TY - JOUR
AU - Wigley, T, Bently
AB - Abstract In the Western Gulf region of the United States cold-tolerant eucalyptus have been explored as pulpwood feedstock. However, non-native plantations may alter understory species diversity, modifying environmental conditions and soil characteristics. Few studies have compared eucalyptus plantations with native ecosystems to understand the impact on understory vegetation in the United States. In this study, we compared understory plant species richness and diversity during 2014–2016 in (1) slash pine (Pinus elliottii) established in 2008, (2) slash pine established in 2013, and (3) and Camden white gum (Eucalyptus benthamii) established in 2013. Overstory characteristics, soil pH, and soil nutrient concentrations were measured to understand factors that affected understory species richness and diversity. Results indicated a decline in understory species richness over time, with Camden white gum in an intermediate condition between same-age slash pine (highest richness) and older slash pine (lowest richness). Leaf area index, soil pH and K, and tree height were the most important factors influencing understory species richness and diversity. The adoption of fast-growing eucalyptus on these sites will probably accelerate the deterioration of natural habitats and reduce open-condition species in favor of shade-tolerant species, overturning the conservation efforts already put in place by governmental agencies and conservation groups. eucalyptus, pine, plantations, species richness, biodiversity, understory Management and Policy Implications Converting from slash pine (Pinus elliottii) to Camden white gum (Eucalyptus benthamii) was associated with relatively fast changes in understory vegetation species richness. One year after plantation establishment, the number of understory species of Camden white gum was comparable to that of the same-age slash pine, and higher than that of similar-height slash pine. However, species richness of Camden white gum understory decreased through the three years of this study to the point of becoming intermediate to same-age and similar-height slash pine plantations. Evidence suggests that changes in species richness were triggered by rapid increases in Camden white gum tree dimensions, which increased leaf area index and reduced total daily radiation under the canopy. Fertilization of the Camden white gum plantations to promote tree growth likely accentuated this trend. Species richness was lower on acidic soils, and it was higher in less acidic same-age slash pine plantations that had been recently prescribed-burned. As such, exclusion of prescribed fire in Camden white gum management may have contributed to its lower understory species richness. At present, Camden white gum plantations are a relatively small component of the region in which this study was conducted. Expanded establishment of Camden white gum plantations on sites formerly occupied by slash pine plantations could have implications at the landscape scale. Combining biodiversity maintenance and wood production at different spatial scales is a critical issue for forest managers (Carnus et al. 2006), and further research is needed for a better understanding of implications at larger spatial and longer temporal scales. Further research is required to understand the effects of disturbances associated with harvesting regimes of these plantations (with Camden white gum clearcut-harvested in seven- to 10-year rotations and slash pine thinned twice then clearcut-harvested in a 30-year rotation) on understory species richness and diversity. Additionally, changes in species richness and diversity can have functional consequences on ecosystem functionality, services, and processes connected to the understory, such as nutrient cycling or net primary productivity. These issues also merit further research. Eucalyptus (Eucalyptus spp.) plantations are common in Asia, Africa, and South America because of their fast growth, high productivity, and good adaptability to various site conditions (Shi et al. 2013), but they have not been widely planted in the United States due to their sensitivity to cold temperatures (Rockwood 2012, Kellison et al. 2013). Eucalyptus plantations can be successfully established in the southeastern US by planting cold-tolerant species, such as Camden white gum (Eucalyptus benthamii (Maiden & Cambage)), which are able to thrive in the areas classified by the US Department of Agriculture (USDA) as Plant Hardiness Zones 8b (annual minimum temperature > 9.4° C) and greater (Hinchee et al. 2011). Wear et al. (2015) recently forecast much of the southern portions of the Southeast as being potentially planted in freeze-tolerant eucalyptus due to advances in eucalyptus breeding and its potential economic benefits relative to native species plantations. In the Western Gulf portion of the southeastern US, cold-tolerant eucalyptus species have been explored as short-rotation pulpwood feedstock for paper mills that require hardwood. Some mills in the region have recurring difficulties obtaining local raw material from bottomland hardwoods during wet periods, when harvesting operations are restricted to protect soil and water quality. During such periods, mills must import feedstock material at high costs (Blazier et al. 2010). Camden white gum plantations offer the opportunity to overcome these supply issues, providing a wider harvesting window because of their establishment on upland soils, usually occupied by pine plantations (Blazier et al. 2012). Establishment of non-native forest plantations is associated with concerns about potential impacts on native species diversity (Brockerhoff et al. 2009). Understory species comprise an important component of forest ecosystems; however, they are studied less frequently and intensively compared to tree species. Although representing only a small fraction of the forest ecosystem biomass, understory vegetation communities take part in many ecological processes, maintaining biodiversity, ecosystem stability, and sustainable productivity (Chastain et al. 2006). Understory communities play an important role in belowground processes as well, influencing decomposition rate and nutrient cycling (Nilsson and Wardle 2005, Hart and Chen 2006). The concept that biodiversity is a major determinant of ecosystem productivity and stability is well accepted (Tilman et al. 2014), and evidence suggests that richer and more diverse forest ecosystems (such as natural forests) are able to support higher levels of ecosystem functioning than species-poor ones (like forest plantations) (Gamfeldt et al. 2013). Studies conducted in an array of countries on the effects of eucalyptus plantations on understory plant diversity have had contrasting results. Lower species diversity in eucalyptus plantations relative to natural forests has been observed in numerous studies (Stallings 1991, Brockerhoff et al. 2013), considering both woody species (Tyynelä 2001, Lemenih et al. 2004, Stephens and Wagner 2007, Abiyu et al. 2011, Zhao et al. 2014) and understory species (Hayek et al. 2010, Zhang et al. 2014, Fork et al. 2015, Tang et al. 2015). Conversely, eucalyptus plantations were shown not to alter understory species richness when eucalyptus was established on barren lands (Shi et al. 2013) when compared with native woodland (Bone et al. 1997). Eucalyptus plantations showed higher (Michelsen et al. 1996, Lemenih et al. 2004) or similar (Geldenhuys 1997) understory and woody species richness than other non-native species plantations. Both forest species and herbaceous species typical of savannas were encountered in eucalyptus plantations established in the Republic of the Congo, suggesting that eucalyptus plantations acted as a connectivity corridor between natural forest patches or as a surrogate habitat for native species (Loumeto and Huttel 1997). A review conducted by Bremer and Farley (2010) emphasized the effect of plantations on biodiversity in relation to land-use change. Plantations of native tree species were richer in species than plantations of exotic tree species; management and structural factors rather than native/exotic dichotomy were identified as primary reasons for the differences in species richness between planation types. In particular, Stephens and Wagner (2007) suggested that native plantations are on the average more similar in habitat structure to natural forests than are exotic plantations and therefore support a more diverse flora and fauna. Supplanting plantations of native tree species with eucalyptus in the southeastern US may alter understory species diversity. Suppressing non-crop vegetation with herbicides is commonly practiced in pine plantation management in the southeastern US (Minogue et al. 1991, Allen et al. 2004). Herbicides are typically applied to the ubiquitous southern pine plantations of the region prior to planting and one year after planting. These herbicide applications initially decrease non-crop plant diversity, but diversity generally recovers as crop trees become established (Zutter and Miller 1998, Miller et al. 2003). Eucalyptus plantations are treated more frequently with herbicides in the initial years of plantation establishment than in southern pine plantations, and crop trees within eucalyptus plantations grow at a much higher rate than southern pine plantations. As such, the potential for understory species diversity to recover after herbicide applications cease within eucalyptus plantations may be lower than that of southern pine plantations. There are relatively few eucalyptus plantations in the southeastern United States, but an operational-scale eucalyptus experiment in the region provided a novel opportunity to explore influences of land use change from southern pine to eucalyptus plantations on understory diversity. In 2007, the MeadWestvaco company began an experiment in cultivating Camden white gum plantations in southwestern Louisiana and southeastern Texas (Blazier et al. 2010). From 2010 to 2016, around 8093 ha of land were procured to lease for 10-year rotations. In Louisiana, the eucalyptus plantations were predominantly on former slash pine (Pinus elliotti) plantations managed for the Rice Land and Lumber Company. In this southwestern Louisiana region, understory species richness and diversity were compared over three years between Camden white gum and slash pine plantations. Due to the fast growth of Camden white gum, two types of slash pine plantations (a. slash pine the same age of the Camden white gum, and b. slash pine comparable in height to the Camden white gum) surrounding the eucalyptus plantations were selected for comparison. Specifically, the following hypotheses were tested: (1) understory species communities