景观尺度上的生态系统健康及其测量:迈向新一代定量评估

Ganapati P. Patil, Robert P. Brooks, Wayne L. Myers, David J. Rapport, Charles Taillie
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引用次数: 61

摘要

本文的目的有两个:(A)描述在景观尺度上报告生态系统健康变化所面临的挑战;(B)回顾从各种数据中得出景观健康评估的统计和数学技术,这些数据包括遥感图像、人口和社会经济普查、自然资源调查、长期生态研究和其他特定地点的地理空间信息。我们借鉴了七个创新和综合的概念和工具,它们将共同提供下一代区域尺度的生态系统健康评估。首先是生态系统健康的概念,它综合了社会科学、自然科学、物理科学和健康科学,为区域环境综合评价提供了基础。第二部分包括创新的随机技术来表示景观中的人类干扰和生态系统响应,以及相应的统计工具来分析它们。第三,通过梯队分析的评价,构建景观空间生物复杂性的表征。第四是基于上层空间扫描统计的创新组合技术,用于检测、描绘和优先考虑关键研究领域,以评估和优先考虑因果因素和影响。第五项涉及根据多个标准对实体集合进行比较和优先排序的能力,使用偏序的偏序数学和秩频率统计,以提供多标准决策支持。第六是扩展数据挖掘和可视化技术,以确定景观尺度上地理空间格局和生态系统退化之间的关联。第七部分包括对不同类型的区域生态系统进行的综合研究。我们的重点是展示定量技术和工具的最新进展将如何促进生态系统健康的评估及其在各种景观尺度上的测量。挑战在于描述、评估和验证社会经济驱动因素、生物地球化学指标、多尺度景观格局指标和人类生活质量指标之间的联系。这些定量技术和工具的最初应用是在美国东部地区,包括美国大西洋斜坡和大西洋中部地区。
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Ecosystem Health and Its Measurement at Landscape Scale: Toward the Next Generation of Quantitative Assessments

ABSTRACT The purpose of this paper is twofold: (A) to describe the challenges of reporting on changes in ecosystem health at landscape scales, and (B) to review the statistical and mathematical techniques that allow the derivation of landscape health assessments from a variety of data consisting of remote sensing imagery, demographic and socioeconomic censuses, natural resource surveys, long-term ecological research, and other geospatial information that is site specific.

We draw upon seven innovative and integrative concepts and tools that together will provide the next generation of ecosystem health assessments at regional scales. The first is the concept of ecosystem health, which integrates across the social, natural, physical, and health sciences to provide the basis for comprehensive assessments of regional environments. The second consists of innovative stochastic techniques for representing human disturbance and ecosystem response in landscapes, and the corresponding statistical tools for analyzing them. The third constitutes representation of spatial biocomplexity in landscapes through application of echelon analysis to assessment. The fourth concerns innovative combination techniques of upper-echelon-based spatial scan statistic to detect, delineate, and prioritize critical study areas for evaluating and prioritizing causal factors and effects. The fifth involves the capability of comparing and prioritizing a collection of entities in light of multiple criteria, using poset mathematics of partial order with rank frequency statistics, to provide multicriterion decision support. The sixth lies in extending data mining and visualization techniques to determine associations between geospatial patterns and ecosystem degradation at landscape scales. The seventh encompasses comprehensive studies conducted on different types of regional ecosystems.

Our focus is to show how the integration of recent advances in quantitative techniques and tools will facilitate the evaluation of ecosystem health and its measurement at a variety of landscape scales. The challenge is to characterize, evaluate, and validate linkages between socioeconomic drivers, biogeochemical indicators, multiscale landscape pattern metrics, and quality of human life indicators. Initial applications of these quantitative techniques and tools have been with respect to regions in the eastern United States, including the U.S. Atlantic Slope and mid-Atlantic region.

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