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Elevation dependent response of soil organic carbon stocks to forest windthrow
Mayer, M., Rusch, S., Didion, M., Baltensweiler, A., Walthert, L., Ranft, F., … Hagedorn, F. (2023). Elevation dependent response of soil organic carbon stocks to forest windthrow. Science of the Total Environment, 857, 159694 (9 pp.). https://doi.org/10.1016/j.scitotenv.2022.159694
Hochauflösende Bodenkarten für den Schweizer Wald
Baltensweiler, A., Walthert, L., Zimmermann, S., & Nussbaum, M. (2022). Hochauflösende Bodenkarten für den Schweizer Wald. Schweizerische Zeitschrift für Forstwesen, 173(6), 288-291. https://doi.org/10.3188/szf.2022.0288
Countrywide classification of permanent grassland habitats at high spatial resolution
Huber, N., Ginzler, C., Pazur, R., Descombes, P., Baltensweiler, A., Ecker, K., … Price, B. (2022). Countrywide classification of permanent grassland habitats at high spatial resolution. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.298
Humusverlust nach Windwurf - Risiko im Bergwald?
Mayer, M., Rusch, S., Didion, M., Baltensweiler, A., Walthert, L., Ranft, F., … Hagedorn, F. (2022). Humusverlust nach Windwurf - Risiko im Bergwald? In Eidg. Forschungsanstalt für Wald, Schnee und Landschaft WSL (Ed.), WSL Berichte: Vol. 126. Waldböden - intakt und funktional (pp. 43-45). https://doi.org/10.55419/wsl:32005
Soil–plant interactions modulated water availability of Swiss forests during the 2015 and 2018 droughts
Meusburger, K., Trotsiuk, V., Schmidt-Walter, P., Baltensweiler, A., Brun, P., Bernhard, F., … Walthert, L. (2022). Soil–plant interactions modulated water availability of Swiss forests during the 2015 and 2018 droughts. Global Change Biology, 28(20), 5928-5944. https://doi.org/10.1111/gcb.16332
Machine learning based soil maps for a wide range of soil properties for the forested area of Switzerland
Baltensweiler, A., Walthert, L., Hanewinkel, M., Zimmermann, S., & Nussbaum, M. (2021). Machine learning based soil maps for a wide range of soil properties for the forested area of Switzerland. Geoderma Regional, 27, e00437 (13 pp.). https://doi.org/10.1016/j.geodrs.2021.e00437
Wo wachsen welche Gehölzarten? Neue Online-Karten verraten es
Baltensweiler, A., & Allgaier Leuch, B. (2021). Wo wachsen welche Gehölzarten? Neue Online-Karten verraten es. Infoblatt Arbeitsgruppe Waldplanung und -management, 21(2), 6-7.
The distribution of a group of keystone species is not associated with anthropogenic habitat disturbance
Fitzpatrick, B. R., Baltensweiler, A., Düggelin, C., Fraefel, M., Freitag, A., Vandegehuchte, M. L., … Risch, A. C. (2021). The distribution of a group of keystone species is not associated with anthropogenic habitat disturbance. Diversity and Distributions, 27(4), 572-584. https://doi.org/10.1111/ddi.13217
Räumlich explizite Modellierung der NaiS-Standorttypen zur Analyse der Waldbestockung
Scherrer, D., Baltensweiler, A., Fischer, C., Frehner, M., Wüest Karpati, R., & Wohlgemuth, T. (2021). Räumlich explizite Modellierung der NaiS-Standorttypen zur Analyse der Waldbestockung. Schweizerische Zeitschrift für Forstwesen, 172(5), 278-285. https://doi.org/10.3188/szf.2021.0278
Modellierte Verbreitungskarten für die häufigsten Gehölzarten der Schweiz
Wüest, R. O., Bergamini, A., Bollmann, K., Brändli, U. B., & Baltensweiler, A. (2021). Modellierte Verbreitungskarten für die häufigsten Gehölzarten der Schweiz. Schweizerische Zeitschrift für Forstwesen, 172(4), 226-233. https://doi.org/10.3188/szf.2021.0226
