Growth of Two Loblolly Pine Clones Planted in Agroforestry and Plantation Settings: Nine-year Results

Growth of Two Loblolly Pine Clones Planted in Agroforestry and Plantation Settings: Nine-year Results | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Growth of Two Loblolly Pine Clones Planted in Agroforestry and Plantation Settings: Nine-year Results Kozma Naka, Shaik Hossain, Luben Dimov This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3860580/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Aug, 2024 Read the published version in Agroforestry Systems → Version 1 posted 4 You are reading this latest preprint version Abstract Selecting suitable tree species, cultivars, or clones in agroforestry is essential for maximizing volume growth and reducing mortality. While most studies have investigated the performance of understory crops, more information is needed about the performance of trees in agroforestry systems. In the last decades, the forest industry in the Southeast has produced high-yielding loblolly pine varieties that can be propagated by cloning. We evaluated the performance of two forest industry-rated loblolly pine clones ( Pinus taeda L.) that we planted in an agroforestry and a plantation setting at a northern Alabama site. Specifically, we assessed and compared the survival and growth of two genetically improved pine clones: clone 1 (Q3802-43) and clone 2 (L3519-41). Clone 1 had a greater overall survival rate than clone 2 (86% vs. 83%). However, clone 2 demonstrated a superior performance growth compared to clone 1. Tree basal area, live crown ratio, height, and total tree volume inside-bark of clone 2 averaged 0.027 m 2 , 70%, 10.7 m, and 0.11 m 3 , respectively, and all were significantly higher than those of clone 1 (0.024 m 2 , 63%, 9.8 m, and 0.09 m 3 ). Therefore, clone 1 is preferred over clone 2 for our region and in similar site conditions if survival is considered a selection criterion and clone 2 is preferred from the wood production viewpoint. However, it will be more advantageous to use clone 2 overall since its higher average tree volume (0.11 m 3 vs. 0.9 m 3 of clone 1) can easily offset the lower survival rate. agroforestry loblolly pine clones survival rate tree volume Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Agroforestry is a land-use practice that combines trees and agricultural crops on the same land simultaneously (USDA, 1997). Agroforestry systems include silvopasture, alley cropping, forest farming, riparian forest buffers, and windbreaks. Environmental benefits of agroforestry practices include increasing forage yields under moderate shade (Garett et al. 2004, Pang et al. 2019 ), increasing soil carbon ) and nutrient cycling (Franzluebbers and Doraiswamy 2007 ; Jose 2009; Nyakatawa et al. 2010; Kirschke et al. 2013 ), reducing soil erosion and nonpoint source pollution and improving water quality (Anderson et al. 2009 ; Udawatta et al. 2010 ), enhancing biodiversity (Harvey et al. 2006 ; Moreno-Calles et al. 2010 ); and increasing landscape aesthetics (Garett et al. 2004). Myriad economic benefits are also available from agroforestry practices through diverse products, such as timber and agricultural production (Franzel, 2004). Depending on the tree species used, agroforestry systems can also provide other revenue-generating activities such as recreation, hunting, and pine straw production (Grado and Husak, 2004 ). The most popular form of agroforestry in North America is silvopasture, in which grazing livestock and foraging crops are incorporated into plantations to sustain economic benefits (USDA, 1997). In the southeastern USA, monoculture plantations with southern pines are the more common forestry practice (Nebeker et al., 2015 ). This production method has been commercially viable due to robust domestic demand for sawtimber and pulpwood (Nyakatawa et al., 2012 ). However, the pulpwood market has been facing ups and downs, including increasing competition from overseas markets, especially South America (Wear and Greis 2002 ), and uncertainty of future domestic wood energy demand (Nepal et al., 2019 ). The unpredictability of a long-term production process has made it difficult for some limited-resource forest landowners to generate a profit from pine plantations. Similarly, farmers on small and medium-sized farms face viability problems when depending on conventional agriculture due to profit uncertainties, particularly in the context of current climate changes (McNulty et al., 2013 ). Hence, interest in small-scale and diversified agroforestry systems as a profitable and sustainable land use practice has increased (Nyakatawa et al., 2012 ). Yet, few landowners have chosen agroforestry as a viable land use option mainly because there is a dearth of science-based information on this production method in the South. Therefore, consultant foresters who traditionally recommend industrial forest management may hesitate to promote atypical forestry practices. Consequently, landowners unfamiliar with agroforestry practices do not adopt them for fear of financial loss. To reverse this trend, landowners need to understand the science of agroforestry to achieve desired financial goals (Barlow et al., 2016 ). Experimental demonstrations can give landowners appropriate knowledge, making them more inclined to accept this forestry farming system (Reiche, 1992 ). Trees planted in agroforestry settings with wider spacing can be used for growing crops or grazing, providing not too much shade come from them as opposed to plantations, in which trees of similar age and size classes compete for the same resources, exerting adverse impacts on survival and growth, particularly when growing in close spacings (Oliver and Larson, 1990 ). Traditionally, loblolly pine has been a suitable tree species for agroforestry systems in the South (Nyakatawa et al., 2012 ). While the trees exert some competition, they provide a number of benefits that generally outweigh the cost of the competition for light, such as reducing desiccation of crops planted under the trees and using soil resources not available to shallow-rooted crops, shade for livestock, pine straw production, and wildlife habitat. Choosing suitable species of trees and crops with proper spacing is important for minimizing the competition between trees and crops (Adams and Clason, 2002 ). Further, appropriate site and environmental conditions are necessary for maximizing the benefits of agroforestry. Even cultivars or clones of the same species may have different shade tolerances and show varying sensitivity to environmental and climatic conditions (Sharma et al., 2013 ; McKeand et al., 2003 ). While most studies have investigated the performance of species and cultivars of understory crops (Gao et al., 2013 ; Barlow et al., 2016 ; Grass et al., 2020 ), more information about wood production in agroforestry systems is needed. The main objective of this study was to evaluate the performance of two forest industry-rated clones of loblolly pine ( Pinus taeda L.) planted in an agroforestry and a plantation setting. In particular, we assessed and compared the survival and growth of two pine clones. A secondary objective was to use the study site for demonstrations and workshops for farmers and non-industrial private forest landowners. Materials and Methods The study was conducted at Alabama A&M University’s Winfred Thomas Agricultural Research Station (34.901589, -86.579392), in Hazel Green, Alabama, USA (Fig. 1 ), at 235 m of elevation. According to the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) soil survey (Soilweb 2022), the soils are classified as Decatur silty clay loam, 2 to 6 percent slope, eroded, and with a typical profile of Ap for the first 18 cm (silty clay loam), Bt1 from 18 to 61 cm (silty clay loam), and Bt2 from 80 to 203 cm (clay). The topsoil (0–25 cm) is dark brown to dark reddish-brown friable and heavy mellow silt loam. The supply of plant nutrients is high. This soil is moderately permeable to roots and moisture with a relatively high capacity for holding the water available to plants. Soil preparation included plowing and disking in the fall. Prior land use was growing agricultural crops such as cotton, corn, and hay, and to a lesser extent, other crops such as potatoes, grain sorghum, soybeans, and field peas. The soil has a thin organic layer, is slightly acidic, and moderately to well drained with high permeability (Gebremedhin 2022). The mean annual precipitation in the area is 1500 mm, while the average minimum, mean, and maximum annual temperatures are 9, 16, and 21 degrees Celsius, respectively (PRISM Climate Group, 2023). The site has a temperate climate. The monthly average temperature from May to November varies from 5.0℃ to 32.2℃. The warmest month is August, and the coldest month is January. The frost-free period is from 180 to 240 days. CellFor Inc. (later acquired by ArborGen) provided the planting stock in January 2007. It consisted of two clones, Q3802-43 (clone 1) and L3519-41 (clone 2) of loblolly pine ( Pinus taeda L. ) 1-0 bare root seedlings (i.e., grown in a nursery for one year before being outplanted in the field for this experiment). These two clones were developed under CellFor’s Varietal Forestry Program using genetic methods to maximize gains in yield and survival. We planted the seedlings in two spacing arrangements: plantation planting pattern (3.0 m x 3.7 m, with 3.0 m between rows and 3.7 m between seedlings within a row) and agroforestry planting pattern (two rows at 3.0 m x 3.7 m, alternating with 12.2 m wide alleys between the double rows). Both spacing arrangements have 24 seedlings in a row. The rows were oriented from west to east for maximum insolation of the alley. To maximize growing space, seedlings of each row were offset (staggered), so they were between rather than opposite to the seedlings of the neighboring row. The alley between the double rows of the agroforestry pattern was less shaded than in a plantation pattern and would be used for growing hay, row crops, or as pasture (Fig. 1 ). Seedlings of the two clones were planted in a randomized block design with three replications of the agroforestry spacing and two replications of the plantation spacing for each clone within three blocks (Fig. 2 ). The agroforestry planting pattern was replicated three times (once in each of the three blocks) for each of the two clones. The forest plantation planting pattern was replicated twice (in blocks 1 and 2) for each clone. This design resulted in 10 rows per replication in agroforestry and 14 rows per replication in plantation, for a total of 88 rows. A total of 2112 seedlings were planted in the three blocks. The seedlings were planted manually using dibble bars. The herbaceous vegetation between the seedlings was sprayed with the herbicide Oustar® in April of the year of planting and March of the following year. The rate per hectare was 1.0 liter of the herbicide mixed into 100 to 400 liters of water. In addition, the vegetation was mowed one to three times during the first through the third growing seasons. In September 2015, nine growing seasons after planting in the field, we used diameter tapes to measure the diameter at breast height (dbh, 1.37 m above the ground) for all the live trees. In January 2016, we selected a subset of the trees (about 12% of all live