Spatial variation of soil characteristics within an urban arboretum. A case study of the Salisbury University Arboretum, Maryland, U.S.A.

Spatial variation of soil characteristics within an urban arboretum. 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A case study of the Salisbury University Arboretum, Maryland, U.S.A. Daniel W. Harris, Michael E. Folkoff, Samuel B. Gelata, Christopher H. Briand This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5448647/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The impact of long-term institutional management on soil chemistry within urban greenspaces is important to recognize given the proliferation of these urban planning methods in our ever-increasing urban environments. Most research on urban soils primarily focuses upon heavy metal pollutant accumulation and its relationship to industrial history and current environmental quality. Far less research, especially in the United States, examines the impact of soil and landscape management practices aimed at providing greenspaces for the residents of the ever-expanding urban environments. Moreover, systematic studies detailing resultant soil chemistry changes in managed greenspaces rarely exist given the lack of a non-urban analogs by which to compare. Also, land use histories of urban sites are often ambiguous and through time soil management practices vary as managers seek to create varied “aesthetically pleasing” landscapes in these institutional environments. This study details soil chemistry differences within the varied landscapes of an urban greenspace, a University arboretum, following almost 100 years of institutional soil management as the University expanded into former agriculture soils. Soil series mapped on the University campus prior to arboretum establishment remain agriculturally active in the surrounding community enabling our analysis. Results indicate the widespread addition of lime throughout arboretum environments has elevated soil pH thereby increasing the availability of macro- and micronutrients in vegetative communities including lawns, gardens and woodlands. Of concern, organic matter amounts are also elevated in the arboretum, fundamentally changing its natural inverse relationship with pH. The over enrichment of nutrients in this greenspace likely represents the outcome of anthropogenic management practices across many types of urban greenspaces. These soil chemistry modifications likely result in significant changes in runoff water chemistry thereby impacting local surface and groundwater resources. “Urban soils often become defined by human activities and land use histories at a particular location rather than by the continuum of geologic processes.” – Solano 2013 “Urban plant communities are as much a product of the cultural environment as they are a part of the physical landscape.” – Whitney and Adams 1980 arboretum land use history soil management soil nutrients urban soil Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Past research on urban soils focused on the methods by which soil fertility can be managed for agricultural production. Far less attention has been devoted to the important role urban soils and their management serve in supporting urban land uses especially urban green spaces, public parks, arboreta, botanical gardens, corporate/government campuses, and zoned open spaces. Most urban soil research has focused on soil contamination by heavy metal accumulation through industrial and commercial land use and/or the impact of airborne deposition from dense transportation infrastructures of cities (Bassetti et al. 2023; Lupolt et al. 2021; Malone and Shakya 2024; Paltseva et al. 2020; Pouyat et al. 2015; Schwarz et al. 2016). Heavy metal accumulations were found to increase across a comprehensive land use gradient in France, with the lower amounts measured in forests, grasslands and agricultural regions, including cultivated areas, orchards, and vineyards and the highest levels observed in urban, industrial, mining and military locations (Joimel et al. 2016). These researchers and Bechet et al. (2020) also identified heavy metal contamination in European urban greenspace soils including gardens. Urban land uses clearly affect urban soils, perhaps more than any other land uses. Given the continued growth of urbanized landscapes, research in this area is increasingly important to understanding how soils are managed in cities and suburbs. While the overall percentage of urban land area on the Earth’s surface is small, approximately 2-3%, human impacts are amplified given the far greater population densities in these areas and the number of environmental interactions that occur. Currently, about 3% of the United States is considered urban and this land cover type is projected to increase to 8% by 2050 (Malone et al. 2023). Worldwide, urban areas are expanding faster than any other land use type (Tresch et al. 2019). Urban soils are highly varied and are often found in small fragmented and isolated areas. However, much larger parcels are also found in lightly disturbed settings such as greenspaces, undeveloped suburban-urban interface parcels, and wooded areas of residential, commercial, and/or industrial park parcels. Of course, some soils in cities with large acreages are now legislatively protected such as wetlands and forest preserves. Unlike in surrounding rural environments, soils’ role in urban landscapes is critical in supporting greenspace as recreational and psychological refuges for urban dwellers as well as an increasingly critical means to mitigate climate change (Mabon et al. 2019). The arboretum on Salisbury University’s campus provides a unique setting to examine the impact of institutional management by comparing our campus’ urban greenspace soil to the same soil types in the surrounding non-urban environment, most of which have been in long-term agricultural production. Institutional management of arboretum soils has been varied to support different landscapes including woodlands, parks, gardens, and turfgrass. In the arboretum, ecology, and soil management are often secondary to plant productivity to create scenic faux landscapes. Exotics are lauded for their uniqueness; leaf removal and weeding are endemic to aesthetics, which are subject to management taste. Gardening to create idealized landscapes is a tradition descended from landscape architecture principles used on the great British estates (e.g., Capability Brown’s on Blenheim Estate): “This blessed plot, this earth, this realm, this England”—Brown planted the idealized England that Shakespeare had evoked. His parklands for aristos and nabobs “look so natural that we are instantly at ease in them” – Rutherford (2016) We argue that institutional soil management practices modify soil properties to a higher degree than agricultural production on the same soils. In this study, we directly compare soil physical and chemical properties in the same soil series on an urban college campus with those under agricultural land uses. We believe the significant manner in which urban soil properties have been transformed, to a greater extent than in surrounding agricultural soils, is an overlooked consequence of urbanization with significant impacts on urban environmental quality and pollution especially runoff to the watershed. Urban/Anthropogenic Soils While urban soil contamination research is extensive and the results of anthropogenic soil modifications are reported for some areas and specific land uses, far less work directly examines how urban soil chemistry and physical properties have been modified in greenspaces, especially in the United States. This gap likely results from the highly dynamic and intensive