Assessing productivity and cost of timber harvesting during longleaf pine ecosystem restoration

Murray, Jacob; Hiesl, Patrick; Hagan, Donald L.; Baldwin, Robert F.

doi:10.1080/14942119.2022.2157184

Cited by 2 publications

(3 citation statements)

References 25 publications

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“…Based on these findings, we recommend that organized landscape-scale restoration and conservation efforts begin at large-parcel hotspots in Kershaw and Lee counties, where there is sufficient high-quality habitat. In this area, Murray et al (2022Murray et al ( , 2023 found that Longleaf Pine restoration was both physically and economically feasible in submesic, subxeric, and xeric sites that were intermediately classified by this study. Findings from this study could help expedite large-scale forest-restoration objectives in the region.…”

Section: Discussionmentioning

confidence: 64%

“…; Shaw and Long 2007; USDA Forest Service 2009; USFWS 2020). Additionally, Murray et al (2023) found that a Longleaf Pine restoration project in this region would be profitable at approximately the same parcel size for Loblolly Pine-to-Longleaf Pine conversion. We conducted a hotspot analysis to calculate the Getis–Ord GI* statistic for each parcel to test for statistically significant clustering of high values, using parcel size as the weighted field.…”

Section: Methodsmentioning

confidence: 97%

“…We identified parcels within our study area that could be restored based on site-specific ecology, operational thresholds, and historical references. Practical restoration sites must be large enough to financially support a restoration timber harvest, or ecologically valuable enough to support an endangered-species reintroduction program (Murray et al 2023). We investigated parcels larger than 30 ha as the lower limit of the reintroduction range for a single Leuconotopicus borealis 2023) found that a Longleaf Pine restoration project in this region would be profitable at approximately the same parcel size for Loblolly Pine-to-Longleaf Pine conversion.…”

Section: Parcel Analysismentioning

confidence: 99%

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Spatial Multi-Criteria Decision Modeling for Pinus palustris Mill. (Longleaf Pine) Restoration in the South Carolina Sandhills Wiregrass Gap

Murray,

Baldwin,

Hagan

et al. 2023

Southeastern Naturalist

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Currently found in less than 3% of its pre-European range, Pinus palustris (Longleaf Pine) ecosystems are increasingly important for forest-restoration initiatives in the southeastern US. Compared to other areas of the Atlantic Coastal Plain, sites in the Carolina Sandhills often have higher restoration potentials for Longleaf Pine habitat. Distinct sandhill ecology and prevailing biological legacies make Longleaf Pines competitive in this region. Spatial investigations into potential restoration sites are essential preliminary steps to optimize resource allocation for large-scale restoration objectives. This study aimed to illustrate the applicability of various modeling techniques while providing a framework for restoration-parcel identification and selection. We developed multiple weighted spatial multi-criteria decision models to identify Longleaf Pine-restoration sites in the South Carolina Sandhills Wiregrass Gap, an ecologically distinct and understudied region of Longleaf Pine occupancy. Using advanced spatial modeling and analysis tools, we developed a classification system that combined and weighted vegetation cover, land use, and soil property raster data. The models are designed to identify potential sites for restoration, which will ultimately improve resource allocation during the project planning process. We found significant (P < 0.001) spatial clustering of large parcels and 94.7-98.3% pixel similarity between predictive models. An ensemble model, developed by averaging the pixel values of each predictive model, found that Longleaf Pine-restoration potential was highest in large rural parcels primarily east of Kershaw County. Large-parcel clustering and ecological input factors applied to a decision-making model in this study provide a precedent for systematically allocating resources to improve and increase forest restoration and management in South Carolina.