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ATP - Automated Intra-Annual Tree-Ring Profiling for Dendroecological Research

ATP - 用于树木生态学研究的自动年轮分析

基本信息

批准号：
269191667
负责人：
Professor Dr. Rolf Backofen
金额：
--
依托单位：
Professur für Waldwachstum und Dendroökologie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/269191667?language=en
关键词：
ATP Automated Intra Annual Tree

项目摘要

Tree-rings integrate and conserve precisely datable environmental information on the growing conditions of trees during the time of their development. Dendrochronology builds on the basic principle of cross-dating, i.e. the identification and synchronization of time specific patterns between multiple tree-ring sequences to develop absolutely dated tree-ring chronologies. The integration of statistical findings and consolidated knowledge about the relations between environmental factors and the tree growth response as manifested in the tree-ring structures serve as the basis for the reconstruction of past environmental conditions. Such tree-ring based studies provide significant contributions to the fields of climate reconstruction (dendroclimatology), reconstruction of human history (dendroarchaeology) and to a wide range of ecological aspects of the environment.Within this interdisciplinary project, we aim at implementing methods of pattern matching to the analysis of intra-annual tree-ring density profiles for dendrochronological and dendroecological research questions. The project joins the expert knowledge of the Dendroecology group (Prof. Spiecker et al.) in tree-ring based research with the extensive experience of the Bioinformatics group (Prof. Backofen et al.) concerning alignment and clustering method development for bioinformatics applications. Our activities are targeted towards the development of improved methods (1) to enhance environmental signal strength when aggregating multiple intra-annual tree-ring density profiles, (2) to generate high-resolution temporal annotations for intra-annual tree-ring positions, (3) to cross-date tree-ring sequences and build tree-ring chronologies.To this end, we will extend and improve our MICA approach (Multiple Interval-based Curve Alignment), which generates signal-enhanced consensus profiles building on established curve and sequence alignment techniques. Applied on the available extensive intra-annual tree-ring density data, we will generate spatial consensus profile chronologies for various tree species. Using appendant quasi-continuous point dendrometer data, temporal annotation of these intra-annual density data via dedicated MICA adaptions will result in time-annotated chronologies. Both types of chronologies are used to establish new alignment-based cross-dating techniques through the exploitation of intra-annual density profile information. Due to the extended information content of the latter compared to e.g. just ring-width, these new methods will require less sample material while enhancing dating precision. Finally, we will establish a pipeline to investigate the correlation of environmental factors with tree-ring density profiles. An initial study will focus on the application to probabilistically allocate a location or site to an un-located tree-ring sample. All tools and pipelines will be made publicly available and accompanied with extensive documentation.

树木年轮整合并保存了树木生长过程中的环境信息。树木年代学建立在交叉定年的基本原则上，即在多个树木年轮序列之间识别和同步时间特定模式，以开发绝对定年的树木年轮年表。整合的统计结果和巩固的知识之间的关系，环境因素和树木的生长反应，表现在树木年轮结构作为重建过去的环境条件的基础。这种树木年轮为基础的研究提供了重大贡献的领域的气候重建（树木气候学），重建人类历史（树木考古学）和广泛的生态方面的environment.Within这个跨学科的项目，我们的目标是实施模式匹配的方法来分析一年内的树木年轮密度配置文件的树木年代学和树木生态学研究问题。该项目结合了树木生态学小组的专业知识（Spiecker教授等人）在基于树木年轮的研究中，生物信息学小组拥有丰富的经验（Backofen教授等人）。关于生物信息学应用的比对和聚类方法开发。我们的活动目标是开发改进的方法：（1）在聚合多个年内树木年轮密度剖面时增强环境信号强度，（2）为年内树木年轮位置生成高分辨率时间注释，（3）交叉确定树木年轮序列的日期并建立树木年轮年表。我们将扩展和改进我们的云母方法（基于多个间隔的曲线比对），该方法在已建立的曲线和序列比对技术的基础上生成信号增强的共识图谱。应用于现有的广泛的年内树木年轮密度数据，我们将产生空间共识配置文件年表的各种树种。使用附加的准连续点测树仪数据，这些年内密度数据通过专用云母适应时间注释将导致时间注释年表。这两种类型的年表都被用来通过利用年内密度剖面信息来建立新的基于测量的交叉定年技术。由于后者的扩展信息内容相比，例如只是环宽，这些新方法将需要更少的样品材料，同时提高定年精度。最后，我们将建立一个管道来调查环境因素与树木年轮密度分布的相关性。初步研究将集中在应用程序的概率分配一个位置或网站的一个unlocated树轮样本。所有工具和管道都将公开提供，并附有大量文档。