Dendroclimatic Reconstructions from Multiple Co-Occurring Species from Old-Growth Deciduous Forests in Indiana, USA

Abstract:

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 for climate reconstructions based in the eastern United States (US). Using a variety of techniques, we first compare the climate signals of canopy-dominant species at three old-growth forests in southern Indiana. We then determine if a composite time series of these co-occurring species increases or decreases the reconstruction model skill. In all cases, climate-growth correlation analyses of the species reveal strong relationships with summer (June–August) Palmer Drought Severity Index during the period 1895–2013 CE. 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 for each site against which to compare the individual species chronologies. The composite chronologies consistently outperformed each individual species model, indicating that using multiple co-occurring species increases reconstruction skill. Furthermore, the stability of the climate signal increases with the inclusion of more species, even those that are rarely used in dendroclimatic work (i.e. Juglans nigra). These results indicate that sampling co-occurring species captures greater drought variance and more accurately explains how drought is experienced within a forest. Further, sampling co-occurring species at multiple sites in the Eastern US can improve broader scale regional drought reconstructions over the Common Era.