of slash pine plantations are richer and more diverse than Camden white gum plantations; (2) understory species richness and diversity decrease more in Camden white gum plantations over time than in slash pine plantations; (3) overstory, canopy, and soil characteristics are ecological determinants of understory species richness and diversity. Understory species communities were compared between the three plantation types through rarefaction curves and two diversity indices (species richness and the Shannon index). Multivariate techniques were also used to understand the differences among the plantation types in terms of richness and diversity indices, overstory biometrics, leaf area index, total daily radiation under the canopy, and soil characteristics. Methods Site Description The study was conducted in forest plantations in the area surrounding the town of Merryville, Louisiana, USA (30°45′14″ N, 93°32′13″ W), shown in Figure 1. Topography of the stands was quite uniform and relatively flat. The mean elevation of all the sites was 47 m above sea level. Average monthly minimum and maximum air temperatures for the study region were 12° C and 26° C respectively, and average annual temperature was 19° C. Annual rainfall averaged 1412 mm. The climate of the site was defined as humid subtropical subtype Cfa (humid temperate with uniform rainfall) under the Köppen classification (Kottek et al. 2006). All climatic data were obtained through the National Oceanic and Atmospheric Administration website (http://www.noaa.gov/) (NOAA—National Oceanic and Atmospheric Administration 2016) for the Leesville station (8.5 m above sea level, 31°8′37″ N, 93°16′16″ W, about 45 km from the plantations) (Figure 2). Soils of the study area belonged to the Ultisol (73% of the sites) and Alfisol (27%) orders, and they were classified as Udults, Udalfs, Aqualfs, and Fluvents, according to USDA Soil Taxonomy (USDA 2002, Soil Survey Staff 2014). Soil textures of the study plantations were generally sandy and silty loam, and site indices of the sites for slash pine were similar (Table 1). Figure 1. Open in new tabDownload slide Locations of Eucalyptus bethamii (E13), and Pinus elliottii (S08, S13) plantations near Merryville, LA. Figure 1. Open in new tabDownload slide Locations of Eucalyptus bethamii (E13), and Pinus elliottii (S08, S13) plantations near Merryville, LA. Table 1. Area, site index for slash pine on a 50-year basis, and soil characteristics of plantations of slash pine planted in 2008 (S08) and 2013 (S13) and Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. Site index and soil characteristic information for the plantations were derived from the USDA Natural Resource Conservation Service Web Soil Survey (https://wesoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx). Site . Area (ha) . Site index (m) . Soil type & texture . Soil taxonomic class . E13-1 24.3 26.8 Beauregard—silt loam Plinthaquic Paleudult Kolin—silt loam Glossaquic Paleudalf Sugartown—very fine sandy loam Ultic Hapludalf E13-2 74.1 27.4 Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult E13-3 18.2 27.4 Kolin—silt loam Glossaquic Paleudalf Malbis—fine sandy loam Plinthic Paleudult E13-4 29.5 27.7 Boykin—loamy fine sand Arenic Paleudult Doucette—loamy fine sand Arenic Plinthic Paleudult Ruston—fine sandy loam Typic Paleudult E13-5 42.9 27.3 Bearhead-Merryville—fine sandy loam Typic Hapludult, Typic Glossaqualf Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult S08-1 31.2 27.4 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-2 35.2 28.0 Beauregard—silt loam Plinthaquic Paleudult S08-3 42.9 28.3 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-4 41.3 28.0 Sugartown—very fine sandy loam Plinthic Paleudult S08-5 36.4 27.4 Beauregard—silt loam Plinthaquic Paleudult Malbis—fine sandy loam Plinthic Paleudult S13-1 29.5 27.4 Blevins—very fine sandy loam Typic Paleudult Sugartown—very fine sandy loam Ultic Hapludalf S13-2 17.0 27.4 Sugartown—very fine sandy loam Ultic Hapludalf S13-3 48.6 27.4 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf Guyton—silt loam Typic Glossaqualf S13-4 38.4 29.9 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S13-5 33.2 27.4 Beauregard—silt loam Plinthaquic Paleudult Site . Area (ha) . Site index (m) . Soil type & texture . Soil taxonomic class . E13-1 24.3 26.8 Beauregard—silt loam Plinthaquic Paleudult Kolin—silt loam Glossaquic Paleudalf Sugartown—very fine sandy loam Ultic Hapludalf E13-2 74.1 27.4 Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult E13-3 18.2 27.4 Kolin—silt loam Glossaquic Paleudalf Malbis—fine sandy loam Plinthic Paleudult E13-4 29.5 27.7 Boykin—loamy fine sand Arenic Paleudult Doucette—loamy fine sand Arenic Plinthic Paleudult Ruston—fine sandy loam Typic Paleudult E13-5 42.9 27.3 Bearhead-Merryville—fine sandy loam Typic Hapludult, Typic Glossaqualf Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult S08-1 31.2 27.4 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-2 35.2 28.0 Beauregard—silt loam Plinthaquic Paleudult S08-3 42.9 28.3 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-4 41.3 28.0 Sugartown—very fine sandy loam Plinthic Paleudult S08-5 36.4 27.4 Beauregard—silt loam Plinthaquic Paleudult Malbis—fine sandy loam Plinthic Paleudult S13-1 29.5 27.4 Blevins—very fine sandy loam Typic Paleudult Sugartown—very fine sandy loam Ultic Hapludalf S13-2 17.0 27.4 Sugartown—very fine sandy loam Ultic Hapludalf S13-3 48.6 27.4 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf Guyton—silt loam Typic Glossaqualf S13-4 38.4 29.9 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S13-5 33.2 27.4 Beauregard—silt loam Plinthaquic Paleudult Open in new tab Table 1. Area, site index for slash pine on a 50-year basis, and soil characteristics of plantations of slash pine planted in 2008 (S08) and 2013 (S13) and Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. Site index and soil characteristic information for the plantations were derived from the USDA Natural Resource Conservation Service Web Soil Survey (https://wesoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx). Site . Area (ha) . Site index (m) . Soil type & texture . Soil taxonomic class . E13-1 24.3 26.8 Beauregard—silt loam Plinthaquic Paleudult Kolin—silt loam Glossaquic Paleudalf Sugartown—very fine sandy loam Ultic Hapludalf E13-2 74.1 27.4 Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult E13-3 18.2 27.4 Kolin—silt loam Glossaquic Paleudalf Malbis—fine sandy loam Plinthic Paleudult E13-4 29.5 27.7 Boykin—loamy fine sand Arenic Paleudult Doucette—loamy fine sand Arenic Plinthic Paleudult Ruston—fine sandy loam Typic Paleudult E13-5 42.9 27.3 Bearhead-Merryville—fine sandy loam Typic Hapludult, Typic Glossaqualf Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult S08-1 31.2 27.4 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-2 35.2 28.0 Beauregard—silt loam Plinthaquic Paleudult S08-3 42.9 28.3 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-4 41.3 28.0 Sugartown—very fine sandy loam Plinthic Paleudult S08-5 36.4 27.4 Beauregard—silt loam Plinthaquic Paleudult Malbis—fine sandy loam Plinthic Paleudult S13-1 29.5 27.4 Blevins—very fine sandy loam Typic Paleudult Sugartown—very fine sandy loam Ultic Hapludalf S13-2 17.0 27.4 Sugartown—very fine sandy loam Ultic Hapludalf S13-3 48.6 27.4 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf Guyton—silt loam Typic Glossaqualf S13-4 38.4 29.9 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S13-5 33.2 27.4 Beauregard—silt loam Plinthaquic Paleudult Site . Area (ha) . Site index (m) . Soil type & texture . Soil taxonomic class . E13-1 24.3 26.8 Beauregard—silt loam Plinthaquic Paleudult Kolin—silt loam Glossaquic Paleudalf Sugartown—very fine sandy loam Ultic Hapludalf E13-2 74.1 27.4 Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult E13-3 18.2 27.4 Kolin—silt loam Glossaquic Paleudalf Malbis—fine sandy loam Plinthic Paleudult E13-4 29.5 27.7 Boykin—loamy fine sand Arenic Paleudult Doucette—loamy fine sand Arenic Plinthic Paleudult Ruston—fine sandy loam Typic Paleudult E13-5 42.9 27.3 Bearhead-Merryville—fine sandy loam Typic Hapludult, Typic Glossaqualf Doucette—loamy fine sand Arenic Plinthic Paleudult Malbis—fine sandy loam Plinthic Paleudult S08-1 31.2 27.4 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-2 35.2 28.0 Beauregard—silt loam Plinthaquic Paleudult S08-3 42.9 28.3 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S08-4 41.3 28.0 Sugartown—very fine sandy loam Plinthic Paleudult S08-5 36.4 27.4 Beauregard—silt loam Plinthaquic Paleudult Malbis—fine sandy loam Plinthic Paleudult S13-1 29.5 27.4 Blevins—very fine sandy loam Typic Paleudult Sugartown—very fine sandy loam Ultic Hapludalf S13-2 17.0 27.4 Sugartown—very fine sandy loam Ultic Hapludalf S13-3 48.6 27.4 Beauregard—silt loam Plinthaquic Paleudult Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf Guyton—silt loam Typic Glossaqualf S13-4 38.4 29.9 Caddo-Messer—silt loam Typic Glossaqualf, Oxyaquic Glossudalf S13-5 33.2 27.4 Beauregard—silt loam Plinthaquic Paleudult Open in new tab Figure 2. Open in new tabDownload slide Annual temperature and precipitation comparison with 30-year monthly average for the National Oceanic and Atmospheric Administration Leesville station, LA, approximately 45 km from Merryville, LA. The figures show three years of study: (a) 2014, (b) 2015, and (c) 2016. Figure 2. Open in new tabDownload slide Annual temperature and precipitation comparison with 30-year monthly average for the National Oceanic and Atmospheric Administration Leesville station, LA, approximately 45 km from Merryville, LA. The figures show three years of study: (a) 2014, (b) 2015, and (c) 2016. Precipitation in 2014 was high relative to the 30-year (long-term) average in the summer months, and drier in the winter period (Figure 2). In 2015, precipitation was higher than the long-term average in the spring; lower in late summer and early fall, and higher in late fall. Precipitation patterns of 2016 were relatively wet in spring through summer (with the exception of July). Temperature seemed to deviate less from the long-term average than precipitation. In 2014, temperatures were similar to those of the 30-year average, with the greatest deviation in January. Temperatures in 2015 were often slightly above the 30-year average. In 2016, temperatures continued to be slightly above the long-term average for the region. The study locations were within West Gulf Coastal Plain Wet Longleaf Pine Savanna and Flatwoods ecotypes (Holcomb et al. 2015). These ecotypes are floristically-rich, herb-dominated wetlands that are naturally sparsely stocked with longleaf pine (Pinus palustris). More than 140 species of vascular plants have been observed in a 1000-m2 area, and more