DENDROCLIM2002: A C++ program for statistical calibration of climate signals in tree-ring chronologies

By Franco Biondi, Kishor K. Waikul. Computational Geosciences, 2004

1,178 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/7d4f6331b8d728f9c0bcafc0895ce4a420e8f10f

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Citations in the corpus

Selective drought-induced decline of pine species in southeastern Spain (2012, methodology): “Correlation and bootstrap response functions were calculated using the program Dendroclim2002 (Biondi and Waikul 2004).”
Size mediated climate–growth relationships in Pinus halepensis and Pinus pinea (2009, methodology): “Thus, a correlation function analysis was performed using the DendroClim2002 programme (Biondi and Waikul 2004).”
Intensity and timing of warming and drought differentially affect growth patterns of co-occurring Mediterranean tree species (2013, methodology): “To calculate the correlation and response coefficients, we used the program Dendroclim2002 (Biondi and Waikul 2004).”
Radial growth responses to drought of Pinus sylvestris and Quercus pubescens in an inner-Alpine dry valley (2007, methodology): “Moving response functions (Biondi & Waikul 2004) could be applied for the Valais to longer chronologies than ours to detect a possible shift in the response pattern.”
Tree-ring variation, wood formation and phenology of beech (Fagus sylvatica) from a representative site in Slovenia, SE Central Europe (2008, positive): “Climate–growth relationships were calculated using the program DendroClim2002 through correlation function analysis (Biondi and Waikul 2004), where the residual version of the tree-ring chronology was the dependent variable and the regressors were the monthly minimum, maximum and mean temperatures a”
Extreme drought alters competitive dominance within and between tree species in a mixed forest stand (2013, methodology): “…series of coefficients were calculated, relating the ring width indices from the de-trended chronologies to monthly climate variables covering from the beginning of the previous year’s growing season until the end of the current year’s growing season (Cook & Kairiukstis 1990; Biondi & Waikul 2004).”
Growth response to climate and drought in Pinus nigra Arn. trees of different crown classes (2008, methodology): “Correlation and response function were calculated with DENDROCLIM2002 (Biondi and Waikul 2004), which uses bootstrapped error estimates (Guiot 1991).”
Bioclimatology of beech (Fagus sylvatica L.) in the Eastern Alps: spatial and altitudinal climatic signals identified through a tree‐ring network (2007, methodology): “Dendroclimatic correlation and response functions (Biondi & Waikul, 2004) were calculated between monthly climate variables and two types of tree-ring bioindicators.”
Time-dependent effects of climate and drought on tree growth in a Neotropical dry forest: Short-term tolerance vs. long-term sensitivity (2014, methodology): “Bootstrapped correlation analyses were performed to 190 evaluate the relationships between residual ring-width chronologies of each species and 78 191 climatically different periods using the software Dendroclim2002 (Biondi and Waikul, 2004).”
Drought response and changing mean sensitivity of European beech close to the dry distribution limit (2013, methodology): “In addition, we used the software DENDROCLIM (Biondi and Waikul 2004) to compute moving response functions in a 30-year window, which allowed dynamical changes in the drought response pattern to be detected across time.”
Contrasting vulnerability and resilience to drought-induced decline of densely planted vs. natural rear-edge Pinus nigra forests (2013, methodology): “Correlation and bootstrap confident intervals were calculated using the program Dendroclim2002 (Biondi and Waikul, 2004).”
Climate increases regional tree‐growth variability in Iberian pine forests (2007, methodology): “Correlation and response function analyses were performed using the program Dendroclim2002 (Biondi & Waikul, 2004) to quantify the climate–growth relationships between the regional chronology (PC1) and the Spanish climate series (monthly mean temperature and precipitation data) from 1902 to 2000.”