CoulombeBernierRaulier2010

Reference

Coulombe, S., Bernier, P.Y., Raulier, F. (2010) Uncertainty in detecting climate change impact on the projected yield of black spruce (Picea mariana). Forest Ecology and Management, 259(4):730-738. (Scopus )

Abstract

The empirical growth and yield (G&Y) curves used in most timber supply models assume that growth conditions are invariable over time, which may not be correct given the projected future climate. However, errors in G&Y models can be quite large, and we therefore wanted to know the probability of detecting climate change-induced growth anomalies as a departure from current G&Y predictions. The work was carried out in a boreal forest study area in Eastern Canada, where Picea mariana Mill. BSP (black spruce) is the dominant species. Climate change effects were incorporated into G&Y predictions as correction factors obtained from process-based simulations of growth using current or projected climate. Uncertainty in G&Y projections was quantified through the inclusion of sampling and model errors in a bootstrap re-sampling scheme that yielded a percentile distribution of possible differences between G&Y curves that included or did not include climate change effects. Results yielded an average projected increase in productivity of 29% under future climate conditions for the black spruce strata in the study area. The probability of the climate change-modified G&Y predictions being significantly different from the current G&Y projections is 75% when considering the sampling error alone, and of 67% when both the sampling and modelling errors are included. Although incomplete in terms of what sources of error have been included, this study demonstrates the type of information that can be generated on the propagation of uncertainty in G&Y projections and, ultimately, on timber supply. Crown Copyright © 2009.

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@ARTICLE { CoulombeBernierRaulier2010,
    AUTHOR = { Coulombe, S. and Bernier, P.Y. and Raulier, F. },
    TITLE = { Uncertainty in detecting climate change impact on the projected yield of black spruce (Picea mariana) },
    JOURNAL = { Forest Ecology and Management },
    YEAR = { 2010 },
    VOLUME = { 259 },
    PAGES = { 730-738 },
    NUMBER = { 4 },
    ABSTRACT = { The empirical growth and yield (G&Y) curves used in most timber supply models assume that growth conditions are invariable over time, which may not be correct given the projected future climate. However, errors in G&Y models can be quite large, and we therefore wanted to know the probability of detecting climate change-induced growth anomalies as a departure from current G&Y predictions. The work was carried out in a boreal forest study area in Eastern Canada, where Picea mariana Mill. BSP (black spruce) is the dominant species. Climate change effects were incorporated into G&Y predictions as correction factors obtained from process-based simulations of growth using current or projected climate. Uncertainty in G&Y projections was quantified through the inclusion of sampling and model errors in a bootstrap re-sampling scheme that yielded a percentile distribution of possible differences between G&Y curves that included or did not include climate change effects. Results yielded an average projected increase in productivity of 29% under future climate conditions for the black spruce strata in the study area. The probability of the climate change-modified G&Y predictions being significantly different from the current G&Y projections is 75% when considering the sampling error alone, and of 67% when both the sampling and modelling errors are included. Although incomplete in terms of what sources of error have been included, this study demonstrates the type of information that can be generated on the propagation of uncertainty in G&Y projections and, ultimately, on timber supply. Crown Copyright © 2009. },
    COMMENT = { Export Date: 12 February 2010 Source: Scopus CODEN: FECMD doi: 10.1016/j.foreco.2009.06.028 },
    ISSN = { 03781127 (ISSN) },
    OWNER = { Luc },
    TIMESTAMP = { 2010.02.12 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-73449122230&partnerID=40&md5=c476ab32a57a8890797c82adf6ee83ff },
}

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