nature of anthropogenic soil management which results in significant spatial heterogeneity in soil geochemistry and physical properties in urban environments. Howard (2020) identified three categories of urban anthropogenic soil (UAS) formation based on common processes: or the addition of organic matter to a native soil creating a new profile and thus a new soil type, technopedogenesis, whereby a soil profile changes through the mechanical mixture metapedogenesis of human-deposited sediments and debris which are often incorporated from distant sources and mixed with the native soil, and ekranopedogenesis, or the sealing of a pre-existing soil by pavement, concrete, or any other impervious material or structure. Byrne (2007) states that managed soils exhibit rapidly changing characteristics and compositions reflecting current management goals and their often “ambiguous” pasts. Few researchers have access to pre-urbanization baseline soil characteristics to assess the impacts of anthropogenic soil management, especially in greenspaces such as parks and arboreta. Most studies, therefore, are relegated to comparisons between different locations and land use classes. In a review of anthropogenic soil properties in botanical gardens in subtropical Asia, the Mediterranean, and northern Europe, Chupina (2020) reports management-induced increases in humus content, higher pH, and more available nutrients especially phosphorus and sometimes potassium. Zukswert et al. (2021) examined soil characteristics for three native tree species ( Acer saccharum, Quercus alba, and Tsuga canadensis ) in the northeastern United States comparing native forests to heavily managed habitats within the Boston arboretum. Intentional soil management led to increased pH, and more calcium and magnesium, with lower amounts of aluminum and manganese (to reduce toxicity). Interestingly, the water source used for irrigation was found to be treated to increase alkalinity. Joimel et al.’s (2016) land use transect detailing topsoil characteristics across French landscapes did not specifically focus on greenspaces but urban samples were included in these settings. This study also found higher pH in anthropized soils and that the incorporation of organic matter and mineral fertilizers increased carbon, nitrogen, and phosphorus amounts relative to non-urban soils. Phosphorus levels increased toward urban land use, reaching their maximum in garden soils. Byrne (2007) notes that native soil profiles and their ecological communities are altered through management by many common landscaping practices including the application of mulch, mulching grass clipping in lawn areas, and the use of heavy machinery which can reduce soil voids unless counteracted by aeration. The increased organic matter and carbon result in higher net primary productivity above and below ground. Scharenbroch et al. (2005) also noted increased soil carbon and nitrogen pools and stated that rapid fluxes in these soil constituents through human management can rapidly alter soil characteristics and their resulting ecological communities. Soil degradation by erosion is widespread in both agricultural and urban soils, is historically a major problem, and is accelerated with the intensity of use in high-usage urban green spaces. In addition, anthropogenic soil processes are also impacted by temperature and moisture changes associated with urbanization (Seto et al., 2013). Urban soil temperatures are notably higher than rural environments, 1.2 to 2.1° C, and exhibit larger diurnal temperature swings to a greater depth, most notably beneath grass surfaces (Howard 2020). Soil moisture levels are often lower due to sealing, compaction, and stormwater management, although this change is often mitigated in urban greenspace environments with frequent irrigation and the construction of surficial stormwater retention features. Temperature and moisture regime changes impact organic matter decomposition rates, the composition and extent of macro- and micro-faunal colonies, as well as the weathering rates of the inorganic mineral components within soils. Cumulatively, these processes result in significant heterogeneity, at often very small scales, and while individual studies have examined the physical and chemical properties of urban soils, these properties are not inventoried and reported in the widely-used Web Soil Survey for researchers in the United States (Green et al. 2016). As noted in Joimel et al. (2016): “Agriculture and forestry are often considered as having little disturbing effects on soil, whereas urban and industrial activities could potentially involve organic and inorganic pollution causing a significant alteration of physical, geochemical, and biological properties” In this study, we assess the dramatic changes to soil properties in different urban arboretum land covers induced by intensive soil management for almost 100 years. Soil sample characteristics in four different urban arboretum environments, woodlands, parks, lawns, and gardens, are compared to the chemical and physical properties of the same soils in agricultural and natural settings in the surrounding region experiencing less intensive management. Site History and Description It is not possible to disentangle all long-term influences of “ambiguous past practices” in our study site but soil management probably has affected our results in some way (Byrne (2007). The current grounds of the University are within the boundaries of Wicomico Manor , a plantation laid out in 1674 in Old Somerset County, now Wicomico County, Maryland (Maryland Land Office. 1673-1679). A 1756 map of Wicomico Manor shows sixteen tenant farms (Stiverson 1977). The 1783 and 1793 Tax Assessments (General Assembly House of Delegates 1783, Reedy 1999) for tracts within the former Wicomico Manor indicated that general soil quality was sandy, with one tract, Toadvines Adventure , listed as “high level sandy land originally kind, but worn” suggesting continuous intensive agricultural use, likely related to years of soil erosion. Our study area was initially forested, as was most of the Eastern United States, but in the early colonial period, forest clearance was soon followed by intensive agriculture (Briand and Folkoff 2019). In 1870, the first agricultural census of Wicomico Co. showed that 51.2% of county land was “Improved”, 47.3% “Woodland” and 1.5% “Other unimproved,” with the principal crops listed as maize, oats, potatoes, and wheat. Maize accounted for 93% of the grain harvest in Wicomico Co. (U.S. Census Office 1872; Walker 1872). By 1924, a year before the opening of Maryland State Normal School (precursor to Salisbury University), the principal county crops were sweet potatoes and maize however most of the campus area produced small fruit and orchard crops (USDA 1927). Opened in 1925, the campus was initially built on an 11.7 ha parcel of farmland, that produced strawberries and other small fruit such as blackberries and raspberries, as well as peaches (Fig. 1.A.). Patterson (1907) noted that strawberry was the most extensively grown small fruit in Maryland. Both plants and fresh fruit were shipped by rail to nearby metropolitan areas including Philadelphia and New York City (Allen Co. 1917; Maryland Inventory of Historic Properties 1993, 2000). The farm was “well manured with N.Y. City stable manure and fertilizer” (Allen Co. 1899; Fig. 1.B.) and on an area of higher ground, farm owner W.F. Allen’s residence contained “a beautiful grove of pine, oak, cedar, and dogwood trees” (Maryland Inventory of Historic Properties. 