"Researching, modelling and mapping forest productivity in relation to topographically influenced soil properties, including soil moisture"

“研究、建模和绘制与地形影响的土壤特性（包括土壤湿度）相关的森林生产力”

• 批准号: 7803-2012
• 负责人: Arp, Paul
• 金额: $ 1.97万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=592889
• 关键词: Researching; modelling; mapping; forest; productivity

This proposal deals with learning how forest productivity varies from ridge tops to depressions, according to topography- and substrate-influenced moisture and nutrient regimes. Until now, this continuum has been represented by thematic soil and forest surveying and mapping methods. High-resolution digital elevation models (DEM), however, are now enabling a functional approach to model and map this change in a comprehensive manner at, e.g., 1m resolution. The individual research questions addressed with this proposal are as follows: (1) How well do LiDAR-mapped metrics such as the cartographic depth-to-water index (DTW) perform in reproducing plot-based determinations of ridge-to-depression variations regarding (i) forest productivity, (ii) soil, drainage and vegetation type, (iii) productivity affecting variables such as soil texture, bulk density (or pore space), organic matter content and rooting depth, and (iv) end-of summer levels pertaining to depth-to-water and soil moisture content. (2) How well are all these measures related to the DEM-derived DTW index and other DEM-derived indices such as slope, curvature and other widely used terrain wetness indices? (3)What combination of DEM-generated soil and site variables including DTW work best in modelling and mapping tree growth across the landscape? This research, to be done in New Brunswick with industrial facilitation, features natural forest conditions interspersed by forest plantations (jack pine, black spruce, white spruce). Data layers dealing with up-to-date forest inventories, and high-resolution surface images and topography (LiDAR, point cloud data) are already available. This proposal supports a team involving graduate students, summer assistants, and technical staff to conduct the field work (plot-based soil and vegetation surveying and sampling), laboratory analyses, GIS programming, and forest productivity modelling. This research will generate GIS-based models designed to map forest productivity by dominant species type across the forest management of immediate interest, and will also deal with matters pertaining to model generalization and mapping applications elsewhere.

这项建议涉及了解森林生产力如何根据地形和基材影响的湿度和营养状况，从山脊顶部到洼地变化。到目前为止，这一连续体一直以专题土壤和森林测绘方法为代表。然而，高分辨率数字高程模型（DEM）现在能够以一种全面的方式建模和绘制这种变化的功能方法，例如1m分辨率。本建议涉及的个别研究问题如下：(1)激光雷达绘制的指标，如地图深度到水指数（DTW），在再现基于图的山脊到洼地变化的决定方面表现如何，这些变化涉及(i)森林生产力，（ii）土壤、排水和植被类型，（iii）影响土壤质地、体积密度（或孔隙空间）、有机质含量和生根深度等变量的生产力，以及（iv）与深度到水和土壤含水量有关的夏末水平。(2)这些指标与dem衍生的DTW指数以及其他dem衍生的坡度、曲率等广泛使用的地形湿度指数的相关性如何？(3) dem生成的土壤和场地变量（包括DTW）的哪种组合最适合建模和绘制整个景观中的树木生长情况？这项研究将在工业便利的新不伦瑞克省进行，其特点是自然森林条件穿插着森林人工林（杰克松、黑云杉、白云杉）。处理最新森林清单的数据层、高分辨率表面图像和地形（激光雷达、点云数据）已经可用。该提案支持一个由研究生、暑期助理和技术人员组成的团队进行实地工作（基于地块的土壤和植被调查和采样）、实验室分析、GIS编程和森林生产力建模。这项研究将产生基于地理信息系统的模型，旨在通过直接感兴趣的森林管理按优势物种类型绘制森林生产力图，并将处理与模型推广和其他地方制图应用有关的问题。