than 40 species m-2 have been recorded in many longleaf pine communities, including a large number of endemic species (Peet and Allard 1993). Pine savannas are characterized by high fluctuations of water tables, ranging from surface saturation/shallow flooding in late fall/winter/early spring to growing season drought. Soils are generally acidic, nutrient-poor, fine sandy loams and silt loams low in organic matter. Fires play a major role in controlling species and community structure. Without frequent fire, shrubs and trees will become predominant in these ecotypes, and they eventually exclude the herbaceous flora (Holcomb et al. 2015). Moreover, the establishment of pulp mills during the 1950s created high demand for smaller trees, which accelerated the conversion of naturally-regenerated longleaf pine forests into loblolly pine and slash pine plantations, resulting in a continuous decline of the area occupied by longleaf pine ecosystems (Brockway et al. 2005). All plantations of this study were on land owned since 1895 by the Rice Land and Lumber Company (RLLC). Loblolly and slash pine were managed by RLLC in the studied region, but since the 1970s 99% of the land owned by RLLC was planted in slash pine and managed on a 50–60-year rotation to maximize timber production and income, with the rest of the land planted in longleaf pine (Messick 2016). Beginning at the first thinning (approximately age 12–15 years), a three-year burning cycle was conducted within the slash pine plantations. All slash pine plantations selected for this study received pre-planting broadcast herbicide (imazapyr, sulfometuron methyl, metsulfuron methyl), burning of logging debris, and bedding prior to planting. Beginning in 2007, MeadWestvaco Company began an operational-scale experiment in cultivating Camden white gum in the studied region. All Camden white gum plantations in this study were also on land owned by RLLC; the plantations were established on recently harvested slash pine plantations managed as described above. For Camden white gum silviculture in the area (Blazier et al. 2015), management operations consisted of mechanical site preparation (shearing, raking and piling of standing trees and logging debris; bedding and subsoiling to ameliorate root-restrictive soil textures), frequent herbicide applications in the initial years of the plantation, and fertilization (Table 2). Those silvicultural operations were conducted on the Camden white gum sites in this study. Eucalyptus sites selected for this study were considered clear enough of non-crop vegetation to cease all herbicide applications after the first year, so no herbicides were applied to the plantations during the study. At mid-rotation (age 3), all eucalyptus plantations (but not slash pine plantations) in this study were operationally fertilized via aerial broadcast application of urea (57 kg ha-1) and diammonium phosphate (57 kg ha-1). Average stand density of the Camden white gum plantations selected for the study was 1688 trees ha-1, which was similar to the 1668 trees ha-1 of the slash pine plantations included in this study. Table 2. Management activities of Camden white gum plantations in southwestern Louisiana. Adapted from Blazier et al. (2015). Management Activity . Timing Relative to Planting . Broadcast site preparation herbicide (glyphosate) 4–6 months PrP Mechanical site preparation (shear, pile, rake, bedding/subsoiling) 2–8 months PrP Banded site preparation herbicide 1–2 months PrP Banded P fertilization 2 months PrP to 4 months PoP Inter-bed pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 1–3 months PoP Banded pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 2–5 months PoP Banded or hand NP fertilization 4–6 months PoP Banded or DS post-emergent herbicide (clopyralid, fluazifop) 6–8 months PoP Early-summer DS post-emergent herbicide (glyphosate) 7–8 months PoP Late-summer DS post-emergent herbicide (glyphosate) 8–10 months PoP Banded or hand NPK fertilization 9–10 months PoP Broadcast pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 13–15 months PoP Banded or hand NPK fertilization 14–16 months PoP Aerial broadcast N fertilization 3–4 years PoP Management Activity . Timing Relative to Planting . Broadcast site preparation herbicide (glyphosate) 4–6 months PrP Mechanical site preparation (shear, pile, rake, bedding/subsoiling) 2–8 months PrP Banded site preparation herbicide 1–2 months PrP Banded P fertilization 2 months PrP to 4 months PoP Inter-bed pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 1–3 months PoP Banded pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 2–5 months PoP Banded or hand NP fertilization 4–6 months PoP Banded or DS post-emergent herbicide (clopyralid, fluazifop) 6–8 months PoP Early-summer DS post-emergent herbicide (glyphosate) 7–8 months PoP Late-summer DS post-emergent herbicide (glyphosate) 8–10 months PoP Banded or hand NPK fertilization 9–10 months PoP Broadcast pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 13–15 months PoP Banded or hand NPK fertilization 14–16 months PoP Aerial broadcast N fertilization 3–4 years PoP DS = directed spray, N = nitrogen, P = phosphorus, K = potassium, PrP = pre-planting, PoP = post-planting Tree planting is typically conducted in fall (October-November). Open in new tab Table 2. Management activities of Camden white gum plantations in southwestern Louisiana. Adapted from Blazier et al. (2015). Management Activity . Timing Relative to Planting . Broadcast site preparation herbicide (glyphosate) 4–6 months PrP Mechanical site preparation (shear, pile, rake, bedding/subsoiling) 2–8 months PrP Banded site preparation herbicide 1–2 months PrP Banded P fertilization 2 months PrP to 4 months PoP Inter-bed pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 1–3 months PoP Banded pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 2–5 months PoP Banded or hand NP fertilization 4–6 months PoP Banded or DS post-emergent herbicide (clopyralid, fluazifop) 6–8 months PoP Early-summer DS post-emergent herbicide (glyphosate) 7–8 months PoP Late-summer DS post-emergent herbicide (glyphosate) 8–10 months PoP Banded or hand NPK fertilization 9–10 months PoP Broadcast pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 13–15 months PoP Banded or hand NPK fertilization 14–16 months PoP Aerial broadcast N fertilization 3–4 years PoP Management Activity . Timing Relative to Planting . Broadcast site preparation herbicide (glyphosate) 4–6 months PrP Mechanical site preparation (shear, pile, rake, bedding/subsoiling) 2–8 months PrP Banded site preparation herbicide 1–2 months PrP Banded P fertilization 2 months PrP to 4 months PoP Inter-bed pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 1–3 months PoP Banded pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 2–5 months PoP Banded or hand NP fertilization 4–6 months PoP Banded or DS post-emergent herbicide (clopyralid, fluazifop) 6–8 months PoP Early-summer DS post-emergent herbicide (glyphosate) 7–8 months PoP Late-summer DS post-emergent herbicide (glyphosate) 8–10 months PoP Banded or hand NPK fertilization 9–10 months PoP Broadcast pre-emergent herbicide (oxyfluorfen or sulfometuron methyl) 13–15 months PoP Banded or hand NPK fertilization 14–16 months PoP Aerial broadcast N fertilization 3–4 years PoP DS = directed spray, N = nitrogen, P = phosphorus, K = potassium, PrP = pre-planting, PoP = post-planting Tree planting is typically conducted in fall (October-November). Open in new tab Experimental Design We selected three different plantation types: (1) slash pine plantation established in 2008 (S08); (2) slash pine plantation established in 2013 (S13); (3) and Camden white gum plantation established in 2013 (E13). For each plantation type, we identified five study stands (15 study sites in total) from among those available on lands owned by cooperating landowners. Slash pine plantations established in 2013 and 2008 were similar in age and height (at the beginning of the study), respectively, to the Camden white gum plantations. At each study site, we established four 6 m × 50 m plots along a transect in the center of the stand with plots separated from each other and plantation edges by > 50 m. This protocol was adapted from forest inventory and analysis, and plant ecology laboratory methods (Curtis 1959, Beals and Cottam 1960, Johnson et al. 2008). Each transect was designed to start at a random point and to stretch along a random azimuth that was restricted to keep the transect within the stand (Messick 2016). To reduce edge effect, transects were buffered by 50 m from the stand edges (Jensen and Finck 2004, Kaiser and Lindell 2007). Vegetation Surveys The quadrat method (Kent and Coker 1992) was used to conduct understory vegetation surveys within the 6 m × 50 m plots. Ten vegetation sampling points each separated by 5 m were established along the center of each plot. A 1 m × 1 m frame was placed at each of the 10 sampling points per plot, and species present were recorded (Gotelli and Colwell 2010). This method has been employed in studies of understory species richness and diversity of Eucalyptus globulus plantations in Portugal (Carneiro et al. 2007, 2008). Two floristic surveys (one in spring and one in fall) were conducted each year from 2014 to 2016, and all the species were identified and recorded in each quadrat. These surveys began in spring 2014 because all herbicide treatments within the Camden white gum plantations had ceased in late fall 2013 consistent with operational silvicultural protocols for these plantations, allowing understory vegetation to become established in those plantations. Species were also classified according their growth form and life cycle duration as listed in the USDA PLANTS Database (https://plants.usda.gov/). Leaf Area Index and Total Daily Radiation under Canopy Light availability and intensity have critical effects on understory vegetation composition and abundance, influencing temperature and humidity of the site (Parrotta 1995, Battles et al. 2001, Lemenih et al. 2004, Yirdaw and Luukkanen 2004, Bartemucci et al. 2006, Barbier et al. 2008). Light radiation transmittance depends on the overstory characteristics, which can be synthetically described using leaf area index (Barbier et al. 2008). We measured leaf area index (LAI) (Walter 2009) using a hemispherical (fisheye) lens placed under the canopy (Anderson 1964, Jonckheere et al. 2004), with a 180° field of view, such that all sky directions were simultaneously visible (Hill 1924, Rich 1990). Leaf area index was then mathematically derived from inversion of gap fraction (Walter 2009), with LAI being proportional to the natural logarithm of gap fraction (Chianucci et al. 2015). WinSCANOPY software (Regent Instruments, Ste-Foy, Quebec) was