Microtopography shapes soil pH in flysch regions across Switzerland
Baltensweiler, A., Heuvelink, G. B. M., Hanewinkel, M., & Walthert, L. (2020). Microtopography shapes soil pH in flysch regions across Switzerland. Geoderma, 380, 114663 (10 pp.). https://doi.org/10.1016/j.geoderma.2020.114663
Räumliche Analyse von Trockenheitssymptomen im Schweizer Wald mit Sentinel-2-Satellitendaten
Baltensweiler, A., Brun, P., Pranga, J., Psomas, A., Zimmermann, N. E., & Ginzler, C. (2020). Räumliche Analyse von Trockenheitssymptomen im Schweizer Wald mit Sentinel-2-Satellitendaten. Schweizerische Zeitschrift für Forstwesen, 171(5), 298-301. https://doi.org/10.3188/szf.2020.0298
Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes
Descombes, P., Walthert, L., Baltensweiler, A., Meuli, R. G., Karger, D. N., Ginzler, C., … Zimmermann, N. E. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography, 43(10), 1448-1463. https://doi.org/10.1111/ecog.05117
Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion
Trotsiuk, V., Hartig, F., Cailleret, M., Babst, F., Forrester, D. I., Baltensweiler, A., … Schaub, M. (2020). Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion. Global Change Biology, 26(4), 2463-2476. https://doi.org/10.1111/gcb.15011
LiDAR data as a proxy for light availability improve distribution modelling of woody species
Wüest, R. O., Bergamini, A., Bollmann, K., & Baltensweiler, A. (2020). LiDAR data as a proxy for light availability improve distribution modelling of woody species. Forest Ecology and Management, 456, 117644 (10 pp.). https://doi.org/10.1016/j.foreco.2019.117644
Testing species assemblage predictions from stacked and joint species distribution models
Zurell, D., Zimmermann, N. E., Gross, H., Baltensweiler, A., Sattler, T., & Wüest, R. O. (2020). Testing species assemblage predictions from stacked and joint species distribution models. Journal of Biogeography, 47(1), 101-113. https://doi.org/10.1111/jbi.13608
Estimating below‐canopy light regimes using airborne laser scanning: an application to plant community analysis
Zellweger, F., Baltensweiler, A., Schleppi, P., Huber, M., Küchler, M., Ginzler, C., & Jonas, T. (2019). Estimating below‐canopy light regimes using airborne laser scanning: an application to plant community analysis. Ecology and Evolution, 9(16), 9149-9159. https://doi.org/10.1002/ece3.5462
Evaluation of digital soil mapping approaches with large sets of environmental covariates
Nussbaum, M., Spiess, K., Baltensweiler, A., Grob, U., Keller, A., Greiner, L., … Papritz, A. (2018). Evaluation of digital soil mapping approaches with large sets of environmental covariates. Soil, 4(1), 1-22. https://doi.org/10.5194/soil-4-1-2018
Alternative tree species under climate warming in managed European forests
Thurm, E. A., Hernandez, L., Baltensweiler, A., Ayan, S., Rasztovits, E., Bielak, K., … Falk, W. (2018). Alternative tree species under climate warming in managed European forests. Forest Ecology and Management, 430, 485-497. https://doi.org/10.1016/j.foreco.2018.08.028
Terrestrial laser scanning improves digital elevation models and topsoil pH modelling in regions with complex topography and dense vegetation
Baltensweiler, A., Walthert, L., Ginzler, C., Sutter, F., Purves, R. S., & Hanewinkel, M. (2017). Terrestrial laser scanning improves digital elevation models and topsoil pH modelling in regions with complex topography and dense vegetation. Environmental Modelling and Software, 95, 13-21. https://doi.org/10.1016/j.envsoft.2017.05.009