled heat and mass diffusion in order to estimation the spatial pattern of water vapor deposition and sublimation, which controls the evolution of the SSA over time. We notably studied the influence of the condensation coefficient, a key but poorly constrained physical parameter.
This dataset provides the parameters used for the mesh generation and the finite element simulations. It also includes the ice fraction, specific surface area per unit volume and surface average of mean curvature and vapor field obtained as outputs from the mesh process and the simulations.
[1]: Braun, A., Fourteau, K., and Löwe, H.: A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1947, 2023.
[2]: Pinzer, B. R., Schneebeli, M., and Kaempfer, T. U.: Vapor flux and recrystallization during dry snow metamorphism under a steady temperature gradient as observed by time-lapse micro-tomography, The Cryosphere, 6, 1141–1155, https://doi.org/10.5194/tc-6-1141-2012, 2012.

en: time-series microstructure fem metamorphism snow x-ray-tomography

envidat

approval_status: approved

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Simulation parameters and outputs for a rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

format: ODS

fem

display_name: fem

metamorphism

display_name: metamorphism

microstructure

display_name: microstructure

snow

display_name: snow

time-series

display_name: time-series

x-ray-tomography

display_name: x-ray-tomography


en: This dataset collection contains all datasets collected during the ring wind tunnel experiments in January and May 2023 at the SLF cold laboratory facilities in Davos. A full description of the experiment set-up can be found in Wahl et al. (2024). The collection contains data from 19 experiments. The dataset collection entails measurements of the stable water isotopic composition of snow samples and the water vapour inside the wind tunnel, measurements of the meteorological variables inside the wind tunnel and snow sample properties as measured with microCT measurements (sphere size distribution and specific surface area (SSA)).

en: blowing-snow snow-saltation wind-tunnel water-isotopes metamorphism experiments drifting-snow cold-lab

en: Ring wind tunnel experiments - airborne snow metamorphism and stable water isotopes

en:
Resource Title: Snow samples - sphere size statistics files
    Size: 62459 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f2ebc8e9-e757-47a8-8713-8892cb1cb25f/resource/d91180d7-3057-462d-b893-20a01974b0a1/download/snowsamples_spheresizedistributions.zip
    Description: The individual measurement reports of the microCT scan for each snow sample as combined zip file. The file names and the sample number indicate which snow sample it is, see "Snow samples - microCT measurements". Each file contains the statistics and the count of fitted sphere size diameters and the respective share (in-%) in the frequency distribution. Immediately after snow sampling, a small portion of snow was transferred to the cylindrical μCT sample holder with a diameter of 15 mm and analysed at -20°C using a Scanco® CT-40 scanner. The analysis followed Hildebrand and Rüegsegger (1997).

format: ZIP

media_type: application/zip

en:
Resource Title: Snow samples - microCT measurements
    Size: 3800 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f2ebc8e9-e757-47a8-8713-8892cb1cb25f/resource/93606a69-9f2e-4f8d-bca5-3f28001ee056/download/windtunnel2023_ct_measurements.txt
    Description: The data of the snow samples that were analysed in a Scanco® CT-40 scanner using a sample holder of 15 mm diameter which allowed for a high-resolution analysis with voxel size of 8 μm. The timestamp (local time, Davos, Switzerland) of snow sampling is given as well as the type of snow sample (see Snow samples - stable water isotopic composition dataset), the corresponding wind tunnel experiment number ("ExpNo", Wahl et al. (2024), Table 1) and the time since the snow introduction to the wind tunnel. The measured SSA is given in units 1/mm. The column "hist_filename" lists the name of the corresponding .txt file which contains the sphere size statistics of the snow samples. The sphere size statistics files are compressed in a .zip file.

format: TXT

media_type: text/plain

en:
Resource Title: Meteorological variables measured inside the wind tunnel during the January 2023 experiments
    Size: 41430 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f2ebc8e9-e757-47a8-8713-8892cb1cb25f/resource/a9edeb00-0547-47a3-821d-0a70b86af7ab/download/windtunnel2023_janmetvariables_1min.txt
    Description: The dataset contains the 1-minute averages of the calibrated meteorological variables: temperature (T, °C), relative humidity (RH, %), relative humidity referenced against saturation over ice (RHice, %), specific humidity (q, g/kg) and wind speed (WS, m/s) as measured in the observation section of the wind tunnel at different heights. The measurement heights correspond to: "Top"=42.5cm, "Mid"=30cm, "Bot"=15cm, "PT100_Ta"=3cm. "WS" was measured at 36.5cm height. The timestamp is in local time (UTC+1) and indicates the start of the averaging period.

en:
Resource Title: Meteorological variables measured inside the wind tunnel during the May 2023 experiments
    Size: 290145 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f2ebc8e9-e757-47a8-8713-8892cb1cb25f/resource/1fcb9bb3-769d-40ee-948f-1b6899c6d488/download/windtunnel2023_metvariables_1min.txt
    Description: The dataset contains the 1-minute averages of the calibrated meteorological variables: temperature (T, °C), relative humidity (RH, %), relative humidity referenced against saturation over ice (RHice, %), specific humidity (q, g/kg) and wind speed (WS, m/s) as measured in the observation section of the wind tunnel at different heights and the room temperature of the laboratory measured outside the wind tunnel (Lab_Ta, °C). The measurement heights correspond to: "Top"=42.5cm, "Mid"=30cm, "Bot"=15cm, "PT100_Ta"=3cm. "WS" was measured at 36.5cm height. The time was synchronised to the concurrent CRDS measurements (which are UTC) and adjusted for the time lag resulting from pumping vapour from inside the wind tunnel to the CRDS. The timestamps indicate the beginning of the averaging period.

en:
Resource Title: Wind tunnel water vapour isotopic composition
    Size: 46068957 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f2ebc8e9-e757-47a8-8713-8892cb1cb25f/resource/e1ffe37c-e289-4eb5-a65f-af474e56fae7/download/windtunnel2023_vapor_isotopes.txt
    Description: The water vapour and its calibrated isotopic composition sampled inside the wind tunnel at 46cm height during the experiments. The vapour was pumped through a heated copper tube at a rate of 0.2 l/min to the CRDS instrument located in a temperate room outside the cold laboratory. The data has 1 second resolution with the timestamp in UTC (CRDS reference time). The measured variables are the calibrated d18O (‰), dD (‰) and d-excess (‰) signals and the uncalibrated ("H2Oraw", ppmv) and calibrated ("H2Ocali",ppmv) humidity readings of the CRDS and converted to specific humidity ("spechum", g/kg). The isotope data was corrected for its humidity-isotope dependency and referenced against the VSMOW-SLAP scale. Calibration runs were performed daily and details can be found in Wahl et al. (2024) including the Supplementary Materials.

en:
Resource Title: Snow samples - stable water isotopic composition
    Size: 20365 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f2ebc8e9-e757-47a8-8713-8892cb1cb25f/resource/68873e4c-7b30-4f82-b97c-446c80546216/download/windtunnel2023_snow_isotopes.txt
    Description: The dataset contains the stable water isotopic composition (d18O, dD. d-excess) of the snow samples taken during the ring wind tunnel experiments in January and May 2023 at the SLF cold laboratory facilities in Davos. The snow samples were collected in air-tight WhirlPaks and kept frozen at -20°C until they were melted in the closed sampling bags, filtered and 1.8ml were transferred into a 2ml glass vial and shipped to the Paul Scherrer Institut in Villigen, Switzerland where they were analysed following established laboratory procedures. The combined uncertainty on the individual isotopic composition is <0.5‰ for dD and <0.1‰ for d18O which yields an uncertainty of 0.9‰ on d-excess.
Timestamps are given for local Davos time (LT) and synchronised to the CRDS instrument which is in UTC. The "ExpNo" column refers to the experiment numbers given in Wahl et al. (2024), Table 1. The "type" of the snow samples is: "ini" = initial snow before introduction to the wind tunnel, "airborne" = snow sampled out of the air, "acc_in" = inner part of accumulated snow, "acc_out" = outer surface layer of accumulated snow.

blowing-snow

display_name: blowing-snow

cold-lab

display_name: cold-lab

drifting-snow

display_name: drifting-snow

experiments

display_name: experiments

snow-saltation

display_name: snow-saltation

water-isotopes

display_name: water-isotopes

wind-tunnel

display_name: wind-tunnel


en:
This dataset includes the necessary files to reproduce the results presented in Melo et al. (2024):
- code version used in the simulations (also available at the institutional [GitLab repository](https://gitlabext.wsl.ch/atmospheric-models/les-lsm) - tag 'r2024')
- input files to run the simulations
- post-processing scripts (MATLAB and FORTRAN)
- selected raw output files
- post-processed results (MATLAB data files).
 	**Note:** Direct model outputs are not provided because of their size, but they can be shared upon request. They can be reproduced by running the code. The post-processed results allow you to reproduce all figures in Melo et al. (2024).

