Browsing by Author "Kleindl, William"

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Aquatic Ecosystem Services Survey: Round One Results
(Montana State University, 2021-04) Gilbert, Ashlie; Kleindl, William; Chruch, Sarah P.
Wetlands, streams, and floodplains (hereafter called aquatic systems) are an important resource for social and ecological wellbeing. Since the early 1990s, Federal policy has required a no overall net loss (NNL) of wetland area (i.e. aquatic systems), functions, and values in the United States (US). Past efforts to build assessment tools have focused primarily on wetland structure and function, and less on inherent services provided by aquatic ecosystems that are valued by people (hereafter referred to as ecosystem services (ES)). Moreover, there has been little effort to develop assessment tools that measure wetland services in a rapid and repeatable manner. Our intent with this research is to develop a framework and generalized methodology for the rapid assessment of ES provided by wetlands, streams and their riparian buffers for use in permitting, compensatory mitigation, and preservation decisions. Moreover, we seek to understand aquatic systems decision-makers’ perceptions of planning and land use surrounding wetland protection and mitigation.
Aquatic Ecosystem Services Survey: Round Two Results
(Montana State University, 2022-05) Gilbert, Ashlie; Kleindl, William; Church, Sarah P.
Wetlands, streams, and floodplains (hereafter called aquatic systems) are an important resource for social and ecological wellbeing. Since the early 1990s, Federal policy has required a no overall net loss (NNL) of wetland area (i.e., aquatic systems), functions, and values in the United States (US). Past efforts to build assessment tools have focused primarily on wetland structure and function, and less on inherent services provided by aquatic ecosystems that are valued by people (hereafter referred to as ecosystem services (ES)). Moreover, there has been little effort to develop assessment tools that measure wetland services in a rapid and repeatable manner. Our intent with this research is to develop a framework and generalized methodology for the rapid assessment of ES provided by wetlands, streams, and their riparian buffers for use in permitting, compensatory mitigation, and preservation decisions. Moreover, we seek to understand aquatic systems decision-makers’ perceptions of planning and land use surrounding wetland protection and mitigation.
Effect of thematic map misclassification on landscape multi-metric assessment
(2015-05) Kleindl, William; Powell, Scott L.; Hauer, F. Richard
Advancements in remote sensing and computational tools have increased our awareness of large-scale environmental problems, thereby creating a need for monitoring, assessment, and management at these scales. Over the last decade, several watershed and regional multi-metric indices have been developed to assist decision-makers with planning actions of these scales. However, these tools use remote-sensing products that are subject to land-cover misclassification, and these errors are rarely incorporated in the assessment results. Here, we examined the sensitivity of a landscape-scale multi-metric index (MMI) to error from thematic land-cover misclassification and the implications of this uncertainty for resource management decisions. Through a case study, we used a simplified floodplain MMI assessment tool, whose metrics were derived from Landsat thematic maps, to initially provide results that were naive to thematic misclassification error. Using a Monte Carlo simulation model, we then incorporated map misclassification error into our MMI, resulting in four important conclusions: (1) each metric had a different sensitivity to error; (2) within each metric, the bias between the error-naive metric scores and simulated scores that incorporate potential error varied in magnitude and direction depending on the underlying land cover at each assessment site; (3) collectively, when the metrics were combined into a multi-metric index, the effects were attenuated; and (4) the index bias indicated that our naive assessment model may overestimate floodplain condition of sites with limited human impacts and, to a lesser extent, either over- or underestimated floodplain condition of sites with mixed land use.