Structure area curves in Eastern Hardwoods: implications for minimum plot sizes to capture spatially explicit structure indices

Jerilynn Peck (1) , Eric Zenner (1)

1 Penn State - Pennsylvania State University

Context: Managing forest stand structures for multiple objectives require accurate and precise estimates of structural features that may be best estimated at different scales. Aims: We document minimum necessary plot sizes for structural metrics and spatially explicit indices to characterize structure in a mature North American Eastern hardwoods forest.• MethodsMetrics and indices (Index of Aggregation, Diameter Differentiation Index, Dissimilarity Coefficient, Structural Complexity Index) were calculated within 0.05–1.75-ha plots for 1000 iterations of random placement in two 2.0-ha macroplots. Estimation adequacy required (1) precision (varied < 10% among plots) and (2) accuracy (within 10% of the 2.0-ha value at 5th and 95th percentiles). Results: Minimum single plot sizes to achieve estimation adequacy were 0.25–0.75 ha for spatially explicit indices and 0.5–2 ha for stand metrics. A minimum of five 0.10-ha subplots would be needed for most indices and 6–25 for most metrics, but an untenable 375+ for the density of large diameter trees. Conclusion: Estimation adequacy for structural complexity requires no greater sampling intensity than for timber metrics, except for density of large trees. A single large plot may be most cost-effective. National inventories in Eastern hardwoods may not estimate structural complexity well due to inadequate sampling intensity.

Mots clés: Quercus; Structural complexity; Sampling; Rarity; Estimation error; Oak

Domaines: Sylviculture, foresterie

Jerilynn Peck, Eric Zenner. Structure area curves in Eastern Hardwoods: implications for minimum plot sizes to capture spatially explicit structure indices. Annals of Forest Science, 2021, 78 (1), pp.16. ⟨10.1007/s13595-021-01036-5⟩. ⟨hal-03582023⟩