en: drifting-snow large-eddy-simulation saltation-parameterizations snow-saltation splash aerodynamic-entrainment

en: Understanding snow saltation parameterizations - Reproducibility

aerodynamic-entrainment

display_name: aerodynamic-entrainment

large-eddy-simulation

display_name: large-eddy-simulation

saltation-parameterizations

display_name: saltation-parameterizations

splash

display_name: splash


tree-species-map-of-switzerland

en:
Dominant tree species map of Switzerland
We created a tree species map of Switzerland for the dominant tree species in the forested areas. The spatial resolution of the map is 10 m and the coordinate system is ETRS89-extended / LAEA Europe (EPSG 3035). The map comprises Sentinel-2 index time series from the year 2020, a digital elevation model and species reference data from the Swiss National Forest Inventory. The map is available as raster (.tif) or vector dataset (.gpkg).
**Access will be granted upon request.**
In total, the following 15 species were mapped:
*Abies alba*, *Acer pseudoplatanus*, *Alnus glutinosa*, *Alnus incana*, *Betula pendula*, *Castanea sativa*, *Fagus sylvatica*, *Fraxinus excelsior*, *Picea abies*, *Pinus cembra*, *Pinus mugo arborea*, *Pinus sylvestris*, *Quercus petraea*, *Quercus robur*, *Sorbus aucuparia*.
-br/--br/-
 Approach
-br/--br/-
 Data
- Swiss National Forest Inventory Data (stand species with - 60 % dominance in upper canopy; on at least more than 9 plots dominant)
- Sentinel-2 time series (2020, Indices: CCI, CIRE, NDMI, EVI, NDVI)
- Digital elevation model (DEM) (swissalti3d, 5 m)
- Biogeographical regions (Federal Office for the Environment FOEN)
- Forest mask 2017 (Approach: Waser et al., 2015)
-br/--br/-
 Modeling approach
We identified the most meaningful variables that led to separation of the respective groups by using random forest models with a forward feature selection (Meyer et al., 2018; Ververidis & Kotropoulos, 2005). In this approach, the final random forest model is solely built from the selected meaningful variables. By identifying meaningful variables, we can determine which variables might influence the grouping. Further, to avoid overfitting and overly optimistic results, we applied 10-fold spatial cross-validation and put all pixels from a plot in the same spatial fold.
The modeling was realized using the CAST package in R (Meyer et al., 2022), based on the well-known caret package (Kuhn, 2022). We used the ranger package in R (Wright & Ziegler, 2017) to implement the random forest models, due to its short computation time.
-br/--br/-
 Training data for modeling
- 295 Sentinel-2, DEM & Biogeographical variables
- 10525 tree species pixels
-br/--br/-
 Selected variables for final model
1. EVI of 2020.05.16
2. NDMI of 2020.03.12
3. CIRE of 2020.04.16
4. NDMI of 2020.07.05
5. CCI of 2020.05.11
6. dem
7. CCI of 2020.08.14
8. NDMI of 2020.08.24
9. CCI of 2020.12.22
10. NDMI of 2020.04.21
11. NDMI of 2020.11.17
12. NDMI of 2020.08.09
13. CIRE of 2020.03.22
14. CIRE of 2020.08.09
14. CCI of 2020.11.02
15. CIRE of 2020.06.10
-br/--br/-
 Overall Accuracy of final model
- 0.759
-br/--br/-
 Nationwide prediction
- Predicted throughout forest mask 2017 (Approach: Waser et al., 2015)
- Not applied on incomplete Sentinel-2 time series (own category in final map: incomplete_ts)
- Applied the Area of Applicability (Meyer 2022) to sort out pixels outside of the feature space; basically where the model had not the same values for pixels as in the available training data
-br/--br/-
-br/--br/-
 *Be aware that the map is only validated with the training data itself, an independent validation with other data sources remains missing*
-br/--br/-
-br/--br/-
 References
- Kuhn, M. (2022). Classification and Regression Training.  6.0-93.
- Meyer, H., Reudenbach, C., Hengl, T., Katurji, M., & Nauss, T. (2018). *Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation*. Environmental Modelling and Software, 101, 1-9. https://doi.org/10.1016/j.envsoft.2017.12.001
- Meyer, H., Milà, C., & Ludwig, M. (2022). *CAST: 'caret' Applications for Spatial-Temporal Models*.  0.7.0.
- Ververidis, D., & Kotropoulos, C. (2005). *Sequential forward feature selection with low computational cost*. 2005 13th European Signal Processing Conference.
- Waser, L., Fischer, C.,Wang, Z., & Ginzler, C. (2015). *Wall-to-Wall Forest Mapping Based on Digital Surface Models from Image-Based Point Clouds and a NFI Forest Definition*. Forests, 6, 12, 4510–4528.
- Wright, M. N., & Ziegler, A. (2017). *ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R*. Journal of Statistical Software, 77(1), 1-17. https://doi.org/doi:10.18637/jss.v077.i01

en: map forest remote-sensing switzerland tree-species

en: Tree species map of Switzerland

title_for_slug: tree-species-map-of-switzerland

format: PNG

forest

display_name: forest

map

display_name: map

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

tree-species

display_name: tree-species


en:
On this repository you can find the monitoring data of the 3 PV power-plants analysed in the article _"Confirmation of the power gain for solar photovoltaic systems in alpine areas"_ (doi: 10.3389/fenrg.2024.1372680) . Each folder contains the following two elements:
1.  **README.txt**  : describes the content of the folder. Especially it describes the plant's monitoring system's architecture and relates it to the various files included in the data sub-folder.  It also provides a detailed description of all processing steps leading to the data sets as available in the data sub-folder and used in the pre-cited article.
3. **data/** : sub-folder containing the file(s) used in the referenced article.

en: alps bifaciality winter-electricity photovoltaic snow

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en: Monitoring data sets of alpine photovoltaic power-plants

en:
Resource Title: A2.zip
    Size: 27177550 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/40024d58-c912-499e-8f4f-8a9b9189955a/resource/e68bb1d0-915a-49a5-a108-c607356b1889/download/a2.zip
    Description: Title: Monitoring data set at A2 (utility-scale power-plant Muttsee), months 10.2022-09.2023
Provider: AXPO - IWB Industrielle Werke Basel
Last edition: 17.01.2024
Editor: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL

File name structure:
The power-plant is made of 23 string boxes (GAK) and inverters (WR) named after their given number. One file per device is provided in the data/ subfolder, following the same naming convention  (e.g. for the string box number 1, the file name is: “A2_GAK01.csv” and for the corresponding inverter, the file name is “A2_WR01.csv”). Refer to the publication for further details on the setup of the power plant.

File format:
All files are provided in the CSV format.

Column headings:
	String boxes and inverters (GAK & WR):
	⁃	device_name (string): name of the device (same as file name)
	⁃	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC

	String boxes (GAK):
	⁃	I_# (double): input current from the substring number # (W)
	⁃	I_SUM (double): output current of string box (A)
	⁃	U_DC (double): output voltage of string box (V)
	⁃	P_DC_# (double):  input DC power from the substring number # (W)
	⁃	P_DC (double): output DC power of string box (W)
	⁃	$S$_T#_$T$ (double): temperature from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S)  of table T. Two types of temperature measurements (#) are available: 1=standard cell temperature (°C) , 2=module temperature on the rear side (°C) .
	⁃	$S$_SRAD_T (double): poa irradiation (W/m**2) from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S)  of table T.

		Inverters (WR):
	⁃	I_DC (double): input DC current(A)
	⁃	U_DC(double): input DC voltage(V)
	⁃	P_DC (double): input DC power (W)
	⁃	P_AC (double): output AC power (W)

Preprocessing:
	1. Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.

	2. Missing data:
	⁃	Data holes of less or equal to 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).

	3. Wiring losses:
	⁃	To be consistent with A1, wiring losses are corrected at A2. The wiring loss between the string boxes and the inverters is removed by multiplying the value of input P_DC at the inverter level (P_DC,inv) by the mean ratio P_DC,inv / P_DC,arr.
	⁃	The computed mean wiring loss is 2.3\%. It is computed from 2023-02-01 to 2023-09-30, after the long data hole in the data sets of the string boxes.

Mean uptime:
	Raw:
	⁃	WR: 98.2%
	⁃	GAK*: 38.5%
	Processed:
	⁃	WR: 99.6%
	⁃	GAK*: 56.4%

	*The uptime at the string box level (GAK) is low because PMUs at this level shut down during steady and low signal leading to unavailable data at night. In addition, the 23 days downtime of 	January 2023 could not be interpolated nor replaced.

en:
Resource Title: A1.zip
    Size: 5999205 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/40024d58-c912-499e-8f4f-8a9b9189955a/resource/1a7597fd-203a-427f-851a-009673c29374/download/a1.zip
    Description: Title: Monitoring data set at A1 (test-site of Totalp), years 2018-2022
Provider: ZHAW - EKZ

Edition: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
Last edition: 17.01.2024

File name structure:
The test site contains 6 segments named from A to F. The six files provided in the data/ subfolder follow the same naming convention (e.g. for segment A, the file name is: “A1_A.csv”). Refer to the publication for further details on the setups of the segments.

File format:
All files are provided in the CSV format.

Column headings:
	•	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	•	poa_front (double): front plane-of-array irradiation (W/m**2)
	•	poa_back (double): rear plane-of-array irradiation (W/m**2)
	•	mod_temp (double): module’s temperature (°C)
	•	P_AC (double): output AC power (W)

Preprocessing:
	Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.

	Missing data:
	⁃	Data holes of less than 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).

	Wiring losses :
	⁃	As described in [1] , the test-site setup caused abnormally large wiring losses,  mainly due to the distance to optimisers and to the low installed power per DC-wire.
	⁃	The wiring losses comprised between 10% and 15%, are averaged hourly and added to the measured DC power.

	Misc.:
	⁃	P_AC is computed for each segment based on the measured DC power and the average inverter’s efficiency (96.1%).
	⁃	As described in [1],  the peak power of the installed module, used to compute the final yield is slightly different from the values announced by the manufacturer.

Mean uptime:
	Raw:
	⁃	95.2%
	Processed:
	⁃	100%

References:
[1] 	D. Anderegg, S. Strebel, and J. Rohrer, “Alpine Photovoltaik Versuchsanlage Davos Totalp : Erkenntnisse aus 5 Jahren Betrieb,” de, Sep. 	2023, Accepted: 2023-09-29T09:13:16Z Publisher: ZHAW Zürcher Hochschule für Angewandte Wissenschaften.DOI: 10.21256/	zhaw-2524. [Online]. Available: https://digitalcollection.zhaw.ch/handle/11475/28797 (visited on 12/15/2023).

