Tree-ring-based climate reconstructions are typically derived from either (1) a single species from one or multiple locations or (2) multiple species from multiple locations. Here, we investigate the ability of using multiple co-occurring canopy-dominant species from a single location for climate reconstructions based in the eastern United States. Using a variety of techniques, we first compare the climate signals of three canopy-dominant species (Quercus rubra, Quercus alba, Liriodendron tulipifera) at an old-growth forest in southern Indiana. We then determine if a composite time series of these co-occurring species increases or decreases the reconstruction model skill. Climate-growth correlation analysis of the species reveals strong and consistent relationships with summer [June-August (JJA)] Palmer Drought Severity Index (PDSI) during the period 1895-2012. We first use a split-sample reconstruction technique to compare the performance of species reconstruction models. We then use a nested technique to build a composite chronology against which to compare the individual species chronologies. The composite chronology of all three species accounts for up to 38% of the mean variation in JJA PDSI, and verification statistics indicate robust statistical skill from 1870 to 2012. The composite chronology reconstruction also outperforms each individual species model, indicating that using multiple co-occurring species increases reconstruction skill, at least from a single study site. Furthermore, model performance is improved by using nested reconstruction techniques, and implicates the potential ability to use multiple co-occurring species across multiple locations in the eastern United States.
Abstract. Our understanding of the natural variability of hydroclimate
before the instrumental period (ca. 1900 CE in the United States) is largely
dependent on tree-ring-based reconstructions. Large-scale soil moisture
reconstructions from a network of tree-ring chronologies have greatly
improved our understanding of the spatial and temporal variability in
hydroclimate conditions, particularly extremes of both drought and pluvial
(wet) events. However, certain regions within these large-scale network
reconstructions in the US are modeled by few tree-ring chronologies.
Further, many of the chronologies currently publicly available on the
International Tree-Ring Data Bank (ITRDB) were collected in the 1980s and
1990s, and thus our understanding of the sensitivity of radial growth to soil
moisture in the US is based on a period that experienced multiple extremely
severe droughts and neglects the impacts of recent, rapid global change. In
this study, we expanded the tree-ring network of the Ohio River valley in
the US, a region with sparse coverage. We used a total of 72 chronologies
across 15 species to examine how increasing the density of the tree-ring
network influences the representation of reconstructing the Palmer
Meteorological Drought Index (PMDI). Further, we tested how the sampling
date and therefore the calibration period influenced the reconstruction
models by creating reconstructions that ended in the year 1980 and compared
them to reconstructions ending in 2010 from the same chronologies. We found
that increasing the density of the tree-ring network resulted in
reconstructed values that better matched the spatial variability of
instrumentally recorded droughts and, to a lesser extent, pluvials. By
extending the calibration period to 2010 compared to 1980, the sensitivity
of tree rings to PMDI decreased in the southern portion of our region where
severe drought conditions have been absent over recent decades. We emphasize
the need of building a high-density tree-ring network to better represent
the spatial variability of past droughts and pluvials. Further, chronologies
on the ITRDB need updating regularly to better understand how the
sensitivity of tree rings to climate may vary through time.
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