Statistical and visual crossdating in R using the dplR library
By A. Bunn. 2010
576 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/c15630aa22e5ec42089848d4093d0473495e462f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- Jesús Julio Camarero
- R. Sánchez‐Salguero
- J. Linares
- Hans Pretzsch
- Antonio Gazol
- M. de Luis
- M. Río
- Enno Uhl
In Global and Planetary Change
- M. Río
- Jesús Julio Camarero
- Hans Pretzsch
- R. Sánchez‐Salguero
- Antonio Gazol
- K. Bielak
- M. Pach
- J. Linares
Citations in the corpus
- The greater resilience of mixed forests to drought mainly depends on their composition: Analysis along a climate gradient across Europe (2021, methodology): “To assess the reliability of the chronologies, we calculated descriptive statistics using “dplR” R package (Bunn 2010) for each species and plot, including Rbar (mean interseries correlation) and EPS (expressed population signal of detrended BAI series) (Table A2).”
- Resist, recover or both? Growth plasticity in response to drought is geographically structured and linked to intraspecific variability in Pinus pinaster (2018, methodology): “Chronology building and climate– growth associations were performed using the packages dplR (Bunn, 2010) and treeclim (Zang & Biondi, 2015) respectively.”