Alpine-treeline spatial patterns as indicators for climate-change responses: a global study using community-supported pattern-based modelling

高山林线空间模式作为气候变化响应指标：使用社区支持的基于模式的建模进行的全球研究

• 批准号: 419961979
• 负责人: Professorin Dr. Maaike Bader
• 金额: --
• 依托单位: Department Ökologische Systemanalyse
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/419961979?language=en
• 关键词: Alpine; treeline; spatial; patterns; indicators

The potential elevation of alpine treelines can be predicted well at the global scale based on temperature. However, at more local scales positions of treeline ecotones vary strongly and are harder to predict because other, more site- and species-specific factors play an increasingly important role. Similarly, local dynamics are highly variable among sites and it is unclear whether and how different treelines may advance because of climatic change. Advancing treelines, or denser forests below the treeline, would have important implications for the global carbon cycle and alpine biodiversity. To better understand treeline-forming processes and to predict treeline shifts in response to climatic changes, we will collaborate with an established group of treeline experts and modellers to reveal the links between spatial patterns and ecological processes in alpine-treeline ecotones around the world. In this project we aim to 1) develop a spatially-explicit individual-based treeline simulation model, 2) test hypotheses of pattern-process relationships using the model and existing spatiotemporal treeline datasets, and 3) predict treeline dynamics and shifts in response to climate change. By synthesising and formalising process knowledge as well as geographically dispersed spatio-temporal treeline data, this project will create a step-change in treeline research by providing the tools for globally-coordinated observational, experimental and simulation research at treeline in the context of ecological regime shifts.

可以根据温度在全球范围内很好地预测高山树皮线的潜在升高。但是，在更局部的天范围内，绿琳的位置差异很强，很难预测，因为其他，更多的地点和物种特异性因素起着越来越重要的作用。同样，局部动力学在站点之间是高度变化的，目前尚不清楚由于气候变化而不同的树皮线可能会发展。促进树木下方的树木或茂密的森林将对全球碳循环和高山生物多样性具有重要意义。为了更好地理解树木形成的过程并预测响应气候变化的绿晶转变，我们将与一组既定的树林专家和建模者合作，以揭示世界各地高山基因生态酮的空间模式与生态过程之间的联系。在该项目中，我们的目的是1）开发一个基于空间的基于个体的条纹模拟模型，2）使用模型和现有时空的treeline数据集检验模式过程关系的假设，以及3）预测对气候变化响应的条线动力学和变化。通过综合和形式化的过程知识以及地理分散的时空绿素数据，该项目将通过在生态方面的环境中为Treeline提供全球协调的观察，实验和仿真研究的工具，从而在Treeline研究中产生逐步变化。