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Quantitative Habitat Analysis: A New Tool for the Integration of Modeling, Planning, and Management of Natural Resources

机译:定量生境分析:自然资源的建模,规划和管理集成的新工具

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Federal laboratories are often caught between the need to meet mission objectives and the mandate to act as national stewards for natural resources. Following the initiation of the Manhattan Project in 1943, restricted land use at Los Alamos National Laboratory (LANL) retained many undisturbed areas that function as ecosystem sanctuaries for plants and animals throughout the 43 mi~2 site. We developed a Quantitative Habitat Analysis (QHA) that enables both managers and scientists to better meet the goals of ecosystem management and sustainable development for LANL. QHA is a multi-faceted modeling, planning, and management tool with the goal of applying existing models in a new way. QHA provides an objective, standardized, and replicable system for management of wild areas by federal agencies. As part of the development of QHA, we reviewed 42 existing wildlife and habitat models, assessments, or evaluation methods and 12 computer programs. A pilot field study was conducted on 12 plots testing five different methods to determine the most suitable for data collection for the tool. Once methods were selected and models determined, a QHA application tool was created in ArcView to test the pilot data within the tool for user-friendly application. This year, 45 field sites were sampled. QHA currently comprises five main sub-models analyzed within a geographic information system using ArcView: 1) Ecological Land Classification (landscape level effects), 2) Rapid Ecological Assessment (general assessment)/U.S. National Vegetation Classification Element Occurrence (ecosystem "health"), 3) BEHAVE (wildfire and fuels monitoring), 4) Habitat Analysis and Modeling System (wildlife), and 5) ECORSK.6 (bio-contaminants). Key to this QHA tool was the use of "common currencies." The common currencies consist of weighted scores that calculate a "grade" or means of comparison between different programs and scoring methods. Development and calibration of the QHA continues.
机译:联邦实验室通常介于实现任务目标的需要和充当国家自然资源管理者的任务之间。在1943年启动曼哈顿项目后,洛斯阿拉莫斯国家实验室(LANL)的土地限制使用保留了许多未受干扰的地区,这些地区在整个43英里至2处成为动植物的生态系统庇护所。我们开发了定量栖息地分析(QHA),使管理人员和科学家都能更好地实现LANL的生态系统管理和可持续发展目标。 QHA是一个多方面的建模,计划和管理工具,旨在以一种新的方式应用现有模型。 QHA为联邦机构的野外管理提供了一个客观,标准化和可复制的系统。作为QHA开发的一部分,我们审查了42种现有的野生动植物和栖息地模型,评估或评估方法以及12种计算机程序。在12个地块上进行了中试研究,测试了五种不同方法,以确定最适合该工具数据收集的方法。一旦选择了方法并确定了模型,就可以在ArcView中创建一个QHA应用程序工具,以测试该工具中的试验数据,以实现用户友好的应用程序。今年,对45个现场地点进行了采样。 QHA目前包括使用ArcView在地理信息系统中分析的五个主要子模型:1)生态土地分类(景观水平效应),2)快速生态评估(一般评估)/美国。国家植被分类要素的发生(生态系统“健康”),3)行为(野火和燃料监测),4)栖息地分析和建模系统(野生生物)和5)ECORSK.6(生物污染物)。此QHA工具的关键是使用“通用货币”。通用货币由加权分数组成,这些分数计算出“等级”或不同程序与计分方法之间的比较手段。 QHA的开发和校准仍在继续。

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