used to analyze hemispherical pictures and calculate LAI and total (direct + diffuse) daily radiation under the canopy. Hemispherical photos were taken in August-September 2016 (a period of seasonal maximum leaf area) using a Nikon Coolpix 4500 camera equipped with Nikon FC-E8 fish-eye converter lens. The camera was placed on a levelled tripod at 147 cm above the ground. Images were collected at maximum resolution (3,871,488 pixels total), pointing the levelled camera directly upwards at zenith. Five pictures per plot were taken in E13 and S08 stands during early morning or late afternoon to avoid direct sunlight. The picture sampling locations corresponded to five of the sampling locations used for vegetation sampling. In S13 stands, one picture per plot (at the vegetation sampling point at the center of the plot) was considered sufficient due to their open-canopy conditions (which fosters direct sunlight in images until a narrow timeframe in early morning and late afternoon). Overstory Stand densities within each plot, tree heights, and diameters were measured three times: February 2015, January 2016, and December 2016. Due to frequent rain and labor availability, part of the 2015 measures were taken in April 2015. Diameter at breast height (dbh) was measured on all trees with height > 1.3 m and diameter > 1.2 cm. Diameter at breast height measurements were used to calculate basal area (m2 ha-1). Total tree height was measured using a height pole for S13 plots and a Haglof Vertex IV hypsometer (Haglof Inc., Madison, MS, USA) for S08 and E13 plots. Soil Sampling and Analysis Differences in understory diversity and composition are often a consequence of differences in topsoil (Barbier et al. 2008). Five composite soil samples per plot (2.5-cm diameter cores taken to a 30-cm depth) were collected within 50 cm from (but not inside) vegetation sampling quadrats (numbers 1, 3, 5, 7, and 9) during August 2016. The soil subsamples were pooled into one composite sample per plot, yielding four subsamples per site and five replicates per plantation type. Soil samples were immediately placed on ice packs and sent to the laboratory in a cooler. All soil samples were oven-dried (40° C), passed through a 2-mm sieve, and sent to the laboratory for chemical analysis, including pH, Mehlich 3 extractable nutrients (P, K, Ca, Mg, Na, S, Cu, and Zn), total C, and total N (Allen and Schlesinger 2004, Blazier et al. 2005, Van der Heijde et al. 2008, Zhao et al. 2014). Species Richness, Diversity Indices, and Rarefaction Curves Understory vegetation data collected during the vegetation surveys were used to compute the community diversity indices of species richness (S) and the Shannon index (H’) (Magurran 2004, Jost 2006, 2007, Wang et al. 2011). Although species richness represents just the number of species without any information about abundance, the Shannon index considers both abundance and evenness of species present in the community, usually ranging from 1.3 to 3.5, with higher values indicating higher diversity (Margalef 1972, Magurran 2004). Understory species richness was calculated on a plot basis, adding together all the species recorded in the 10 sampling quadrats within each plot. An alternative way to estimate species richness is to construct species accumulation curves, which defines the cumulative number of species discovered in a community as function of sampling effort, defined as numbers of collected individuals or the cumulative number of samples (Colwell and Coddington 1994). Species-area curves are widely used in botanical research (Magurran 2004); the x-axis is the number of samples and the y-axis is the accumulated number of species (Gotelli and Colwell 2010). Statistical Analysis: Generalized Linear Mixed Models, Correlation Analysis, and Multiple Regression Analysis Analyses of variance (ANOVA) at α = 0.05 were conducted through generalized linear mixed models using the GLIMMIX procedure in SAS 9.4 (SAS Institute Inc., 2002–03) to test for differences in species richness, Shannon index, overstory metrics, LAI, total daily radiation under the canopy, and soil characteristics. Year, plantation type, and year × plantation type interaction were used as fixed effects. When ANOVA revealed significant effects, means separations were performed using Tukey’s honest significant difference test. Relationships among parameters were explored with correlation and regression analyses. We determined Pearson’s correlation coefficients (r) to explore possible relationships between variables related to forest structural conditions (LAI, daily total radiation under canopy, tree dbh, height, basal area), plant community metrics (species richness and Shannon index), and soil characteristics (pH, C, N, etc.). Multiple linear regression analysis was performed at α = 0.05 to characterize the influence of overstory and soil parameters on understory species richness and diversity. The stepwise method of the REG procedure of SAS 9.4 was used for this analysis, using 0.15 and 0.05 as significance levels for entry and staying in the model, respectively. Species richness and Shannon index were dependent variables for the regression equations. Overstory metrics, LAI, total daily radiation under canopy, pH, and soil nutrient concentrations were independent (explanatory) variables in the models. Multicollinearity of independent variables was assessed using variance inflation factor, eigensystem analysis of correlation matrix, and condition index. Statistical Analysis: Canonical Discriminant Analysis To further explore the relationships between understory, overstory, and soil variables during 2016, stepwise discriminant analysis (SDA)—STEPDISC procedure in SAS—was used to reduce the dimension of the dataset. This analysis identifies the variables that contribute most to the discriminatory power of the model, as measured by Wilk’s lambda (Huberty and Olejnik 2006). Contrary to ordination techniques, which aim to represent sample/species relationships as accurately as possible in a low-dimensional space and possibly extract gradients of variation, discriminant analysis allows for finding a linear combination of variables that characterizes or separates two or more classes of objects or groups. We used discriminant analysis in this study because we were interested in describing and testing possible differences among groups, describing also the inter-group variance structure. A significance threshold of α = 0.05 was used for variables to enter and be retained in the discriminant function, and the corresponding partial R2 values were listed. Partial R2 characterizes the amount of variation accounted for by that variable in discriminating between groups; the larger the partial R2 value, the greater the contribution of the respective variable to discrimination between groups. The reduced dataset was then used in a discriminant canonical analysis (DCA), conducted using the candisc package (Friendly and Fox 2017) in R version 3.5.1 (R Core Team 2018), to derive canonical functions representing linear combinations of the variables selected through DCA that best summarize the differences among plantations. Results Families, Species, Life Cycle, and Form of Understory Vegetation The number of families and species and the life cycle and form of understory vegetation observed throughout this study are reported in Table 3. Overall, the Asteraceae contained the highest number of species (28), followed by the Fabaceae (8) and Poaceae (7). Common species present in all plantation types were little blue stem (Schizachyrium scoparium), southern dewberry (Rubus trivialis), cat greenbrier (Smilax glauca), swamp sunflower (Helianthus angustifolius), and several species of the genera Eupatorium, Solidago, Dichanthelium, Rhynchospora, Diodia and Rhexia. Information about families, species, incidence, life form, and duration observed is reported in Supplemental Material. Table 3. Number of families, species, life cycle (%), and form (%) of understory vegetation in slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. Variable . Type . S08 . . . S13 . . . E13 . . . . . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . Families - 30 32 26 34 37 35 34 34 23 Species - 53 56 40 74 85 66 72 75 52 Cycle Annual 1.9 7.1 5.0 3.8 10.5 6.6 8.3 5.3 11.5 Biennial 0.0 0.0 0.0 1.9 0.0 1.6 1.4 1.3 0.0 Annual/biennial 1.9 0.0 7.5 5.7 2.3 6.6 5.6 5.3 9.6 Perennial 96.2 92.9 87.5 88.7 87.2 85.3 84.7 88.0 78.9 Form Graminoid 13.2 16.1 12.5 18.9 17.4 13.1 13.9 12.0 9.6 Forb/herb 50.9 44.6 45.0 56.8 57.0 59.0 55.6 56.0 61.5 Shrub 17.0 19.6 20.0 14.9 16.3 14.8 15.3 16.0 15.4 Tree 5.7 7.1 5.0 1.4 2.3 6.6 5.6 5.3 0.0 Vine 13.2 12.5 17.5 8.1 7.0 6.6 9.7 10.7 13.5 Variable . Type . S08 . . . S13 . . . E13 . . . . . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . Families - 30 32 26 34 37 35 34 34 23 Species - 53 56 40 74 85 66 72 75 52 Cycle Annual 1.9 7.1 5.0 3.8 10.5 6.6 8.3 5.3 11.5 Biennial 0.0 0.0 0.0 1.9 0.0 1.6 1.4 1.3 0.0 Annual/biennial 1.9 0.0 7.5 5.7 2.3 6.6 5.6 5.3 9.6 Perennial 96.2 92.9 87.5 88.7 87.2 85.3 84.7 88.0 78.9 Form Graminoid 13.2 16.1 12.5 18.9 17.4 13.1 13.9 12.0 9.6 Forb/herb 50.9 44.6 45.0 56.8 57.0 59.0 55.6 56.0 61.5 Shrub 17.0 19.6 20.0 14.9 16.3 14.8 15.3 16.0 15.4 Tree 5.7 7.1 5.0 1.4 2.3 6.6 5.6 5.3 0.0 Vine 13.2 12.5 17.5 8.1 7.0 6.6 9.7 10.7 13.5 Open in new tab Table 3. Number of families, species, life cycle (%), and form (%) of understory vegetation in slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. Variable . Type . S08 . . . S13 . . . E13 . . . . . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . Families - 30 32 26 34 37 35 34 34 23 Species - 53 56 40 74 85 66 72 75 52 Cycle Annual 1.9 7.1 5.0 3.8 10.5 6.6 8.3 5.3 11.5 Biennial 0.0 0.0 0.0 1.9 0.0 1.6 1.4 1.3 0.0 Annual/biennial 1.9 0.0 7.5 5.7 2.3 6.6 5.6 5.3 9.6 Perennial 96.2 92.9 87.5 88.7 87.2 85.3 84.7 88.0 78.9 Form Graminoid 13.2 16.1 12.5 18.9 17.4 13.1 13.9 12.0 9.6 Forb/herb 50.9 44.6 45.0 56.8 57.0 59.0 55.6 56.0 61.5 Shrub 17.0 19.6 20.0 14.9 16.3 14.8 15.3 16.0 15.4 Tree 5.7 7.1 5.0 1.4 2.3 6.6 5.6 5.3 0.0 Vine 13.2 12.5 17.5 8.1 7.0 6.6 9.7 10.7 13.5 Variable . Type . S08 . . . S13 . . . E13 . . . . . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . 2014 . 2015 . 