Corrigendum to “Patterns of conifer regeneration following high severity wildfire in ponderosa pine–dominated forests of the Colorado Front Range” [For. Ecol. Manage. 378 (2016) 57–67] (Forest Ecology and Managementyy (2016) 378 (57–67), (S0378112716303474), (10.1016/j.foreco.2016.07.001))
Other Scholarly Work
Chambers, ME, Fornwalt, PJ, Malone, SL et al. (2022). Corrigendum to “Patterns of conifer regeneration following high severity wildfire in ponderosa pine–dominated forests of the Colorado Front Range” [For. Ecol. Manage. 378 (2016) 57–67] (Forest Ecology and Managementyy (2016) 378 (57–67), (S0378112716303474), (10.1016/j.foreco.2016.07.001))
. FOREST ECOLOGY AND MANAGEMENT, 507 10.1016/j.foreco.2021.119971
Chambers, ME, Fornwalt, PJ, Malone, SL et al. (2022). Corrigendum to “Patterns of conifer regeneration following high severity wildfire in ponderosa pine–dominated forests of the Colorado Front Range” [For. Ecol. Manage. 378 (2016) 57–67] (Forest Ecology and Managementyy (2016) 378 (57–67), (S0378112716303474), (10.1016/j.foreco.2016.07.001))
. FOREST ECOLOGY AND MANAGEMENT, 507 10.1016/j.foreco.2021.119971
We regret to report that we discovered errors in our data as we prepared them for archival. The errors arose from a sorting mistake and affected a portion of the explanatory variable data used to predict all conifer, ponderosa pine, and Douglas-fir regeneration densities via generalized estimating equation and regression tree analyses. The explanatory variables with some mis-sorted data were pre-fire stand basal area, coarse wood, fine wood, understory vegetation, productivity index, drainage index, topographic wetness index, and solar radiation. We also found a miscalculation in the explanatory variable aspect. We have carefully corrected the data and rerun the analyses. The original findings stemming from the generalized estimating equation analyses remain largely unchanged: distance from surviving forest continues to be an important predictor of all conifer and ponderosa pine regeneration density, and elevation continues to be an important predictor of all conifer, ponderosa pine, and Douglas-fir regeneration density. However, understory vegetation is no longer a predictor of Douglas-fir regeneration density. Additionally, some new findings have emerged from the updated generalized estimating equation analyses that add depth to the original findings. Specifically, the updated analyses now also show that: (1) distance from surviving forest is also a predictor of Douglas-fir regeneration density, (2) pre-fire basal area is a predictor of all conifer and ponderosa pine regeneration density, (3) fine wood is a predictor of all conifer, ponderosa pine, and Douglas-fir regeneration density, (4) drainage index is a predictor of Douglas-fir regeneration density, and (5) solar radiation is a predictor of Douglas-fir regeneration density. The findings stemming from the regression tree analyses remain unchanged, as do all other findings. Below is an updated version of the generalized estimating equation p-values presented in Table 2. P-values in black type indicate that the significance assessment (α = 0.050) for the relationship remains unchanged from the original assessment (although p-values may differ somewhat). P-values in blue type indicate that the relationship is now significant, while p-values in red type indicate that the relationship is now no longer significant. For all relationships that are now significant, the symbol in parentheses indicates whether the relationship is positive (+) or negative (-). [Figure presented] We apologize for any inconvenience.
