The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
Predictive mapping of alpine grasslands in Switzerland: Species versus community approach
Abstract
Abstract. Separate logistic regression models were developed to predict the distribution and large‐scale spatial patterns of dominant graminoid species and communities in alpine grasslands. The models are driven by four bioclimatic parameters: degree‐days of growing season (basis 0 °C), a moisture index for July, potential direct solar radiation for March, and a continentality index. Geology and slope angle were used as a surrogate for nutrient availability and soil water capacity. The bioclimatic parameters were derived from monthly mean temperature, precipitation, cloudiness and potential direct solar radiation. The environmental parameters were interpolated using a digital elevation model with a resolution of 50 m. The vegetation data for model calibration originate from field surveys and literature. An independent test data set with samples from three different climatic zones was used to test the model. The degree of coincidence between simulated and observed patterns was similar for species and communities, but the κ‐values for communities were generally higher (κ= 0.539) than for species (mean individual κ= 0.201). Information on land use was detected as a major factor that could significantly improve both the species and the community model. Nevertheless, the climatic factors used to drive the model explained a major part of the observed patterns.
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Predictive habitat distribution models in ecology
Guisan, A., & Zimmermann, N. E. (2000) · Ecological Modelling · doi:10.1016/s0304-3800(00)00354-9 · Cited by 7,359
Self-citationSpecies Distribution Models: Ecological Explanation and Prediction Across Space and Time
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Guisan, A., Edwards, T. C., & Hastie, T. (2002) · Ecological Modelling · doi:10.1016/s0304-3800(02)00204-1 · Cited by 2,356
Evaluating presence–absence models in ecology: the need to account for prevalence
Manel, S., Williams, H. C., & Ormerod, S. J. (2001) · Journal of Applied Ecology · doi:10.1046/j.1365-2664.2001.00647.x · Cited by 1,759
Climate change and plant distribution: local models predict high‐elevation persistence
RANDIN, C. F., ENGLER, R., NORMAND, S., ZAPPA, M., ZIMMERMANN, N. E., PEARMAN, P. B., VITTOZ, P., THUILLER, W., & GUISAN, A. (2009) · Global Change Biology · doi:10.1111/j.1365-2486.2008.01766.x · Cited by 555
Self-citation
Metadata
- Authors
- Zimmermann, N. E., & Kienast, F.
- Venue
- Journal of Vegetation Science
- Publisher
- Wiley
- Published
- 1999-08
- Volume
- 10
- Issue
- 4
- Pages
- 469-482
- ISSN
- 1100-9233 (ISSN-L)
- 1654-1103
- OpenAlex
- W2109342520
- Cited by
- 396
- References
- 68
- FWCI
- 7.03
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
