TY - JOUR
T1 - Factors influencing ponderosa pine regeneration in the southwestern USA
AU - Puhlick, Joshua J.
AU - Laughlin, Daniel C.
AU - Moore, Margaret M.
N1 - Funding Information:
We acknowledge A. Stevenson and S. Sesnie for their help with the GIS aspects of this project. We thank W. Robbie, J. Youtz and M. Manthei for their expert opinions, advice and discussions about the project. We acknowledge J. Blackard, A. Sánchez Meador and D. Vandendriesche for their help with the FIA aspects of this project. We thank J. Bakker for his advice and help with the project. We thank the staff and students of the Ecological Restoration Institute, Northern Arizona University for field and laboratory assistance. We thank A. Finkral, P. Fulé and K. Waring for reviewing the study design and results of this project. We also thank two anonymous reviewers who provided useful comments that helped us to improve the paper. Funding for this project was provided by the USDA National Research Initiative , Grant number 2008-35101-19046 .
PY - 2012/1/15
Y1 - 2012/1/15
N2 - Improving predictions of ponderosa pine (Pinus ponderosa var. scopulorum) regeneration is critical as landscape-scale restoration efforts are being implemented across the western United States. The establishment of new ponderosa pine cohorts following restoration treatments will have long-term impacts on the future development of forest stands. At a regional scale, we used data associated with 364 Forest Inventory and Analysis (FIA) plots within the ponderosa pine forest type on National Forests in Arizona and New Mexico. At a local scale, we sampled 28 stands on basalt and sedimentary parent materials on the Coconino National Forest in northern Arizona. Structural equation models were developed to determine the relative importance of direct and indirect factors affecting ponderosa pine seedling densities at both regional and local scales. The regional model only explained 13% of the variation in pine seedling density. The model indicated that ponderosa pine seedling density was highest where (1) mean annual precipitation was highest, (2) average May minimum temperature was highest, (3) overstory stand basal area was lowest and (4) Muhlenbergia spp. were dominant herbaceous plants. The local model explained 76% of the variation in pine seedling density. Densities were highest where (1) mean annual precipitation was highest, (2) soil clay content was lowest, (3) soil pH was lowest, (4) Muhlenbergia virescens frequency was highest and (5) seed tree frequency was highest. If additional factors such as soil texture, soil pH, screwleaf muhly frequency and seed tree frequency were measured on FIA plots, then perhaps more variation in pine seedling density could be explained at the regional scale.
AB - Improving predictions of ponderosa pine (Pinus ponderosa var. scopulorum) regeneration is critical as landscape-scale restoration efforts are being implemented across the western United States. The establishment of new ponderosa pine cohorts following restoration treatments will have long-term impacts on the future development of forest stands. At a regional scale, we used data associated with 364 Forest Inventory and Analysis (FIA) plots within the ponderosa pine forest type on National Forests in Arizona and New Mexico. At a local scale, we sampled 28 stands on basalt and sedimentary parent materials on the Coconino National Forest in northern Arizona. Structural equation models were developed to determine the relative importance of direct and indirect factors affecting ponderosa pine seedling densities at both regional and local scales. The regional model only explained 13% of the variation in pine seedling density. The model indicated that ponderosa pine seedling density was highest where (1) mean annual precipitation was highest, (2) average May minimum temperature was highest, (3) overstory stand basal area was lowest and (4) Muhlenbergia spp. were dominant herbaceous plants. The local model explained 76% of the variation in pine seedling density. Densities were highest where (1) mean annual precipitation was highest, (2) soil clay content was lowest, (3) soil pH was lowest, (4) Muhlenbergia virescens frequency was highest and (5) seed tree frequency was highest. If additional factors such as soil texture, soil pH, screwleaf muhly frequency and seed tree frequency were measured on FIA plots, then perhaps more variation in pine seedling density could be explained at the regional scale.
KW - Climate
KW - Coconino National Forest
KW - Ecological restoration
KW - Forest Inventory and Analysis
KW - Structural equation modeling
KW - Tree regeneration
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U2 - 10.1016/j.foreco.2011.10.002
DO - 10.1016/j.foreco.2011.10.002
M3 - Article
AN - SCOPUS:80055017753
SN - 0378-1127
VL - 264
SP - 10
EP - 19
JO - Forest Ecology and Management
JF - Forest Ecology and Management
ER -