trees) by stratified random sampling and measured their total tree height (HT) and height from the ground to the base of the live crown (HBLC). All the heights were measured using clinometers. We also tallied all dead trees to assess the survival rate through the ninth growing season. The diameters and heights were measured to the nearest 0.1 inch (0.254 cm) and the nearest foot (30.5 cm), respectively. Before conducting the analysis, we converted the English units to metric. Analytical Approach Our analysis evaluated pine clone responses both at stand and tree levels. Stand-level patterns were tested using the survival rate of clones, estimated as the percentage of trees initially planted in 2007 tallied as live during the sampling in 2015. Three dependent variables were used for testing tree-level responses: tree basal area (BAt), live crown ratio (LCR), and total tree volume inside-bark (Vt). Tree-level statistics for BAt were calculated based on the measurements of all the trees, while statistics for LCR and Vt were based on a subset of the trees. BAt was calculated using the following standard equation: BAt (m 2 ) = 0.00007854 x dbh 2 where dbh is the diameter at breast height in centimeters LCR was calculated by subtracting HBLC from the total tree height and dividing the result by the total tree height. Therefore, LCR = (HT-HBLC)/HT. LRC represents a ratio value; hence, it does not have units. We adopted the following equation developed by Tasissa et al. ( 1997 ) to determine Vt of our pine trees: Vt = -0.01039 + 0.00196 x dbh 2 x HT [1], where Vt is the inside-bark total tree volume in cubic meters, dbh is the diameter at breast height in centimeters, and HT is the total height of the tree in meters. Equation [1] was developed using data from the sampling of loblolly pine plantations across multiple locations within its geographic range. It is widely used to calculate the inside-bark volume of unthinned loblolly pine tree stems in cutover, site-prepared plantations similar to trees on our site. The analysis of variance (ANOVA) was used to assess the effect of clones and planting patterns on BAt, LCR, HT, and Vt using RStudio version 1.1.456. Because the experiment was based on a randomized block design, we used a two-way ANOVA to evaluate the effect of predictors on the three response variables. Residuals were checked for normality and equal variance. Since residual variance met the model assumptions, there was no need for data transformation. When ANOVA detected significant effects, pairwise comparisons were performed to determine the difference between means using Tukey’s HSD test. Because both the clone and the survival rate are binary variables, we conducted a “proportion test” to determine whether the survival percentage varied between the planted clones. Also, two-sample t-tests were used to compare BAt, LCR, HT, and Vt between the clones and the planting patterns. We used Welch’s t-tests in particular because the variances of response variables in both groups (clone and planting pattern) were unequal. Statistical significance was assessed at the 0.05 level ( P < 0.05). Results At the end of nine growing seasons, 866 of 1008 clone 1 (Q3802-43) seedlings survived, while 915 of 1104 clone 2 (L3519-41) seedlings survived. Proportion tests revealed that mean seedling survival was significantly different ( P < 0.05) between the two pine clones (Table 1 and Fig. 3 ), with clone 1 showing a slightly greater survival rate (86%) compared to clone 2 (83%). When it came to planting patterns, the agroforestry pattern demonstrated a significantly higher ( P < 0.05) survival rate than the plantation pattern, averaging 90% and 72% survival, respectively (Table 1 and Fig. 3 ). Both clone and planting pattern were significant factors ( P < 0.05) in the ANOVA model for BAt, LCR, HT, and Vt (Fig. 4 – 7 ; Table 2 ). Additionally, there was a significant ( P < 0.05) interaction between clones and planting patterns for BAt and Vt (Table 2 ), indicating that one clone responded better than the other within a particular planting pattern. However, interactions between clones and planting patterns were insignificant ( P > 0.05) for LCR and HT (Table 2 ). Pairwise comparisons revealed that in both agroforestry and plantation settings, clone 2 gained, on average, 0.002 and 0.005 m 2 , respectively, more in BAt than clone 1 (Table 3 ). Similarly, the LCR of clone 2 showed greater values (5.1% higher in agroforestry and 8.2% higher in plantation) than the LCR of clone 1. Also, the HT of clone 2 was higher than the HT of clone 1 in both planting patterns (a difference of 0.95 m in agroforestry and 1.21 m in plantation). When Vt was considered, clone 2 showed a higher response of 0.03 m 3 in the plantation setting than clone 1. However, there was no difference in Vt between the two clones in the agroforestry setting ( P > 0.05). According to the t-tests, there was a significant difference ( P < 0.05) between the two pine clones for the four response variables during the growth period irrespective of planting patterns, with clone 2 generally demonstrating a greater growth than clone 1 (Table 4 ). BAt, LCR, HT, and Vt of clone 2 averaged 0.027 m 2 , 70%, 10.7 m, and 0.11 m 3 , respectively, and all were significantly higher than those of clone 1. As for planting patterns, except for BAt ( P > 0.05), all other response variables (LCR, HT, and Vt) differed significantly ( P < 0.05) between agroforestry and plantation regardless of pine clones (Table 4 ). On average, LCR was higher in the agroforestry setting than in the plantation setting (0.70 vs. 0.64). In contrast, HT and Vt showed a higher value in the plantation setting than in the agroforestry setting (an average of 10.8 m vs. 9.8 m and 0.11 m 3 vs. 0.09 m 3 , respectively). Discussion By deploying different pine clones, we were able to assess some of the variability associated with their genetics. Survival of both pine clones at the end of the ninth growing season was relatively high (> 83%), reaffirming that our region has favorable site conditions for planting loblolly pine (Adams and Clason, 2002 ; Little, 1971 ). A silvopasture study conducted in southern Alabama found a similar survival rate (81%) of planted loblolly pine at age eight (Barlow et al., 2016 ). Moreover, pine clones in this study had a comparable survival rate with those originating from seeds mentioned in prior research (Stelzer et al., 1998 ). However, clone 1 (Q3802-43) had a 3% greater survival rate than clone 2 (L3519-41). Data collected at the end of the second growing season showed similar survival rates between the two planted clones (88% in clone 1 vs. 84% in clone 2), suggesting that survival differences between the two clones have sustained through time. In contrast, clone 2 performed better than clone 1 for all four growth performance factors (BAt, LCR, HT, and Vt). Second-year estimates, at the seedling stage of our pines, showed no significant differences between the clones in BAt (0.002 m 2 for both clones, P > 0.05) and height (2.0 m and 2.1 m in clone 1 and clone 2, respectively). These results suggest that initial growth patterns between the pine clones diverged at the sapling stage (year nine). The differential performances in the clone’s survival and growth could be attributed to variations in both endogenous (e.g., genetics) and exogenous (e.g., environment and climate) factors. Loblolly pine has been the subject of tree improvement programs for almost 50 years in the South, producing planting stock with appreciable genetic gains in growth and survivorship (McKeand et al., 2006 ). The two pine clones we used were developed by selecting improved genotypes; therefore, genetics significantly affected their performance. However, several exogenous factors can also affect southern pines’ growth and survival rates (Hossain et al., 2021 ; Sharma et al., 2013 ). These include natural disturbances such as diseases, insects, fires, storms (ice and wind), and droughts. Much of the study region experienced extreme drought in 2007 (PRISM Climate Group, 2023), which could have differentially affected the survival and growth of the young pine trees. Based mainly on genetics, clone 1 is preferred over clone 2 for our region if survivorship is considered a selection criterion and clone 2 is recommended from the wood production viewpoint. However, it will be more advantageous to use clone 2 overall since its higher average tree volume (0.11 m 3 vs. 0.9 m 3 of clone 1) can easily offset the lower survival rate. Agroforestry pines had a better survival rate than those of the plantation. The difference in survival performance between planting patterns likely reflects competition-induced mortality associated with spacing (Sharma et al., 2013 ). Loblolly pine is a shade-intolerant species and, therefore, is more sensitive to competition, particularly when grown in planted monocultures with narrow spacing (Fowells, 1965 ). Since there was less available light due to the narrow spacing, there was more competition, and hence more pine mortality, in the plantation pattern than in the agroforestry pattern. However, given that our plantings were just eight years old, it is unlikely that they have yet reached canopy closure, which initiates the onset of competition (Adams et al., 2007 ). We speculate that the full extent of the competition effect cannot be evaluated until these stands become mature (> 15 years of age), and self-thinning would start as a result of more intense intraspecific competition (Sharma et al., 2013 ; Hossain et al., 2021 ). Based on a longer-term study conducted in central Mississippi, Adams et al. ( 2007 ) reported that the survival of loblolly pine at 17 years was significantly affected by spacing, with widely-spaced plantings showing higher survival rates than those with closer spacings, which corroborates with our assumption. Agroforestry pines also had a greater live crown ratio than the plantation because of the wider spacing in agroforestry and the ecology of the species. Loblolly pine can self-prune when growing in plantations with sufficiently dense competition, causing shading on branches in the lower part of the crown (Smith et al., 1997 ). With fewer trees crowding around, there was less shading on the lower branches in the agroforestry pattern, leading to less self-pruning and more live crown area. Furthermore, the agroforestry pattern received more light on the sides of the crowns than the plantation pattern, allowing trees to allocate more resources to branch growth. In a study with loblolly pine silvopasture based in Louisiana, Adams and Clason ( 2002 ) reported that the height to the first live limb was the least for trees planted at wider spacing, resulting in greater live crown area than those at close spacing. This result is consistent with our study. We expected a greater BAt in agroforestry simply because trees had more available growing space, but there was no difference in BAt between the two planting patterns. This is surprising because loblolly pine is expected to grow favorably in stem diameter at wide spacings (Adams and Clason, 2002 ). Conversely, HT was greater in plantation than agroforestry, which was expected since height growth in even-aged stands like these is primarily triggered by intraspecific competition (Oliver and Larson, 1990 ). Therefore, trees allocate more resources to height