Methods for robust estimates of tree biomass from pollen accumulation rates: Quantifying paleoecological reconstruction uncertainty

Author:

Knight Clarke A.,Battles John J.,Bunting M. Jane,Champagne Marie,Wanket James A.,Wahl David B.

Abstract

Pollen accumulation rates (PAR, grains cm–2 year–1) have been shown to be a reliable but methodologically complex bioproxy for quantitative reconstruction of past tree abundance. In a prior study, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and the pollen group TC (Taxaceae and Cupressaceae families) – were robust and precise estimators of contemporary tree biomass. This paper expands our earlier work. Here, we more fully evaluate the errors associated with biomass reconstructions to identify weaknesses and recommend improvements in PAR-based reconstructions of forest biomass. We account for uncertainty in our biomass proxy in a formal, coherent fashion. The greatest error was introduced by the age models, underscoring the need for improved statistical approaches to age-depth modeling. Documenting the uncertainty in pollen vegetation models should be standard practice in paleoecology. We also share insights gained from the delineation of the relevant source area of pollen, advances in Bayesian 210Pb modeling, the importance of site selection, and the use of independent data to corroborate biomass estimates. Lastly, we demonstrate our workflow with a new dataset of reconstructed tree biomass between 1850 and 2018 AD from lakes in the Klamath Mountains, California. Our biomass records followed a broad trend of low mean biomass in the ∼1850s followed by large contemporary increases, consistent with expectations of forest densification due to twentieth century fire suppression policies in the American West. More recent reconstructed tree biomass estimates also corresponded with silviculture treatments occurring within the relevant source area of pollen of our lake sites.

Publisher

Frontiers Media SA

Subject

Ecology,Ecology, Evolution, Behavior and Systematics

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