2016 . Families - 30 32 26 34 37 35 34 34 23 Species - 53 56 40 74 85 66 72 75 52 Cycle Annual 1.9 7.1 5.0 3.8 10.5 6.6 8.3 5.3 11.5 Biennial 0.0 0.0 0.0 1.9 0.0 1.6 1.4 1.3 0.0 Annual/biennial 1.9 0.0 7.5 5.7 2.3 6.6 5.6 5.3 9.6 Perennial 96.2 92.9 87.5 88.7 87.2 85.3 84.7 88.0 78.9 Form Graminoid 13.2 16.1 12.5 18.9 17.4 13.1 13.9 12.0 9.6 Forb/herb 50.9 44.6 45.0 56.8 57.0 59.0 55.6 56.0 61.5 Shrub 17.0 19.6 20.0 14.9 16.3 14.8 15.3 16.0 15.4 Tree 5.7 7.1 5.0 1.4 2.3 6.6 5.6 5.3 0.0 Vine 13.2 12.5 17.5 8.1 7.0 6.6 9.7 10.7 13.5 Open in new tab The predominant form was forb/herb for all the plantation types, while trees and vines were more common in S08 and E13 than in S13, except for 2016 when S13 showed the highest number of tree species (Table 3). Shrubs and graminoids were present in all the plantation types. Perennial species were slightly more frequent in S08 than in the other plantation types, whereas annual and annual/biennial species had higher proportions in S13 and E13. Biennial species were not found in S08 during the three years, and they were not found in S13 and E13 during 2015 and 2016, respectively. Rarefaction Curves Rarefaction curves were different among and within plantations types in all years of the study. During 2014, understory species richness was greater in E13 (72) and S13 (74) than in S08 (53), as shown in Figure 3a. In 2015 and 2016, species richness was highest in S13 (85 and 66, respectively), intermediate in E13 (75 and 52), and lowest in S08 (56 and 40) (Figure 3b and c). Within each plantation type, species richness did not change from 2014 to 2015, whereas richness declined from 2015 to 2016 in E13 and S08, but not in S13 (Figure 4). Figure 3. Open in new tabDownload slide Species accumulation curves for slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana as observed in 2014 (a), 2015 (b), and 2016 (c). Dotted lines represent 95% confidence intervals, overlapping confidence intervals denote non-significant difference, and different letters indicate significant difference (α = 0.05). Figure 3. Open in new tabDownload slide Species accumulation curves for slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana as observed in 2014 (a), 2015 (b), and 2016 (c). Dotted lines represent 95% confidence intervals, overlapping confidence intervals denote non-significant difference, and different letters indicate significant difference (α = 0.05). Figure 4. Open in new tabDownload slide Species accumulation curves in 2014, 2015, and 2016 for (a) Camden white gum plantations planted in 2013 (E13), (b) slash pine plantations planted in 2008 (S08), and (c) slash pine plantations planted in 2013 (S13) plantations. Dotted lines represent 95% confidence intervals, overlapping confidence intervals denote non-significant difference, and different letters indicate significant difference (α = 0.05). Figure 4. Open in new tabDownload slide Species accumulation curves in 2014, 2015, and 2016 for (a) Camden white gum plantations planted in 2013 (E13), (b) slash pine plantations planted in 2008 (S08), and (c) slash pine plantations planted in 2013 (S13) plantations. Dotted lines represent 95% confidence intervals, overlapping confidence intervals denote non-significant difference, and different letters indicate significant difference (α = 0.05). Species Richness and Diversity Indices Understory species richness and Shannon index were significantly different among the three plantation types and among years (Table 4 and Figure 5). Both species richness and Shannon index were greatest in S13, intermediate in E13, and lowest in S08 during 2014 and 2015. In 2015, they were similar in S13 and E13, but different from S08. Within plantation types, species richness and Shannon index were similar in 2014 and 2015 then declined in 2016. Table 4. Test of fixed effects for species richness and Shannon index (H’). Main effects consisted of plantation type (plant), year (yr), and their interaction (plant*yr) (n = 180). Effect . NDF . DDF . Richness . . H’ . . . . . F . P-value . F . P-value . plant 2 36 34.61 <0.0001 44.22 <0.0001 yr 2 36 46.15 <0.0001 49.07 <0.0001 plant*yr 4 36 0.56 0.6921 0.83 0.5173 Effect . NDF . DDF . Richness . . H’ . . . . . F . P-value . F . P-value . plant 2 36 34.61 <0.0001 44.22 <0.0001 yr 2 36 46.15 <0.0001 49.07 <0.0001 plant*yr 4 36 0.56 0.6921 0.83 0.5173 NDF = numerator degrees of freedom, DDF = denominator degrees of freedom. Open in new tab Table 4. Test of fixed effects for species richness and Shannon index (H’). Main effects consisted of plantation type (plant), year (yr), and their interaction (plant*yr) (n = 180). Effect . NDF . DDF . Richness . . H’ . . . . . F . P-value . F . P-value . plant 2 36 34.61 <0.0001 44.22 <0.0001 yr 2 36 46.15 <0.0001 49.07 <0.0001 plant*yr 4 36 0.56 0.6921 0.83 0.5173 Effect . NDF . DDF . Richness . . H’ . . . . . F . P-value . F . P-value . plant 2 36 34.61 <0.0001 44.22 <0.0001 yr 2 36 46.15 <0.0001 49.07 <0.0001 plant*yr 4 36 0.56 0.6921 0.83 0.5173 NDF = numerator degrees of freedom, DDF = denominator degrees of freedom. Open in new tab Figure 5. Open in new tabDownload slide Mean and standard error of the mean for species richness (a) and Shannon index (b) in slash pine plantations planted in 2008 (S08) and 2013 (S13), and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana (n = 60 plots). Different capital letters indicate significant difference (p < 0.05) between plantations within the same year, whereas different lowercase letters indicate significant difference between years within the same plantation type. Figure 5. Open in new tabDownload slide Mean and standard error of the mean for species richness (a) and Shannon index (b) in slash pine plantations planted in 2008 (S08) and 2013 (S13), and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana (n = 60 plots). Different capital letters indicate significant difference (p < 0.05) between plantations within the same year, whereas different lowercase letters indicate significant difference between years within the same plantation type. Overstory, Canopy, and Soil Characteristics Diameter at breast height was significantly greater in S08 than E13 plantations over the three years (Tables 5 and 6), and it increased significantly over time in both plantation types. Tree heights for S08 plantations were greater than those of E13 plantations in the first and second years of the study, but they were greater in E13 than for S08 in the third year. Height increased within plantations each year. Basal area of S08 plantations was significantly greater than for E13 plantations over the three years, and it significantly increased from 2014 to 2016 for both plantation types. Leaf area index and total daily radiation under the canopy both were significantly different among plantation types (S08 > E13 > S13 for LAI and S13 > E13 > S08 for radiation) in 2016 (Figure 6). Table 5. Mean and standard error of the mean (SEM) for dbh (cm), height (m), and basal area (m2 ha-1) for slash pine plantations planted in 2008 (S08) and 2013 (S13) as well for Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. For each variable, different capital letters within a row indicate significant difference (p < 0.05) between plantations within the same year, whereas different lowercase letters indicate significant difference between years within the same plantation type. Variable . Measurement . S08 . . . E13 . . . S13 . . . . . Mean . SEM . Obs. . Mean . SEM . Obs. . Mean . SEM . Obs. . dbh cm Feb/Apr 2015 8.69 Ab 0.08 965 4.10 Bc 0.06 1013 - - - Jan 2016 9.33 Aa 0.09 1001 5.01Bb 0.08 1082 1.93 0.05 844 Dec 2016 10.31 Aa 0.10 968 7.31Ba 0.11 1023 3.92 0.05 849 Feb/Apr 2015 6.14 Ac 0.04 965 4.68 Bb 0.05 1013 0.10 0.001 813 Height m Jan 2016 7.26 Ab 0.05 1001 5.45 Bb 0.07 1082 2.23 0.04 844 Dec 2016 8.93 Ba 0.05 968 9.79 Aa 0.12 1023 2.88 0.03 849 Basal area m2 ha-1 Feb/Apr 2015 10.35 Ac 1.10 20 2.69 Bc 0.25 20 - - - Jan 2016 12.36 Ab 1.19 20 4.63 Bb 0.46 20 0.49 0.08 20 Dec 2016 14.53 Aa 1.44 20 7.80 Aa 0.69 20 1.80 0.22 20 Variable . Measurement . S08 . . . E13 . . . S13 . . . . . Mean . SEM . Obs. . Mean . SEM . Obs. . Mean . SEM . Obs. . dbh cm Feb/Apr 2015 8.69 Ab 0.08 965 4.10 Bc 0.06 1013 - - - Jan 2016 9.33 Aa 0.09 1001 5.01Bb 0.08 1082 1.93 0.05 844 Dec 2016 10.31 Aa 0.10 968 7.31Ba 0.11 1023 3.92 0.05 849 Feb/Apr 2015 6.14 Ac 0.04 965 4.68 Bb 0.05 1013 0.10 0.001 813 Height m Jan 2016 7.26 Ab 0.05 1001 5.45 Bb 0.07 1082 2.23 0.04 844 Dec 2016 8.93 Ba 0.05 968 9.79 Aa 0.12 1023 2.88 0.03 849 Basal area m2 ha-1 Feb/Apr 2015 10.35 Ac 1.10 20 2.69 Bc 0.25 20 - - - Jan 2016 12.36 Ab 1.19 20 4.63 Bb 0.46 20 0.49 0.08 20 Dec 2016 14.53 Aa 1.44 20 7.80 Aa 0.69 20 1.80 0.22 20 No dbh and basal area data were available for S13 during Feb-Apr 2015 because no trees had reached dbh at that time. S13 data related to dbh (cm), height (m), and basal (m2 ha-1) area were not included in the statistical analysis because not all trees in this plantation type had reached dbh within this study. Open in new tab Table 5. Mean and standard error of the mean (SEM) for dbh (cm), height (m), and basal area (m2 ha-1) for slash pine plantations planted in 2008 (S08) and 2013 (S13) as well for Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. For each variable, different capital letters within a row indicate significant difference (p < 0.05) between plantations within the same year, whereas different lowercase letters indicate significant difference between years within the same plantation type. Variable . Measurement . S08 . . . E13 . . . S13 . . . . . Mean . SEM . Obs. . Mean . SEM . Obs. . Mean . SEM . Obs. . dbh cm Feb/Apr 2015 8.69 Ab 0.08 965 4.10 Bc 0.06 1013 - - - Jan 2016 9.33 Aa 0.09 1001 5.01Bb 0.08 1082 1.93 0.05 844 Dec 2016 10.31 Aa 0.10 968 7.31Ba 0.11 1023 3.92 0.05 849 Feb/Apr 2015 6.14 Ac 0.04 965 4.68 Bb 0.05 1013 0.10 0.001 813 Height m Jan 2016 7.26 Ab 0.05 1001 5.45 Bb 0.07 1082 2.23 0.04 844 Dec 2016 8.93 Ba 0.05 968 9.79 Aa 0.12 1023 2.88 0.03 849 Basal area m2 ha-1 Feb/Apr 2015 10.35 Ac 1.10 20 2.69 Bc 0.25 20 - - - Jan 2016 12.36 Ab 1.19 20 4.63 Bb 0.46 20 0.49 0.08 20 Dec 2016 14.53 Aa 1.44 20 7.80 Aa 0.69 20 1.80 0.22 20 Variable . Measurement . S08 . . . E13 . . . S13 . . . . . Mean . SEM . Obs. . Mean . SEM . Obs. . Mean . SEM . Obs. . dbh cm Feb/Apr 2015 8.69 Ab 0.08 965 4.10 Bc 0.06 1013 - - - Jan 2016 9.33 Aa 0.09 1001 5.01Bb 0.08 1082 1.93 0.05 844 Dec 2016 10.31 Aa 0.10 968 7.31Ba 0.11 1023 3.92 0.05 849 Feb/Apr 2015 6.14 Ac 0.04 965 4.68 Bb 0.05 1013 0.10 0.001 813 Height m Jan 2016 7.26 Ab 0.05 1001 5.45 Bb 0.07 1082 2.23 0.04 844 Dec 2016 8.93 Ba 0.05 968 9.79 Aa 0.12 1023 2.88 0.03 849 Basal area m2 ha-1 Feb/Apr 2015 10.35 Ac 1.10 20 2.69 Bc 0.25 20 - - - Jan 2016 12.36 Ab 1.19 20 4.63 Bb 0.46 20 0.49 0.08 20 Dec 2016 14.53 Aa 1.44 20 7.80 Aa 0.69 20 1.80 0.22 20 No dbh and basal area data were available for S13 during Feb-Apr 2015 because no trees had reached dbh at that time. S13 data related to dbh (cm), height (m), and basal (m2 ha-1) area were not included in the statistical analysis because not all trees in this plantation type had reached dbh within this study. Open in new tab Table 6. Test of fixed effects for dbh, height, and basal area. Main effects consisted of plantation type (plant), year (yr), and their