2000; Fig. 1.C.). Our forest category, effectively a managed woodland given its land use history and subsequent management, abutted and was contiguous to the homestead site. With campus expansion in the last 100 years, the majority of the landscape has been transformed, resulting in a variety of land cover types commonly found on small, urban campuses. Construction began in the farm’s northwest with Holloway Hall and stretched eastward along College Avenue then southward following Camden Avenue (Fig. 2). Holloway Hall (Walter C. Thurston, 1940s). Note the orchard to the right of Holloway Hall (Courtesy of the Edward H. Nabb Research Center for Delmarva History and Culture at Salisbury University). The first State Normal School at Salisbury yearbook stated: “The grounds comprise attractive lawns, ornamented with flowers, trees, shrubbery, and evergreens; playground areas, gardens, and an orchard” (Maryland State Normal School 1926). Hay and corn were grown for the horses, and the orchard and vegetable garden provided fruit and vegetables for the students (Bradley 2002). In all but the oldest, developed northern part of campus, the area was still an agricultural landscape (Hall 1970). This area has the campus’ oldest building and was the first to transition from mainly agricultural use; the “great lawn” area west of the first building contains our largest area of grassland. The campus currently occupies 73 ha but this study focuses on the 27.4 ha of the oldest part of campus. The 1970 Wicomico Soil Survey mapped agricultural soil series showing that much of the campus was not yet intensively developed. These campus soil series are also prevalent in the surrounding agricultural regions; therefore, we can compare how long-term arboretum management changed the soils’ physical and chemical properties in comparison to agricultural land use. Moreover, plantings within the varied arboretum environments on campus required differing management techniques and inputs, therefore we can determine how soil properties across the campus environments have been modified. Materials & Methods The 27.4 hectare (ha) vegetated region of campus, which comprises the Arboretum, is composed of four anthropogenically derived environments: Lawn (50.4%), Park (38.2%), Garden (8.7%) and Forest (2.7%). Areal extents for these four Arboretum classes were delineated by air photo interpretation in a geographic information system using high-resolution aerial photography (e.g. 4-inch pixel spatial resolution) (Fig. 3). Soil samples were taken during the fall of 2016 from four Lawn, six Parks, four Garden, and two Forest sites in the Salisbury University Arboretum (Fig. 3). At each sample site, four composite samples (of four 2 cm diameter cores) were collected with a soil corer to a depth of 20 cm. The soils were dried at 35° C, and ground to 2 mm. Tests for soil chemical properties (pH, %OM, and extractableFig macro- and micronutrients) were conducted at AgroLabs, Milford DE following procedures for the Northeastern United States (NEC-67 1995). Physical and chemical properties for surrounding agricultural soils in the same soil series were obtained using an identical methodology during prior published research (Geleta et al. 2014). Baseline soil series properties were also downloaded from Soil Characterization Lab Data provided by the National Cooperative Soil Survey (https://ncsslabdatamart.sc.egov.usda.gov/). The soil series identified in the campus area prior to University founding included Klej, Fort Mott, Evesboro and Rockawalkin. Klej, with the minor components of Fort Mott and Evesboro, formed the wooded habitat (i.e., Forest) in the current campus arboretum while Fort Mott soil dominated the Lawn habitat and Rockawalkin soils is now urban soils within the Gardens (Table 3) (Hall, 1970). While soil series classification criteria have changed somewhat since 1970 and archival soil series were tested in the surrounding region not including actual soil samples on campus, we believe our comparisons are valid given the relative homogeneity of the region’s physical environment. Although soil mapping units have changed names and criteria with survey updates, the soil properties examined in a specific sampling location have not changed. To determine the degree to which soil properties varied within and between the sampled campus environments, Cluster Analysis was performed on the aggregate soil sample data to determine the variation in soil properties between campus land uses?: individual land uses? should show similar soil properties changes due to individual management schemes. Clustering was performed using Ward’s linkage and squared Euclidean distance to delineate soil groups by properties and their linkage to campus arboretum environments. The resultant clusters were used as independent variables in Principal Components Analysis (PCA) by using a correlation matrix to standardize the variables. One-way ANOVA and Tukey multiple comparison tests were done on both the individual variables and the coefficients of PC 1, 2 and 3 to evaluate collinearity and independent variable relationships. A Kruskal-Wallis test followed by Dunn’s multiple comparisons test was used when data could not be normalized. Bayesian ANOVA was also used to check the strength of the evidence for the alternative hypothesis. Bayes factor (BF 10 ) interpretation follows Wagenmakers et al. (2018). Pearson Correlation Coefficients were calculated between all individual variables. Data analyses were performed using Minitab 17 (Minitab 17 Statistical Software 2010), IBM SPSS Statistics 23 (IBM Corp. 2015) and JASP (JASP Team 2018). Results Five clusters were identified that closely matched our anthropogenically derived ecosystem classification based on management (Fig. 4). The Lawn Cluster contained 81.3% of the lawn samples and the Park Cluster contained 90% of the park samples. Interestingly, the second Forest area we identified clustered with the Park samples, so this area was reclassified solely as park. There were two Garden Clusters. Garden Cluster 1 was made up of 92% of the samples from Gardens 1-3, while Garden Cluster 2 contained all of the samples from Garden 4. The remaining Forest Cluster contained all the natural forest samples. Average values of the soil chemistry variables, by cluster, are shown in Table 1. Principal components analysis was used to understand variation in soil chemical characteristics across the aggregated soil samples. The first three principal components accounted for 72.2% of the total variance. The remaining principal components each accounted for < 6 % of the variance. Bartlett’s test of sphericity (χ2 = 838.1, DF = 105, P < 0.001) indicated that correlations among the variables were sufficient for PCA, while the Kaiser-Meyer-Olkin measure verified sampling adequacy (KMO = 0.811; ‘great’ according to Field 2009). PC1 explained 47.3% of the total variance. There were high positive loadings for pH, the macronutrients Ca, N, P, K and the micronutrients B, Cu, Fe and Zn (Table 2). PC1 represents the majority (60%) of the soil chemistry parameters measured which is consistent with Joimel et al.’s (2016) study of multiple land uses in a French landscape, suggesting decreased acidity and OM enrichment in anthropomorphic soils. From the plot of PC2 vs. PC1 (Fig. 5) and the one-way ANOVA of the PC1 scores (Fig. 6), one can see that Garden cluster 2, had the highest overall levels of soil nutrients, followed by the Forest cluster and Garden cluster 1. The Lawn and Park clusters had the lowest levels of soil nutrients. These results are confirmed by one-way ANOVA on individual nutrients, indicating that within highly anthropomorphic soils basic cations and OM increase with increasing management (Table. 