Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA

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Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA

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dc.contributor.author BRADY, TIMOTHY
dc.contributor.author MONLEON, VICENTE
dc.contributor.author GRAY, ANDREW
dc.date.accessioned 2012-06-26T21:55:48Z
dc.date.available 2012-06-26T21:55:48Z
dc.date.issued 2010
dc.identifier.citation Brady, T. J., V. J. Monleon, and A. N. Gray. 2010. Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA. Ecological Indicators 10:657-667. en_US
dc.identifier.uri http://hdl.handle.net/1773/19893
dc.description.abstract We propose using future vascular plant abundances as indicators of future climate in a way analogous to the reconstruction of past environments by many palaeoecologists. To begin monitoring future short-term climate changes in the forests of Oregon and Washington, USA, we developed a set of transfer functions for a present-day calibration set consisting of climate parameters estimated, and species abundances measured, at 107 USDA Forest Service FIA (Forest Inventory and Analysis) Phase 3 plots. For each plot, we derived climate estimates from the Daymet model database, and we computed species abundance as quadrat frequency and subplot frequency. We submitted three climate variables (mean January temperature, MJAT; mean July temperature, MJUT; and mean annual precipitation transformed to natural logarithms, MANPt) to canonical correspondence analysis (CCA), and verified their importances in structuring the species frequency data. Weighted averaging-partial least squares regression (WA-PLS) provided the means for calculating six transfer functions. In all cases, based on performance statistics generated by leave-one-out cross-validation, we identified two-component WA-PLS models as the most desirable. The predictive abilities of our transfer functions are comparable to, or better than, those reported in the literature, probably due both data quality and statistical considerations. However, model overfitting as a result of spatial autocorrelation remains a possibility. The large errors associated with our MJAT transfer functions connote that even the highest amount of change in mean January temperature predicted for Oregon and Washington for 2010-2039 would be indistinguishable from current conditions. The higher predictions indicate that our MJAT transfer functions may be able to track climate changes by the 2040s. Our MJUT transfer functions can detect change in mean July temperature under the highest projection for 2010-2039. Our MANPt transfer functions will be of limited use until the 2070s, given the predictions of only slight changes in mean annual precipitation during the early part of the twenty-first century. Our MJAT and MANPt transfer functions may prove useful at the present time to verify relative climatic stability. Because the predicted climate values sometimes deviate substantially from the observed values for individual plots, our transfer functions are appropriate for monitoring climatic trends over the entire Pacific Northwest or large regions within it, not for assessing climate change at individual plots. en_US
dc.language.iso en_US en_US
dc.publisher ECOLOGICAL INDICATORS en_US
dc.subject Vascular plant species; Climate indicators; Transfer functions; Canonical correspondence analysis; Weighted averaging-partial least squares regression en_US
dc.title Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA en_US
dc.type Article en_US


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