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36 results for “ponderosa pine”
Fig. 1 in Emergence of Buprestidae, Cerambycidae, and Scolytinae (Coleoptera) from Mountain Pine Beetle-Killed and Fire-Killed Ponderosa Pines in the Black Hills, South Dakota, USA
Fig. 1. Box plot showing the number of wood borers collected from bolts of one-year-old mountain pine beetle (MPB)-killed trees (n = 4), two-year- old MPB-killed trees (n = 6), one-year-old fire-killed trees (n = 5), and two-year-old fire-killed trees (n = 5). Letters above the bars represent means which if followed by the same letter are not significantly different (p ≤ 0.05, Tukey- Kramer multiple comparisons test). The solid and dashed lines within the box represent the median and the mean, respectively. Box ends represent the first and third quartiles. The lower and upper horizontal lines above and below the box are at the last points less than 1.5 times the interquartile range from the first and third quartiles. Points represent the actual data, and the circle for the 1-yr fire indicates that the point next to it is an outlier.
Divergent growth-differentiation balance strategies and resource competition shape mortality patterns in ponderosa pine
<p><span>Dynamic resource availability leads to trade-offs among functions in plants. The growth-differentiation balance hypothesis (GDBH) predicts greater allocation of carbon to defense than growth when resources are scarce; with optimum defense production occurring at a point between the minimum and maximum growth rates. While the GDBH has been widely tested, consideration of phenotypic variation in rates for which defense is traded for growth and what this variation means for plant resistance remains rare. For defense, pines produce and store oleoresin in "resin ducts." Retrospective comparisons of resin ducts in pines have revealed that trees with greater numbers, sizes, or areas of xylem resin ducts are more likely to avoid or survive insect attacks. We used tree ring chronologies to quantify phenotypic variation in growth and resin duct defenses in pairs of living and bark beetle-killed <em>Pinus ponderosa</em> trees in southern New Mexico, USA, and to test the utility of the GDBH for explaining tree mortality. We also assessed the sensitivity of annual growth to climate and competitor density in years preceding mortality in each pair. Survivors had greater growth rates and total cross-sectional areas of resin ducts than trees killed by bark beetles. We did not observe a difference in climate-growth relationships among the groups, however, trees killed by bark beetles suffered negative effects of competition while survivors did not. Growth-defense trade-offs conformed to the GDBH's prediction of a quadratic relationship, however, the two groups significantly differed in the rate at which defense was traded for increasing levels of annual growth.<em> </em> Our results demonstrate that phenotypic variation in the trade-off between growth and defense could be used to characterize trees that were killed by or survived recent natural enemy epidemics. We hypothesize that the GDBH could be integrated with the characterization of phenotypic variation in growth-differentiation strategies—along with parsing of gene versus environment influences on phenotypes—at both local and landscape scales to increase our understanding of patterns of natural enemy impacts in plant populations.</span></p>
Phylogenomics in the hard pines (Pinus subsection Ponderosae; Pinaceae) confirms paraphyly in Pinus ponderosa, and places Pinus jeffreyi with the California big cone pines
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Data from: Fire legacies in eastern ponderosa pine forests
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Data from: Spatial genetic structure of the mountain pine beetle (Dendroctonus ponderosae) outbreak in western Canada: historical patterns and contemporary dispersal
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Data from: Rapid increases in forest understory diversity and productivity following a mountain pine beetle (Dendroctonus ponderosae) outbreak in pine forests
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Data from: Impacts of growing-season climate on tree growth and post-fire regeneration in ponderosa pine and Douglas-fir forests
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Data from: Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change.
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Data from: Repurposing population genetics data to discern genomic architecture: a case study of linkage cohort detection in mountain pine beetle (Dendroctonus ponderosae)
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Data from: Development of genetic diversity, differentiation and structure over 500 years in four ponderosa pine populations
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Divergent growth-differentiation balance strategies and resource competition shape mortality patterns in ponderosa pine
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Data from: Multi-decadal vegetation transformations of a New Mexico ponderosa pine landscape after severe fires and aerial seeding
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Data from: Adaptive and neutral markers both show continent-wide population structure of mountain pine beetle (Dendroctonus ponderosae)
Assessments of population genetic structure and demographic history have traditionally been based on neutral markers while explicitly excluding adaptive markers. In this study, we compared the utility of putatively adaptive and neutral single-nucleotide polymorphisms (SNPs) for inferring mountain pine beetle population structure across its geographic range. Both adaptive and neutral SNPs, and their combination, allowed range-wide structure to be distinguished and delimited a population that has recently undergone range expansion across northern British Columbia and Alberta. Using an equal number of both adaptive and neutral SNPs revealed that adaptive SNPs resulted in a stronger correlation between sampled populations and inferred clustering. Our results suggest that adaptive SNPs should not be excluded prior to analysis from neutral SNPs as a combination of both marker sets resulted in better resolution of genetic differentiation between populations than either marker set alone. These results demonstrate the utility of adaptive loci for resolving population genetic structure in a nonmodel organism.
Data from: Adaptive and neutral markers both show continent-wide population structure of mountain pine beetle (Dendroctonus ponderosae)
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Biome-BGC: Modeling Carbon Dynamics in Ponderosa Pine Stands (Law et al. 2003)
This archived model product contains the directions, executables, and procedures for running Biome-BGC, Version 4.1.2, to recreate the results of Law BE, Sun OJ, Campbell J, Van Tuyl S, Thornton PE, 2003. Changes in carbon storage and fluxes in a chronosequence of ponderosa pine. Global Change Biology, 9(4), 510-514.Law et al. 2003 excerpt: Abstract Forest development following stand-replacing disturbance influences a variety of ecosystem processes including carbon exchange with the atmosphere. On a series of ponderosa pine (Pinius ponderosa var. Laws.) stands ranging from 9 to > 300 years in central Oregon, USA, we used biological measurements to estimate carbon storage in vegetation and soil pools, net primary productivity (NPP) and net ecosystem productivity (NEP) to examine variation with stand age. Measurements were made in 2000 on a chronosequence of 12 ponderosa pine stands. Total ecosystem carbon storage and the fraction of ecosystem carbon in aboveground wood mass increased rapidly until 150-200 years, and did not decline in older stands. Forest inventory data on 950 ponderosa pine plots in Oregon show that the greatest proportion of plots exist in stands ~ 100 years old, indicating that a majority of stands are approaching maximum carbon storage and net carbon uptake. Our data suggests that NEP averages ~ 70 g C m-2 year-1 for ponderosa pine forests in Oregon. About 85% of the total carbon storage in biomass on the survey plots exists in stands greater than 100 years, which has implications for managing forests for carbon sequestration. To investigate variation in carbon storage and fluxes with disturbance, simulation with process models requires a dynamic parameterization for biomass allocation that depends on stand age, and should include a representation of competition between multiple plant functional types for space, water, and nutrients.
Functional genomics of mountain pine beetle (Dendroctonus ponderosae) midguts and fatbodies
GEO Series GSE17858. Dendroctonus ponderosae. 44 samples. Type: Expression profiling by array.
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