Sampling density and date along with species selection influence spatial representation of tree-ring reconstructions

Sampling density and date along with species selection influence spatial representation of tree-ring reconstructions

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 underst...

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Bibliographic Details
Published in:Climate of the past Vol. 16; no. 5; pp. 1901 - 1916
Main Authors: Maxwell, Justin T, Harley, Grant L, Matheus, Trevis J, Strange, Brandon M, Van Aken, Kayla, Au, Tsun Fung, Bregy, Joshua C
Format: Journal Article
Language:English
Published: Katlenburg-Lindau Copernicus GmbH 19-10-2020
Copernicus Publications
Subjects:
Analysis
Banks (Finance)
Calibration
Dendrochronology
Density
Drought
Drought conditions
Drought index
Droughts
Extreme weather
Hydroclimate
Hypotheses
Natural variability
Principal components analysis
Representations
River valleys
Sampling
Sensitivity
Soil
Soil moisture
Soils
Spatial variability
Spatial variations
Temporal variability
Temporal variations
Tree rings
Trees
Variability
United States > US
North America
Ohio River
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Summary: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.
ISSN:1814-9332
1814-9324
1814-9332
DOI:10.5194/cp-16-1901-2020