alps

display_name: alps

bifaciality

display_name: bifaciality

photovoltaic

display_name: photovoltaic

snow

display_name: snow

winter-electricity

display_name: winter-electricity


en:
Environmental DNA complements scientific trawling in surveys of marine fish biodiversity (Dataset 2019)
In October 2019 we chose 15 sites from the 2019 EVHOE survey for eDNA sampling. The French international EVHOE bottom trawl survey is carried out annually during autumn in the BoB to monitor demersal fish resources. At each site, we sampled seawater using Niskin bottles deployed with a circular rosette. There were nine bottles on the rosette, each of them able to hold ∼5 l of water. At each site, we first cleaned the circular rosette and bottles with freshwater, then lowered the rosette (with bottles open) to 5 m above the sea bottom, and finally closed the bottles remotely from the boat. The 45 l of sampled water was transferred to four disposable and sterilized plastic bags of 11.25 l each to perform the filtration on-board in a laboratory dedicated to the processing of eDNA samples. To speed up the filtration process, we used two identical filtration devices, each composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 l min–1 ), a VigiDNA 0.20 μm filtration capsule (SPYGEN, le Bourget du Lac, France), and disposable sterile tubing. Each filtration device filtered the water contained in two plastic bags (22.5 l), which represent two replicates per sampling site. We followed a rigorous protocol to avoid contamination during fieldwork, using disposable gloves and single-use filtration equipment and plastic bags to process each water sample. At the end of each filtration, we emptied the water inside the capsule that we replaced by 80 ml of CL1 conservation buffer and stored the samples at room temperature following the specifications of the manufacturer (SPYGEN, Le Bourget du Lac, France). We processed the eDNA capsules at SPYGEN, following the protocol proposed by Polanco-Fernández et al., (2020). We performed library preparation and sequencing at Fasteris (Geneva, Switzerland). Specifically, we prepared four libraries using the MetaFast protocol (a ligation-based method) and sequenced them separately. We carried out paired-end sequencing using a MiSeq sequencer (2 × 125 bp, Illumina, San Diego, CA, USA) on two MiSeq Flow Cell Kits (v3; Illumina), following the manufacturer’s instructions. We analysed the sequence reads using the OBITools package (http://metabarcoding.org/obitools; Boyer et al., 2016), following the protocol described by Valentini et al. (2016).
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: edna teleo bayofbiscay metabarcoding atlantic-region fish-composition actinopterygii chondrichthyes

en: Environmental DNA Marine France Evhoe 2019

envi

en: Environment

actinopterygii

display_name: actinopterygii

atlantic-region

display_name: atlantic-region

bayofbiscay

display_name: bayofbiscay

chondrichthyes

display_name: chondrichthyes

edna

display_name: edna

fish-composition

display_name: fish-composition

metabarcoding

display_name: metabarcoding

teleo

display_name: teleo


en: Data (Quantitative Wood Anatomy, Maximum Latewood Density, Volumetric Density, holo-cellulose-to-wood-ratio) used in the manuscript "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy". Wood samples stem from Larix sibirica collected in the Yamal region, northeastern Siberia, Russia. We investigated wood properties of living trees and subfossil wood buried in riverbank sediments, dated to approximately -2760 to -2600 BCE. Our goal was to evaluate the integrity of climate proxies in sub-fossil wood and develop practical methods to detect wood degradation when reconstructing Late Holocene and Common Era climate conditions using tree-ring data.

en: temperature-reconstruction tree-ring paleoclimate wood-anatomy mxd

en: Quantitative Wood Anatomy and Maximum Latewood Density from Yamal peninsula

en:
Resource Title: Figure3_dataset.txt
    Size: 8581 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/743a897f-26e7-4871-a014-b0f95238564d/resource/2435516e-8dfc-4347-a35c-893eadcdf569/download/figure3_dataset.txt
    Description: This dataset contains the mean chronologies of MXD and QWA of the relict and living wood material presented in Figure 3. It also contains the JJA temperature record of the Salekhard Meteo station.

en:
Resource Title: Figure2_dataset.csv
    Size: 1668 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/743a897f-26e7-4871-a014-b0f95238564d/resource/b0e00f50-78a2-4006-ab8d-7d4d796efc05/download/bulkdensity.csv
    Description: This dataset contains data presented in Figure 2 in the paper "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy".

Sample ID = Sample ID
group = living or relict wood material
Bulk wood density = volumetric measured density (kg / m^3)
Mean Tree Ring Density	= Density derived via X-ray densitometry (kg / m^3)
Cellulose_to_wood ratio = Holo-cellulose-to-wood ratio
Anatomical density = Area of cell wall / (area of cell wall + lumen area)

format: CSV

media_type: text/csv

mxd

display_name: mxd

paleoclimate

display_name: paleoclimate

temperature-reconstruction

display_name: temperature-reconstruction

tree-ring

display_name: tree-ring

wood-anatomy

display_name: wood-anatomy


en:
Transport infrastructure such as **highways** are important corridors for the spread of invasive species. In this project, an automated detection and mapping of **two invasive alien plant species**  was developed and applied along highways in the **Swiss Central Plateau**, based on **artificial intelligence (AI, Deep Learning)**. The two target species are **tree of heaven *(Ailanthus altissima)*** and **narrow-leaved ragwort *(Senecio inaequidens)***.
The data is part of the project report and shows the mapping results in **interactive maps**. Technically speaking, these are **self-contained HTML files** that can be displayed with standard web browsers. To reduce the file size, the downloads are provided in zip format.
**Report**: [https://www.mobilityplatform.ch/de/research-data-shop/product/1690](https://www.mobilityplatform.ch/de/research-data-shop/product/1690)
**Project**: [https://www.wsl.ch/en/projects/automated-detection-of-invasive-alien-plants-along-highways/](https://www.wsl.ch/en/projects/automated-detection-of-invasive-alien-plants-along-highways/)

en: automatic-detection artificial-intelligence computer-vision invasive-species plants biological-invasions

en: Automated detection of invasive alien plants along highways

en:
Resource Title: Ailanthus_maxF1_Pts_strips_v2024.html.zip
    Size: 18633094 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1bf97970-cc9e-4101-aaf3-b47a3906e7a1/resource/8a96b1cf-2d57-45f4-bc79-280dd5603f99/download/ailanthus_maxf1_pts_strips_v2024.html.zip
    Description: Detected occurrences of Ailanthus altissima along highways on the Swiss Plateau. The number of image tiles in which the species was recognized is shown (Fig. 23 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

en:
Resource Title: Senecio_frame_min3_Pts_strips_v2024.html.zip
    Size: 21519085 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1bf97970-cc9e-4101-aaf3-b47a3906e7a1/resource/0b6a46c9-53e5-4420-a77a-883b2e4ac351/download/senecio_frame_min3_pts_strips_v2024.html.zip
    Description: Detected occurrences of Senecio inaequidens along highways on the Swiss Plateau. To reduce false-positives, only images in which the species was recognized in at least three of 16 image tiles are considered as occurrences (Fig. 40 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

en:
Resource Title: Ailanthus_frame_min3_Pts_strips_v2024.html.zip
    Size: 18185776 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1bf97970-cc9e-4101-aaf3-b47a3906e7a1/resource/26102858-9e76-41ac-b4b9-7e1a9f03dd02/download/ailanthus_frame_min3_pts_strips_v2024.html.zip
    Description: Detected occurrences of Ailanthus altissima along highways on the Swiss Plateau. To reduce false-positives, only images in which the species was recognized in at least three of 16 image tiles are considered as occurrences (Fig. 38 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

en:
Resource Title: Senecio_maxF1_Pts_strips_v2024.html.zip
    Size: 24847774 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1bf97970-cc9e-4101-aaf3-b47a3906e7a1/resource/ffd01a5d-4711-4bc7-b1fd-8afe0db89e50/download/senecio_maxf1_pts_strips_v2024.html.zip
    Description: Detected occurrences of Senecio inaequidens along highways on the Swiss Plateau. The number of image tiles in which the species was recognized is shown (Fig. 25 in the report). Image coordinates of the middle and side strips can be displayed separately in the interactive map.

artificial-intelligence

display_name: artificial-intelligence

automatic-detection

display_name: automatic-detection

biological-invasions

display_name: biological-invasions

computer-vision

display_name: computer-vision

invasive-species

display_name: invasive-species

plants

display_name: plants


en:
Data on the diet of urban and rural bumblebees individuals, Bombus lapidarius and Bombus pascuorum, collected in Switzerland (cantons Bern, Basel and Zürich) obtained using metabarconding and chemical analyses from two pollen transportation structures, that is, the body and the leg-baskets (i.e., corbicula). The bumblebees were collected by Egenberger et al., 2019 (https://doi.org/10.5061/dryad.qt8mr4v)
The data contains:
- The composition and relartive abundance of plant species in the body and the leg-baskets, separately.
- The content and ratios of two groups of macronutrients, that is, amino acids and fatty acids.
The dataset contains the data used in the paper "Urban bumblebees diversify their foraging strategy to maintain nutrient intake" as well as unpublished data.

en: urban bern rural basel macronutrients pollen-metabarcoding zurich bombus-lapidarius lad-use-chages nutrient-intake dietary-patterns foraging-behaviour bumblebees bombus-pasquorum bees

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Dataset6_Functional_Diversity.csv
    Size: 86806 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/06afcb49-cc9f-45da-b64f-5860c277d498/download/dataset6_functional_diversity.csv
    Description: Processed data. The dataset contains the functional diversity metrics based on the plant composition from the leg-baskets per bumblebee individual. It contains:

- SampleID: Combining bumblebee ID, location, landscape and replica
- Location: canton, levels: Bern =BE; Basel = BS; Zurich =ZH
- Landscape: landscape type, levels: Urban = U; Rural = R
- Replicate: sampling place (800-m buffer) within location and landscape. Levels:  A-E.
- LocationLandscape: combining location and landscape
- Bumblebee_species: the two studied species, levels: B.pasquorum; B. lapidarius
- Fric.w: Weighted functional richness
-Fric: functional richness
-FEve.w: Weighted functional evenness
- FEve: functional evenness
- FDiv.w: weighted functional divergence
- FDiv: functional divergence

en:
Resource Title: Dataset2_sites.csv
    Size: 1248 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/75bace68-f772-4103-9fdf-8395ce1c3d51/download/dataset2_sites.csv
    Description: The dataset contains the information on the 16 study sites:

- Location: the three Swiss cantons studied. Levels: Bern =BE; Basel = BS; Zurich =ZH
- Landscape: the two typea of human-dominated ecosystems, nested to the Swiss canton. Levels: Urban = U; Rural = R
- Replicate: sampling place (800-m buffer) nested with the location and the landscape. Levels:  A-E.
- Site_ID: combination of location, landscape and replicate
- X: X coordinate, WGS84
- Y: Y coordinate WGS84
- Plant S in landscape: Plant species richness within the 800 m calculated using both information from the Global Biodiversity Information. Facility (GBIF) and InfoFlora (www.infoflora.ch).
- % Buildings: the proportion of buildings and other impervious surfaces within 800 m radius.
- % Agricultural: the proportion of agricultural land and other impervious surfaces within 800 m radius.
- % Water: the proportion of water and other impervious surfaces within 800 m radius.
- % Meadows & grasslands: the proportion of meadows and grasslands and other impervious surfaces within 800 m radius.