1). PC2 explained 15.7% of the total variance. There were high positive loadings for %OM, the macronutrients Mg and S, and the micronutrient Mn (Table 2). There was little variation among the clusters (Fig. 7) with regards to PC2, except the Park cluster which had lower values than the other four clusters. These results are confirmed by one-way ANOVA on individual nutrients (Fig. 7). PC3 explained 9.1% of the total variance. There was a high negative loading for Al (Table 2). The Garden and Lawn clusters had relatively high values (Fig. 8), indicative of relatively low levels of Al. In comparison, the Park and Forest clusters exhibited lower values, indicative of higher levels of Al, consistent with lower pH. This is confirmed by the one-ANOVA for Al (Fig. 8). Results from the principal components analysis reveal where soil management has been most intensive in the arboretum, in the Garden and Forest clusters. Soil amendments have significantly increased pH in these campus environments as well as a suite of macro- and micronutrients especially in the Garden sites, where rotating annual plantings require high soil fertility. Alternately, Lawns encompass a large arboretum area and are solely managed to ensure turfgrass growth. This monoculture requires a less extensive array of soil amendments and therefore soil management minimizes their application given their expense. While Parks form a distinct and varied campus ecosystem, the land cover is extensive in the University arboretum and is primarily composed of turfgrass some combination of shrubbery and trees. Given the areal extent and plantings, nutrient management likely mimics that of Lawn environments as indicated by soil chemistry results. Arboreta cluster soil properties were next compared to soil chemistry data in the regional agricultural soils to evaluate differences resulting from long-term campus arboretum management. Agricultural soil properties utilized in this comparison were obtained from two sources: soil series standards defined by the National Cooperative Soil Survey’s Soil Characterization Lab and 216 soil samples collected and processed by study co-authors from five surrounding Wicomico County farms. Soil series in the campus arboretum were identified for comparisons from the 1970 Wicomico County Soil Survey. These agricultural soil series analogous to campus soils prior to University founding include Klej, Evesboro, Rockwalkin and Fort Mott (Table 3). Discussion Comparisons indicate significant soil chemistry changes, especially in macro- and micronutrient levels in the arboretum, resulting from long-term landscape management. In most cases, Arboretum soil pHs were far higher than values measured in the agricultural analogs. Given the pre-campus agricultural soil’s acidity, and even greater natural acidity of pre-settlement eastern U.S. soils, large amounts of lime and/or dolomite have been applied to campus landscapes for years to raise pH to support robust vegetative across planting types. By the late 18 th century, German American farmers had introduced gypsum, commonly known as plaster of Paris, as a fertilizer. The United States imported large quantities of gypsum from Nova Scotia quarries during the late 18 th and early 19 th centuries (Halm 2020; Stone 1920). The long-term input of carbonates to manage soil acidity is especially important for the apparent historic trend on much of our site. This soil management practice continues in the Lawn and Garden clusters on campus. Enrichment in organic matter (OM) and high pH levels, particularly in Garden soils, was evident. While OM is normally acidifying, the basic response of the Garden soils has been likely intensified by the addition of organic matter (OM) which can increase CEC resulting in increased capacity for adsorption of basic ions, Ca and Mg raising pH. The negative relationship between OM amounts and pH is an example of both technopedogenesis and metapedogenesis. In the highly leached soils of the eastern United States, intensive liming supersedes the influence of OM enrichment, and is evidence of heavy-handed management. Prairie soils (i.e., Mollisols) are extensive in areas with more limited precipitation and also have high OM and pH levels. This result suggests a fundamental change in campus soil processes and the ongoing addition of generously applied OM by student workers continues to be witnessed by this study’s authors. The forested Fort Mott, Klej and Evesboro soils had 10 to 40 times less Ca than other land uses on site (Table 4). Still the Forest habitat soil, while less acid than Garden or Lawn sites, were much higher than archival wooded soil’s pH. Along with grooming, such as leaf removal and plantings, and treatment of exotics around the forested area, our Forest site’s proximity to extensive landscaping has elevated most basic cation concentrations to a lesser degree than other habitants but much more than forest sites near agricultural lands (Table 4). We next compared arboreta soil chemistry to soil characteristics obtained from prior research in Wicomico County in a Fort Mott soil (Geleta et al. 2014). Soil pH across the arboreta vegetation habitats was significantly higher than the sampled agricultural soils as was organic matter percentage, and calcium, iron, magnesium and zinc (Table 5). Arboretum soils have been consistently amended with lime and/or dolomite since management began increasing pH and also increasing calcium and magnesium levels in these soils in comparison with the surrounding region. Iron amounts are also far greater in campus habitats likely the result of continuing soil amendments but perhaps a relic of manure additions prior to University founding. Zinc quantities are also much higher in the arboretum land covers, strongly suggesting their addition through management given the native sandy, acidic soils and high precipitation amounts in the climate leading to leaching. Boron amounts in the arboretum are also much higher, especially in the Garden clusters, than the surrounding environment likely due to the addition of large amounts of organic material in soil management. Organic matter additions also likely explain the increased the amounts of nitrogen, phosphorus and sulfur in arboretum habitats. Aluminum amounts on campus were in most cases lower than the amounts found in agricultural sites which is consistent with high pH levels; a benefit of enrichment of OM and liming. Aluminum toxicity is a significant concern for many of the ornamental plants and non-native tree species found in arboretum planting. Interestingly, Garden Cluster 2 levels across almost all soil chemistry measures far exceeded other campus vegetation zones and measurements in nearby agricultural soils the result of intensive management for the bedded plantings. Conclusion Our results reveal the fundamental transformation of inherent soil chemistry properties through long-term anthropogenic management of the Salisbury University arboretum’s varied landscapes. Gardening for aesthetic sensibility seems to greatly modify soil chemistry enriching soil water nutrients. Because pH is a function of the many different soil processes, the negative relationship between pH and OM in garden soils may indicate a major short-circuiting of geochemical cycling with little understood long-term and short-term effects. Current soil properties in no way reflect parent material native characteristics or even the soil properties found in nearby heavily utilized agricultural land uses. Fewer studies looked at the effect of differing urban land uses (within variation); most studies tend to clump urban as one land use category. Our results align with similar findings in European and Asian greenspaces (Chupina 2020 ; Joimel et al. 2016 ; Scharenbroch at al. 2005). We believe that the soil management processes