interaction (plant*yr) (n = 120). Means followed by different letters within each row indicate statistically significant difference (p-value < 0.05). Effect . NDF . DDF . dbh . . Height . . BA . . . . . F-statitstic . p-value . F-statitstic . p-value . F-statitstic . p-value . plant 1 24 110.96 <0.0001 3.59 0.0704 46.12 <0.0001 yr 2 24 92.69 <0.0001 149.67 <0.0001 78.23 <0.0001 plant*yr 2 24 13.01 0.0001 221.24 <0.0001 1.09 0.3511 Effect . NDF . DDF . dbh . . Height . . BA . . . . . F-statitstic . p-value . F-statitstic . p-value . F-statitstic . p-value . plant 1 24 110.96 <0.0001 3.59 0.0704 46.12 <0.0001 yr 2 24 92.69 <0.0001 149.67 <0.0001 78.23 <0.0001 plant*yr 2 24 13.01 0.0001 221.24 <0.0001 1.09 0.3511 NDF = numerator degrees of freedom, DDF = denominator degrees of freedom. Open in new tab Table 6. Test of fixed effects for dbh, height, and basal area. Main effects consisted of plantation type (plant), year (yr), and their interaction (plant*yr) (n = 120). Means followed by different letters within each row indicate statistically significant difference (p-value < 0.05). Effect . NDF . DDF . dbh . . Height . . BA . . . . . F-statitstic . p-value . F-statitstic . p-value . F-statitstic . p-value . plant 1 24 110.96 <0.0001 3.59 0.0704 46.12 <0.0001 yr 2 24 92.69 <0.0001 149.67 <0.0001 78.23 <0.0001 plant*yr 2 24 13.01 0.0001 221.24 <0.0001 1.09 0.3511 Effect . NDF . DDF . dbh . . Height . . BA . . . . . F-statitstic . p-value . F-statitstic . p-value . F-statitstic . p-value . plant 1 24 110.96 <0.0001 3.59 0.0704 46.12 <0.0001 yr 2 24 92.69 <0.0001 149.67 <0.0001 78.23 <0.0001 plant*yr 2 24 13.01 0.0001 221.24 <0.0001 1.09 0.3511 NDF = numerator degrees of freedom, DDF = denominator degrees of freedom. Open in new tab Figure 6. Open in new tabDownload slide Leaf area index (LAI) (a) and total daily radiation under the canopy (b) in slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana (n = 60 plots) in 2016. Different capital letters indicate statistically significant differences (p < 0.05). Figure 6. Open in new tabDownload slide Leaf area index (LAI) (a) and total daily radiation under the canopy (b) in slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana (n = 60 plots) in 2016. Different capital letters indicate statistically significant differences (p < 0.05). There were differences among plantation types in some of the soil parameters (Table 7). S13 stands were less acidic than S08 and S13. The S13 stands had greater Cu concentrations than S08. Higher concentrations of S were observed in S08 stands than in S13 and E13 stands, and both slash pine plantation types were richer in Na and Zn than E13. The E13 stands had higher P concentrations than the other plantation types. Table 7. Soil nutrients, and pH means, and standard error of the mean (SEM) in slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations (n = 60 plots) planted in 2013 (E13) in southwestern Louisiana in 2016. Means followed by different letters within each row indicate statistically significant difference (p-value < 0.05). Variable . E13 . . S08 . . S13 . . . Mean . SEM . Mean . SEM . Mean . SEM . C (%) 1.08 0.062 1.14 0.077 1.21 0.116 N (%) 0.04 0.003 0.05 0.003 0.05 0.003 Ca (μg g-1) 123.15 8.886 128.24 11.785 149.67 20.001 Cu (μg g-1) 0.52 AB 0.033 0.45 B 0.027 0.60 A 0.037 Mg (μg g-1) 30.01 1.773 38.88 4.826 44.98 9.034 P (μg g-1) 7.22 A 2.096 2.43B 0.214 2.30 B 0.205 K (μg g-1) 26.03 1.252 20.30 2.775 19.70 1.541 Na (μg g-1) 14.55 B 0.640 19.56 A 0.860 19.04 A 1.845 S (μg g-1) 7.88 B 0.322 13.13A 1.139 9.83 B 0.798 Zn (μg g-1) 0.75 B 0.071 1.51A 0.250 1.53 A 0.179 pH 4.77 B 0.045 4.67 B 0.062 5.24 A 0.050 Variable . E13 . . S08 . . S13 . . . Mean . SEM . Mean . SEM . Mean . SEM . C (%) 1.08 0.062 1.14 0.077 1.21 0.116 N (%) 0.04 0.003 0.05 0.003 0.05 0.003 Ca (μg g-1) 123.15 8.886 128.24 11.785 149.67 20.001 Cu (μg g-1) 0.52 AB 0.033 0.45 B 0.027 0.60 A 0.037 Mg (μg g-1) 30.01 1.773 38.88 4.826 44.98 9.034 P (μg g-1) 7.22 A 2.096 2.43B 0.214 2.30 B 0.205 K (μg g-1) 26.03 1.252 20.30 2.775 19.70 1.541 Na (μg g-1) 14.55 B 0.640 19.56 A 0.860 19.04 A 1.845 S (μg g-1) 7.88 B 0.322 13.13A 1.139 9.83 B 0.798 Zn (μg g-1) 0.75 B 0.071 1.51A 0.250 1.53 A 0.179 pH 4.77 B 0.045 4.67 B 0.062 5.24 A 0.050 Open in new tab Table 7. Soil nutrients, and pH means, and standard error of the mean (SEM) in slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations (n = 60 plots) planted in 2013 (E13) in southwestern Louisiana in 2016. Means followed by different letters within each row indicate statistically significant difference (p-value < 0.05). Variable . E13 . . S08 . . S13 . . . Mean . SEM . Mean . SEM . Mean . SEM . C (%) 1.08 0.062 1.14 0.077 1.21 0.116 N (%) 0.04 0.003 0.05 0.003 0.05 0.003 Ca (μg g-1) 123.15 8.886 128.24 11.785 149.67 20.001 Cu (μg g-1) 0.52 AB 0.033 0.45 B 0.027 0.60 A 0.037 Mg (μg g-1) 30.01 1.773 38.88 4.826 44.98 9.034 P (μg g-1) 7.22 A 2.096 2.43B 0.214 2.30 B 0.205 K (μg g-1) 26.03 1.252 20.30 2.775 19.70 1.541 Na (μg g-1) 14.55 B 0.640 19.56 A 0.860 19.04 A 1.845 S (μg g-1) 7.88 B 0.322 13.13A 1.139 9.83 B 0.798 Zn (μg g-1) 0.75 B 0.071 1.51A 0.250 1.53 A 0.179 pH 4.77 B 0.045 4.67 B 0.062 5.24 A 0.050 Variable . E13 . . S08 . . S13 . . . Mean . SEM . Mean . SEM . Mean . SEM . C (%) 1.08 0.062 1.14 0.077 1.21 0.116 N (%) 0.04 0.003 0.05 0.003 0.05 0.003 Ca (μg g-1) 123.15 8.886 128.24 11.785 149.67 20.001 Cu (μg g-1) 0.52 AB 0.033 0.45 B 0.027 0.60 A 0.037 Mg (μg g-1) 30.01 1.773 38.88 4.826 44.98 9.034 P (μg g-1) 7.22 A 2.096 2.43B 0.214 2.30 B 0.205 K (μg g-1) 26.03 1.252 20.30 2.775 19.70 1.541 Na (μg g-1) 14.55 B 0.640 19.56 A 0.860 19.04 A 1.845 S (μg g-1) 7.88 B 0.322 13.13A 1.139 9.83 B 0.798 Zn (μg g-1) 0.75 B 0.071 1.51A 0.250 1.53 A 0.179 pH 4.77 B 0.045 4.67 B 0.062 5.24 A 0.050 Open in new tab Correlation and Multiple Regression Analyses Species richness and Shannon index were positively correlated with total daily radiation under the canopy, pH, and Cu, and negatively correlated with LAI, dbh, basal area, and tree height (Figure 7). Overstory variables (height, dbh, basal area) were positively related with LAI and negatively correlated with pH and total daily radiation under the canopy. Among soil variables, Ca was positively correlated with C, Mg, and K; Cu was positively correlated with pH. Positive correlations were also found between N and C, K and Mg, and Na and Zn. Figure 7. Open in new tabDownload slide Pearson correlation plot for species richness, Shannon index (H’), diameter at breast height (dbh), tree height, leaf area index (LAI), total daily radiation under the canopy (RAD), soil nutrients, and pH. Upper diagonal denotes correlation magnitude, with correlations in blue (positive) and red (negative) tonalities. Lower diagonal denotes correlation coefficients. Figure 7. Open in new tabDownload slide Pearson correlation plot for species richness, Shannon index (H’), diameter at breast height (dbh), tree height, leaf area index (LAI), total daily radiation under the canopy (RAD), soil nutrients, and pH. Upper diagonal denotes correlation magnitude, with correlations in blue (positive) and red (negative) tonalities. Lower diagonal denotes correlation coefficients. Stepwise regression indicated significant influences of LAI (negative) and pH (positive) for species richness and Shannon richness index (Table 8). Potassium was a positive predictor for species richness, whereas tree height was a positive predictor for Shannon index. The variance explained by the model was 51% for both species richness and Shannon index. Multicollinearity was indicated by condition index values (> 30) for each model except for Simpson inverse index, whereas tolerance and variance inflation factors failed to detect multicollinearity for any model, because their values were greater than 0.1 and less than 9, respectively (Belsley et al. 2005). Table 8. Multiple linear regression models for mean species richness and Shannon index (H’) (n = 60), including stepwise selection procedure, ANOVA table, and parameter estimates. Model . R2 . ANOVA table . . . . Parameter estimates . . . . . . . . . Source . DF . F . p-value . Parameter . Estimate . SE . p-value . Tol. . VIF . CI . Richness 0.51 Model 3 19.73 <0.0001 Intercept -5.766 7.787 0.462 0 0 1 Error 56 LAI -3.084 0.766 <0.0001 0.625 1.601 3.992 Total 59 pH 3.779 1.470 0.013 0.626 1.596 6.026 K 0.102 0.044 0.023 0.992 1.008 51.721 H’ 0.51 Model 3 19.21 <0.0001 Intercept -0.145 0.715 0.8402 0 0 1 Error 56 LAI -0.357 0.081 <0.0001 0.407 2.458 3.875 Total 59 height 0.043 0.015 0.006 0.393 2.546 8.155 pH 0.481 0.133 0.0006 0.560 1.785 55.378 Model . R2 . ANOVA table . . . . Parameter estimates . . . . . . . . . Source . DF . F . p-value . Parameter . Estimate . SE . p-value . Tol. . VIF . CI . Richness 0.51 Model 3 19.73 <0.0001 Intercept -5.766 7.787 0.462 0 0 1 Error 56 LAI -3.084 0.766 <0.0001 0.625 1.601 3.992 Total 59 pH 3.779 1.470 0.013 0.626 1.596 6.026 K 0.102 0.044 0.023 0.992 1.008 51.721 H’ 0.51 Model 3 19.21 <0.0001 Intercept -0.145 0.715 0.8402 0 0 1 Error 56 LAI -0.357 0.081 <0.0001 0.407 2.458 3.875 Total 59 height 0.043 0.015 0.006 0.393 2.546 8.155 pH 0.481 0.133 0.0006 0.560 1.785 55.378 SE = standard error, Tol. = tolerance, VIF = variance inflation factor, CI = condition index. Open in new tab Table 8. Multiple linear regression models for mean species richness and Shannon index (H’) (n = 60), including stepwise selection procedure, ANOVA table, and parameter estimates. Model . R2 . ANOVA table . . . . Parameter estimates . . . . . . . . . Source . DF . F . p-value . Parameter . Estimate . SE . p-value . Tol. . VIF . CI . Richness 0.51 Model 3 19.73 <0.0001 Intercept -5.766 7.787 0.462 0 0 1 Error 56 LAI -3.084 0.766 <0.0001 0.625 1.601 3.992 Total 59 pH 3.779 1.470 0.013 0.626 1.596 6.026 K 0.102 0.044 0.023 0.992 1.008 51.721 H’ 0.51 Model 3 19.21 <0.0001 Intercept -0.145 0.715 0.8402 0 0 1 Error 56 LAI -0.357 0.081 <0.0001 0.407 2.458 3.875 Total 59 height 0.043 0.015 0.006 0.393 2.546 8.155 pH 0.481 0.133 0.0006 0.560 1.785 55.378 Model . R2 . ANOVA table . . . . Parameter estimates . . . . . . . . . Source . DF . F . p-value . Parameter . Estimate . SE . p-value . Tol. . VIF . CI . Richness 0.51 Model 3 19.73 <0.0001 Intercept -5.766 7.787 0.462 0 0 1 Error 56 LAI -3.084 0.766 <0.0001 0.625 1.601 3.992 Total 59 pH 3.779 1.470 0.013 0.626 1.596 6.026 K 0.102 0.044 0.023 0.992 1.008 51.721 H’ 0.51 Model 3 19.21 <0.0001 Intercept -0.145 0.715 0.8402 0 0 1 Error 56 LAI -0.357 0.081 <0.0001 0.407 2.458 3.875 Total 59 height 0.043 0.015 0.006 0.393 2.546 8.155 pH 0.481 0.133 0.0006 0.560 1.785 55.378 SE = standard error, Tol. = tolerance, VIF = variance inflation factor, CI = condition index. Open in new tab Canonical Discriminant Analysis A total of 19 variables were initially included in the DCA. The stepwise discriminant analysis (SDA) procedure retained six variables (Table 9). The discriminant analysis yielded two significant functions (Can1 and Can2), which are the linear combination of the variables previously selected in the stepwise procedure. The total canonical structure identifies the degree of correlation, positive or negative, between the continuous variables and the two discriminant functions. Almost all the variables loaded on the first canonical axis, with LAI, height, and dbh negatively loaded, whereas species richness and pH positively loaded. Soil Zn loaded positively on the second axis. Table 9. Variables retained (p ≤ 0.05) in the SDA. Total canonical structure indicates the correlation degree between the variables and the canonical functions, while canonical standardized coefficients represent the coefficients of the variables (standardized) in the linear combination. Step . Variable . Partial R2 . Wilk’s λ . p-value . Tot. can. structure . . Can. std coefficients . . . . . . . Can1 . Can2 . Can1 . Can2 . 