growth than branch growth in plantations to avoid fierce competition for light associated with close spacings. As a result, Vt was higher in the plantation than in the agroforestry setting, despite similar BAt in both planting patterns because of higher HT in the plantation setting. However, the trees in our study were only eight years old. As mortality continues to rise with stand age, spacings are expected to become less variable over time, resulting in more equality in height between the two planting patterns. More time is needed to determine if factors such as competition-induced mortality may change the outcomes of these growth performance measures. The Loblolly pine is a commercially important tree species in the southern US. Considerable work has been completed to produce productive clones for our region (Stelzer et al. 1998 ). The species is also well suited for agroforestry due to its ease of establishment and diversified benefits. However, very few studies have investigated the performance of loblolly pine cultivars in agroforestry systems (Barlow et al. 2016 ; Grass et al. 2020 ). To our knowledge, this is the first study in our region to assess and compare the survival and growth of two industry-rated loblolly pine clones planted both in agroforestry and plantation settings. We also recently introduced goats to graze the site so their impact on stand productivity can be examined. Introducing goats into the site will not only ensure biological control of unwanted vegetation but also provide an opportunity to increase farm profits (Luginbuhl et al., 2005 ). Additionally, trees in the agroforestry settings were pruned and are being monitored to evaluate the pruning impact. We expect this study site to be used as a demonstration site for farmers and non-industrial private forest landowners unfamiliar with the practice of silvopasture so they can adopt it to maximize farm profits by diversifying their farm operations. As additional information on relative improvements in stand productivity (timber and non-timber) becomes available over time, we hope more farmers and non-industrial private forest landowners will be interested in silvopasture systems. More demonstrations are necessary to give landowners a broader perspective on this emerging forestry farming system. Declarations Financial support was provided by the USDA National Institute of Food and Agriculture, McIntire-Stennis project accession number 1008953, and Alabama A&M University. CellFor Inc. provided the seedlings and the herbicide. The dataset generated and analyzed during the current study is available from the corresponding author upon request. Dr. Dimov was a faculty at Alabama A&M University during the time frame of this study. Competing Interests : Authors have no financial or non-financial interests directly or indirectly related to the work submitted for this publication. Author Contribution L.D. designed the experiment and secured the planting site. L.D. and K.N. were involved in tree planting, herbicide treatment, mowing, support for technicians, pruning, and measurements. L.D. wrote the methods section; S.H. performed the statistical analysis. All authors contributed to the introduction, results, and discussion sections. K.N. reviewed and prepared the manuscript for submission. Acknowledgments The authors extend their gratitude to Dr. Greg Ruark, former Director of the US Forest Service National Agroforestry Center, Dr. George Brown, former Director of the Center for Forestry and Ecology, and Dr. McArthur Floyd, former Agriculture Research Director at Alabama A&M University, for their help in securing financial support and setting up the experiment. Additionally, we would like to express our appreciation to CellFor Inc. (ArborGen Inc.) for providing the pine seedlings and herbicides and to the technicians and undergraduate students who participated in planting and measuring the trees. References Adams, J.C., Clason, T.R. 2002. Loblolly pruning and growth characteristics at different planting spacings. 153–155. In Outcalt, K.W., ed. 2002. Proceedings of the 11th Biennial Southern Silvicultural Research Conference. Gen. Tech. Rep. SRS–48. Asheville, NC: USDA Forest Service, SRS. 622p. Adams, J.P., S.B. Land, Jr., K.L. Belli, and T.G. Matney. 2007. Comparison of 17–year realized plot volume gains with selection for early traits for loblolly pine. Forest Ecology and Management 255:1781–1788 Anderson S.H., Udawatta R.P., Seobi T., Garrett H.E. (2009) Soil water content and infiltration in Agroforestry buffer strips. Agroforest Syst 75:5–16 Barlow, R.J., Hunt, S. and Kush, J.S. 2016. The Silviculture of Silvopasture. In: Schweitzer, C. J.; Clatterbuck, W.K.; Oswalt, C.M., eds. 2016. Proceedings of the 18th Biennial Southern Silvicultural Research Conference. e–Gen. Tech. Rep. SRS–212. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 614 p Fowells, H.A.1965. Silvics of forest trees of the United States. U.S. Department of Agriculture, Agriculture Handbook 271. Washington, DC. 762 p. Franze, S. 2004. Financial analysis of agroforestry practices: Fodder shrubs in Kenya, woodlots in Tanzania, and improved fallows in Zambia. In: Alavalapati J.R.R., Mercer D.E. (eds.), Valuing Agroforestry System: Methods and Applications, Kluwer Academic Publishers Netherlands, pp 9–37. Franzluebbers A., Doraiswamy P. (2007) Carbon sequestration and land degradation. In: Sivakumar MVK, Ndegwa N. (eds.), Climate and land degradation. Springer, Berlin, pp. 343–358. Gao L., Xu H., Bi H., Xi W., Bao B., Wang X., et al. (2013) Intercropping Competition between Apple Trees and Crops in Agroforestry Systems on the Loess Plateau of China. PLoS ONE 8(7): e70739. https://doi.org/10.1371/journal.pone.0070739 Grado, S.C. and Husak, A.L. 2004. Economic analysis of a sustainable agroforestry system in the Southeastern United States. In: Alavalapati J.R.R., Mercer D.E. (eds.), Valuing Agroforestry System: Methods and Applications, Kluwer Academic Publishers Netherlands, pp 39–57. Garrett H.E., Kerley M.S., Ladyman K.P., Walter W.D., Godsey L.D., Van Sambeek J.W., Brauer D.K. 2004. Hardwood silvopasture management in North America. Agroforest Syst 61:21–33 Gebremedhin M, Brown J, Ries I. 2022. Soil Management and Microclimate Effects on Ecosystem Evapotranspiration of Winter Wheat–Soybean Cropping in Northern Alabama. Atmosphere. 2022; 13(10):1653. https://doi.org/10.3390/atmos13101653 Grass, R.; Malec, S.; Wachendorf, M. 2020. Biomass Performance and Competition Effects in an Established Temperate Agroforestry System of Willow and Grassland—Results of the 2nd Rotation. Agronomy, 10, 1819. https://doi.org/10.3390/agronomy10111819 Harvey, C.A., Gonzales J.G., Somarriba E. (2006) Dung beetle and terrestrial mammal diversity in forest, indigenous agroforestry systems and plantain monocultures in Talamanca, Costa Rica. Biodivers Conserv 15:555–585 Hossain, S.M.; Bragg, D.C.; McDaniel, V.L.; Pike, C.C.; Crane, B.S.; Nelson, D. 2021. Evaluation of Long-Term Shortleaf Pine Progeny Tests in the Ouachita and Ozark National Forests, USA. Forests, 12: 953. Kirschke, S. et al. (2013) Three decades of global methane sources and sinks. Nat Geosci 6:813–823. Little, Elbert L., Jr. 1971. Atlas of United States trees. vol. 1. Conifers and important hardwoods. U.S. Department of Agriculture, Miscellaneous Publication 1146. Washington, DC. 9 p., 313 maps. Luginbuhl J.M., Green J.T., Mueller J.P., Poore M.H. (2005) Forage needs for meat goats and sheep. In: Production and utilization of pastures and forages—technical bulletin 305. McKeand, S.E.; Abt, R.C.; Allen, H.L.; Li, B.; Catts, G.P. 2006. What are the best loblolly pine genotypes worth to landowners? Journal of Forestry, 104: 352–358. McKeand, S.E.; Mullin, T.L.; Byram, T.D.; White, T.L. 2003. Deployment of Genetically Improved Loblolly and Slash Pines in the South. Journal of Forestry 101 (1), 32–37, https://doi.org/10.1093/jof/101.3.32 . McNulty, S.; Caldwell, P.; Doyle, Thomas W.; Johnsen, K.; Liu, Y.Q.; Mohan, J.; Prestemon, J.; Sun, Ge. 2013. Forests and Climate Change in the Southeast USA. In: Ingram, K.; Dow, K.; Carter, L.; Anderson, J., eds. 2013. Climate of the Southeast United States: Variability, change, impacts, and vulnerability. Washington, DC: Island Press. 165–189. Melesse A, Steingass H, Schollenberger M, Holstein J, Rodehutscord M (2019) Nutrient compositions and in vitro methane production profiles of leaves and whole pods of twelve tropical multipurpose tree species cultivated in Ethiopia. Agroforest Syst 93, 135–147 https://doi.org/10.1007/s10457-017-0110-9 Moreno-Calles A, Casas A, Blancas J, Torres I, Masera O, Caballero J, Garcia-Barrios L, Perez-Negron E, Rangel-Landa S (2010) Agroforestry systems and biodiversity conservation in arid zones: the case of the Tehuacan Valley. Central Mexico. Agroforest Syst 80:315–331 Nebeker, T. E., John Riggins, John Auel, James Henderson, Andrew Ezell; A. Brady Self, Thomas Matney, Andrew Londo (2015). Southern Pine Density Management for a Healthier Forest. Mississippi State University Extension Service. https://extension.msstate.edu/sites/default/files/publications/publications/p2893.pdf Nepal, P, K L Abt, K E Skog, J P Prestemon, R C Abt (2019) Projected Market Competition for Wood Biomass between Traditional Products and Energy: A Simulated Interaction of US Regional, National, and Global Forest Product Markets. Forest Science, Volume 65, Issue 1, February 2019, Pages 14–26, https://doi.org/10.1093/forsci/fxy031 North Carolina Agricultural Research Service, North Carolina State University, Raleigh Nyakatawa, E. Z., D. A. Mays, K. Naka, J. O. Bukenya (2012). Carbon, nitrogen, and phosphorus dynamics in a loblolly pine-goat silvopasture system in the Southeast USA. Agroforest Syst 86, 129–140 (2012). https://doi.org/10.1007/s10457-011-9431-2 Oliver, C.D., and B.C. Larson. 1990. Forest Stand Dynamics. McGraw-Hill, New York, USA. Pang K, Van Sambeek JW, Lin C-H, Jose S, Garrett HE (2019) Responses of legumes and grasses to non-, moderate, and dense shade in Missouri, USA. I. Forage yield and its species-level plasticity. Agroforest Syst. 93: 11–24. https://doi.org/10.1007/s10457-017-0067-8 . PRISM Climate Group. 30-yr Normal Mean Temperature [Map]: Annual (1981–2010); PRISM Climate Group: Oregon State University, Corvallis, OR, USA, 2013. Available online: http://www.prism.oregonstate.edu/normals/ (accessed on 1 May 2023). Reiche, C.C. 1992. Economic Analysis of Living Fences in Central America: Development of a Methodology for the Collection and Analysis of Data with an Illustrative Example. In: Sullivan, G.M.; Huke, S.M., Fox, J.M., eds. 1992. Financial and Economic Analysis of Agroforestry Systems. Honolulu Hawaii, USA, pp. 193–205. Sharma, S., Adams, J.P., Schuler, J.L., Bragg, D.C. and Ficklin, R.L. 2013. Genetic effects on early stand development of improved loblolly pine (Pinus taeda L.) seedlings. In: Proceedings of the 32nd Southern Forest Tree Improvement Conference; 10–13 June 2013 Clemson, South Carolina. http://www.sftic.org , pp. 30–35. Smith, D. M., Larson, B.C., Kelty, M.J. and Ashton, P.M.S. 1997. The Practice of Silviculture: Applied Forest Ecology. New York: John Wiley and Sons, Inc. p. 537. SoilWeb: An Online Soil Survey Browser, California Soil Resource Lab - UC Davis. https://casoilresource.lawr.ucdavis.edu/gmap . Accessed on 2022/10/20. Stelzer, H.E., Foster, G. S., Shaw, D.V. and McRae, J.B. 1998. Ten-year growth comparison between rooted cuttings and seedlings of loblolly pine. Canadian Journal of Forest Research 28: p. 5. Tasissa, G., Burkhart, H.E. and Amateis, R.L. (1997) Volume and Taper Equations for Thinned and Unthinned Loblolly Pine Trees in Cutover, Site-Prepared Plantations. Southern Journal of Applied Forestry 21(3): 146–152, https://doi.org/10.1093/sjaf/21.3.146 United States Department of Agriculture. 