The raw metabarcoding data is archived in NCBI project PRJNA1137320.

en:
Resource Title: Dataset7_Phylogenetic_Diversity.csv
    Size: 74413 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/f34a3f6e-91f3-4619-a258-8e4408050032/download/dataset7_phylogenetic_diversity.csv
    Description: Processed data. The dataset contains the phylogeneitc diversity metrics based on the plant composition from the leg-baskets per bumblebee individual. It contains:

- SampleID: Combining bumblebee ID, location, landscape and replica
- Location: canton, levels: Bern =BE; Basel = BS; Zurich =ZH
- Landscape: landscape type, levels: Urban = U; Rural = R
- Replicate: sampling place (800-m buffer) within location and landscape. Levels:  A-E.
- LocationLandscape: combining location and landscape
- Bumblebee_species: the two studied species, levels: B.pasquorum; B. lapidarius
- PVar: phylogenetic variance
- PRic: Phylogenetic richness
- PEve: Phylogenetic evenness
- PClu: Phylogenetic clustering

en:
Resource Title: Dataset5_Species_richness.csv
    Size: 14377 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/79d981d0-0c62-4e78-810f-750644a08176/download/dataset5_species_richness.csv
    Description: Processed data. The dataset contains the plant species richness in the leg-baskets per bumblebee individual. It contains:

- SampleID: Combining bumblebee ID, location, landscape and replica
- Location: canton, levels: Bern =BE; Basel = BS; Zurich =ZH
- Landscape: landscape type, levels: Urban = U; Rural = R
- Replicate: sampling place (800-m buffer) within location and landscape. Levels:  A-E.
- LocationLandscape: combining location and landscape
- Bumblebee_species: the two studied species, levels: B.pasquorum; B. lapidarius
- Plant species richness: the number of plant species found in the pollen of the leg-baskets.

en:
Resource Title: Dataset8_PlantTraits.csv
    Size: 33177 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/79128caa-e0a4-43d6-8b60-ff111075a984/download/dataset8_planttraits.csv
    Description: The dataset contains the plant trait values obtined from published sources. It contains:
- Kingddom: taxonomic
- Phylum: taxonomic
- Order: taxonomic
- Family: taxonomic
- Genus: taxonomic
- Species: species name
- plant.species: full scientific name
- native_exotic: origin status. As presented in https://www.doi.org/10.16904/envidat.210
- pollination mode: vector of pollination. As presented in https://www.doi.org/10.16904/envidat.210
- Flowering_months_duration: Number of flowering months. As presented in https://www.doi.org/10.16904/envidat.210
- start_flowering: month of the starting of the flowering. As presented in https://www.doi.org/10.16904/envidat.210
- growth_form_category: plant growth form. As presented in https://www.doi.org/10.16904/envidat.210
- plant-height: plant heght in meters. As presented in https://www.doi.org/10.16904/envidat.210
- inflorescence: Logic, plant with single flowers (0) or inflorescences (1). As presented in https://www.doi.org/10.16904/envidat.210
- structural_blossom_class: depicting the accessibility of the flowers. As presented in https://www.doi.org/10.16904/envidat.210
- symmetry: floral symmetry. As presented in https://www.doi.org/10.16904/envidat.210
- nectar: logic, nectar present. As presented in https://www.doi.org/10.16904/envidat.210
- pollen: logic, pollen rewards present. As presented in https://www.doi.org/10.16904/envidat.210
- oil: logic. oil present. As presented in https://www.doi.org/10.16904/envidat.210
- sugar.concentration: the amount of sugar present in the nectar, in mg.

Additional information can be found in https://doi.org/10.1016/j.dib.2021.107243

en:
Resource Title: Dataset1_Composotion_pollen.csv
    Size: 709634 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/0fd97e8a-015e-4f9b-8c28-14ce1ae4dc6a/download/dataset1_metabarcoding_pollen.csv
    Description: The dataset contains the filtered plant composition1  (removing species with too low relative abundances) and the relative abundance obtained from DNA metabarcoding on pollen samples for both the leg-baskets and the body. The dataset contains the following columns:

- SampleID: Combining bumblebee ID, location, landscape and replica
- Abundance: numeric, relative abundance
- BumblebeeID: numerical ID for each bumblebee individual within a location, landscape and replicate sampling place.
- Location: canton, levels: Bern =BE; Basel = BS; Zurich =ZH
- Landscape: landscape type, levels: Urban = U; Rural = R
- Replicate: sampling place (800-m buffer) within location and landscape. Levels:  A-E.
- LocationLandscape:
- Bumblebee_species: the two studied species, levels: B.pasquorum; B. lapidarius
- Transportation_structure: bumblebee pollen transportation structure, levels: B = Body; L = leg-baskets (i.e. corbicula)
- Kingddom: taxonomic
- Phylum: taxonomic
- Order: taxonomic
- Family: taxonomic
- Genus: taxonomic
- Species: plant sicentific name
-Binomial_abundance: Logic, indicating if the plant species is included (1).

The raw metabarcoding data is archived in NCBI project PRJNA1137320

en:
Resource Title: Dataset4_Fattyacids.csv
    Size: 58574 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/0b2c5c45-629f-4b01-8c58-535c06c74fb2/download/dataset4_fattyacids.csv
    Description: The dataset contains the fatty acid content and ratios for the two bumblebees. Measures are taken only from pollen from the leg-baskets. SampleID is not the same as in the metabarcoding, several samples from different bumblebees were merged within a Location ,Landscape and Replica. Not for all the samples there is information on both amino acids and fatty acids. The columns are:

- SampleID_chemical: The ID for chemical analyses
- Location: the three Swiss cantons studied. Levels: Bern =BE; Basel = BS; Zurich =ZH
- Landscape: the two typea of human-dominated ecosystems, nested to the Swiss canton. Levels: Urban = U; Rural = R
- Replicate: sampling place (800-m buffer) nested with the location and the landscape. Levels:  A-E.
- Bumblebee_species: the two studied species, levels: B.pasquorum; B. lapidarius
- LocationLandscape: combination between location and landscape
- Caprylic, Pelargonic, ..., Lacceroic: Content of individual fatty acids acids.
- sum: total sum of fatty acid content (mg)
- unsaturatedsum: total sum unsaturated fatty acids (mg)
- saturatedsum: total sum saturated fatty acids (mg)
- omega3sum: total sum Omega 3 fatty acids (mg)
- omega6sum: total sum Omega 6 fatty acids (mg)
- omega9sum: total sum Omega 9 fatty acids (mg)
- omega6to3ratio: ratio Omega 6 to Omega3 fatty acids
-saturatedtounsaturatedration: ratio between saturated and unsaturated fatty acids

en:
Resource Title: Dataset3_Aminoacids.csv
    Size: 23314 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ae82037f-c201-4f1d-9a57-162a25264ddb/resource/ce8bb95f-caaf-4959-a7c9-07bf93806939/download/dataset3_aminoacids.csv
    Description: The dataset contains the amino acid content and ratios for the two bumblebees. Measures are taken only from pollen from the leg-baskets. SampleID is not the same as in the metabarcoding, several samples from different bumblebees were merged within a Location ,Landscape and Replica. Not for all the samples there is information on both amino acids and fatty acids. The columns are:

- SampleID_chemical: The ID for chemical analyses
- Location: the three Swiss cantons studied. Levels: Bern =BE; Basel = BS; Zurich =ZH
- Landscape: the two typea of human-dominated ecosystems, nested to the Swiss canton. Levels: Urban = U; Rural = R
- Replicate: sampling place (800-m buffer) nested with the location and the landscape. Levels:  A-E.
- Bumblebee_species: the two studied species, levels: B.pasquorum; B. lapidarius
- LocationLandscape: Combining location and landscape
- Asp,  Thr, ..., Arg: Content of individual amino acids. Amino acids are written as abbreviated names. FUll names be checked here: https://en.wikipedia.org/wiki/Amino_acid
- sum: total sum of amino acid content (mg)
- sumessential: total sum essential amino acids  (mg)
-sumnon-essential: total sum non-essential amino acids (mg)
- proportionnonessentialessential: proportion between essential and non-essential amino acids.

basel

display_name: basel

bees

display_name: bees

bern

display_name: bern

bombus-lapidarius

display_name: bombus-lapidarius

bombus-pasquorum

display_name: bombus-pasquorum

bumblebees

display_name: bumblebees

dietary-patterns

display_name: dietary-patterns

foraging-behaviour

display_name: foraging-behaviour

lad-use-chages

display_name: lad-use-chages

macronutrients

display_name: macronutrients

nutrient-intake

display_name: nutrient-intake

pollen-metabarcoding

display_name: pollen-metabarcoding

rural

display_name: rural

urban

display_name: urban

zurich

display_name: zurich


en:
This dataset includes geomorphic predictors and plant biodiversity patterns in the Hengduan Mountains, published in the Geological Society of London special volume: Asian Geodynamics, Climate and Biodiversity (https://doi.org/10.1144/SP549-2024-17).
The geomorphic predictors include catchment-restricted relief and chi maps, while the climate predictors comprise site water balance, growing degree days, and climate change velocity from the Last Glacial Maximum (LGM) to the present.
The plant biodiversity patterns are represented by a plant richness map for 13,321 species in the Hengduan Mountains. Species-level plant range maps are available in the dataset, previously published under DOI: 10.16904/envidat.424.

