4.4 Article

Cost implications of cluster plot design choices for precise estimation of forest attributes in landscapes and forests of varying heterogeneity

Journal

CANADIAN JOURNAL OF FOREST RESEARCH
Volume 52, Issue 2, Pages 188-200

Publisher

CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cjfr-2020-0509

Keywords

cluster plot design; forest inventory design optimization; forest inventory cost model; forest pattern simulation; forest sampling simulation

Categories

Funding

  1. USDA National Institute of Food and Agriculture and Hatch Appropriations [PEN04700, 1019151]

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This study examines the tradeoffs between increasing sample size and modifying cluster plot design factors for improving forest inventory precision. The findings suggest that the type and scale of spatial heterogeneity have significant implications for plot design choices, with homogeneous stands and landscapes being the least costly to inventory. Subplot area and count have a greater impact on cost efficiency than subplot separation, especially in landscapes with aggregated forest patterns and stands with homogeneous tree patterns.
Tradeoffs occur when deciding between improving forest inventory precision by increasing sample size or by augmenting cluster plot design factors like size or subplot separation distance. The nature of these tradeoffs changes with variation in type and scale of the spatial pattern of the attribute of interest. To understand the impacts of relationships between type and scale of spatial heterogeneity and cluster plot design efficiency, we constructed a factorial simulation experiment and analysed relationships among forest inventory cost, cluster plot design factors, and different spatial heterogeneity scenarios constructed via simulation. To calculate cost, we constructed a cost model that accounted for both on-and between-plot costs. We found that type and scale of heterogeneity have important implications for plot design choices. Homogeneous stands and landscapes are the least costly to inventory. Subplot area and count have stronger impacts than subplot separation on cost efficiency, particularly in landscapes with aggregated forest patterns and in stands with homogeneous tree patterns. We discuss results in the context of the physical interaction between cluster plot geometry and spatial patterns at different scales, provide computer code for simulations, and suggest principles that forest inventory cluster plot design specialists should consider when designing inventories.

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