1997. Agroforestry – functions and values. (Issue Brief 14). Washington, D.C.: United States Department of Agriculture Natural Resources Conservation Service/Soil and Water Resources Conservation Act. Udawatta RP, Garrett HE, Kallenbach RL (2010) Agroforestry and grass buffer effects on water quality in grazed pastures. Agroforest Syst 79:81–87 Wear DN, Greis JG (2002) The southern forest resource assessment—summary report. USDA Forest Service, Southern Research Station, Gen Tech. Report SRS-53 Tables Table 1 Effect of loblolly pine clone and planting pattern on survival rate Dependent variable Predictor variable Chi-square df P Survival rate Clone 3.44 1 0.048 Planting pattern 103.5 1 0.000 Table 2 Effect of loblolly pine clone and planting pattern on basal area, live crown ratio, height, and volume Dependent and predictor variables F-value df P Tree basal area (BAt, m 2 ) Clone Planting pattern Clone*planting pattern 10.37 1 0.001 62.45 1 0.001 8.26 1 0.001 Live crown ratio (LCR) Clone Planting pattern Clone*planting pattern 55.12 1 0.001 41.81 1 0.001 2.28 1 0.132 Tree height (HT, m) Clone Planting pattern Clone*planting pattern 38.27 1 0.001 44.26 1 0.001 0.02 1 0.961 Volume (Vt, m 3 ) Clone Planting pattern Clone*planting pattern 27.84 1 0.001 7.61 1 0.006 4.07 1 0.044 Table 3 Pairwise comparison of basal area, live crown ratio, height, and volume between two loblolly pine clones, Q3802-43 and L3519-41, within two planting patterns. Variables Planting pattern Difference between two clones* P Tree basal area (m 2 ) Agroforestry 0.002 0.001 Plantation 0.005 0.001 Live crown ratio Agroforestry 0.051 0.001 Plantation 0.082 0.001 Tree height (m) Agroforestry 0.951 0.001 Plantation 1.211 0.001 Tree volume (m 3 ) Agroforestry 0.013 0.081 Plantation 0.031 0.001 *Tukey HSD test was used to identify the significant difference between the means (α = 0.05). Table 4 Mean ± standard errors of basal area, live crown ratio, height, and volume of loblolly pine clones and planting patterns. Means with different letters indicate a significant difference (α = 0.05). Predictor Tree basal area (m 2 ) Live crown ratio Tree height (m) Tree volume (m 3 ) Clone Mean SE Mean SE Mean SE Mean SE Clone L3519-41 0.027 a 0.01 0.70 a 0.01 10.7 a 0.13 0.11 a 0.08 Clone Q3802-43 0.024 b 0.01 0.63 b 0.01 9.8 b 0.11 0.09 b 0.06 Planting pattern Agroforestry 0.026 a 0.01 0.70 a 0.01 9.8 a 0.12 0.09 a 0.02 Plantation 0.027 a 0.02 0.64 b 0.01 10.8 b 0.09 0.11 b 0.09 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Aug, 2024 Read the published version in Agroforestry Systems → Version 1 posted Editorial decision: Revision requested 19 Jan, 2024 Editor assigned by journal 19 Jan, 2024 Submission checks completed at journal 15 Jan, 2024 First submitted to journal 13 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3860580","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267216276,"identity":"691788bb-a8ed-446d-98fe-20c87732a01b","order_by":0,"name":"Kozma Naka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYBACCQSD+QCUmUC0FjaYUuK18BgQp0Wyvf3phh8Md+Ql2898/PAz5zADP3uOAV4t0jwH0m72MDwznM2Tu1myd9thBsmeN/i1yEkkHLvBw3CYcR5D7gYJXqAWgxsEbJGTSGy7+YfhsP08/jePf/4FarEnpEVaIpntNtCWxNkSOWzSYFskCGiR7DnGdlvG4HDyzBnPzKxlt6XzSJx5VoBXi8Tx9mc331Qctp1xPvnxzbfbrOX425M34NUCAUgu4SFC+SgYBaNgFIwCQgAAEtNH9ruYtpcAAAAASUVORK5CYII=","orcid":"","institution":"Alabama A\u0026M University","correspondingAuthor":true,"prefix":"","firstName":"Kozma","middleName":"","lastName":"Naka","suffix":""},{"id":267216277,"identity":"32ab2c96-7256-4eaf-afd6-c63edff433f7","order_by":1,"name":"Shaik Hossain","email":"","orcid":"","institution":"Alabama A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"Shaik","middleName":"","lastName":"Hossain","suffix":""},{"id":267216278,"identity":"2d90fb0b-43a1-4302-bd21-0de1a0111f18","order_by":2,"name":"Luben Dimov","email":"","orcid":"","institution":"University of Vermont","correspondingAuthor":false,"prefix":"","firstName":"Luben","middleName":"","lastName":"Dimov","suffix":""}],"badges":[],"createdAt":"2024-01-13 15:44:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3860580/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3860580/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10457-024-01040-4","type":"published","date":"2024-08-03T15:57:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49732165,"identity":"2a230ef0-8ace-430d-b434-cd9096051474","added_by":"auto","created_at":"2024-01-17 06:23:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":595737,"visible":true,"origin":"","legend":"\u003cp\u003eLocation (red star on map), aerial (top right), and ground (bottom right) view of the research site.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/73345bd60d73efd8a632ea3c.png"},{"id":49732161,"identity":"d77e4e23-892b-42ee-9467-9ee9274db3bc","added_by":"auto","created_at":"2024-01-17 06:23:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":67979,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental design layout (not to scale).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/36d468c947d607a9f2e9a7f1.png"},{"id":49732159,"identity":"9e1e58f4-7fc7-4595-a457-62d1ad2cbd92","added_by":"auto","created_at":"2024-01-17 06:23:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":66075,"visible":true,"origin":"","legend":"\u003cp\u003eMortality (M) and survival (S) rates with standard error bars at the end of nine growing seasons for two loblolly pine clones, Q3802-43 (C1) and L3519-41(C2), and two planting patterns, agroforestry (AF) and plantation (PL).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/083ddafdc95a9628c8284de6.png"},{"id":49732164,"identity":"60511391-2fea-410e-8e91-fcbe8fde198e","added_by":"auto","created_at":"2024-01-17 06:23:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":58522,"visible":true,"origin":"","legend":"\u003cp\u003eMean ± standard errors of tree basal area for each loblolly pine clone, Q3802-43 (C1) and L3519-41(C2), within each planting pattern (agroforestry and plantation). Means with different letters indicate a significant difference (α=0.05).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/56f86d18f5b56ab5e3b07791.png"},{"id":49732158,"identity":"ae16c3a8-fbb4-4dbb-85d9-3da7a2c69cb7","added_by":"auto","created_at":"2024-01-17 06:23:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":64410,"visible":true,"origin":"","legend":"\u003cp\u003eMean ± standard errors of live crown ratio for each loblolly pine clone, Q3802-43 (C1) and L3519-41(C2), within each planting pattern (agroforestry and plantation). Means with different letters indicate a significant difference (α=0.05).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/a36ff836b5dd98c79f45a976.png"},{"id":49732163,"identity":"7601ef81-6ea0-45f2-8144-f4b2dec5e8bc","added_by":"auto","created_at":"2024-01-17 06:23:57","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":56217,"visible":true,"origin":"","legend":"\u003cp\u003eMean ± standard errors of tree height area for each loblolly pine clone, Q3802-43 (C1) and L3519-41(C2), within each planting pattern (agroforestry and plantation). Means with different letters indicate a significant difference (α=0.05).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/82a450f5dd760756e36d42d3.png"},{"id":49732734,"identity":"7e92f5c7-256b-423f-9f11-435e6ce49076","added_by":"auto","created_at":"2024-01-17 06:31:57","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":47200,"visible":true,"origin":"","legend":"\u003cp\u003eMean ± standard errors of tree volume for each loblolly pine clone, Q3802-43 (C1) and L3519-41(C2), within each planting pattern (agroforestry and plantation). Means with different letters indicate a significant difference (α=0.05).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/91129821a97e3d3f652977c2.png"},{"id":61793385,"identity":"579ed1db-da29-48da-ab45-3a1857e02324","added_by":"auto","created_at":"2024-08-05 16:11:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1421166,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3860580/v1/52755c1e-db42-43e3-bf05-9793e0a785d7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Growth of Two Loblolly Pine Clones Planted in Agroforestry and Plantation Settings: Nine-year Results","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAgroforestry is a land-use practice that combines trees and agricultural crops on the same land simultaneously (USDA, 1997). Agroforestry systems include silvopasture, alley cropping, forest farming, riparian forest buffers, and windbreaks. Environmental benefits of agroforestry practices include increasing forage yields under moderate shade (Garett et al. 2004, Pang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), increasing soil carbon ) and nutrient cycling (Franzluebbers and Doraiswamy \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Jose 2009; Nyakatawa et al. 2010; Kirschke et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), reducing soil erosion and nonpoint source pollution and improving water quality (Anderson et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Udawatta et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), enhancing biodiversity (Harvey et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Moreno-Calles et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); and increasing landscape aesthetics (Garett et al. 2004). Myriad economic benefits are also available from agroforestry practices through diverse products, such as timber and agricultural production (Franzel, 2004). Depending on the tree species used, agroforestry systems can also provide other revenue-generating activities such as recreation, hunting, and pine straw production (Grado and Husak, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe most popular form of agroforestry in North America is silvopasture, in which grazing livestock and foraging crops are incorporated into plantations to sustain economic benefits (USDA, 1997). In the southeastern USA, monoculture plantations with southern pines are the more common forestry practice (Nebeker et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This production method has been commercially viable due to robust domestic demand for sawtimber and pulpwood (Nyakatawa et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, the pulpwood market has been facing ups and downs, including increasing competition from overseas markets, especially South America (Wear and Greis \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), and uncertainty of future domestic wood energy demand (Nepal et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The unpredictability of a long-term production process has made it difficult for some limited-resource forest landowners to generate a profit from pine plantations. Similarly, farmers on small and medium-sized farms face viability problems when depending on conventional agriculture due to profit uncertainties, particularly in the