1 LAI 0.90 0.097 <0.0001 -0.97 0.05 -0.89 -0.01 2 Height 0.60 0.038 <0.0001 -0.81 -0.47 -0.13 -2.05 3 dbh 0.73 0.011 <0.0001 -0.91 0.09 -0.36 1.94 4 Richness 0.33 0.007 <0.0001 0.74 -0.17 0.50 -0.13 5 pH 0.15 0.006 <0.0001 0.73 0.15 0.48 0.06 6 Zn 0.13 0.005 <0.0001 0.09 0.44 0.22 0.36 Step . Variable . Partial R2 . Wilk’s λ . p-value . Tot. can. structure . . Can. std coefficients . . . . . . . Can1 . Can2 . Can1 . Can2 . 1 LAI 0.90 0.097 <0.0001 -0.97 0.05 -0.89 -0.01 2 Height 0.60 0.038 <0.0001 -0.81 -0.47 -0.13 -2.05 3 dbh 0.73 0.011 <0.0001 -0.91 0.09 -0.36 1.94 4 Richness 0.33 0.007 <0.0001 0.74 -0.17 0.50 -0.13 5 pH 0.15 0.006 <0.0001 0.73 0.15 0.48 0.06 6 Zn 0.13 0.005 <0.0001 0.09 0.44 0.22 0.36 Open in new tab Table 9. Variables retained (p ≤ 0.05) in the SDA. Total canonical structure indicates the correlation degree between the variables and the canonical functions, while canonical standardized coefficients represent the coefficients of the variables (standardized) in the linear combination. Step . Variable . Partial R2 . Wilk’s λ . p-value . Tot. can. structure . . Can. std coefficients . . . . . . . Can1 . Can2 . Can1 . Can2 . 1 LAI 0.90 0.097 <0.0001 -0.97 0.05 -0.89 -0.01 2 Height 0.60 0.038 <0.0001 -0.81 -0.47 -0.13 -2.05 3 dbh 0.73 0.011 <0.0001 -0.91 0.09 -0.36 1.94 4 Richness 0.33 0.007 <0.0001 0.74 -0.17 0.50 -0.13 5 pH 0.15 0.006 <0.0001 0.73 0.15 0.48 0.06 6 Zn 0.13 0.005 <0.0001 0.09 0.44 0.22 0.36 Step . Variable . Partial R2 . Wilk’s λ . p-value . Tot. can. structure . . Can. std coefficients . . . . . . . Can1 . Can2 . Can1 . Can2 . 1 LAI 0.90 0.097 <0.0001 -0.97 0.05 -0.89 -0.01 2 Height 0.60 0.038 <0.0001 -0.81 -0.47 -0.13 -2.05 3 dbh 0.73 0.011 <0.0001 -0.91 0.09 -0.36 1.94 4 Richness 0.33 0.007 <0.0001 0.74 -0.17 0.50 -0.13 5 pH 0.15 0.006 <0.0001 0.73 0.15 0.48 0.06 6 Zn 0.13 0.005 <0.0001 0.09 0.44 0.22 0.36 Open in new tab A canonical biplot was produced, showing the canonical scores for the groups defined by the term as points and the canonical structure coefficients as vectors from the origin (Figure 8 and Table 9). The DCA offered an overview of the differences in the three plantation types: Can1 clearly discriminated the plantation types in terms of overstory complexity (more complex overstory on the left side of the axis) and higher floristic richness and soil pH levels (right side of the axis). The second canonical axis discriminated in terms of soil Zn, which increased towards the positive side (upper) of the axis. S13 plots were clearly separated from S08 and E13 in the first canonical axis, whereas the second axis separated E13 from the slash pine plots (no overlapping in the 95% confidence level ellipses was detected). Figure 8. Open in new tabDownload slide Canonical plot for slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. Multivariate mean for each group is denoted by a plus (+) marker. A 95% confidence level (inner) ellipse is plotted for each means. To facilitate the interpretation, rays are enlarged by a scaling factor of five. Figure 8. Open in new tabDownload slide Canonical plot for slash pine plantations planted in 2008 (S08) and 2013 (S13) and in Camden white gum plantations planted in 2013 (E13) in southwestern Louisiana. Multivariate mean for each group is denoted by a plus (+) marker. A 95% confidence level (inner) ellipse is plotted for each means. To facilitate the interpretation, rays are enlarged by a scaling factor of five. Discussion In the three years of this study, the fast growth rate of Camden white gum modified habitat conditions, altering the understory composition and making it similar to older slash pine, which was characterized by a more developed overstory. These findings support the idea of negative effects of plantation age on understory species diversity as a consequence of growth rate of the plantation species used (Hartley 2002, Cusack and Montagnini 2004). Overall understory species richness quantified by the rarefaction curves declined more rapidly in Camden white gum than in slash pine plantations, which occur more commonly in the region, over the three years of this study. During the study, E13 understory vegetation richness went from being similar to that of S13 (in 2014), to intermediate between S13 and S08 (in 2015 and 2016). The rapid changes in tree dimensions in Camden white gum likely produced a faster change in understory conditions and consequently a faster decrease in species richness. The substantial increase in Camden white gum height and corresponding decline in richness was likely promoted by the operational fertilization in November 2015, which also likely led to the higher soil P concentrations of Camden white gum plantations. This management facet of the Camden white gum plantations may indicate that the understory changes observed in this study could occur more rapidly if such plantations are treated with more aggressive fertility management, as observed in Portugal where fertilization and harrowing practices decreased the understory species diversity in E. globulus plantations over 5 years (Carneiro et al. 2008). The confounding of operational fertilization with Camden white gum management in this study may also lead to different levels of contrast in understory condition development in similar studies if another fertilized plantation type were compared with fertilized eucalyptus plantations. It is noteworthy that plot-level richness analysis did not detect the shift in species richness in the Camden white gum plantations relative to slash pine plantation types consistent with that revealed by the rarefaction approach. Inconsistencies in species richness between the rarefaction and plot-level methods were observed in 2014 and 2015, and it is illustrative of the elusive nature of measuring species richness (May 1988) and the relative sensitivity of rarefaction for detecting differences in richness (James and Rathbun 1981). An inherent issue with species richness determination is that more species are recorded as sampling intensity increases (Bunge and Fitzpatrick 1993). Sampling equal-sized areas as done with plot-level richness determination ameliorates this issue, but as species sampling progresses fewer species are discovered. In addition, the order in which sampling units are added affects this accumulation of species detection, and variation in species detection accumulation arises from sampling error and from heterogeneity of sampling units (Colwell and Coddington 1994). Rarefaction curves account for the increasing rarity of species detection during sampling through curve shape (with asymptotes substantiating sampling adequacy for richness characterization) and the arbitrary nature of species detection via randomization of sample accumulation order (Gotelli and Colwell 2001, Colwell 2009). As such, rarefaction was likely more sensitive than plot-level richness at detecting differences in richness, and both together provided a comprehensive view of the change in species richness. Species richness and Shannon index followed a similar pattern during the years and within plantation types. Camden white gum and same-age slash pine plantations may have been more conducive to higher understory species diversity than the older slash pine plantations because they had more recently been clearcut-harvested and treated with vegetation suppression operations (burning with single applications of herbicide for slash pine, one year of near-complete vegetation suppression with herbicides for Camden white gum). After these harvesting and vegetation control operations, colonization of the sites with an array of species occurred. The older slash pine plantations had a longer time for canopy closure to affect understory species diversity. Camden white gum interestingly had similar understory species diversity (as measured by rarefaction) as same-age slash pine at the inception of this study, which was the year immediately following the cessation of operational herbicide treatments in those plantations; the slash pine plantations were treated with herbicides only once prior to planting. The banded herbicide application in E13, carried out to constrain vegetation suppression costs, likely fostered colonization of species between tree rows that expanded once herbicide applications ceased. Richness (for rarefaction and plot-level methods) and Shannon index declined in all three plantation types in 2016 relative to the prior years. Timing of spring and fall floristic surveys was similar in all years, so species detection in the surveys was likely unaffected by survey timing. The spring portion of the 2016 assessment may have been affected by precipitation patterns. March 2016 had ~2.5 times greater precipitation than the long-term average for the region (Figure 2), which led to standing water in the flatwoods sites of this study. This standing water could have reduced vegetation germination in spring 2016. In prior years of the study, deviations from long-term precipitation patterns were not of the magnitude observed during the spring sampling period of 2016. As of the final year of this study, the plantation types were different primarily in understory species richness, overstory parameters (LAI, height, dbh), and soil pH and Zn, as evidenced by discriminant analysis results. Multiple regression indicated that LAI had a strong negative influence on understory vegetation richness and diversity, while soil pH had a positive influence on these parameters. Together these results suggest that LAI and soil pH had the strongest influences on understory richness and diversity in this study. Leaf area index was the dominant factor among the overstory and soil variables observed in this study influencing