observed in our arboretum likely reflect similar management strategies employed in many urban greenspaces, including public parks, schoolyards, community gardens, athletic fields, and plazas and even cemeteries, thereby radically altering native landscapes through nutrient over enrichment. Even suburb landholders attempt to create an idealized natural environment; one so ingrained in the societal psyche that resultant ecologic shortcomings are not considered. Given the mobility of many of the over-enriched soil nutrients, these landscapes’ contributions to stormwater runoff is an overlooked consequence of commonly employed and intensive soil management practices. The contribution of these environments to changes in the water chemistry of retention features and piping feeding into local waterways and into surficial groundwater aquifers may also be as impactful than the frequently noted agricultural contributions. Additional research quantifying the areal extent of these landscapes within urban environments, and direct measurements of these areas’ impact on water chemistry during stormwater runoff events is increasingly important as urban populations grow and intensively managed greenspace incorporation into urban designs increase. The magnitude of the observed soil chemistry changes in our case study of a small University arboretum highlights the importance of understanding how these environments impact soil nutrient and hydrologic cycles within urban settings. Declarations Funding Declaration The only financial assistance provided for this research was obtained from the authors’ academic institution in the form of an internal grant to support undergraduate student research. The authors received no compensation, including consulting fees, equity and/or stock ownership nor non-financial support related to this research within the last three years. The authors hold no patents or copyrights relevant to the work described within the manuscript. Ethics, Consent to Participate, and Consent to Publish Declaration Ethics, Consent to Participate, and Consent to Publish declarations: not applicable. Author Contribution Each author contributed substantially to this research. S. G. and C. B. supervised data collection. C. B. , M. F., S. G. and D. H. provided input on data analysis, figure creation, and manuscript preparation/writing. Data Availability Soil chemistry data utilized in this research is available upon request from the authors. References Allen Co. (1899). W.F. Allen Jr. Strawberry Catalogue 1899 . Allen Co., Salisbury MD. Allen Co. (1917). Allen’s Book of Berries . Allen Co., Salisbury MD. Bassetti O.G., McDonough R.A., and Shakya K.M. (2023). Soil contamination in community gardens of Philadelphia and Pittsburgh, Pennsylvania. 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Trends in the occurrence and accumulation of microplastics in urban soil of Nanjing and their policy implications, Science of The Total Environment , Volume 903, 66144, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2023.166144. Zukswert, J. M., Hallett, R., Bailey, S. W., and Sonti, N. F. (2021). Using regional forest nutrition data to inform urban tree management in the northeastern United States, Urban Forestry & Urban Greening , Volume 57, 126917, ISSN 1618-8667,https://doi.org/10.1016/j.ufug.2020.126917. Tables Table 1. Mean 1 values for soil chemical properties across soil clusters in the Salisbury University Arboretum. Lawn cluster Park cluster Garden cluster 1 Garden cluster 2 Forest cluster Variable pH 7.45 a 2 6.05 b 7.10 a 7.10 ab 6.40 ab % OM 1.50 b 2.00 b 4.55 a 7.90 a 3.20 ab Al (ppm) 552 ab 557 a 481 b 463 ab 570 ab B (ppm) 0.323 c 0.233 d 0.510 b 0.928 a 0.485 b Ca (ppm) 1645 c 705 d 2662 ab 4183 a 1539 bc Cu (ppm) 2.92 b 2.18 b 2.85 b 18.9 a 4.21 b Fe (ppm) 155 c 148 c 212 b 240 b 410 a Mg (ppm) 153 a 96.7 b 192 a 209 a 144 b Mn (ppm) 27.5 a 15.8 b 21.7 a 29.1 a 24.7 a N (ppm) 7.37 bc 5.78 c 7.24 bc 14.7 a 9.84 ab P (ppm) 62.9 c 61.0 c 101.3 b 226.6 a 163.1 ab K (ppm) 57.2 b 44.6 c 62.9 ab 78.0 a 70.3 ab Na (ppm) 20.6 a 7.86 b 21.9 a 24.3 a 15.1 b S (ppm) 20.1 a 10.7 c 14.1 bc 16.8 ab 16.5 ab Zn (ppm) 5.27 c 7.01 c 13.5 b 48.5 a 23.0 ab CEC (meq 100g -1 ) 10.1 c 5.34 d 15.7 ab 23.8 a 10.1 bc 1 Median values shown for Al 2 Means (Tukey test) or medians (Dunn’s test) across clusters with different letters are significantly different (α = 0.05). Table 2. Results of principle component analysis of soil chemical properties, excluding heavy metals (Rotation Method: Varimax with Kaiser normalization; rotation converged in 5 iterations). Loadings of the first three components are shown (total variance explained = 72.2%). Component 1 2 3 OM 0.016 0.733 0.547 pH 0.864 0.088 0.302 Al -0.163 -0.004 -0.909 B 0.847 0.387 0.274 Ca 0.637 0.550 0.467 Cu 0.688 -0.055 0.111 Fe 0.669 0.158 -0.261 Mg 0.445 0.737 0.130 Mn 0.166 0.777 -0.175 N 0.651 0.266 0.264 P 0.864 0.080 0.018 K 0.632 0.502 -0.009 Na 0.094 0.573 0.415 S -0.018 0.794 0.006 Zn 0.930 0.066 0.035 Table 3. Salisbury University Arboretum Soil Series Soil Series Taxonomy Evesboro Mesic, coated Lamellic Quartzipsamments Fort Mott Loamy, siliceous, semiactive, mesic Arenic Hapludults Klej Mesic, coated Aquic Quartzipsamments Rockawalkin Loamy, mixed, semiactive, mesic Aquic Arenic Hapludults Source : United States Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center, Kellogg Soil Survey Lab, Lincoln, Nebraska, 68508-3866 Table 4. Arboreta Soil Cluster Properties Compared to Regional Soil Series (centimoles) Hall, Richard L., 1970-. Soil Survey, Wicomico County, Maryland. [Washington] :U.S. Soil Conservation Service; [for sale by the Supt. of Docs., U.S. Govt. Print. Off.], 1970. Lawn cluster Park cluster Garden cluster 1 Garden cluster 2 Forest cluster Evesboro Klej Rockawalkin Fort Mott Field Fort Mott Forest Al 6.13 6.19 5.34 5.14 6.33 0 0 0.40 0 2 Ca 8.23 3.53 13.31 20.92 7.70 1.00 0.20 1.40 2.20 0.70 Mg 1.28 0.81 1.60 1.74 1.20 0.20 0.20 0.70 0.50 0.30 K 0.15 0.11 0.16 0.20 0.18 trace 0.30 0.60 0.10 0.20 Na 0.09 0.03 0.10 0.11 0.07 0 0.30 0.20 trace trace P pH 7.45 6.05 7.1 7.1 6.4 5.4/6.0 3.1/3.8 4.9/5.0 5.9/6.4 4.0/4.6 Table 5. Arboreta Soil Cluster Properties Compared to Wicomico County Studies (ppm). Geleta et al 2014. Variable Lawn cluster Park cluster Garden cluster 1 Garden cluster 2 Forest cluster Graveyard (36) Ridge (36) Slope (36) Site CP (27) Site EM (27) Site LR (27) Site SD (27) Al 552.0 557.0 481.0 463.0 570.0 589.7 636.2 628.0 749.6 636.4 510.7 575.2 B 0.323 0.233 0.510 0.928 0.485 0.409 0.361 0.385 0.505 0.326 0.347 0.361 Ca 1645.0 705.0 2662.0 4183.0 1539.0 211.9 288.2 236.9 400.7 135.6 204.8 241.5 Cu 2.9 2.2 2.9 18.9 4.2 1.3 2.9 3.4 2.3 1.4 1.0 5.4 Fe 155.0 148.0 212.0 240.0 410.0 90.4 102.4 92.3 125.8 117.4 63.1 73.8 K 57.2 44.6 62.9 78.0 70.3 37.8 74.3 70.9 112.7 26.7 37.7 66.9 Mg 153.0 96.7 192.0 209.0 144.0 27.4 47.9 39.7 77.5 14.2 28.6 32.9 Mn 27.5 15.8 21.7 29.1 24.7 15.6 16.5 13.8 19.4 11.4 17.8 12.6 N 7.37 5.78 7.24 14.7 9.84 n.d. n.d. n.d. n.d. n.d. n.d. n.d. Na 20.6 7.86 21.9 24.3 15.1 n.d. n.d. n.d. n.d. n.d. n.d. n.d. OM% 1.5 2.0 4.6 7.9 3.2 1.2 0.4 0.4 1.1 0.7 0.3 0.6 P 62.9 61.0 101.3 226.6 163.1 39.9 94.0 75.1 46.3 114.8 76.0 41.4 pH 7.45 6.05 7.10 7.10 6.40 4.88 5.92 5.46 5.24 4.90 5.68 5.86 S 20.1 10.7 14.1 16.8 16.5 14.3 12.9 13.7 20.0 11.8 9.0 13.6 Zn 5.3 7.0 13.5 48.5 23.0 2.1 1.6 1.6 2.4 1.5 1.4 1.9 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-5448647","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":382504420,"identity":"f0fa0a57-1ddf-4b7f-821a-21708ff4c157","order_by":0,"name":"Daniel W. 