Restoring forest structure and process stabilizes forest carbon in wildfire-prone southwestern ponderosa pine forests

2016 ◽  
Vol 26 (2) ◽  
pp. 382-391 ◽  
Author(s):  
Matthew D. Hurteau ◽  
Shuang Liang ◽  
Katherine L. Martin ◽  
Malcolm P. North ◽  
George W. Koch ◽  
...  
Keyword(s):  
Forest Structure ◽  
Ponderosa Pine ◽  
Forest Carbon ◽  
Pine Forests ◽  
Ponderosa Pine Forests

Historical (1860) forest structure in ponderosa pine forests of the northern Front Range, Colorado

2015 ◽  
Vol 45 (11) ◽  
pp. 1462-1473 ◽  
Author(s):  
Peter M. Brown ◽  
Michael A. Battaglia ◽  
Paula J. Fornwalt ◽  
Benjamin Gannon ◽  
Laurie S. Huckaby ◽  
...  
Keyword(s):  
Pinus Ponderosa ◽  
Forest Structure ◽  
Ponderosa Pine ◽  
Rocky Mountain ◽  
Structural Data ◽  
Pine Forests ◽  
Land Use Impacts ◽  
Quadratic Mean ◽  
Ponderosa Pine Forests ◽  
Northern Colorado

Management of many dry conifer forests in western North America is focused on promoting resilience to future wildfires, climate change, and land use impacts through restoration of historical patterns of forest structure and disturbance processes. Historical structural data provide models for past resilient conditions that inform the design of silvicultural treatments and help to assess the success of treatments at achieving desired conditions. We used dendrochronological data to reconstruct nonspatial and spatial forest structure at 1860 in fourteen 0.5 ha plots in lower elevation (∼1900–2100 m) ponderosa pine (Pinus ponderosa Douglas ex P. Lawson & C. Lawson) forests across two study areas in northern Colorado. Fires recorded by trees in two or more plots from 1667 to 1859 occurred, on average, every 8–15 years depending on scale of analysis. The last fire recorded in two or more plots occurred in 1859. Reconstructed 1860 stand structures were very diverse, with tree densities ranging from 0 to 320 trees·ha−1, basal areas ranging from 0.0 to 17.1 m2·ha−1, and quadratic mean diameters ranging from 0.0 to 57.5 cm. All trees in 1860 were ponderosa pine. Trees were significantly aggregated in 62% of plots in which spatial patterns could be estimated, with 10% to 90% of trees mainly occurring in groups of two to eight (maximum, 26). Current stands based on living trees with a diameter at breast height of ≥4 cm are more dense (range, 175–1010 trees·ha−1) with generally increased basal areas (4.4 to 23.1 m2·ha−1) and smaller trees (quadratic mean diameters ranging from 15.7 to 28.2 cm) and contain greater proportions of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and Rocky Mountain juniper (Juniperus scopulorum Sarg.). This is the first study to provide detailed quantitative metrics to guide restoration prescription development, implementation, and evaluation in these and similar ponderosa pine forests in northern Colorado.

scholarly journals Uncertainty in surface-fire history: the case of ponderosa pine forests in the western United States

2001 ◽  
Vol 31 (7) ◽  
pp. 1205-1226 ◽  
Author(s):  
William L Baker ◽  
Donna Ehle
Keyword(s):  
United States ◽  
Forest Structure ◽  
Ponderosa Pine ◽  
Fire History ◽  
Pine Forests ◽  
Western United States ◽  
Surface Fire ◽  
Population Mean ◽  
Ponderosa Pine Forests ◽  
Fire Scar

