Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden.
Ambio. 2012;41 Suppl 3(Suppl 3):292-302. doi: 10.1007/s13280-012-0307-0.
Recent studies have shown that the complexities of the surface features in mountainous terrain require a re-assessment of climate impacts at the local level. We explored the importance of surface-air-temperature based on a recently published 50-m-gridded dataset, versus soil variables for explaining vegetation distribution in Swedish Lapland using generalised linear models (GLMs). The results demonstrated that the current distribution of the birch forest and snowbed community strongly relied on the surface-air-temperature. However, temperature alone is a poor predictor of many plant communities (wetland, meadow). Because of diminishing sample representation with increasing altitude, the snowbed community was under-sampled at higher altitudes. This results in underestimation of the current distribution of the snowbed community around the mountain summits. The analysis suggests that caution is warranted when applying GLMs at the local level.
最近的研究表明，山区地表特征的复杂性要求重新评估当地的气候影响。我们使用广义线性模型（GLMs）探讨了基于最近发表的 50 米网格化数据集的地表气温与土壤变量对解释瑞典拉普兰植被分布的重要性。结果表明，目前桦树林和雪床群落的分布强烈依赖于地表气温。然而，温度本身并不能很好地预测许多植物群落（湿地、草地）。由于随着海拔的升高，样本代表性逐渐减少，雪床群落的采样在较高的海拔地区不足。这导致对山顶周围雪床群落的当前分布的低估。该分析表明，在当地应用 GLMs 时需要谨慎。