species richness and diversity. It had a strong correlation with, and was a robust predictor of, species richness and diversity indices. Under-canopy radiation was also correlated with species richness and Shannon index; however, it may have been eliminated in stepwise regression due to its high (94%) correlation with LAI. Moreover, both LAI and radiation values are mathematically calculated from gap fraction derived from hemispherical canopy pictures. Leaf area index has a strong effect on understory light regimes. Light regime is a key factor in determining the microclimatic conditions of sites and associated plant communities (Richardson et al. 1989, Parrotta 1995). Several elements influence overstory transmittance, such as spatial arrangement of leaves, leaf size, and optical properties of leaves, which can be approximatively described by variables such as canopy closure or LAI (Barbier et al. 2008). In 2016, Camden white gum height was greater than older slash pine, but its LAI was intermediate between same-age and older slash pine. Those findings suggested a canopy architecture of Camden white gum with less-dense foliage, which allowed more light to the understory and correspondingly higher richness and diversity than older slash pine. Prior studies observed relationships between LAI and understory vegetation similar to findings of this study. Lemenih et al. (2004) identified a correlation between canopy characteristics of plantation stands and understory species richness, with species richness decreasing from open-canopy to closed-canopy plantations. A decrease in understory richness with increasing overstory LAI and basal area was observed in Eucalyptus saligna, Flindersia brayleyana, and Fraxinus uhde plantations in Hawaii (Harrington and Ewel 1997). In a study conducted in six plantation types (Acacia mangium, Schima superba, Eucalyptus citriodora, Eucalyptus exserta, mixed-coniferous, and mixed native species plantations) in South China, light was the most important environmental factor influencing composition and structure of understory vegetation (Duan et al. 2010). Light was positively correlated with Shannon diversity indices (r = 0.4, P = 0.002) in the Duan et al. (2010) study; similar levels of correlation (r = 0.53) were observed between diversity indices and parameters associated with light (LAI and under-canopy radiation) in this study, further confirming the idea that light was one of the most influencing factors in determining understory species composition. Shade-tolerant and partial shade-tolerant species were observed more frequently in S08 and E13 stands than in S13 stands, indicating a difference in light regimes among the plantations associated with different vegetation. For instance, Carolina jessamine (Gelsemium sempervirens) was observed in more than 41–46.5% of the sampling quadrats in S08, 5–7% of the quadrats of E13, and nearly absent in S13 over the years observed. Similarly, yaupon holly (Ilex vomitoria), a perennial tree shrub, was observed in 6.5–11.5% of sampling quadrats in S08, 6.5–11% in E13, and 0–1.5% of S13 quadrats. The incidence of Japanese climbing fern (Lygodium japonicum), a non-native invasive, perennial, vine-like fern, was 8–10.5% in E13, 0.5–1.5% in S08, and 0–2% in S13, raising potential concerns on the dissemination of invasive non-native species within the Camden white gum plantations. On the other hand, annual and perennial forbs and herbs typical of open-pine savannas and flatwoods, such as Agalinis filicaulis, Centaurium pulchellum, Lobelia puberula, Lobelia appendiculata, Polygala cruciata, Polygala cymosa, and Polygala mariana were nearly absent in S08 and E13 but present in S13, although with a low incidence rate over the three years. Based on Camden white gum having a moderate level of intermediate shade-tolerance-preferring species over the course of this study, understory vegetation of eucalyptus sites may become more representative of plant communities in closed-canopy forests, similar to older slash pine, where shade-tolerant woody perennial vines and shrubs are common. However, eucalyptus stands are harvested in very short rotations (3–10 years), which might prevent the attainment of fully closed-canopy conditions, with important implications on understory vegetation succession. Successional processes in understory vegetation—shifting from early successional understory conditions (where heliophilic species are dominant) towards late successional (dominated by shade-tolerant species) due to forest canopy closure over time—normally occur in plantations (although thinning affects this progression), and this process is profoundly linked to several ecosystem services and functions, such as nutrient cycling and faunal habitats (Carnus et al. 2006, Brockerhoff et al. 2009). Vegetation successional patterns under the different harvesting patterns of Camden white gum (which are clearcut on 7–10-year intervals) and slash pine (which are thinned two or three times within 30- to 40-year rotations) is an unexplored issue for future research. Soil pH positively affected understory species richness and diversity in this study. Similar to findings of our study, Eycott et al. (2006) reported higher species richness in recently clear-felled Pinus nigra and Pinus sylvestris stands, where soil pH was higher. Likewise, Hutchinson et al. (1999) reported a positive correlation between floristic richness and soil pH in oak forests in Ohio. Their results matched the condition of younger slash pine in this study, where both richness and pH were higher compared to older slash pine and eucalyptus stands. The higher pH of the S13 plantations was likely due to prescribed burning that preceded their establishment (Messick et al. 2018); no prescribed burning was conducted prior to Camden white gum establishment. The S08 stands also had prescribed burning prior to their establishment, but the time interval between burning and the years observed in our study was longer than that for S13 plantations. Soil pH increases with heating (Certini 2005); with temperatures > 450–500° C, bases are released as a consequence of complete combustion of fuel (Arocena and Opio 2003), and base saturation is enhanced (Macadam 1987). Ulery et al. (1993) reported three-unit pH increases in topsoil immediately after burning in Quercus engelmanii, Pinus ponderosa, and mixed conifer stands. Soil pH is a key factor in determining nutrient availability: macronutrient (N, P, K, Ca, S, and Mg), and various micronutrient (Cu, Fe, Mo, and B) deficiencies occur for pH values lower than 5–5.5 (Havlin et al. 2014). The higher pH values in same-age slash pine may have increased the availability of nutrients for the understory, promoting higher richness and diversity. These findings highlight another facet of conversion to eucalyptus plantations on understory species richness; exclusion of fire from management in eucalyptus plantations can contribute to lower species richness. Although differences in soil K were not detected between plantations, it was a significant positive predictor in the species richness regression model, which indicates that understory vegetation may benefit from higher soil K levels. Janssens et al. (1998) determined that the number of plant species in a grassland increased with increasing soil K concentration up to 150–200 μg g-1 of soil (optimal levels for grass nutrition), which was 10-fold higher than the K concentrations observed in this study. Higher soil K may have helped support the herbaceous species found in greater numbers in the S13 and E13 plantations than in the S08 plantations. However, Crawley et al. (2005) reported no significant effect of K on species richness in the Parkland Grass experiment, and Huston (1980) pointed out that forests with the greatest species richness were observed on sites with the lowest nutrient values, expressed as total bases (Ca, K, Mg and Na). Conclusions Results of the study suggest that converting species use from slash pine to Camden white gum is associated with a relative decline in understory species richness, and silvicultural differences in these plantation types (such as fertilization of Camden white gum and pre-planting burning of slash pine) may have accentuated changes in understory species richness. Species richness of Camden white gum understory decreased through the three years of this study to the point of becoming intermediate to same-age and similar-height slash pine plantations. Evidence suggests that those changes were triggered by rapid increases in Camden white gum tree dimensions, which increased LAI and reduced total daily radiation under the canopy. Fertilization of the Camden white gum plantations to promote tree growth likely contributed to this trend. Species richness was lower on acidic soils, and it was higher in less acidic same-age slash pine plantations that had been recently prescribed-burned. Further research is required to understand the effects of disturbances associated with the different harvesting regimes of these plantations (with Camden white gum clearcut-harvested in 7- to 10-year rotations and slash pine thinned twice then clearcut-harvested in a 30- to 40-year rotations) on understory species richness and diversity. Furthermore, changes in species richness and diversity can have functional consequences on ecosystem functionality, services, and processes connected to the understory, such as nutrient cycling or net primary productivity. These issues also merit further research. At present, Camden white gum plantations are a relatively small component of the region in which this study was conducted; expanded establishment of Camden white gum plantations on sites formerly occupied by slash pine plantations could have implications at the landscape scale. Combining biodiversity maintenance and wood production at different spatial scales is a critical issue for forest managers (Carnus et al. 2006), and further research is needed for a better understanding of implications at larger spatial and longer temporal scales. Acknowledgments The authors are grateful to the National Council for Air and Stream Improvement, Inc. (NCASI), WestRock, and International Paper for funding this project, as well as Hill Farm Research Station personnel Michelle Moore, Robert Hane, and Kenny Kidd for their priceless help in the field and laboratory. 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TI - Understory Vegetation Richness and Diversity of Eucalyptus benthamii and Pinus elliottii Plantations in the Midsouth US
JF - Forest Science
DO - 10.1093/forsci/fxz051
DA - 2020-02-04
UR - https://www.deepdyve.com/lp/springer-journals/understory-vegetation-richness-and-diversity-of-eucalyptus-benthamii-tOKm3pC2za
SP - 66
VL - 66
IS - 1
DP - DeepDyve
ER -