Data from: Disentangling the formation of contrasting tree-line physiognomies combining model selection and Bayesian parameterization for simulation models

Alpine tree-line ecotones are characterized by marked changes at small spatial scales that may result in a variety of physiognomies. A set of alternative individual-based models was tested with data from four contrasting Pinus uncinata ecotones in the central Spanish Pyrenees to reveal the minimal subset of processes required for tree-line formation. A Bayesian approach combined with Markov chain Monte Carlo methods was employed to obtain the posterior distribution of model parameters, allowing the use of model selection procedures. The main features of real tree lines emerged only in models considering nonlinear responses in individual rates of growth or mortality with respect to the altitudinal gradient. Variation in tree-line physiognomy reflected mainly changes in the relative importance of these nonlinear responses, while other processes, such as dispersal limitation and facilitation, played a secondary role. Different nonlinear responses also determined the presence or absence of krummholz, in agreement with recent findings highlighting a different response of diffuse and abrupt or krummholz tree lines to climate change. The method presented here can be widely applied in individual-based simulation models and will turn model selection and evaluation in this type of models into a more transparent, effective, and efficient exercise.

高山林线交错带（Alpine tree-line ecotones）的典型特征为小尺度空间范围内存在显著变化，进而催生多种植被外貌。本研究采用西班牙中部比利牛斯山四处不同的Pinus uncinata林线交错带的实测数据，对一系列备选的基于个体的模型（individual-based models）进行检验，以揭示林线形成所需的最少过程子集。研究采用贝叶斯方法（Bayesian approach）结合马尔可夫链蒙特卡洛（Markov chain Monte Carlo）方法获取模型参数的后验分布，从而支持模型选择流程的应用。真实林线的核心特征仅在纳入了个体生长率或死亡率沿海拔梯度的非线性响应的模型中得以重现。林线植被外貌的差异主要反映了这些非线性响应的相对重要性变化，而扩散限制、促进作用等其他过程则仅起到次要作用。不同的非线性响应同样决定了矮曲林（krummholz）是否出现，这与近期研究发现一致——即弥散型林线、陡峭型林线及矮曲林对气候变化的响应存在差异。本文提出的方法可广泛应用于基于个体的模拟模型，且将使此类模型的模型选择与评估工作变得更为透明、高效且便捷。