en: tectonic-faults plant-biodiversity endemism climate-history relief

en: Tectonic and climatic controls on plant biodiversity in the Hengduan Mountains China

envi

en: Environment

climate-history

display_name: climate-history

endemism

display_name: endemism

plant-biodiversity

display_name: plant-biodiversity

relief

display_name: relief

tectonic-faults

display_name: tectonic-faults


en:
Soil chemical and biological properties of soils affected by 10 different perturbations related with global change, applied individually or in combination. Greenhouse experiment. Perturbations applied to intact soil cores (15 cm diameter, 15 cm deep) collected in an extensively managed grassland on the WSL grounds in June 2023.
This dataset contains all data on which the publication below was based:
"Fioratti Junod M, Gombeer S, Holmes J, Zimmerman S, Rillig M, Risch AC and Cordero I. Soil functionality declines under multiple superimposed global change perturbations. XXXX "
Please, cite this publication together with the citation of the datafile.
Database includes:
Pot_ID: pot or soil core identifier.
Batch: numeric, 1 or 2.
Enzyme_plate: numeric, from 1 to 6.
Number_of_perturbations: numeric, from 0 to 10.
N_addition: binary. Yes = 1, No = 0.
P_addition: binary. Yes = 1, No = 0.
Defoliation: binary. Yes = 1, No = 0.
Trampling: binary. Yes = 1, No = 0.
Insecticide: binary. Yes = 1, No = 0.
Fungicide: binary. Yes = 1, No = 0.
Herbicide: binary. Yes = 1, No = 0.
Antibiotic: binary. Yes = 1, No = 0.
Drought: binary. Yes = 1, No = 0.
Heat_wave: binary. Yes = 1, No = 0.
Treatment: character. Description of the treatment, 15 levels.
SWC: soil water content. Numeric, unitless.
Green_biomass: green plant biomass. Numeric, g.
Brown_biomass: brown or dead plant biomass. Numeric, g.
Biomass_cut: plant biomass cut during defoliation treatments. Numeric, g.
CO2_flux_light: net CO2 flux under ambient light. Numeric, mg CO2 m-2 h-1.
CO2_flux_dark: ecosystem respiration. Numeric, mg CO2 m-2 h-1.
S: organic matter stabilisation factor (tea bag index). Numeric, unitless.
k: organic matter decomposition rate (tea bag index). Numeric, unitless.
DOC: dissolved organic carbon, mg Kg-1 dry soil.
IC: inorganic carbon, mg Kg-1 dry soil.
Ammonium_KCl:  plant available ammonium, mg Kg-1 dry soil.
Nitrate_KCl:  plant available nitrate, mg Kg-1 dry soil.
Phosphate: phosphate, mg Kg-1 dry soil.
MBC: microbial biomass carbon,  mg Kg-1 dry soil.
MBN: microbial biomass nitrogen,  mg Kg-1 dry soil.
PHO: phosphatase activity, nmol h-1 g-1 dry soil.
BG: β-glucosidase, nmol h-1 g-1 dry soil.
XYL: xylosidase, nmol h-1 g-1 dry soil.
CBH: cellobiohydrolase, nmol h-1 g-1 dry soil.
NAG: N-acetylglucosaminidase, nmol h-1 g-1 dry soil.
LAP: leucine aminopeptidase, nmol h-1 g-1 dry soil.
POX: phenoloxidase, nmol h-1 g-1 dry soil.
PER: peroxidase, nmol h-1 g-1 dry soil.
pH: soil pH, unitless
Water_stable_aggregates: water stable aggregates, %
Surface_infiltration_time: water surface infiltration time, s.

en: heatwave pesticide soil-nutrients land-use drought soil-biodiversity soil

en: Escalating effects of multiple perturbations on soil functionality

drought

display_name: drought

heatwave

display_name: heatwave

land-use

display_name: land-use

pesticide

display_name: pesticide

soil

display_name: soil

soil-biodiversity

display_name: soil-biodiversity

soil-nutrients

display_name: soil-nutrients


en:
Continuous measurement of soil matrix potential at 15, 50 and 100 cm depth with Decagon MPS-2 sensors  1 m N, SE and SW from the stem of 3 threes within much and 3 trees within few shrubs
 Purpose:
Explore the effect of shrubs on the water availability for pine trees in Visp.

en: icp-forests soil-water-matrix-potential swiss-forest-lab long-term-forest-ecosystem-research shrubs

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: MPS-2 on LWF Visp to survey 2017 mortality wave

format: HTML

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

shrubs

display_name: shrubs

soil-water-matrix-potential

display_name: soil-water-matrix-potential

swiss-forest-lab

display_name: swiss-forest-lab


stemflow-lwf

en:
Stemflow (portion of precipitation running down the branches and the trunk and depositing at the base of the tree) can represent a substantial fraction of the total water and nutrient input in stands of smoothbarked species with upright branches. Stemflow was measured with silicone gutters installed on the trunk of 5 trees at three LWF plots during 1-2 years. High capacity containers were used at Novaggio. An automated tipping bucket system, allowing continuous recording of volumes and sampling of representative proportional fraction, is currentlx used at the LWF sites Laegeren, Lausanne, Othmarsingen and Schänis.
 Purpose:
To quantify the contribution of stemflow to the water and nutrient budget and to the atmospheric deposition in selected forests stands.
 Manual Citation:
 * Thimonier, A., Brang, P., Wenger, K., 1997. Kapitel C4. Atmosphärische Deposition: Freiland- und Bestandesniederschläge, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-48.
 *  Clarke  N,  Žlindra  D,  Ulrich  E,  Mosello  R,  Derome  J,  Derome  K,  König  N,  Lövblad  G,  Draaijers  GPJ,  Hansen K, Thimonier A, Waldner P, 2016: Part XIV: Sampling and Analysis of Deposition. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling,  assessment,  monitoring  and  analysis  of the  effects  of  air  pollution  on  forests.  Thünen  Institute    of    Forest    Ecosystems,    Eberswalde,    Germany,    32    p.    +    Annex    [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

en: swiss-forest-lab stemflow long-term-forest-ecosystem-research chemical-composition icp-forests

envidat

en: EnviDat: the Environmental Data Portal

en: Stemflow LWF

title_for_slug: stemflow-lwf

chemical-composition

display_name: chemical-composition

stemflow

display_name: stemflow


en:
Throughfall (precipitation under forest canopy) is a major pathway in forest nutrient cycling, and its quantification is necessary to establish both water and nutrient budgets. Furthermore, parallel sampling of throughfall and precipitation in the open field (bulk precipitation), together with assumptions about the canopy exchange processes (uptake and leaching of nutrients), allow the atmospheric deposition of nutrients and pollutants to be quantifed. Bulk precipitation and throughfall have been sampled since 1994 or later on 15 LWF plots using 3 (in the open) and 16 (in the forest) funnel-type precipitation collectors. These collectors are replaced by 1 (open area) and 4 (forest stand) snow buckets in winter on plots with abundant precipitation in the form of snow. The length of sampling intervals is usually 14 days.
 Purpose:
To assess a major flux of the water and nutrient budget in forests, and to quantify the atmospheric deposition of nitrogen, sulphur and other nutrients. Atmospheric deposition is one of the key factors in the causal chain between emission of air pollutants and acidifying or eutrophying effects in forest ecosystems.
 Manual Citation:
 * Thimonier, A., Brang, P., Wenger, K., 1997. Kapitel C4. Atmosphärische Deposition: Freiland- und Bestandesniederschläge, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-48.
 *  Clarke  N,  Žlindra  D,  Ulrich  E,  Mosello  R,  Derome  J,  Derome  K,  König  N,  Lövblad  G,  Draaijers  GPJ,  Hansen K, Thimonier A, Waldner P, 2016: Part XIV: Sampling and Analysis of Deposition. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling,  assessment,  monitoring  and  analysis  of the  effects  of  air  pollution  on  forests.  Thünen  Institute    of    Forest    Ecosystems,    Eberswalde,    Germany,    32    p.    +    Annex    [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Thimonier A, Schmitt M, Waldner P, Rihm B (2005) Atmospheric deposition on Swiss Long-term Forest Ecosystem Research (LWF) plots. Environmental Monitoring and Assessment, 104: 81-118. [doi: 10.1007/s10661-005-1605-9](http://doi.org/10.1007/s10661-005-1605-9)
 *  Thimonier A, Kosonen Z, Braun S, Rihm B, Schleppi P, Schmitt M, Seitler E, Waldner P, Thöni L (2019) Total deposition of nitrogen in Swiss forests: Comparison of assessment methods and evaluation of changes over two decades. Atmospheric Environment, 198: 335-350. [doi: 10.1016/j.atmosenv.2018.10.051](http://doi.org/10.1016/j.atmosenv.2018.10.051)

en: atmospheric-deposition nitrogen swiss-forest-lab acidity long-term-forest-ecosystem-research base-cations icp-forests

en: Atmospheric deposition (throughfall and bulk deposition) LWF

acidity

display_name: acidity

atmospheric-deposition

display_name: atmospheric-deposition

base-cations

display_name: base-cations

nitrogen

display_name: nitrogen


phenological-observations-lwf

en:
Phenological observations are recorded every 14 days on LWF plots where throughfall and bulk precipitation are sampled. The percentage of foliage in reference to its maximum potential development in summer, the percentage of foliage with autumnal discoloration and the percentage of fallen leaves (broadleaved stands) are estimated at the plot level. At two LWF plots (Othmarsingen, Vordemwald), phenological stages are documented on individual trees
 Purpose:
To document the seasonal development of the canopy of trees and shrubs at the plot level

en: precipitation long-term-forest-ecosystem-research tree-phenology icp-forests swiss-forest-lab

en: Phenological observations LWF

title_for_slug: phenological-observations-lwf

precipitation

display_name: precipitation

tree-phenology

display_name: tree-phenology


leaf-area-index-lai-lwf

en:
Leaf area index (LAI), defined as the total one-sided foliage area per unit ground surface area, is one of the most important characteristics of plant canopy structure. Leaves are the active interface between the atmosphere and the ecosystem. Thus, LAI affects many ecosystem processes, including light and precipitation interception, evapotranspiration, CO2 fluxes and dry deposition. LAI was measured repeatedly in the period 1996-2013 at 18 LWF plots using 1) a LAI-2000 plant canopy analyser (Licor, Inc) and 2) hemispherical photographs of the canopy. Measurements were performed above the 16 vegetation quadrats in the 43 m x 43 m intensive monitoring subplot. In 1996-2003, LAI measurements were usually carried out on the same day as the vegetation surveys. It is also planned to characterise the potential light conditions (diffuse and direct) using the hemispherical photographs of the canopy.
 Purpose:
1) To estimate an important structural parameter of the forest stand, which is needed as an input variable in most ecosystem process models simulating carbon and water cycles on a stand or regional scale; and 2) to document changes in the canopy structure, and thus in light conditions, which may be responsible for changes in ground vegetation
 Manual Citation:
 * Thimonier, A., 1997. Kapitel C6. Blattflächenindex (LAI), in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-5.
 *  Thimonier, A., 1997. Kapitel C7. Lichtverhältnisse im Wald, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-4.
 *  Fleck  S,  Raspe  S,  Cater  M,  Schleppi  P,  Ukonmaanaho  L,  Greve  M,  Hertel  C,  Weis  W,  Rumpf,  S.,  Thimonier, A., Chianucci, F., Beckschäfer, P., 2016: Part XVII: Leaf Area Measurements. In: UNECE ICP Forests  Programme  Co-ordinating  Centre  (ed.):  Manual  on  methods  and  criteria  for  harmonized  sampling,  assessment,  monitoring  and  analysis  of  the  effects  of  air  pollution  on  forests.  Thünen  Institute    of    Forest    Ecosystems,    Eberswalde,    Germany,    34    p.    +    Annex    [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Thimonier A, Kull P, Keller W, Moser B, Wohlgemuth T (2011) Ground vegetation monitoring in Swiss forests: comparison of survey methods and implications for trend assessments. Environmental Monitoring and Assessment, 174: 47-63. [doi: 10.1007/s10661-010-1759-y](https://doi.org/10.1007/s10661-010-1759-y)
 *  Thimonier A, Sedivy I, Schleppi P (2010) Estimating leaf area index in different types of mature forest stands in Switzerland: a comparison of methods. European Journal of Forest Research, 129 (4): 543-562. [10.1007/s10342-009-0353-8](https://doi.org/10.1007/s10342-009-0353-8)

