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Terry N. Brown

Researcher at Natural Resources Research Institute

Publications -  36
Citations -  827

Terry N. Brown is an academic researcher from Natural Resources Research Institute. The author has contributed to research in topics: Wetland & Watershed. The author has an hindex of 15, co-authored 36 publications receiving 751 citations. Previous affiliations of Terry N. Brown include University of Minnesota & Lincoln University (New Zealand).

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Environmentally stratified sampling design for the development of Great Lakes environmental indicators.

TL;DR: The site selection process allowed us to exclude sites that were inaccessible and was shown to successfully distribute sites across the range of environmental variation in the authors' GIS data, which has broad applicability when the goal is to develop ecological indicators using observational data from large-scale surveys.
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Standardized Measures of Coastal Wetland Condition: Implementation at a Laurentian Great Lakes Basin-Wide Scale

TL;DR: In this paper, the authors developed standardized methods and indicators used for assessing wetland condition and implemented a standardized basin-wide coastal wetland monitoring program that would be a powerful tool to inform decision-makers on coastal wetlands conservation and restoration priorities throughout the Great Lakes basin.
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Responsiveness of Great Lakes Wetland Indicators to Human Disturbances at Multiple Spatial Scales: A Multi-Assemblage Assessment

TL;DR: In this article, the responsiveness of 66 candidate indicators to human disturbance (agriculture, urban devel- opment, and point source contaminants) characterized at multiple spatial scales (100, 500, 1,000, and 5,000 m buffers and whole watersheds) using classification and regression tree analysis (CART).
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Diatom-based weighted-averaging transfer functions for Great Lakes coastal water quality: Relationships to watershed characteristics

TL;DR: In this article, a diatom inference transfer function for total phosphorus (TP) was developed from 155 samples collected from coastal Great Lakes wetlands, embayments and high-energy shoreline sites.
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Validating models of complex, stochastic, biological systems

TL;DR: It is concluded that, while time consuming, development of system-specific objective indices may often be the most useful way to compare simulation output and field data when complex biological entities are modelled.