Present understanding of fire ecology in forests subject to surface fires is based on fire-scar evidence. We present theory and empirical results that suggest that fire-history data have uncertainties and biases when used to estimate the population mean fire interval (FI) or other parameters of the fire regime. First, the population mean FI is difficult to estimate precisely because of unrecorded fires and can only be shown to lie in a broad range. Second, the interval between tree origin and first fire scar estimates a real fire-free interval that warrants inclusion in mean-FI calculations. Finally, inadequate sampling and targeting of multiple-scarred trees and high scar densities bias mean FIs toward shorter intervals. In ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws.) forests of the western United States, these uncertainties and biases suggest that reported mean FIs of 2-25 years significantly underestimate population mean FIs, which instead may be between 22 and 308 years. We suggest that uncertainty be explicitly stated in fire-history results by bracketing the range of possible population mean FIs. Research and improved methods may narrow the range, but there is no statistical or other method that can eliminate all uncertainty. Longer mean FIs in ponderosa pine forests suggest that (i) surface fire is still important, but less so in maintaining forest structure, and (ii) some dense patches of trees may have occurred in the pre-Euro-American landscape. Creation of low-density forest structure across all parts of ponderosa pine landscapes, particularly in valuable parks and reserves, is not supported by these results.

scholarly journals Does forest structure affect reproduction of northern goshawks in ponderosa pine forests?

2007 ◽  
Vol 45 (1) ◽  
pp. 342-350 ◽  
Author(s):  
Paul Beier ◽  
Erik C Rogan ◽  
Michael F Ingraldi ◽  
Steven S Rosenstock
Keyword(s):  
Forest Structure ◽  
Ponderosa Pine ◽  
Pine Forests ◽  
Ponderosa Pine Forests ◽  
Northern Goshawks

Fire-induced erosion and millennial-scale climate change in northern ponderosa pine forests

Nature ◽  
2004 ◽  
Vol 432 (7013) ◽  
pp. 87-90 ◽  
Author(s):  
Jennifer L. Pierce ◽  
Grant A. Meyer ◽  
A. J. Timothy Jull
Keyword(s):  
Climate Change ◽  
Ponderosa Pine ◽  
Pine Forests ◽  
Ponderosa Pine Forests ◽  
Millennial Scale

Potential for Individual Tree Monitoring in Ponderosa Pine-Dominated Forests Using Unmanned Aerial System Structure from Motion Point Clouds

2021 ◽  
Author(s):  
Matthew B. Creasy ◽  
Wade Travis Tinkham ◽  
Chad M. Hoffman ◽  
Jody C. Vogeler
Keyword(s):  
Forest Structure ◽  
Ponderosa Pine ◽  
Laser Scanning ◽  
Point Clouds ◽  
System Structure ◽  
Detection Methods ◽  
Unmanned Aerial System ◽  
Individual Tree ◽  
Detection Rates ◽  
Ponderosa Pine Forests

Characterization of forest structure is important for management-related decision making, monitoring, and adaptive management. Increasingly, observations of forest structure are needed at both finer resolutions and across greater extents to support spatially explicit management planning. Unmanned aerial system (UAS)-based photogrammetry provides an airborne method of forest structure data acquisition at a significantly lower cost and time commitment than existing methods such as airborne laser scanning (LiDAR). This study utilizes nearly 5,000 stem-mapped trees in ponderosa pine-dominated forests to evaluate several algorithms for detecting individual tree locations and characterizing crown area across tree sizes. Our results indicate that adaptive variable-window detection methods with UAS-based canopy height models have greater tree detection rates compared to fixed window analysis across a range of tree sizes. Using the UAS approach, probability of detecting individual trees decreases from 97% for dominant overstory to 67% for suppressed understory trees. Additionally, crown radii were correctly determined within 0.5 m for approximately two-thirds of sampled trees. These findings highlight the potential for UAS photogrammetry to characterize forest structure through the detection of trees and tree groups in open-canopy ponderosa pine forests. Further work should investigate how these methods transfer to more diverse species compositions and forest structures.

BREEDING BIOLOGY OF THE CHIPPING SPARROW IN PONDEROSA PINE FORESTS OF THE COLORADO FRONT RANGE

2004 ◽  
Vol 116 (3) ◽  
pp. 246-251 ◽  
Author(s):  
HEATHER M. SWANSON ◽  
BREANNA KINNEY ◽  
ALEXANDER CRUZ
Keyword(s):  
Ponderosa Pine ◽  
Breeding Biology ◽  
Pine Forests ◽  
Colorado Front Range ◽  
Front Range ◽  
Ponderosa Pine Forests
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