en: icp-forests swiss-forest-lab leaf-area-index foliage long-term-forest-ecosystem-research

en: Leaf area index (LAI) LWF

title_for_slug: leaf-area-index-lai-lwf

envi

en: Environment

foliage

display_name: foliage

leaf-area-index

display_name: leaf-area-index


permanent-vegetation-quadrats-lwf

en:
Ground vegetation is an important compartment of the ecosystem in terms of biodiversity and it takes an active part in the general functioning of the ecosystem. It is also a useful bio-indicator of the site conditions and its monitoring may enable the detection of environmental changes. Ground vegetation relevés were carried out repeatedly at 17 LWF plots during in the the period between 1994 and 2011. In 2013, ground vegetation was surveyed at an additional LWF plot (Laegeren). The cover of all plant species occurring in 16 1-m2 quadrats, distributed over the 43 x 43 m intensive monitoring subplot was visually assessed. Seedlings and saplings were also counted and their position within the quadrat was noted in order to assess tree regeneration.
 Purpose:
To assess the species diversity of ground vegetation and detect possible environmental changes using its bio-indicator value.
 Manual Citation:
 * Kull, P., 1997. Kapitel D2. Vegetationsaufnahmen. In: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-9.
 * Canullo  R,  Starlinger  F,  Granke  O,  Fischer  R,  Aamlid  D,  2016:  Part  VI.1:  Assessment  of  Ground  Vegetation. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on  forests.  Thünen  Institute  of  Forest  Ecosystems,  Eberswalde,  12  p.  +  Annex  [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Thimonier A, Kull P, Keller W, Moser B, Wohlgemuth T (2011) Ground vegetation monitoring in Swiss forests: comparison of survey methods and implications for trend assessments. Environmental Monitoring and Assessment, 174: 47-63. [doi: 10.1007/s10661-010-1759-y](http://doi.org/10.1007/s10661-010-1759-y)

en: ground-vegetation long-term-forest-ecosystem-research species-composition icp-forests swiss-forest-lab

en: Permanent vegetation quadrats LWF

title_for_slug: permanent-vegetation-quadrats-lwf

ground-vegetation

display_name: ground-vegetation

species-composition

display_name: species-composition


litterfall-lwf

en:
Litterfall is a key parameter in the biogeochemical cycle of forest ecosystems, linking the tree part to the soil compartment. Litterfall has been collected on 15 LWF plots using 10 traps that are emptied every 4 to 8 weeks since 1996 or later. Both the biomass of the litter and its chemical content (including heavy metals) are measured, in order to quantify the annual return of nutrients and organic matter to the soil. Furthermore, the analysis of the temporal pattern of litterfall production gives insight into possible effects of anthropogenic and natural factors (e.g. severe drought) on the ecosystem and the vitality of the forest stand, provides information on the phenological development of the stand, and, in particular, allows mast years to be identified. At 7 broadleaved sites, litterfall was also used to estimate the leaf area index (LAI) of the forest stand.
 Purpose:
To quantify the annual return of nutrients and organic matter to the soil.
 Manual Citation:
 * Thimonier, A., Brang, P., Ottiger, A., 1997. Kapitel C5. Streufall, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-18.
 *  Ukonmaanaho  L.,  Pitman  R,  Bastrup-Birk  A,  Breda  N,  Rautio  P,  2016:  Part  XIII:  Sampling  and  Analysis  of  Litterfall.  In:  UNECE  ICP  Forests  Programme  Co-ordinating  Centre  (ed.):  Manual  on  methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute for Forests Ecosystems, Eberswalde, Germany, 14 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Thimonier A, Sedivy I, Schleppi P (2010) Estimating leaf area index in different types of mature forest stands in Switzerland: a comparison of methods. European Journal of Forest Research, 129 (4): 543-562. [doi: 10.1007/s10342-009-0353-8](http://doi.org/10.1007/s10342-009-0353-8 )

en: branches swiss-forest-lab nutrient-content long-term-forest-ecosystem-research fruit-production icp-forests foliage-production litterfall

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Litterfall LWF

title_for_slug: litterfall-lwf

branches

display_name: branches

foliage-production

display_name: foliage-production

fruit-production

display_name: fruit-production

icp-forests

display_name: icp-forests

litterfall

display_name: litterfall

nutrient-content

display_name: nutrient-content


circular-vegetation-plots-lwf

en:
Ground vegetation is an important compartment of the ecosystem in terms of biodiversity and it takes an active part in the general functioning of the ecosystem. It is also a useful bio-indicator of the site conditions and its monitoring may enable the detection of environmental changes. Ground vegetation relevés were repeatedly carried out at 17 LWF plots in the period between 1994 and 2011. In 2013, ground vegetation was surveyed at an additional LWF plot (Laegeren). Phytosociological relevés were carried out in one or two concentric circular plots of 30, 200, 400 and 500 m2. All species occurring on the whole area of the LWF plot were also noted during the first vegetation survey.
 Purpose:
To assess the species diversity of ground vegetation and detect possible environmental changes using its bio-indicator value.
 Manual Citation:
 * Kull, P., 1997. Kapitel D2. Vegetationsaufnahmen. In: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-9.
 * Canullo  R,  Starlinger  F,  Granke  O,  Fischer  R,  Aamlid  D,  2016:  Part  VI.1:  Assessment  of  Ground  Vegetation. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on  forests.  Thünen  Institute  of  Forest  Ecosystems,  Eberswalde,  12  p.  +  Annex  [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Thimonier A, Kull P, Keller W, Moser B, Wohlgemuth T (2011) Ground vegetation monitoring in Swiss forests: comparison of survey methods and implications for trend assessments. Environmental Monitoring and Assessment, 174: 47-63. [doi: 10.1007/s10661-010-1759-y](http://doi.org/10.1007/s10661-010-1759-y)

en: species-composition icp-forests swiss-forest-lab ground-vegetation long-term-forest-ecosystem-research

envidat

en: EnviDat: the Environmental Data Portal

en: Circular vegetation plots LWF

title_for_slug: circular-vegetation-plots-lwf

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

swiss-forest-lab

display_name: swiss-forest-lab


en:
Annual Crown Condition Assessment including mortality and removal and Damage Causse Assessment on the Sanasilva-Sites and LWF plots.
 Purpose:
To assess tree and forest health and its changes and to assess occurence and extent of diseases
 Manual Citation:
 * Matthias Dobbertin, Christian Hug, Andreas Schwyzer, Serge Borer, Hanna Schmalz, 2016: Aufnahmeanleitung Kronenansprachen auf den Sanasilva- und den LWF-Flächen (Version 10). Sanasilva Inventur und Langfristige Waldökosystem-Forschung, Birmensdorf, 86 S. [---](https://www.wsl.ch/fileadmin/user_upload/WSL/Wald/Waldentwicklung_Monitoring/LWF/Sanasilva/ssi_anleitung_v10_extern.pdf)
 *  Eichhorn  J,  Roskams  P,  Potocic  N,  Timmermann  V,  Ferretti  M,  Mues  V,  Szepesi  A,  Durrant  D,  Seletkovic   I,   Schröck   H-W,   Nevalainen   S,   Bussotti   F,   Garcia   P,   Wulff   S,   2016:   Part   IV:   Visual   Assessment  of  Crown  Condition  and  Damaging Agents.  In:  UNECE  ICP  Forests  Programme  Co-ordinating  Centre  (ed.):  Manual  on  methods  and  criteria  for  harmonized  sampling,  assessment,  monitoring  and  analysis  of  the  effects  of  air  pollution  on  forests.  Thünen  Institute  of  Forest  Ecosystems, Eberswalde, Germany, 49 p. + Annex [---](https://www.icp-forests.org/pdf/manual/2016/ICP_Manual_2017_02_part04.pdf )
 Paper Citation:
 * BAFU (2017) Jahrbuch Wald und Holz 2017. Umwelt-Zustand, Bundesamt für Umwelt, Bern, Vol. 1718: 110 p. [---](http://www.bafu.admin.ch/uz-1718-d)
 *  Michel A, Seidling W, Prescher A K (2018) Forest Condition in Europe. 2018 Technical Report of ICP Forests. Report under the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). BFW-Dokumentation 25/2018, BFW Austrian Research Centre for Forests, Vienna, 92 p. [Technical Reports](http://icp-forests.net/page/icp-forests-technical-report)
 *  Brang P., 1998: Sanasilva-Bericht 1997. Zustand und Gefährdung des Schweizer Waldes – eine Zwischenbilanz nach 15 Jahren Waldschadenforschung. Berichte der Eidg. Forschungsanstalt für Wald, Schnee und Landschaft, Vol. 345. Eidg. Forschungsanstalt WSL, Birmensdorf, 102 S. [---](https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:14555)

en: damage-causes swiss-forest-lab crown-condition long-term-forest-ecosystem-research forest-vitality icp-forests damaging-agents forest-condition