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Folkoff","email":"","orcid":"","institution":"Salisbury University","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"E.","lastName":"Folkoff","suffix":""},{"id":382504422,"identity":"404ccc0c-b073-4207-a194-bf61d4764c42","order_by":2,"name":"Samuel B. Gelata","email":"","orcid":"","institution":"Salisbury University","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"B.","lastName":"Gelata","suffix":""},{"id":382504423,"identity":"225fc74f-0474-419d-97c8-02a4f96586d2","order_by":3,"name":"Christopher H. Briand","email":"","orcid":"","institution":"Salisbury University","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"H.","lastName":"Briand","suffix":""}],"badges":[],"createdAt":"2024-11-13 16:53:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5448647/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5448647/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72301599,"identity":"f8b0dde5-ab1b-413b-a664-ed50a25a5c79","added_by":"auto","created_at":"2024-12-25 01:47:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":921788,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003e Strawberries in a young orchard of peach trees on the W.F. Allen fruit farm (Allen Co. 1917). \u003cstrong\u003eb.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHorse manure brought in by rail for the fertilization of the W.F. Allen fruit farm (Allen Co. 1917). \u003cstrong\u003ec.\u003c/strong\u003e Workers in the strawberry field of the W.F. Allen fruit farm (facing south south west). The Allen residence can be seen on the top of the dune, surrounded on three sides by mature trees (Allen Co. 1921).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/092bb4ad8e7db9459d5428af.png"},{"id":72300687,"identity":"3b588b08-1c5d-4d1b-9bbd-9dcb30f8f294","added_by":"auto","created_at":"2024-12-25 01:23:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":676010,"visible":true,"origin":"","legend":"\u003cp\u003eAerial view of Maryland State Teachers College, now Salisbury University, showing\u003c/p\u003e\n\u003cp\u003eHolloway Hall (Walter C. Thurston, 1940s). Note the orchard to the right of Holloway Hall (Courtesy of the Edward H. Nabb Research Center for Delmarva History and Culture at Salisbury University).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/a5ab191f23296d0abfc8ff1e.png"},{"id":72300684,"identity":"0a61b741-51c5-41b6-ad7a-8659b8ce85f3","added_by":"auto","created_at":"2024-12-25 01:23:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":968734,"visible":true,"origin":"","legend":"\u003cp\u003eSalisbury University Arboretum Land Cover with Sample Sites.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/45857cbef98b0207909aaa3d.png"},{"id":72299980,"identity":"8430b28e-04bd-4e5c-8bca-01220909336b","added_by":"auto","created_at":"2024-12-25 01:15:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":35524,"visible":true,"origin":"","legend":"\u003cp\u003eDendrogram showing the relationship between soil samples based on soil chemistry. F = Forest, G = Garden L = Lawn and P = Park. Different colors indicate different clusters.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/d11e0e2fbe1810dcad96545d.png"},{"id":72301296,"identity":"8feabf5d-21c9-4a3e-aafb-e346236a7561","added_by":"auto","created_at":"2024-12-25 01:31:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":19912,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot of Principal Component 2 vs. Principal Component 1.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/f1a092f77dc75632c0d5c38f.png"},{"id":72301508,"identity":"3cdd1c4b-2385-4504-a74d-bf47d8efc06a","added_by":"auto","created_at":"2024-12-25 01:39:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":14904,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots showing the relationship between Principal Component 1 scores and the soil clusters (One-way ANOVA, F = 83.76, DF = 4, P \u0026lt; 0.001, r\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e = 84.87%; Bayesian ANOVA, BF\u003csub\u003e10\u003c/sub\u003e = 1.205 x 10\u003csup\u003e19\u003c/sup\u003e; BF\u003csub\u003e10\u003c/sub\u003e \u0026gt; 100, extreme evidence of variation among sites).\u0026nbsp; Means shown as ‘+’ symbols and outliers as solid circles.\u0026nbsp; Boxplots with different letters have means that are significantly different (Tukey-test, α = 0.05).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/d0b062125de855276ddcc861.png"},{"id":72299978,"identity":"8e05408d-786a-475a-bec9-888cc822d370","added_by":"auto","created_at":"2024-12-25 01:15:50","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":15416,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots showing the relationship between Principal Component 2 scores and the soil clusters (One-way ANOVA, \u003cem\u003eF\u003c/em\u003e = 26.05, DF = 4, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003er\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e = 62.94%; Bayesian ANOVA, BF\u003csub\u003e10\u003c/sub\u003e = 1.122 x 10\u003csup\u003e10\u003c/sup\u003e; BF\u003csub\u003e10\u003c/sub\u003e \u0026gt; 100, extreme evidence of variation among sites).\u0026nbsp; Means shown as ‘+’ symbols and outliers as solid circles.\u0026nbsp; Boxplots with different letters have means that are significantly different (Tukey-test, α = 0.05).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/6c9f1b84f409f302bf78e226.png"},{"id":72299984,"identity":"ae09705c-63af-4411-b0f2-e4c3cc9b83b7","added_by":"auto","created_at":"2024-12-25 01:15:50","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":16465,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots showing the relationship between Principal Component 3 scores and the soil clusters (One-way ANOVA, \u003cem\u003eF\u003c/em\u003e = 7.27, DF = 4, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003er\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e = 29.82%; Bayesian ANOVA, BF\u003csub\u003e10\u003c/sub\u003e = 117.4; BF\u003csub\u003e10\u003c/sub\u003e \u0026gt; 100, extreme evidence of variation among sites).\u0026nbsp; Means shown as ‘+’ symbols.\u0026nbsp; Boxplots with different letters have means that are significantly different (Tukey-test, α = 0.05).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/0d1a0c6cdc054d4b769e8631.png"},{"id":74448529,"identity":"e5df2475-315a-47a8-b6d4-2e67da9891f7","added_by":"auto","created_at":"2025-01-22 11:31:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3879526,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5448647/v1/6d799477-887c-46a9-84f1-e6487a308baf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Spatial variation of soil characteristics within an urban arboretum. A case study of the Salisbury University Arboretum, Maryland, U.S.A.","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePast research on urban soils focused on the methods by which soil fertility can be managed for agricultural production. \u0026nbsp;Far less attention has been devoted to the important role urban soils and their management serve in supporting urban land uses especially urban green spaces, public parks, arboreta, botanical gardens, corporate/government campuses, and zoned open spaces. Most urban soil research has focused on soil contamination by heavy metal accumulation through industrial and commercial land use and/or the impact of airborne deposition from dense transportation infrastructures of cities (Bassetti et al. 2023; Lupolt et al. 2021; Malone and Shakya 2024; Paltseva et al. 2020; Pouyat et al. 2015; Schwarz et al. 2016). \u0026nbsp;Heavy metal accumulations were found to increase across a comprehensive land use gradient in France, with the lower amounts measured in forests, grasslands and agricultural regions, including cultivated areas, orchards, and vineyards and the highest levels observed