context of current climate changes (McNulty et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Hence, interest in small-scale and diversified agroforestry systems as a profitable and sustainable land use practice has increased (Nyakatawa et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eYet, few landowners have chosen agroforestry as a viable land use option mainly because there is a dearth of science-based information on this production method in the South. Therefore, consultant foresters who traditionally recommend industrial forest management may hesitate to promote atypical forestry practices. Consequently, landowners unfamiliar with agroforestry practices do not adopt them for fear of financial loss. To reverse this trend, landowners need to understand the science of agroforestry to achieve desired financial goals (Barlow et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Experimental demonstrations can give landowners appropriate knowledge, making them more inclined to accept this forestry farming system (Reiche, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTrees planted in agroforestry settings with wider spacing can be used for growing crops or grazing, providing not too much shade come from them as opposed to plantations, in which trees of similar age and size classes compete for the same resources, exerting adverse impacts on survival and growth, particularly when growing in close spacings (Oliver and Larson, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Traditionally, loblolly pine has been a suitable tree species for agroforestry systems in the South (Nyakatawa et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). While the trees exert some competition, they provide a number of benefits that generally outweigh the cost of the competition for light, such as reducing desiccation of crops planted under the trees and using soil resources not available to shallow-rooted crops, shade for livestock, pine straw production, and wildlife habitat. Choosing suitable species of trees and crops with proper spacing is important for minimizing the competition between trees and crops (Adams and Clason, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Further, appropriate site and environmental conditions are necessary for maximizing the benefits of agroforestry. Even cultivars or clones of the same species may have different shade tolerances and show varying sensitivity to environmental and climatic conditions (Sharma et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; McKeand et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). While most studies have investigated the performance of species and cultivars of understory crops (Gao et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Barlow et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Grass et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), more information about wood production in agroforestry systems is needed.\u003c/p\u003e \u003cp\u003eThe main objective of this study was to evaluate the performance of two forest industry-rated clones of loblolly pine (\u003cem\u003ePinus taeda\u003c/em\u003e L.) planted in an agroforestry and a plantation setting. In particular, we assessed and compared the survival and growth of two pine clones. A secondary objective was to use the study site for demonstrations and workshops for farmers and non-industrial private forest landowners.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe study was conducted at Alabama A\u0026amp;M University\u0026rsquo;s Winfred Thomas Agricultural Research Station (34.901589, -86.579392), in Hazel Green, Alabama, USA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), at 235 m of elevation. According to the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) soil survey (Soilweb 2022), the soils are classified as Decatur silty clay loam, 2 to 6 percent slope, eroded, and with a typical profile of Ap for the first 18 cm (silty clay loam), Bt1 from 18 to 61 cm (silty clay loam), and Bt2 from 80 to 203 cm (clay). The topsoil (0\u0026ndash;25 cm) is dark brown to dark reddish-brown friable and heavy mellow silt loam. The supply of plant nutrients is high. This soil is moderately permeable to roots and moisture with a relatively high capacity for holding the water available to plants. Soil preparation included plowing and disking in the fall. Prior land use was growing agricultural crops such as cotton, corn, and hay, and to a lesser extent, other crops such as potatoes, grain sorghum, soybeans, and field peas. The soil has a thin organic layer, is slightly acidic, and moderately to well drained with high permeability (Gebremedhin 2022).\u003c/p\u003e \u003cp\u003eThe mean annual precipitation in the area is 1500 mm, while the average minimum, mean, and maximum annual temperatures are 9, 16, and 21 degrees Celsius, respectively (PRISM Climate Group, 2023). The site has a temperate climate. The monthly average temperature from May to November varies from 5.0℃ to 32.2℃. The warmest month is August, and the coldest month is January. The frost-free period is from 180 to 240 days.\u003c/p\u003e \u003cp\u003eCellFor Inc. (later acquired by ArborGen) provided the planting stock in January 2007. It consisted of two clones, Q3802-43 (clone 1) and L3519-41 (clone 2) of loblolly pine (\u003cem\u003ePinus taeda L.\u003c/em\u003e) 1-0 bare root seedlings (i.e., grown in a nursery for one year before being outplanted in the field for this experiment). These two clones were developed under CellFor\u0026rsquo;s Varietal Forestry Program using genetic methods to maximize gains in yield and survival.\u003c/p\u003e \u003cp\u003eWe planted the seedlings in two spacing arrangements: plantation planting pattern (3.0 m x 3.7 m, with 3.0 m between rows and 3.7 m between seedlings within a row) and agroforestry planting pattern (two rows at 3.0 m x 3.7 m, alternating with 12.2 m wide alleys between the double rows). Both spacing arrangements have 24 seedlings in a row. The rows were oriented from west to east for maximum insolation of the alley. To maximize growing space, seedlings of each row were offset (staggered), so they were between rather than opposite to the seedlings of the neighboring row. The alley between the double rows of the agroforestry pattern was less shaded than in a plantation pattern and would be used for growing hay, row crops, or as pasture (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeedlings of the two clones were planted in a randomized block design with three replications of the agroforestry spacing and two replications of the plantation spacing for each clone within three blocks (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The agroforestry planting pattern was replicated three times (once in each of the three blocks) for each of the two clones. The forest plantation planting pattern was replicated twice (in blocks 1 and 2) for each clone. This design resulted in 10 rows per replication in agroforestry and 14 rows per replication in plantation, for a total of 88 rows. A total of 2112 seedlings were planted in the three blocks. The seedlings were planted manually using dibble bars. The herbaceous vegetation between the seedlings was sprayed with the herbicide Oustar\u0026reg; in April of the year of planting and March of the following year. The rate per hectare was 1.0 liter of the herbicide mixed into 100 to 400 liters of water. In addition, the vegetation was mowed one to three times during the first through the third growing seasons.\u003c/p\u003e \u003cp\u003eIn September 2015, nine growing seasons after planting in the field, we used diameter tapes to measure the diameter at breast height (dbh, 1.37 m above the ground) for all the live trees. In January 2016, we selected a subset of the trees (about 12% of all live trees) by stratified random sampling and measured their total tree height (HT) and height from the ground to the base of the live crown (HBLC). All the heights were measured using clinometers. We also tallied all dead trees to assess the survival rate through the ninth growing season. The diameters and heights were measured to the nearest 0.1 inch (0.254 cm) and the nearest foot (30.5 cm), respectively. Before conducting the analysis, we converted the English units to metric.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnalytical Approach\u003c/h2\u003e \u003cp\u003eOur analysis evaluated pine clone responses both at stand and tree levels. Stand-level patterns were tested using the survival rate of clones, estimated as the percentage of trees initially planted in 2007 tallied as live during the sampling in 2015. Three dependent variables were used for testing tree-level responses: tree basal area (BAt), live crown ratio (LCR), and total tree volume inside-bark (Vt). Tree-level statistics for BAt were calculated based on the measurements of all the trees, while statistics for LCR and Vt were based on a subset of the trees.\u003c/p\u003e \u003cp\u003eBAt was calculated using the following standard equation:\u003c/p\u003e \u003cp\u003eBAt (m\u003csup\u003e2\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;0.00007854 x dbh\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ewhere dbh is the diameter at breast height in centimeters\u003c/p\u003e \u003cp\u003eLCR was calculated by subtracting HBLC from the total tree height and dividing the result by the total tree height. Therefore, LCR = (HT-HBLC)/HT. LRC represents a ratio value; hence, it does not have units.\u003c/p\u003e \u003cp\u003eWe adopted the following equation developed by Tasissa et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) to determine Vt of our pine trees:\u003c/p\u003e \u003cp\u003eVt = -0.01039\u0026thinsp;+\u0026thinsp;0.00196 x dbh\u003csup\u003e2\u003c/sup\u003e x HT [1],\u003c/p\u003e \u003cp\u003ewhere\u003c/p\u003e \u003cp\u003eVt is the inside-bark total tree volume in cubic meters, dbh is the diameter at breast height in centimeters, and HT is the total height of the tree in meters.\u003c/p\u003e \u003cp\u003eEquation [1] was developed using data from the sampling of loblolly pine plantations across multiple locations within its geographic range. It is widely used to calculate the inside-bark volume of unthinned loblolly pine tree stems in cutover, site-prepared plantations similar to trees on our site.\u003c/p\u003e \u003cp\u003eThe analysis of variance (ANOVA) was used to assess the effect of clones and planting patterns on BAt, LCR, HT, and Vt using RStudio version 1.1.456. Because the experiment was based on a randomized block design, we used a two-way ANOVA to evaluate the effect of predictors on the three response variables. Residuals were checked for normality and equal variance. Since residual variance met the model assumptions, there was no need for data transformation. When ANOVA detected significant effects, pairwise comparisons were performed to determine the difference between means using Tukey\u0026rsquo;s HSD test.