en: Crown Condition Assessment and Damage Cause Assessment Sanasilva

crown-condition

display_name: crown-condition

damage-causes

display_name: damage-causes

damaging-agents

display_name: damaging-agents

forest-condition

display_name: forest-condition

forest-vitality

display_name: forest-vitality


en:
Measuring air pollutants in forests is important for evaluating the risk for vegetation in areas not covered by conventional air quality monitoring networks. Ozone measurements are carried out at LWF, applying the harmonized methodologies from UNECE/ICP Forests and running under the 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone. Data are also collected on ozone-induced visible symptoms and other ecosystem properties such as tree growth, nutrition, and biodiversity, as well as climate. This makes this long-term monitoring data series essential for impact assessment and air pollution modelling.
 Purpose:
Ozone risk assessment: Continuous measurements of ozone concentrations
 Manual Citation:
 * Schaub  M,  Calatayud  V,  Ferretti  M,  Brunialti  G,  Lövblad  G,  Krause  G,  Sanz  MJ,  2016:  Part  XV:  Monitoring of Air Quality. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of  air  pollution  on  forests.  Thünen  Institute  of  Forest  Ecosystems,  Eberswalde,  Germany,  11  p.  +  Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Schaub M, Häni M, Calatayud V, Ferretti M, Gottardini E (2018) ICP Forests Brief No 3 - Ozone concentrations are decreasing but exposure remains high in European forests. Programme Co-ordinating Centre of ICP Forests, Thu¨nen Institute of Forest Ecosystems. [doi: 10.3220/ICP1525258743000](https://icp-forests.org/pdf/ICPForestsBriefNo2.pdf)
 *  Cailleret M, Ferretti M, Gessler A, Rigling A, Schaub M (2018) Ozone effects on European forest growth – towards an integrative approach. Journal of Ecology. [doi:10.1111/1365-2745.12941](https://doi.org/10.1111/1365-2745.12941)
 *  Calatayud V and Schaub M (2013) Methods for Measuring Gaseous Air Pollutants in Forests. In: Marco Ferretti and Richard Fischer (Eds). Forest Monitoring: Methods for Terrestrial Investigations in Europe with an Overview of North America and Asia, Vol 12, DENS, UK: Elsevier, 2013, pp. 375-384. [doi:10.1016/B978-0-08-098222-9.00019-4](https://doi.org/10.1016/B978-0-08-098222-9.00019-4)

en: long-term-forest-ecosystem-research ozone icp-forests swiss-forest-lab ambient-air-quality

en: Continuous measurement of O3 LWF

ambient-air-quality

display_name: ambient-air-quality

ozone

display_name: ozone


en:
Measuring air pollutants in forests is important for evaluating the risk for vegetation in areas not covered by conventional air quality monitoring networks. Ozone measurements are carried out at LWF, applying the harmonized methodologies from UNECE/ICP Forests and running under the 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone. Data are also collected on ozone-induced visible symptoms and other ecosystem properties such as tree growth, nutrition, and biodiversity, as well as climate. This makes this long-term monitoring data series essential for impact assessment and air pollution modelling.
 Purpose:
Ozone risk assessment: Measurements of mean ozone concentrations with passive samplers (passam ag).
 Manual Citation:
 * Schaub  M,  Calatayud  V,  Ferretti  M,  Brunialti  G,  Lövblad  G,  Krause  G,  Sanz  MJ,  2016:  Part  XV:  Monitoring of Air Quality. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of  air  pollution  on  forests.  Thünen  Institute  of  Forest  Ecosystems,  Eberswalde,  Germany,  11  p.  +  Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Schaub M, Häni M, Calatayud V, Ferretti M, Gottardini E (2018) ICP Forests Brief No 3 - Ozone concentrations are decreasing but exposure remains high in European forests. Programme Co-ordinating Centre of ICP Forests, Thu¨nen Institute of Forest Ecosystems. [doi: 10.3220/ICP1525258743000](https://icp-forests.org/pdf/ICPForestsBriefNo2.pdf)
 *  Cailleret M, Ferretti M, Gessler A, Rigling A, Schaub M (2018) Ozone effects on European forest growth – towards an integrative approach. Journal of Ecology. [doi:10.1111/1365-2745.12941](http://doi.org/10.1111/1365-2745.12941)
 *  Calatayud V, Diéguez JJ, Sicard P, Schaub M, De Marco A (2016) Testing approaches for calculating stomatal ozone fluxes from passive sampler. Science of the Total Environment. [doi:10.1016/j.scitotenv.2016.07.155](http://doi.org/10.1016/j.scitotenv.2016.07.155)
 *  Calatayud V and Schaub M (2013) Methods for Measuring Gaseous Air Pollutants in Forests. In: Marco Ferretti and Richard Fischer (Eds). Forest Monitoring: Methods for Terrestrial Investigations in Europe with an Overview of North America and Asia, Vol 12, DENS, UK: Elsevier, 2013, pp. 375-384. [doi:10.1016/B978-0-08-098222-9.00019-4](http://doi.org/10.1016/B978-0-08-098222-9.00019-4)

en: ozone icp-forests swiss-forest-lab ambient-air-quality long-term-forest-ecosystem-research

en: Passive sampling of O3 LWF

envi

en: Environment


en:
Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA).
 Purpose:
Monitoring of the soil water matrix potential
 Paper Citation:
 * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123)

en: soil-water-content swiss-forest-lab soil-moisture long-term-forest-ecosystem-research icp-forests

en: 10-HS Pfynwald

soil-moisture

display_name: soil-moisture

soil-water-content

display_name: soil-water-content


en:
Continuous measurement of soil matrix potential at 15, 50 and 80 cm depth with Decagon MPS-2 sensors
 Purpose:
Improve the available data for the calibration or validation of the water cycle modells, i.e. the determination of the water flux needed for calculating the leaching fluxes.

en: icp-forests soil-water-matrix-potential swiss-forest-lab water-cycle long-term-forest-ecosystem-research

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: MPS-2 soil water matric potential LWF

soil-water-matrix-potential

display_name: soil-water-matrix-potential

water-cycle

display_name: water-cycle


tdr-pfynwald

en:
Continuous measurement of soil water content at one control and
in one irrigated plot in 10, 40 and 60 cm depth (4 replications) with TDR (Tektronix
1502B cable tester, Beaverton, OR, US).
 Purpose:
Monitoring of the soil water content
 Paper Citation:
 * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123)

en: long-term-forest-ecosystem-research irrigation icp-forests soil-water-content swiss-forest-lab

envidat

en: EnviDat: the Environmental Data Portal

en: TDR Pfynwald

title_for_slug: tdr-pfynwald

irrigation

display_name: irrigation


en:
Continuous measurement of soil water content at 15, 50 and 70 cm depth in Visp (3 replications) with TDR soil moisture probes (Tektronix 1502 B) from 2001 until 25.04.2013
 Purpose:
Improve the available data for the calibration or validation of the water balance models, i.e. the determination of the water flux needed for calculating the leaching fluxes.

en: long-term-forest-ecosystem-research icp-forests soil-water-content swiss-forest-lab soil-moisture

en: TDR soil water content measurements LWF Visp

icp-forests

display_name: icp-forests


soil-solution-chemistry-lysimeters-lwf

en:
Fortnightly measurement of the soil solution chemistry in 4 soil depths  with zero-tension lysimeter below the litter layer and with tension lysimeters at depths of 15, 50 and 80 cm (8 replicates)
 Purpose:
To characterize the chemical status of the soil solution and to detect trends in soil water quality. To assess the effects of air pollution and climate chnage on soil water quality.
 Manual Citation:
 * Micha Pluess, Daniel Christen, 1999: Kurzanleitung Bodenlösung. Langfristige Waldökosystem-Forschung LWF, Birmensdorf, 2 S.
 * Nieminen  TM,  De  Vos  B,  Cools  N,  König  N,  Fischer  R,  Iost  S,  Meesenburg  H,  Nicolas  M,  O’Dea  P,  Cecchini  G,  Ferretti  M,  De  La  Cruz  A,  Derome  K,  Lindroos  AJ,  Graf  Pannatier  E,  2016:  Part  XI:  Soil  Solution  Collection  and  Analysis.  In:  UNECE  ICP  Forests  Programme  Co-ordinating  Centre  (ed.):  Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 20 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Graf Pannatier, E.; Thimonier, A.; Schmitt, M.; Walthert, L.; Waldner, P., 2011: A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?. Environmental Monitoring and Assessment, 174, 1-4: 3-30. [doi: 10.1007/s10661-010-1754-3](http://doi.org/10.1007/s10661-010-1754-3)

en: long-term-forest-ecosystem-research soil-solution-chemistry icp-forests swiss-forest-lab lwf

en: Soil solution chemistry (lysimeters) LWF

title_for_slug: soil-solution-chemistry-lysimeters-lwf

lwf

display_name: lwf

soil-solution-chemistry

display_name: soil-solution-chemistry


soil-matrix-chemistry-lwf

en:
Assessment of several chemical soil parameters at the beginning of the monitoring campaign. Most parameters were determined accordung to the manual of ICP-Integrated-Monitoring. The parameters were analysed for all genetic horizons in soil pits and additionally for fixed layers in the Intensive-Monitoring-Plots. In heterogeneous LWF-plots, several soil pits were analysed in order to assess the soil variability of the plot. The manual (in German) for soil sampling and soil analyses is available in www: http://e-collection.ethbib.ethz.ch/view/eth:25622?q=walthert. The results and data of the first soil survey are available (in German) in www: http://e-collection.ethbib.ethz.ch/view/eth:26275?q=walthert.
 Purpose:
The chemical characterisation of soil matrix down to the paraent material is realised with data from soil pits. The monitoring of the soil matrix in a frequency of roundly 15 years is effected with soil samples from Intensiv-Monitoring-Plots. For soil monitoring, pooled samples with 16 replicats are used down to a depth of 80 cm. The date of the second soil survey is not yet fixed.
 Manual Citation:
 * Walthert L, Lüscher P, Luster J, Peter B (2002) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Aufnahmeanleitung zur ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 269: 56 p. [10.3929/ethz-a-004375470](https://doi.org/10.3929/ethz-a-004375470)
 Paper Citation:
 * Walthert L, Blaser P, Lüscher P, Luster J, Zimmermann S (2003) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Ergebnisse der ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 276: 340 p.