in urban, industrial, mining and military locations (Joimel et al. 2016). \u0026nbsp;These researchers and Bechet et al. (2020) also identified heavy metal contamination in European urban greenspace soils including gardens. \u0026nbsp;Urban land uses clearly affect urban soils, perhaps more than any other land uses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the continued growth of urbanized landscapes, research in this area is increasingly important to understanding how soils are managed in cities and suburbs. \u0026nbsp;While the overall percentage of urban land area on the Earth\u0026rsquo;s surface is small, approximately 2-3%, human impacts are amplified given the far greater population densities in these areas and the number of environmental interactions that occur. \u0026nbsp;Currently, about 3% of the United States is considered urban and this land cover type is projected to increase to 8% by 2050 (Malone et al. 2023). \u0026nbsp;Worldwide, urban areas are expanding faster than any other land use type (Tresch et al. 2019). \u0026nbsp;Urban soils are highly varied and are often found in small fragmented and isolated areas. \u0026nbsp;However, much larger parcels are also found in lightly disturbed settings such as greenspaces, undeveloped suburban-urban interface parcels, and wooded areas of residential, commercial, and/or industrial park parcels. \u0026nbsp;Of course, some soils in cities with large acreages are now legislatively protected such as wetlands and forest preserves. Unlike in surrounding rural environments, soils\u0026rsquo; role in urban landscapes is critical in supporting greenspace as recreational and psychological refuges for urban dwellers as well as an increasingly critical means to mitigate climate change (Mabon et al. 2019). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe arboretum on Salisbury University\u0026rsquo;s campus provides a unique setting to examine the impact of institutional management by comparing our campus\u0026rsquo; urban greenspace soil to the same\u003cs\u003e\u0026nbsp;\u003c/s\u003esoil types in the surrounding non-urban environment, most of which have been in long-term agricultural production. \u0026nbsp;Institutional management of arboretum soils has been varied to support different landscapes including woodlands, parks, gardens, and turfgrass. \u0026nbsp;In the arboretum, ecology, and soil management are often secondary to plant productivity to create scenic faux landscapes. \u0026nbsp;Exotics are lauded for their uniqueness; leaf removal and weeding are endemic to aesthetics, which are subject to management taste. \u0026nbsp;Gardening to create idealized landscapes is a tradition descended from landscape architecture principles used on the great British estates (e.g., Capability Brown\u0026rsquo;s on Blenheim Estate):\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;This blessed plot, this earth, this realm, this England\u0026rdquo;\u0026mdash;Brown planted the idealized England that Shakespeare had evoked. His parklands for aristos and nabobs \u0026ldquo;look so natural that we are instantly at ease in them\u0026rdquo; \u0026ndash; Rutherford (2016) \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe argue that institutional soil management practices modify soil properties to a higher degree than agricultural production on the same soils. \u0026nbsp;In this study, we directly compare soil physical and chemical properties in the same soil series on an urban college campus with those under agricultural land uses. \u0026nbsp;We believe the significant manner in which urban soil properties have been transformed, to a greater extent than in surrounding agricultural soils, is an overlooked consequence of urbanization with significant impacts on urban environmental quality and pollution especially runoff to the watershed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUrban/Anthropogenic Soils\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile urban soil contamination research is extensive and the results of anthropogenic soil modifications are reported for some areas and specific land uses, far less work directly examines how urban soil chemistry and physical properties have been modified in greenspaces, especially in the United States. \u0026nbsp;This gap likely results from the highly dynamic and intensive nature of anthropogenic soil management which results in significant spatial heterogeneity in soil geochemistry and physical properties in urban environments. \u0026nbsp;Howard (2020) identified three categories of urban anthropogenic soil (UAS) formation based on common processes: or the addition of organic matter to a native soil creating a new profile and thus a new soil type, technopedogenesis, whereby a soil profile changes through the mechanical mixture metapedogenesis of human-deposited sediments and debris which are often incorporated from distant sources and mixed with the native soil, and ekranopedogenesis, or the sealing of a pre-existing soil by pavement, concrete, or any other impervious material or structure. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eByrne (2007) states that managed soils exhibit rapidly changing characteristics and compositions reflecting current management goals and their often \u0026ldquo;ambiguous\u0026rdquo; pasts. Few researchers have access to pre-urbanization baseline soil characteristics to assess the impacts of anthropogenic soil management, especially in greenspaces such as parks and arboreta. Most studies, therefore, are relegated to comparisons between different locations and land use classes. In a review of anthropogenic soil properties in botanical gardens in subtropical Asia, the Mediterranean, and northern Europe, Chupina (2020) reports management-induced increases in humus content, higher pH, and more available nutrients especially phosphorus and sometimes potassium. Zukswert et al. (2021) examined soil characteristics for three native tree species (\u003cem\u003eAcer saccharum, Quercus alba, and Tsuga canadensis\u003c/em\u003e) in the northeastern United States comparing native forests to heavily managed habitats within the Boston arboretum. Intentional soil management led to increased pH, and more calcium and magnesium, with lower amounts of aluminum and manganese (to reduce toxicity). Interestingly, the water source used for irrigation was found to be treated to increase alkalinity. Joimel et al.\u0026rsquo;s (2016) land use transect detailing topsoil characteristics across French landscapes did not specifically focus on greenspaces but urban samples were included in these settings. This study also found higher pH in anthropized soils and that the incorporation of organic matter and mineral fertilizers increased carbon, nitrogen, and phosphorus amounts relative to non-urban soils. Phosphorus levels increased toward urban land use, reaching their maximum in garden soils. Byrne (2007) notes that native soil profiles and their ecological communities are altered through management by many common landscaping practices including the application of mulch, mulching grass clipping in lawn areas, and the use of heavy machinery which can reduce soil voids unless counteracted by aeration. \u0026nbsp;The increased organic matter and carbon result in higher net primary productivity above and below ground. Scharenbroch et al. (2005) also noted increased soil carbon and nitrogen pools and stated that rapid fluxes in these soil constituents through human management can rapidly alter soil characteristics and their resulting ecological communities. Soil degradation by erosion is widespread in both agricultural and urban soils, is historically a major problem, and is accelerated with the intensity of use in high-usage urban green spaces.