Spatial Patterns of Longleaf Pine (Pinus palustris Mill.): A Case Study

Spatial aggregation of forest structure strongly regulates understory light and its spatial variation in longleaf pine (Pinus palustris Mill.) forest ecosystems. Previous studies have demonstrated that light availability strongly influences longleaf pine seedling growth. In this study, the relationship between spatial structure of a longleaf pine forest and spatial pattern of understory light availability were investigated by comparing three retention harvest treatments: single-tree, small-group, large-group, and an uncut control. The harvests retained similar residual basal area but the spatial patterns of the residual trees differed. Hemispherical photographs were taken at 300 stations to calculate gap light index (GLI), an estimate of understory light availability. Stand-level mean, variation, and spatial distribution of GLI were determined for each treatment. By aggregating residual trees, stand mean GLI increased by 20%, as well as its spatial variation. Spatial autocorrelation of GLI increased as the size of the canopy gaps increased and the gaps were better defined; thus, the predictability of GLI was enhanced. The ranges of detrended semivariograms were increased from the control to the large-group harvest indicating the spatial patterns of understory GLI became coarser textured. Our results demonstrated that aggregated canopy structure of longleaf pine forest will facilitate longleaf pine seedling regeneration.

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Microelevational Differences Affect Longleaf Pine (Pinus palustris Mill.) Sensitivity to Tropical Cyclone Precipitation: A Case Study Using Lidar

Tree-Ring Research ◽

10.3959/trr2019-9 ◽

2020 ◽

Vol 76 (2) ◽

pp. 89

Author(s):

Evan E. Montpellier ◽

Paul A. Knapp ◽

Peter T. Soulé ◽

Justin T. Maxwell

Keyword(s):

Tropical Cyclone ◽

Longleaf Pine ◽

Pinus Palustris

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Simulated Longleaf Pine ( Pinus palustris Mill.) Restoration Increased Streamflow ‐‐ a Case Study in the Lower Flint River Basin

Ecohydrology ◽

10.1002/eco.2365 ◽

2021 ◽

Author(s):

Ji Qi ◽

Steven T. Brantley ◽

Stephen W. Golladay

Keyword(s):

River Basin ◽

Longleaf Pine ◽

Pinus Palustris ◽

Flint River

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Longleaf Pine Management on the DeSoto National Forest—A Case Study

Southern Journal of Applied Forestry ◽

10.1093/sjaf/13.1.34 ◽

1989 ◽

Vol 13 (1) ◽

pp. 34-40

Author(s):

Gene A. Sirmon ◽

Roger W. Dennington

Keyword(s):

Natural Regeneration ◽

Longleaf Pine ◽

Pinus Palustris ◽

National Forest ◽

Culture Care ◽

Artificial Regeneration ◽

Pine Regeneration ◽

Trained Personnel ◽

Bareroot Seedlings

Abstract Longleaf pine (Pinus palustris Mill) reforestation efforts were successful on the National Forest in south Mississippi when foresters began applying the proper technology. Artificial regeneration by planting bareroot seedlings and natural regeneration by the shelterwood system bothresulted in a plantation success rate consistently above 90%. This success can be attributed to better site preparation, better seedling culture, care, and handling, and more highly trained personnel committed to excellence in longleaf pine regeneration. South. J. Appl. For. 13(1):34-40.

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Estimating Forest Characteristics for Longleaf Pine Restoration Using Normalized Remotely Sensed Imagery in Florida USA

Forests ◽

10.3390/f11040426 ◽

2020 ◽

Vol 11 (4) ◽

pp. 426 ◽

Cited By ~ 1

Author(s):

John Hogland ◽

David L.R. Affleck ◽

Nathaniel Anderson ◽

Carl Seielstad ◽

Solomon Dobrowski ◽

...

Keyword(s):

Longleaf Pine ◽

Pinus Palustris ◽

Remotely Sensed ◽

Accurate Information ◽

Remotely Sensed Data ◽

Image Normalization ◽

Remotely Sensed Imagery ◽

Generalized Additive Modeling ◽

Additive Modeling

Effective forest management is predicated on accurate information pertaining to the characteristics and condition of forests. Unfortunately, ground-based information that accurately describes the complex spatial and contextual nature of forests across broad landscapes is cost prohibitive to collect. In this case study we address technical challenges associated with estimating forest characteristics from remotely sensed data by incorporating field plot layouts specifically designed for calibrating models from such data, applying new image normalization procedures to bring images of varying spatial resolutions to a common radiometric scale, and implementing an ensemble generalized additive modeling technique. Image normalization and ensemble models provided accurate estimates of forest types, presence/absence of longleaf pine (Pinus palustris), and tree basal areas and tree densities over a large segment of the panhandle of Florida, USA. This study overcomes several of the major barriers associated with linking remotely sensed imagery with plot data to estimate key forest characteristics over large areas.

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A Comparative Analysis of Two Major Approaches for Mapping the Wildland-Urban Interface: A Case Study in California

Land ◽

10.3390/land10070679 ◽

2021 ◽

Vol 10 (7) ◽

pp. 679

Author(s):

Avi Bar-Massada

Keyword(s):

At Risk ◽

Comparative Analysis ◽

Spatial Patterns ◽

Practical Purpose ◽

Spatial Arrangement ◽

Spatial Accuracy ◽

Wildland Urban Interface ◽

Spatial Correspondence ◽

Data Requirements

The Wildland Urban Interface (WUI) is where human settlements border or intermingle with undeveloped land, often with multiple detrimental consequences. Therefore, mapping the WUI is required in order to identify areas-at-risk. There are two main WUI mapping methods, the point-based approach and the zonal approach. Both differ in data requirements and may produce considerably different maps, yet they were never compared before. My objective was to systematically compare the point-based and the zonal-based WUI maps of California, and to test the efficacy of a new database of building locations in the context of WUI mapping. I assessed the spatial accuracy of the building database, and then compared the spatial patterns of WUI maps by estimating the effect of multiple ancillary variables on the amount of agreement between maps. I found that the building database is highly accurate and is suitable for WUI mapping. The point-based approach estimated a consistently larger WUI area across California compared to the zonal approach. The spatial correspondence between maps was low-to-moderate, and was significantly affected by building numbers and by their spatial arrangement. The discrepancy between WUI maps suggests that they are not directly comparable within and across landscapes, and that each WUI map should serve a distinct practical purpose.

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