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1. Regional Assessment of Carbon Pool Response to Intensive Silvicultural Practices in Loblolly Pine Plantations

   https://doi.org/10.3390/f13010036  

   Vogel, Jason G.; Bracho, Rosvel; Akers, Madison; Amateis, Ralph; Bacon, Allan; Burkhart, Harold E.; Gonzalez-Benecke, Carlos A.; Grunwald, Sabine; Jokela, Eric J.; Kane, Michael B.; et al (January 2022, Forests)

   Tree plantations represent an important component of the global carbon (C) cycle and are expected to increase in prevalence during the 21st century. We examined how silvicultural approaches that optimize economic returns in loblolly pine (Pinus taeda L.) plantations affected the accumulation of C in pools of vegetation, detritus, and mineral soil up to 100 cm across the loblolly pine’s natural range in the southeastern United States. Comparisons of silvicultural treatments included competing vegetation or ‘weed’ control, fertilization, thinning, and varying intensities of silvicultural treatment for 106 experimental plantations and 322 plots. The average age of the sampled plantations was 17 years, and the C stored in vegetation (pine and understory) averaged 82.1 ± 3.0 (±std. error) Mg C ha−1, and 14.3 ± 0.6 Mg C ha−1 in detrital pools (soil organic layers, coarse-woody debris, and soil detritus). Mineral soil C (0–100 cm) averaged 79.8 ± 4.6 Mg C ha−1 across sites. For management effects, thinning reduced vegetation by 35.5 ± 1.2 Mg C ha−1 for all treatment combinations. Weed control and fertilization increased vegetation between 2.3 and 5.7 Mg C ha−1 across treatment combinations, with high intensity silvicultural applications producing greater vegetation C than low intensity (increase of 21.4 ± 1.7 Mg C ha−1). Detrital C pools were negatively affected by thinning where either fertilization or weed control were also applied, and were increased with management intensity. Mineral soil C did not respond to any silvicultural treatments. From these data, we constructed regression models that summarized the C accumulation in detritus and detritus + vegetation in response to independent variables commonly monitored by plantation managers (site index (SI), trees per hectare (TPH) and plantation age (AGE)). The C stored in detritus and vegetation increased on average with AGE and both models included SI and TPH. The detritus model explained less variance (adj. R2 = 0.29) than the detritus + vegetation model (adj. R2 = 0.87). A general recommendation for managers looking to maximize C storage would be to maintain a high TPH and increase SI, with SI manipulation having a greater relative effect. From the model, we predict that a plantation managed to achieve the average upper third SI (26.8) within our observations, and planted at 1500 TPH, could accumulate ~85 Mg C ha−1 by 12 years of age in detritus and vegetation, an amount greater than the region’s average mineral soil C pool. Notably, SI can be increased using both genetic and silviculture technologies. 

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2. Arbuscular Mycorrhizal Tree Communities Have Greater Soil Fungal Diversity and Relative Abundances of Saprotrophs and Pathogens than Ectomycorrhizal Tree Communities

   https://doi.org/10.1128/AEM.01782-21  

   Eagar, Andrew C.; Mushinski, Ryan M.; Horning, Amber L.; Smemo, Kurt A.; Phillips, Richard P.; Blackwood, Christopher B. (January 2022, Applied and Environmental Microbiology)

   Druzhinina, Irina S. (Ed.)

   ABSTRACT Trees associating with different mycorrhizas often differ in their effects on litter decomposition, nutrient cycling, soil organic matter (SOM) dynamics, and plant-soil interactions. For example, due to differences between arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) tree leaf and root traits, ECM-associated soil has lower rates of C and N cycling and lower N availability than AM-associated soil. These observations suggest that many groups of nonmycorrhizal fungi should be affected by the mycorrhizal associations of dominant trees through controls on nutrient availability. To test this overarching hypothesis, we explored the influence of predominant forest mycorrhizal type and mineral N availability on soil fungal communities using next-generation amplicon sequencing. Soils from four temperate hardwood forests in southern Indiana, United States, were studied; three forests formed a natural gradient of mycorrhizal dominance (100% AM tree basal area to 100% ECM basal area), while the fourth forest contained a factorial experiment testing long-term N addition in both dominant mycorrhizal types. We found that overall fungal diversity, as well as the diversity and relative abundance of plant pathogenic and saprotrophic fungi, increased with greater AM tree dominance. Additionally, tree community mycorrhizal associations explained more variation in fungal community composition than abiotic variables, including soil depth, SOM content, nitrification rate, and mineral N availability. Our findings suggest that tree mycorrhizal associations may be good predictors of the diversity, composition, and functional potential of soil fungal communities in temperate hardwood forests. These observations help explain differing biogeochemistry and community dynamics found in forest stands dominated by differing mycorrhizal types. IMPORTANCE Our work explores how differing mycorrhizal associations of temperate hardwood trees (i.e., arbuscular [AM] versus ectomycorrhizal [ECM] associations) affect soil fungal communities by altering the diversity and relative abundance of saprotrophic and plant-pathogenic fungi along natural gradients of mycorrhizal dominance. Because temperate hardwood forests are predicted to become more AM dominant with climate change, studies examining soil communities along mycorrhizal gradients are necessary to understand how these global changes may alter future soil fungal communities and their functional potential. Ours, along with other recent studies, identify possible global trends in the frequency of specific fungal functional groups responsible for nutrient cycling and plant-soil interactions as they relate to mycorrhizal associations. 

