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.

年轮整合并保存了有关树木在生长过程中生长条件的精确可数据环境信息。树木年代学建立在交叉定年的基本原理之上，即识别和同步多个树木年轮序列之间的时间特定模式，以开发绝对确定日期的树木年轮年表。统计结果和有关环境因素与树木年轮结构中树木生长反应之间关系的综合知识的整合，成为重建过去环境条件的基础。这种基于树木年轮的研究为气候重建（树木气候学）、人类历史重建（树木考古学）以及环境的广泛生态方面做出了重大贡献。在这个跨学科项目中，我们的目标是实施模式方法与树木年代学和树木生态学研究问题的年内树木年轮密度剖面分析相匹配。该项目结合了树木生态学小组（Spiecker 教授等人）在树木年轮研究方面的专业知识以及生物信息学小组（Backofen 教授等人）在生物信息学应用的比对和聚类方法开发方面的丰富经验。我们的活动旨在开发改进的方法（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) 交叉日期树木年轮序列并建立树木年轮年表。为此，我们将扩展和改进我们的 MICA 方法（基于多区间的曲线对齐），该方法在已建立的曲线上生成信号增强的一致剖面和序列比对技术。应用现有的广泛的年内树木年轮密度数据，我们将为各种树种生成空间共识剖面年表。使用附加的准连续点树仪数据，通过专用 MICA 适配对这些年内密度数据进行时间注释将产生时间注释的年表。两种类型的年表都用于通过利用年内密度剖面信息来建立新的基于对齐的交叉约会技术。由于后者的信息内容比例如只是环宽，这些新方法将需要更少的样品材料，同时提高约会精度。最后，我们将建立一个管道来研究环境因素与树木年轮密度剖面的相关性。初步研究将重点关注如何将位置或地点概率分配给未定位的树木年轮样本的应用程序。所有工具和管道都将公开，并附有大量文档。