\u003c/p\u003e \u003cp\u003eBecause both the clone and the survival rate are binary variables, we conducted a \u0026ldquo;proportion test\u0026rdquo; to determine whether the survival percentage varied between the planted clones. Also, two-sample t-tests were used to compare BAt, LCR, HT, and Vt between the clones and the planting patterns. We used Welch\u0026rsquo;s t-tests in particular because the variances of response variables in both groups (clone and planting pattern) were unequal. Statistical significance was assessed at the 0.05 level (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAt the end of nine growing seasons, 866 of 1008 clone 1 (Q3802-43) seedlings survived, while 915 of 1104 clone 2 (L3519-41) seedlings survived. Proportion tests revealed that mean seedling survival was significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the two pine clones (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), with clone 1 showing a slightly greater survival rate (86%) compared to clone 2 (83%). When it came to planting patterns, the agroforestry pattern demonstrated a significantly higher (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) survival rate than the plantation pattern, averaging 90% and 72% survival, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBoth clone and planting pattern were significant factors (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the ANOVA model for BAt, LCR, HT, and Vt (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Additionally, there was a significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) interaction between clones and planting patterns for BAt and Vt (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating that one clone responded better than the other within a particular planting pattern. However, interactions between clones and planting patterns were insignificant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) for LCR and HT (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePairwise comparisons revealed that in both agroforestry and plantation settings, clone 2 gained, on average, 0.002 and 0.005 m\u003csup\u003e2\u003c/sup\u003e, respectively, more in BAt than clone 1 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Similarly, the LCR of clone 2 showed greater values (5.1% higher in agroforestry and 8.2% higher in plantation) than the LCR of clone 1. Also, the HT of clone 2 was higher than the HT of clone 1 in both planting patterns (a difference of 0.95 m in agroforestry and 1.21 m in plantation). When Vt was considered, clone 2 showed a higher response of 0.03 m\u003csup\u003e3\u003c/sup\u003e in the plantation setting than clone 1. However, there was no difference in Vt between the two clones in the agroforestry setting (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAccording to the t-tests, there was a significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the two pine clones for the four response variables during the growth period irrespective of planting patterns, with clone 2 generally demonstrating a greater growth than clone 1 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). BAt, LCR, HT, and Vt of clone 2 averaged 0.027 m\u003csup\u003e2\u003c/sup\u003e, 70%, 10.7 m, and 0.11 m\u003csup\u003e3\u003c/sup\u003e, respectively, and all were significantly higher than those of clone 1. As for planting patterns, except for BAt (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), all other response variables (LCR, HT, and Vt) differed significantly (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between agroforestry and plantation regardless of pine clones (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). On average, LCR was higher in the agroforestry setting than in the plantation setting (0.70 vs. 0.64). In contrast, HT and Vt showed a higher value in the plantation setting than in the agroforestry setting (an average of 10.8 m vs. 9.8 m and 0.11 m\u003csup\u003e3\u003c/sup\u003e vs. 0.09 m\u003csup\u003e3\u003c/sup\u003e, respectively).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBy deploying different pine clones, we were able to assess some of the variability associated with their genetics. Survival of both pine clones at the end of the ninth growing season was relatively high (\u0026gt;\u0026thinsp;83%), reaffirming that our region has favorable site conditions for planting loblolly pine (Adams and Clason, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Little, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1971\u003c/span\u003e). A silvopasture study conducted in southern Alabama found a similar survival rate (81%) of planted loblolly pine at age eight (Barlow et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Moreover, pine clones in this study had a comparable survival rate with those originating from seeds mentioned in prior research (Stelzer et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). However, clone 1 (Q3802-43) had a 3% greater survival rate than clone 2 (L3519-41). Data collected at the end of the second growing season showed similar survival rates between the two planted clones (88% in clone 1 vs. 84% in clone 2), suggesting that survival differences between the two clones have sustained through time. In contrast, clone 2 performed better than clone 1 for all four growth performance factors (BAt, LCR, HT, and Vt). Second-year estimates, at the seedling stage of our pines, showed no significant differences between the clones in BAt (0.002 m\u003csup\u003e2\u003c/sup\u003e for both clones, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and height (2.0 m and 2.1 m in clone 1 and clone 2, respectively). These results suggest that initial growth patterns between the pine clones diverged at the sapling stage (year nine).\u003c/p\u003e \u003cp\u003eThe differential performances in the clone\u0026rsquo;s survival and growth could be attributed to variations in both endogenous (e.g., genetics) and exogenous (e.g., environment and climate) factors. Loblolly pine has been the subject of tree improvement programs for almost 50 years in the South, producing planting stock with appreciable genetic gains in growth and survivorship (McKeand et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The two pine clones we used were developed by selecting improved genotypes; therefore, genetics significantly affected their performance. However, several exogenous factors can also affect southern pines\u0026rsquo; growth and survival rates (Hossain et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sharma et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These include natural disturbances such as diseases, insects, fires, storms (ice and wind), and droughts. Much of the study region experienced extreme drought in 2007 (PRISM Climate Group, 2023), which could have differentially affected the survival and growth of the young pine trees.\u003c/p\u003e \u003cp\u003eBased mainly on genetics, clone 1 is preferred over clone 2 for our region if survivorship is considered a selection criterion and clone 2 is recommended from the wood production viewpoint. However, it will be more advantageous to use clone 2 overall since its higher average tree volume (0.11 m\u003csup\u003e3\u003c/sup\u003e vs. 0.9 m\u003csup\u003e3\u003c/sup\u003e of clone 1) can easily offset the lower survival rate.\u003c/p\u003e \u003cp\u003eAgroforestry pines had a better survival rate than those of the plantation. The difference in survival performance between planting patterns likely reflects competition-induced mortality associated with spacing (Sharma et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Loblolly pine is a shade-intolerant species and, therefore, is more sensitive to competition, particularly when grown in planted monocultures with narrow spacing (Fowells, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1965\u003c/span\u003e). Since there was less available light due to the narrow spacing, there was more competition, and hence more pine mortality, in the plantation pattern than in the agroforestry pattern. However, given that our plantings were just eight years old, it is unlikely that they have yet reached canopy closure, which initiates the onset of competition (Adams et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). We speculate that the full extent of the competition effect cannot be evaluated until these stands become mature (\u0026gt;\u0026thinsp;15 years of age), and self-thinning would start as a result of more intense intraspecific competition (Sharma et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hossain et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Based on a longer-term study conducted in central Mississippi, Adams et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) reported that the survival of loblolly pine at 17 years was significantly affected by spacing, with widely-spaced plantings showing higher survival rates than those with closer spacings, which corroborates with our assumption.\u003c/p\u003e \u003cp\u003eAgroforestry pines also had a greater live crown ratio than the plantation because of the wider spacing in agroforestry and the ecology of the species. Loblolly pine can self-prune when growing in plantations with sufficiently dense competition, causing shading on branches in the lower part of the crown (Smith et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). With fewer trees crowding around, there was less shading on the lower branches in the agroforestry pattern, leading to less self-pruning and more live crown area. Furthermore, the agroforestry pattern received more light on the sides of the crowns than the plantation pattern, allowing trees to allocate more resources to branch growth. In a study with loblolly pine silvopasture based in Louisiana, Adams and Clason (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) reported that the height to the first live limb was the least for trees planted at wider spacing, resulting in greater live crown area than those at close spacing. This result is consistent with our study.\u003c/p\u003e \u003cp\u003eWe expected a greater BAt in agroforestry simply because trees had more available growing space, but there was no difference in BAt between the two planting patterns. This is surprising because loblolly pine is expected to grow favorably in stem diameter at wide spacings (Adams and Clason, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Conversely, HT was greater in plantation than agroforestry, which was expected since height growth in even-aged stands like these is primarily triggered by intraspecific competition (Oliver and Larson, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Therefore, trees allocate more resources to height growth than branch growth in plantations to avoid fierce competition for light associated with close spacings. As a result, Vt was higher in the plantation than in the agroforestry setting, despite similar BAt in both planting patterns because of higher HT in the plantation setting. However, the trees in our study were only eight years old. As mortality continues to rise with stand age, spacings are expected to become less variable over time, resulting in more equality in height between the two planting patterns. More time is needed to determine if factors such as competition-induced mortality may change the outcomes of these growth performance measures.