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3. Root‐niche separation between savanna trees and grasses is greater on sandier soils

   https://doi.org/10.1111/1365-2745.13475  

   Case, Madelon F.; Nippert, Jesse B.; Holdo, Ricardo M.; Staver, A. Carla; Oliveras, ed., Imma (August 2020, Journal of Ecology)

   Abstract In savannas, partitioning of below‐ground resources by depth could facilitate tree–grass coexistence and shape vegetation responses to changing rainfall patterns. However, most studies assessing tree versus grass root‐niche partitioning have focused on one or two sites, limiting generalization about how rainfall and soil conditions influence the degree of rooting overlap across environmental gradients.We used two complementary stable isotope techniques to quantify variation (a) in water uptake depths and (b) in fine‐root biomass distributions among dominant trees and grasses at eight semi‐arid savanna sites in Kruger National Park, South Africa. Sites were located on contrasting soil textures (clayey basaltic soils vs. sandy granitic soils) and paired along a gradient of mean annual rainfall.Soil texture predicted variation in mean water uptake depths and fine‐root allocation. While grasses maintained roots close to the surface and consistently used shallow water, trees on sandy soils distributed roots more evenly across soil depths and used deeper soil water, resulting in greater divergence between tree and grass rooting on sandy soils. Mean annual rainfall predicted some variation among sites in tree water uptake depth, but had a weaker influence on fine‐root allocation.Synthesis. Savanna trees overlapped more with shallow‐rooted grasses on clayey soils and were more distinct in their use of deeper soil layers on sandy soils, consistent with expected differences in infiltration and percolation. These differences, which could allow trees to escape grass competition more effectively on sandy soils, may explain observed differences in tree densities and rates of woody encroachment with soil texture. Differences in the degree of root‐niche separation could also drive heterogeneous responses of savanna vegetation to predicted shifts in the frequency and intensity of rainfall. 

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4. An Accuracy Assessment of Field and Airborne Laser Scanning–Derived Individual Tree Inventories using Felled Tree Measurements and Log Scaling Data in a Mixed Conifer Forest

   https://doi.org/10.1093/forsci/fxae015  

   Sparks, Aaron M; Corrao, Mark V; Keefe, Robert F; Armstrong, Ryan; Smith, Alistair_M S (March 2024, Forest Science)

   Roberts, Scott (Ed.)

   Abstract On-the-ground sample-based forest inventory methods have been the standard practice for more than a century, however, remote sensing technologies such as airborne laser scanning (ALS) are providing wall-to-wall inventories based on individual tree measurements. In this study, we assess the accuracy of individual tree height, diameter, and volume derived from field-cruising measurements and three ALS data-derived methods in a 1.1 ha stand using direct measurements acquired on felled trees and log-scale volume measurements. Results show that although height derived from indirect conventional field measurements and ALS were statistically equivalent to felled tree height measurements, ALS measured heights had lower root mean square error (RMSE) and bias. Individual tree diameters modeled using a height-to-diameter-at-breast-height model derived from local forest inventory data and the software ForestView had moderate RMSE (8.3–8.5 cm) and bias (-3.0 – -0.3 cm). The ALS-based methods underdetected trees but accounted for 78%–91% of the field reference harvested merchantable volume and 71%–99% of the merchantable volume scaled at the mill. The results also illustrate challenges of using mill-scaled volume estimates as validation data and highlight the need for more research in this area. Overall, the results provide key insights to forest managers on accuracies associated with conventional field-derived and ALS-derived individual tree inventories. Study Implications: Forest inventory data provide critical information for operational decisions and forest product supply chain planning. Traditionally, forest inventories have used field sampling of stand conditions, which is time-intensive and cost-prohibitive to conduct at large spatial scales. Remote sensing technologies such as airborne laser scanning (ALS) provide wall-to-wall inventories based on individual tree measurements. This study advances our understanding of the accuracy of conventional field-derived and ALS-derived individual tree inventories by evaluating these inventories with felled tree and log scaling data. The results provide key insights to forest managers on errors associated with conventional field and ALS-derived individual tree measurements. 

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5. Forest Potential Productivity Mapping by Linking Remote-Sensing-Derived Metrics to Site Variables

   https://doi.org/10.3390/rs12122056  

   Rahimzadeh-Bajgiran, Parinaz; Hennigar, Chris; Weiskittel, Aaron; Lamb, Sean (June 2020, Remote Sensing)

   null (Ed.)

   A fine-resolution region-wide map of forest site productivity is an essential need for effective large-scale forestry planning and management. In this study, we incorporated Sentinel-2 satellite data into an increment-based measure of forest productivity (biomass growth index (BGI)) derived from climate, lithology, soils, and topographic metrics to map improved BGI (iBGI) in parts of North American Acadian regions. Initially, several Sentinel-2 variables including nine single spectral bands and 12 spectral vegetation indices (SVIs) were used in combination with forest management variables to predict tree volume/ha and height using Random Forest. The results showed a 10–12 % increase in out of bag (OOB) r2 when Sentinel-2 variables were included in the prediction of both volume and height together with BGI. Later, selected Sentinel-2 variables were used for biomass growth prediction in Maine, USA and New Brunswick, Canada using data from 7738 provincial permanent sample plots. The Sentinel-2 red-edge position (S2REP) index was identified as the most important variable over others to have known influence on site productivity. While a slight improvement in the iBGI accuracy occurred compared to the base BGI model (~2%), substantial changes to coefficients of other variables were evident and some site variables became less important when S2REP was included. 

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