Canadian Forest Service Publications

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3. 2012. Metsaranta, J.M.; Kurz, W.A. Ecological Modelling 224(1):111-123.

Year: 2012

Issued by: Northern Forestry Centre

Catalog ID: 32936

Language: English

Availability: PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.1016/j.ecolmodel.2011.10.026

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We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41–60 years) to 2004 (when they aged 70–89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm−2 yr−1 (range −31 to 176 g Cm−2 yr−1, NPP 244 g Cm−2 yr−1 (147–376 g Cm−2 yr−1), and Rh 187 g Cm−2 yr−1 (124–270 g Cm−2 yr−1). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Interannual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.