en: icp-forests swiss-forest-lab soil-matrix long-term-forest-ecosystem-research soil-chemistry

en: Soil matrix chemistry LWF

title_for_slug: soil-matrix-chemistry-lwf

envi

en: Environment

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

soil-chemistry

display_name: soil-chemistry

soil-matrix

display_name: soil-matrix


en:
Measurement of the soil water availability to plants at 10 LWF plots  every 14 days in 5 soil depths (15, 30, 50, 80, 130 cm) with 8 replicates (usually in the IM plot). The range of measurement is from water saturation until-80 kPa.
 Purpose:
The long-term measurement of the soil water availability to plants in the root zone provides useful information about the soil moisture conditions (drought, water saturation, water easily available to plants). The measurement of the soil water suction allows to calibrate the water balance models and to validate the modelled matric potential.
 Manual Citation:
 * Peter Waldispühl, 1997: Installation von Tensiometern auf LWF-Flächen. Langfristige Waldökosystem-Forschung LWF, Birmensdorf, 2 S.
 *  Peter Waldispühl, Andreas Rigling, 1997: Vorgehen bei der Ablesung von Teniometern auf LWF-Flächen. Langfristige Waldökosystem-Forschung LWF, Eidg. Forschungsanstalt WSL, Birmensdorf, 2 S.
 *  Peter Waldispühl, 2000: Kurzanleitung für die TensioDB. Langfristige Waldökosystem-Forschung, Eidg. Forschungsanstalt WSL, Birmensdorf, 12 S. + DB-Schema
 Paper Citation:
 * Graf Pannatier, E.; Thimonier, A.; Schmitt, M.; Walthert, L.; Waldner, P., 2011: A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?. Environmental Monitoring and Assessment, 174, 1-4: 3-30. [doi: 10.1007/s10661-010-1754-3](http://doi.org/10.1007/s10661-010-1754-3)

en: soil-water-matrix-potential swiss-forest-lab lwf long-term-forest-ecosystem-research icp-forests

en: Matric potential (manual suction cups) LWF

swiss-forest-lab

display_name: swiss-forest-lab


soil-morphology-lwf

en:
Description of several morphological soil properties at the beginning of the monitoring campaign. The properties were described for all genetic horizons in soil pits if possible down to the parent material. In heterogeneous LWF-plots, several soil profiles were described in order to assess the soil variability of the plot. The manual (in German) for soil sampling and soil analyses is available in www: http://e-collection.ethbib.ethz.ch/view/eth:25622?q=walthert. The results and data of the first soil survey are available (in German) in www: http://e-collection.ethbib.ethz.ch/view/eth:26275?q=walthert.
 Purpose:
Morphological soil properties are important for the calculation or interpretation of chemical or physical soil properties or processes. For instance, root distribution is an important input-parameter of water balance models or soil hydromorphy strongly affects the chemical status of soil matrix and soil solution.
 Manual Citation:
 * Walthert L, Lüscher P, Luster J, Peter B (2002) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Aufnahmeanleitung zur ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 269: 56 p. [10.3929/ethz-a-004375470](https://doi.org/10.3929/ethz-a-004375470)
 Paper Citation:
 * Walthert L, Blaser P, Lüscher P, Luster J, Zimmermann S (2003) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Ergebnisse der ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 276: 340 p.

en: icp-forests soil-matrix soil-classification swiss-forest-lab long-term-forest-ecosystem-research texture

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Soil morphology LWF

title_for_slug: soil-morphology-lwf

soil-classification

display_name: soil-classification

texture

display_name: texture


stem-discs-lwf

en:
Measurement of tree ring widts in tree stem disks according to 'Bräker O.U. (1993) Anleitung zur Entnahme von Stammscheiben auf Ertragskundeflächen'
 Purpose:
tree growth

en: tree-ring-width long-term-forest-ecosystem-research icp-forests stem-disc swiss-forest-lab dendrochronology

envidat

en: EnviDat: the Environmental Data Portal

en: Stem discs LWF

title_for_slug: stem-discs-lwf

dendrochronology

display_name: dendrochronology

stem-disc

display_name: stem-disc

tree-ring-width

display_name: tree-ring-width


en:
Sampling of deadwood for density and chemical analysis during summer 2009
 Purpose:
Determination of N and C pools of deadwood
 Paper Citation:
 * WEGGLER, K.; DOBBERTIN, M.; JÜNGLING, E.; KAUFMANN, E.; THÜRIG, E., 2012. Dead wood volume to dead wood carbon: the issue of conversion factors. European Journal of Forest Research 131, 1423-1438.

en: nitrogen swiss-forest-lab long-term-forest-ecosystem-research icp-forests lignin deadwood carbon

en: Deadwood sampling at Sanasilva and LWF sites

carbon

display_name: carbon

deadwood

display_name: deadwood

lignin

display_name: lignin

nitrogen

display_name: nitrogen


en:
Two stem core samples of all trees of a subplot of approximately 1 a. Basal Area, Wood volume increment per area estimation
 Purpose:
Investigation of the relation between dendroparameters of dominance/surpression and stem growth. Abgleich Jahrringdaten mit Inventurdaten.
 Paper Citation:
 * Nehrbass-Ahles C, Babst F, Klesse S, Nötzli M, Bouriaud O, Neukom R, Dobbertin M, Frank D (2014) The influence of sampling design on tree-ring-based quantification of forest growth. Global Change Biology, 20 (9): 2867–2885. [doi: 10.1111/gcb.12599](http://doi.org/10.1111/gcb.12599)
 *  Klesse S, Etzold S, Frank D (2016) Integrating tree-ring and inventory-based measurements of aboveground biomass growth: research opportunities and carbon cycle consequences from a large snow breakage event in the Swiss Alps. European Journal of Forest Research, 135 (2): 297-311.

en: swiss-forest-lab dendrochronology tree-selection-effects tree-ring-width long-term-forest-ecosystem-research icp-forests

en: Dendrochronological analyses of tree core samples (subplot) LWF

tree-selection-effects

display_name: tree-selection-effects


en:
There were 2 cores taken at 1.3 m height from each of 10 trees outside the LWF plot
 Purpose:
influence of drought and nutrient availabiliy on tree growth
 Paper Citation:
 * Lévesque, M., Walthert, L., Weber, P., 2016. Soil nutrients influence growth response of temperate tree species to drought. J. Ecol. 104, 377-387.

en: swiss-forest-lab dendrochronology tree-ring-width long-term-forest-ecosystem-research dominant-trees icp-forests

en: Dendrochronological analyses of tree core samples (CATS) adjacent to LWF sites

envi

en: Environment

dominant-trees

display_name: dominant-trees

icp-forests

display_name: icp-forests


en:
Two stem core samples of 10 trees outside the plot of each main species in the plot were taken at breast height (1.3 m above ground) with a SUUNTO corer. Tree ring width and density were determined with the instruments CATRAS and TSAP, the Densitometer DENDRO 2003 and a stereo-microscope. The selected trees included at least 10 pre-dominant or dominant trees.
 Purpose:
N and C stable isotope signals
 Paper Citation:
 * Tomlinson, G., Siegwolf, R.T.W., Buchmann, N., Schleppi, P., Waldner, P., Weber, P., 2014. The mobility of nitrogen across tree-rings of Norway spruce (Picea abies L.) and the effect of extraction method on tree-ring d15N and d13C values. Rapid Commun. Mass Spectrom. 28, 1258-1264.

en: dendrochronology tree-ring-width long-term-forest-ecosystem-research dominant-trees icp-forests stable-isotopes swiss-forest-lab

en: Dendrochronological analyses of tree core samples (IsoN) adjacent to LWF sites

stable-isotopes

display_name: stable-isotopes


en:
Two stem core samples of 12 to 20 trees outside the plot of each main species in the plot were taken at breast height (1.3 m above ground) with a SUUNTO corer. Tree ring width and density were determined with the instruments CATRAS and TSAP, the Densitometer DENDRO 2003 and a stereo-microscope. The selected trees included at least 12 pre-dominant or dominant trees and if possible also 4 subdominant or surpressed trees. NOTE: The samplings were carried out between 1996 and 1999 for most plots and in 2003 for the plot Lantsch. The cores cover a time span depending on the age of the oldest trees on a plot. On one plot the oldest sampled tree ring grew in the year 1646.
 Purpose:
Reconstruction of stand history and tree growth
 Manual Citation:
 * Paolo Cherubini, Matthias Dobbertin, 1997: Bestandesgeschichte (Dendrochronologie). In: Peter Brang (ed.), Aufnahmeanleitung LWF. Langfristige Waldökosystem-Forschung LWF, Eidg. Forschungsanstalt WSL, Birmensdorf, 3 S.
 *  Cherubini, P.; Dobbertin, M., 1998: The Swiss long-term forest ecosystem research: methods for reconstructing forest history. In: Borghetti, M. (ed): Società Italiana di Selvicoltura ed Ecologia Forestale (SISEF), Atti I: 19-22.
 Paper Citation:
 * Cherubini, P., Fontana, G., Rigling, D., Dobbertin, M., Brang, P., Innes, J.L., 2002. Tree-life history prior to death: two fungal root pathogens affect tree-ring growth differently. J. Ecol. 90, 839-850.

en: stand-history icp-forests swiss-forest-lab dendrochronology tree-ring-width long-term-forest-ecosystem-research dominant-trees

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Dendrochronological analyses of tree core samples (dominant trees) LWF

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

stand-history

display_name: stand-history


en:
Tree circumference change measurements from plastic girth bands
 Purpose:
Assessment of annual tree stem growth
 Manual Citation:
 * Dobbertin  M,  Neumann  M,  2016:  Part  V:  Tree  Growth.  In:  UNECE  ICP  Forests,  Programme  Co-ordinating  Centre  (ed.):  Manual  on  methods  and  criteria  for  harmonized  sampling,  assessment,  monitoring  and  analysis  of  the  effects  of  air  pollution  on  forests.  Thünen  Institute  of  Forest  Ecosystems, Eberswalde, Germany, 17 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Etzold S, Waldner P, Thimonier A, Schmitt M, Dobbertin M (2014) Tree growth in Swiss forests between 1995 and 2010 in relation to climate and stand conditions: Recent disturbances matter. Forest Ecology and Management, 311: 41-55. [doi: 10.1016/j.foreco.2013.05.040](http://doi.org/10.1016/j.foreco.2013.05.040)

en: icp-forests stem-diameter swiss-forest-lab tree-growth long-term-forest-ecosystem-research

envidat

en: EnviDat: the Environmental Data Portal

en: Manual circumference band measurement LWF

stem-diameter

display_name: stem-diameter

tree-growth

display_name: tree-growth


en:
Continuous stem radius measurements to investigate carbon balance and water relations of trees
 Purpose:
Assessment of growth and water related stem changes

en: Automated point dendrometer measurements at LWF sites

swiss-forest-lab

display_name: swiss-forest-lab