\u003c/p\u003e \u003cp\u003eThe Loblolly pine is a commercially important tree species in the southern US. Considerable work has been completed to produce productive clones for our region (Stelzer et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The species is also well suited for agroforestry due to its ease of establishment and diversified benefits. However, very few studies have investigated the performance of loblolly pine cultivars in agroforestry systems (Barlow et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Grass et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To our knowledge, this is the first study in our region to assess and compare the survival and growth of two industry-rated loblolly pine clones planted both in agroforestry and plantation settings. We also recently introduced goats to graze the site so their impact on stand productivity can be examined. Introducing goats into the site will not only ensure biological control of unwanted vegetation but also provide an opportunity to increase farm profits (Luginbuhl et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Additionally, trees in the agroforestry settings were pruned and are being monitored to evaluate the pruning impact.\u003c/p\u003e \u003cp\u003eWe expect this study site to be used as a demonstration site for farmers and non-industrial private forest landowners unfamiliar with the practice of silvopasture so they can adopt it to maximize farm profits by diversifying their farm operations. As additional information on relative improvements in stand productivity (timber and non-timber) becomes available over time, we hope more farmers and non-industrial private forest landowners will be interested in silvopasture systems. More demonstrations are necessary to give landowners a broader perspective on this emerging forestry farming system.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFinancial support was provided by the USDA National Institute of Food and Agriculture, McIntire-Stennis project accession number 1008953, and Alabama A\u0026amp;M University. CellFor Inc. provided the seedlings and the herbicide. The dataset generated and analyzed during the current study is available from the corresponding author upon request. Dr. Dimov was a faculty at Alabama A\u0026amp;M University during the time frame of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan class=\"Underline\"\u003eCompeting Interests\u003c/span\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors have no financial or non-financial interests directly or indirectly related to the work submitted for this publication.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eL.D. designed the experiment and secured the planting site. L.D. and K.N. were involved in tree planting, herbicide treatment, mowing, support for technicians, pruning, and measurements. L.D. wrote the methods section; S.H. performed the statistical analysis. All authors contributed to the introduction, results, and discussion sections. K.N. reviewed and prepared the manuscript for submission.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors extend their gratitude to Dr. Greg Ruark, former Director of the US Forest Service National Agroforestry Center, Dr. George Brown, former Director of the Center for Forestry and Ecology, and Dr. McArthur Floyd, former Agriculture Research Director at Alabama A\u0026amp;M University, for their help in securing financial support and setting up the experiment. Additionally, we would like to express our appreciation to CellFor Inc. (ArborGen Inc.) for providing the pine seedlings and herbicides and to the technicians and undergraduate students who participated in planting and measuring the trees.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdams, J.C., Clason, T.R. 2002. Loblolly pruning and growth characteristics at different planting spacings. 153\u0026ndash;155. In Outcalt, K.W., ed. 2002. Proceedings of the 11th Biennial Southern Silvicultural Research Conference. Gen. Tech. Rep. SRS\u0026ndash;48. Asheville, NC: USDA Forest Service, SRS. 622p.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdams, J.P., S.B. Land, Jr., K.L. Belli, and T.G. Matney. 2007. Comparison of 17\u0026ndash;year realized plot volume gains with selection for early traits for loblolly pine. Forest Ecology and Management 255:1781\u0026ndash;1788\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson S.H., Udawatta R.P., Seobi T., Garrett H.E. (2009) Soil water content and infiltration in Agroforestry buffer strips. Agroforest Syst 75:5\u0026ndash;16\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarlow, R.J., Hunt, S. and Kush, J.S. 2016. The Silviculture of Silvopasture. In: Schweitzer, C. J.; Clatterbuck, W.K.; Oswalt, C.M., eds. 2016. Proceedings of the 18th Biennial Southern Silvicultural Research Conference. e\u0026ndash;Gen. Tech. Rep. SRS\u0026ndash;212. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 614 p\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFowells, H.A.1965. Silvics of forest trees of the United States. U.S. Department of Agriculture, Agriculture Handbook 271. Washington, DC. 762 p.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFranze, S. 2004. Financial analysis of agroforestry practices: Fodder shrubs in Kenya, woodlots in Tanzania, and improved fallows in Zambia. In: Alavalapati J.R.R., Mercer D.E. (eds.), Valuing Agroforestry System: Methods and Applications, Kluwer Academic Publishers Netherlands, pp 9\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFranzluebbers A., Doraiswamy P. (2007) Carbon sequestration and land degradation. In: Sivakumar MVK, Ndegwa N. (eds.), Climate and land degradation. Springer, Berlin, pp. 343\u0026ndash;358.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao L., Xu H., Bi H., Xi W., Bao B., Wang X., et al. (2013) Intercropping Competition between Apple Trees and Crops in Agroforestry Systems on the Loess Plateau of China. PLoS ONE 8(7): e70739. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0070739\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0070739\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrado, S.C. and Husak, A.L. 2004. Economic analysis of a sustainable agroforestry system in the Southeastern United States. In: Alavalapati J.R.R., Mercer D.E. (eds.), Valuing Agroforestry System: Methods and Applications, Kluwer Academic Publishers Netherlands, pp 39\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarrett H.E., Kerley M.S., Ladyman K.P., Walter W.D., Godsey L.D., Van Sambeek J.W., Brauer D.K. 2004. Hardwood silvopasture management in North America. Agroforest Syst 61:21\u0026ndash;33\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGebremedhin M, Brown J, Ries I. 2022. Soil Management and Microclimate Effects on Ecosystem Evapotranspiration of Winter Wheat\u0026ndash;Soybean Cropping in Northern Alabama. Atmosphere. 2022; 13(10):1653. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/atmos13101653\u003c/span\u003e\u003cspan address=\"10.3390/atmos13101653\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrass, R.; Malec, S.; Wachendorf, M. 2020. Biomass Performance and Competition Effects in an Established Temperate Agroforestry System of Willow and Grassland\u0026mdash;Results of the 2nd Rotation. Agronomy, 10, 1819. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/agronomy10111819\u003c/span\u003e\u003cspan address=\"10.3390/agronomy10111819\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarvey, C.A., Gonzales J.G., Somarriba E. (2006) Dung beetle and terrestrial mammal diversity in forest, indigenous agroforestry systems and plantain monocultures in Talamanca, Costa Rica. Biodivers Conserv 15:555\u0026ndash;585\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHossain, S.M.; Bragg, D.C.; McDaniel, V.L.; Pike, C.C.; Crane, B.S.; Nelson, D. 2021. Evaluation of Long-Term Shortleaf Pine Progeny Tests in the Ouachita and Ozark National Forests, USA. Forests, 12: 953.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKirschke, S. et al. (2013) Three decades of global methane sources and sinks. Nat Geosci 6:813\u0026ndash;823.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLittle, Elbert L., Jr. 1971. Atlas of United States trees. vol. 1. Conifers and important hardwoods. U.S. Department of Agriculture, Miscellaneous Publication 1146. Washington, DC. 9 p., 313 maps.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuginbuhl J.M., Green J.T., Mueller J.P., Poore M.H. (2005) Forage needs for meat goats and sheep. In: Production and utilization of pastures and forages\u0026mdash;technical bulletin 305.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcKeand, S.E.; Abt, R.C.; Allen, H.L.; Li, B.; Catts, G.P. 2006. What are the best loblolly pine genotypes worth to landowners? Journal of Forestry, 104: 352\u0026ndash;358.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcKeand, S.E.; Mullin, T.L.; Byram, T.D.; White, T.L. 2003. Deployment of Genetically Improved Loblolly and Slash Pines in the South. Journal of Forestry 101 (1), 32\u0026ndash;37, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jof/101.3.32\u003c/span\u003e\u003cspan address=\"10.1093/jof/101.3.32\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcNulty, S.; Caldwell, P.; Doyle, Thomas W.; Johnsen, K.; Liu, Y.Q.; Mohan, J.; Prestemon, J.; Sun, Ge. 2013. Forests and Climate Change in the Southeast USA. In: Ingram, K.; Dow, K.; Carter, L.; Anderson, J., eds. 2013. Climate of the Southeast United States: Variability, change, impacts, and vulnerability. Washington, DC: Island Press. 165\u0026ndash;189.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelesse A, Steingass H, Schollenberger M, Holstein J, Rodehutscord M (2019) Nutrient compositions and in vitro methane production profiles of leaves and whole pods of twelve tropical multipurpose tree species cultivated in Ethiopia. Agroforest Syst 93, 135\u0026ndash;147 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10457-017-0110-9\u003c/span\u003e\u003cspan address=\"10.1007/s10457-017-0110-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoreno-Calles A, Casas A, Blancas J, Torres I, Masera O, Caballero J, Garcia-Barrios L, Perez-Negron E, Rangel-Landa S (2010) Agroforestry systems and biodiversity conservation in arid zones: the case of the Tehuacan Valley. Central Mexico. Agroforest Syst 80:315\u0026ndash;331\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNebeker, T. E., John Riggins, John Auel, James Henderson, Andrew Ezell; A. Brady Self, Thomas Matney, Andrew Londo (2015). Southern Pine Density Management for a Healthier Forest. Mississippi State University Extension Service. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://extension.msstate.edu/sites/default/files/publications/publications/p2893.pdf\u003c/span\u003e\u003cspan address=\"https://extension.msstate.edu/sites/default/files/publications/publications/p2893.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNepal, P, K L Abt, K E Skog, J P Prestemon, R C Abt (2019) Projected Market Competition for Wood Biomass between Traditional Products and Energy: A Simulated Interaction of US Regional, National, and Global Forest Product Markets. Forest Science, Volume 65, Issue 1, February 2019, Pages 14\u0026ndash;26, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/forsci/fxy031\u003c/span\u003e\u003cspan address=\"10.1093/forsci/fxy031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNorth Carolina Agricultural Research Service, North Carolina State University, Raleigh\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNyakatawa, E. Z., D. A. Mays, K. Naka, J. O. Bukenya (2012). Carbon, nitrogen, and phosphorus dynamics in a loblolly pine-goat silvopasture system in the Southeast USA. Agroforest Syst 86, 129\u0026ndash;140 (2012). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10457-011-9431-2\u003c/span\u003e\u003cspan address=\"10.1007/s10457-011-9431-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOliver, C.D., and B.C. Larson. 1990. Forest Stand Dynamics. McGraw-Hill, New York, USA.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePang K, Van Sambeek JW, Lin C-H, Jose S, Garrett HE (2019) Responses of legumes and grasses to non-, moderate, and dense shade in Missouri, USA. I. Forage yield and its species-level plasticity. Agroforest Syst. 93: 11\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10457-017-0067-8\u003c/span\u003e\u003cspan address=\"10.1007/s10457-017-0067-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePRISM Climate Group. 30-yr Normal Mean Temperature [Map]: Annual (1981\u0026ndash;2010); PRISM Climate Group: Oregon State University, Corvallis, OR, USA, 2013. Available online: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.prism.oregonstate.edu/normals/\u003c/span\u003e\u003cspan address=\"http://www.prism.oregonstate.edu/normals/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed on 1 May 2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReiche, C.C. 1992. Economic Analysis of Living Fences in Central America: Development of a Methodology for the Collection and Analysis of Data with an Illustrative Example. In: Sullivan, G.M.; Huke, S.M., Fox, J.M., eds. 1992. Financial and Economic Analysis of Agroforestry Systems. Honolulu Hawaii, USA, pp. 193\u0026ndash;205.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma, S., Adams, J.P., Schuler, J.L., Bragg, D.C. and Ficklin, R.L. 2013. Genetic effects on early stand development of improved loblolly pine (Pinus taeda L.) seedlings. In: Proceedings of the 32nd Southern Forest Tree Improvement Conference; 10\u0026ndash;13 June 2013 Clemson, South Carolina. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.sftic.org\u003c/span\u003e\u003cspan address=\"http://www.sftic.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, pp. 30\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith, D. M., Larson, B.C., Kelty, M.J. and Ashton, P.M.S. 1997. The Practice of Silviculture: Applied Forest Ecology. New York: John Wiley and Sons, Inc. p. 537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoilWeb: An Online Soil Survey Browser, California Soil Resource Lab - UC Davis. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://casoilresource.lawr.ucdavis.edu/gmap\u003c/span\u003e\u003cspan address=\"https://casoilresource.lawr.ucdavis.edu/gmap\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on 2022/10/20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStelzer, H.E., Foster, G. S., Shaw, D.V. and McRae, J.B. 1998. Ten-year growth comparison between rooted cuttings and seedlings of loblolly pine. Canadian Journal of Forest Research 28: p. 5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTasissa, G., Burkhart, H.E. and Amateis, R.L. (1997) Volume and Taper Equations for Thinned and Unthinned Loblolly Pine Trees in Cutover, Site-Prepared Plantations. Southern Journal of Applied Forestry 21(3): 146\u0026ndash;152, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/sjaf/21.3.146\u003c/span\u003e\u003cspan address=\"10.1093/sjaf/21.3.146\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnited States Department of Agriculture. 1997. Agroforestry \u0026ndash; functions and values. (Issue Brief 14). Washington, D.C.: United States Department of Agriculture Natural Resources Conservation Service/Soil and Water Resources Conservation Act.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUdawatta RP, Garrett HE, Kallenbach RL (2010) Agroforestry and grass buffer effects on water quality in grazed pastures. Agroforest Syst 79:81\u0026ndash;87\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWear DN, Greis JG (2002) The southern forest resource assessment\u0026mdash;summary report. USDA Forest Service, Southern Research Station, Gen Tech. Report SRS-53\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of loblolly pine clone and planting pattern on survival rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePredictor variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSurvival rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlanting pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of loblolly pine clone and planting pattern on basal area, live crown ratio, height, and volume\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent and predictor variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTree basal area (BAt, m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003cp\u003eClone\u003c/p\u003e \u003cp\u003ePlanting pattern\u003c/p\u003e \u003cp\u003eClone*planting pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLive crown ratio (LCR)\u003c/p\u003e \u003cp\u003eClone\u003c/p\u003e \u003cp\u003ePlanting pattern\u003c/p\u003e \u003cp\u003eClone*planting pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTree height (HT, m)\u003c/p\u003e \u003cp\u003eClone\u003c/p\u003e \u003cp\u003ePlanting pattern\u003c/p\u003e \u003cp\u003eClone*planting pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eVolume (Vt, m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003cp\u003eClone\u003c/p\u003e \u003cp\u003ePlanting pattern\u003c/p\u003e \u003cp\u003eClone*planting pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePairwise comparison of basal area, live crown ratio, height, and volume between two loblolly pine clones, Q3802-43 and L3519-41, within two planting patterns.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlanting pattern\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDifference\u003c/p\u003e \u003cp\u003ebetween two clones*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTree basal area (m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgroforestry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLive crown ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgroforestry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTree height (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgroforestry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTree volume (m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgroforestry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Tukey HSD test was used to identify the significant difference between the means (α\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard errors of basal area, live crown ratio, height, and volume of loblolly pine clones and planting patterns. Means with different letters indicate a significant difference (α\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTree basal area (m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eLive crown ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTree height (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eTree volume (m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClone L3519-41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.7\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClone Q3802-43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.024\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlanting pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgroforestry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.8\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"agroforestry-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"agfo","sideBox":"Learn more about [Agroforestry Systems](http://link.springer.com/journal/10457)","snPcode":"10457","submissionUrl":"https://submission.nature.com/new-submission/10457/3","title":"Agroforestry Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"agroforestry, loblolly pine, clones, survival rate, tree volume","lastPublishedDoi":"10.21203/rs.3.rs-3860580/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3860580/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSelecting suitable tree species, cultivars, or clones in agroforestry is essential for maximizing volume growth and reducing mortality. While most studies have investigated the performance of understory crops, more information is needed about the performance of trees in agroforestry systems. In the last decades, the forest industry in the Southeast has produced high-yielding loblolly pine varieties that can be propagated by cloning. We evaluated the performance of two forest industry-rated loblolly pine clones (\u003cem\u003ePinus taeda\u003c/em\u003e L.) that we planted in an agroforestry and a plantation setting at a northern Alabama site. Specifically, we assessed and compared the survival and growth of two genetically improved pine clones: clone 1 (Q3802-43) and clone 2 (L3519-41). Clone 1 had a greater overall survival rate than clone 2 (86% vs. 83%). However, clone 2 demonstrated a superior performance growth compared to clone 1. Tree basal area, live crown ratio, height, and total tree volume inside-bark of clone 2 averaged 0.027 m\u003csup\u003e2\u003c/sup\u003e, 70%, 10.7 m, and 0.11 m\u003csup\u003e3\u003c/sup\u003e, respectively, and all were significantly higher than those of clone 1 (0.024 m\u003csup\u003e2\u003c/sup\u003e, 63%, 9.8 m, and 0.09 m\u003csup\u003e3\u003c/sup\u003e). Therefore, clone 1 is preferred over clone 2 for our region and in similar site conditions if survival is considered a selection criterion and clone 2 is preferred from the wood production viewpoint. However, it will be more advantageous to use clone 2 overall since its higher average tree volume (0.11 m\u003csup\u003e3\u003c/sup\u003e vs. 0.9 m\u003csup\u003e3\u003c/sup\u003e of clone 1) can easily offset the lower survival rate.\u003c/p\u003e","manuscriptTitle":"Growth of Two Loblolly Pine Clones Planted in Agroforestry and Plantation Settings: Nine-year Results","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-17 06:23:51","doi":"10.21203/rs.3.rs-3860580/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-01-19T17:14:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-19T16:46:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-15T15:33:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Agroforestry Systems","date":"2024-01-13T15:31:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"agroforestry-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"agfo","sideBox":"Learn more about [Agroforestry Systems](http://link.springer.com/journal/10457)","snPcode":"10457","submissionUrl":"https://submission.nature.com/new-submission/10457/3","title":"Agroforestry Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8dd12fd7-144b-4055-868c-98bfcbd693d9","owner":[],"postedDate":"January 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T16:00:12+00:00","versionOfRecord":{"articleIdentity":"rs-3860580","link":"https://doi.org/10.1007/s10457-024-01040-4","journal":{"identity":"agroforestry-systems","isVorOnly":false,"title":"Agroforestry Systems"},"publishedOn":"2024-08-03 15:57:04","publishedOnDateReadable":"August 3rd, 2024"},"versionCreatedAt":"2024-01-17 06:23:51","video":"","vorDoi":"10.1007/s10457-024-01040-4","vorDoiUrl":"https://doi.org/10.1007/s10457-024-01040-4","workflowStages":[]},"version":"v1","identity":"rs-3860580","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3860580","identity":"rs-3860580","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}