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, anthropogenic soil processes are also impacted by temperature and moisture changes associated with urbanization (Seto et al., 2013). Urban soil temperatures are notably higher than rural environments, 1.2 to 2.1\u0026deg; C, and exhibit larger diurnal temperature swings to a greater depth, most notably beneath grass surfaces (Howard 2020). Soil moisture levels are often lower due to sealing, compaction, and stormwater management, although this change is often mitigated in urban greenspace environments with frequent irrigation and the construction of surficial stormwater retention features. Temperature and moisture regime changes impact organic matter decomposition rates, the composition and extent of macro- and micro-faunal colonies, as well as the weathering rates of the inorganic mineral components within soils. Cumulatively, these processes result in significant heterogeneity, at often very small scales, and while individual studies have examined the physical and chemical properties of urban soils, these properties are not inventoried and reported in the widely-used Web Soil Survey for researchers in the United States (Green et al. 2016). As noted in Joimel et al. (2016):\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Agriculture and forestry are often considered as having little disturbing effects on soil, whereas urban and industrial activities could potentially involve organic and inorganic pollution causing a significant alteration of physical, geochemical, and biological properties\u0026rdquo;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, we assess the dramatic changes to soil properties in different urban arboretum land covers induced by intensive soil management for almost 100 years. Soil sample characteristics in four different urban arboretum environments, woodlands, parks, lawns, and gardens, are compared to the chemical and physical properties of the same soils in agricultural and natural settings in the surrounding region experiencing less intensive management. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSite History and Description\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt is not possible to disentangle all long-term influences of \u0026ldquo;ambiguous past practices\u0026rdquo; in our study site but soil management probably has affected our results in some way (Byrne (2007). The current grounds of the University are within the boundaries of \u003cem\u003eWicomico Manor\u003c/em\u003e, a plantation laid out in 1674 in Old Somerset County, now Wicomico County, Maryland (Maryland Land Office. 1673-1679). \u0026nbsp;A 1756 map of Wicomico Manor shows sixteen tenant farms (Stiverson 1977). \u0026nbsp;The 1783 and 1793 Tax Assessments (General Assembly House of Delegates 1783, Reedy 1999) for tracts within the former \u003cem\u003eWicomico Manor\u003c/em\u003e indicated that general soil quality was sandy, with one tract, \u003cem\u003eToadvines Adventure\u003c/em\u003e, listed as \u0026ldquo;high level sandy land originally kind, but worn\u0026rdquo; suggesting continuous intensive agricultural use, likely related to years of soil erosion. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study area was initially forested, as was most of the Eastern United States, but in the early colonial period, forest clearance was soon followed by intensive agriculture (Briand and Folkoff 2019). In 1870, the first agricultural census of Wicomico Co. showed that 51.2% of county land was \u0026ldquo;Improved\u0026rdquo;, 47.3% \u0026ldquo;Woodland\u0026rdquo; and 1.5% \u0026ldquo;Other unimproved,\u0026rdquo; with the principal crops listed as maize, oats, potatoes, and wheat. \u0026nbsp;Maize accounted for 93% of the grain harvest in Wicomico Co. (U.S. Census Office 1872; Walker 1872). \u0026nbsp;By 1924, a year before the opening of Maryland State Normal School (precursor to Salisbury University), the principal county crops were sweet potatoes and maize however most of the campus area produced small fruit and orchard crops (USDA 1927). \u0026nbsp; Opened in 1925, the campus was initially built on an 11.7 ha parcel of farmland, that produced strawberries and other small fruit such as blackberries and raspberries, as well as peaches (Fig. 1.A.). Patterson (1907) noted that strawberry was the most extensively grown small fruit in Maryland. \u0026nbsp;Both plants and fresh fruit were shipped by rail to nearby metropolitan areas including Philadelphia and New York City (Allen Co. 1917; Maryland Inventory of Historic Properties 1993, 2000). \u0026nbsp;The farm was \u0026ldquo;well manured with N.Y. City stable manure and fertilizer\u0026rdquo; (Allen Co. 1899; Fig. 1.B.) and on an area of higher ground, farm owner W.F. Allen\u0026rsquo;s residence contained \u0026ldquo;a beautiful grove of pine, oak, cedar, and dogwood trees\u0026rdquo; (Maryland Inventory of Historic Properties. 2000; Fig. 1.C.). Our forest category, effectively a managed woodland given its land use history and subsequent management, abutted and was contiguous to the homestead site.\u003c/p\u003e\n\u003cp\u003eWith campus expansion in the last 100 years, the majority of the landscape has been transformed, resulting in a variety of land cover types commonly found on small, urban campuses. Construction began in the farm\u0026rsquo;s northwest with Holloway Hall and stretched eastward along College Avenue then southward following Camden Avenue (Fig. 2). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHolloway Hall (Walter C. Thurston, 1940s). \u0026nbsp;Note the orchard to the right of Holloway Hall (Courtesy of the Edward H. Nabb Research Center for Delmarva History and Culture at Salisbury University).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe first State Normal School at Salisbury yearbook stated: \u0026ldquo;The grounds comprise attractive lawns, ornamented with flowers, trees, shrubbery, and evergreens; playground areas, gardens, and an orchard\u0026rdquo; (Maryland State Normal School 1926). \u0026nbsp;Hay and corn were grown for the horses, and the orchard and vegetable garden provided fruit and vegetables for the students (Bradley 2002). \u0026nbsp;In all but the oldest, developed northern part of campus, the area was still an agricultural landscape (Hall 1970). This area has the campus\u0026rsquo; oldest building and was the first to transition from mainly agricultural use; the \u0026ldquo;great lawn\u0026rdquo; area west of the first building contains our largest area of grassland. \u0026nbsp;The campus currently occupies 73 ha but this study focuses on the 27.4 ha of the oldest part of campus. The 1970 Wicomico Soil Survey mapped agricultural soil series showing that much of the campus was not yet intensively developed. These campus soil series are also prevalent in the surrounding agricultural regions; therefore, we can compare how long-term arboretum management changed the soils\u0026rsquo; physical and chemical properties in comparison to agricultural land use. Moreover, plantings within the varied arboretum environments on campus required differing management techniques and inputs, therefore we can determine how soil properties across the campus environments have been modified.\u0026nbsp;\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cp\u003eThe 27.4 hectare (ha) vegetated region of campus, which comprises the Arboretum, is composed of four anthropogenically derived environments: Lawn (50.4%), Park (38.2%), Garden (8.7%) and Forest (2.7%). \u0026nbsp;Areal extents for these four Arboretum classes were delineated by air photo interpretation in a geographic information system using high-resolution aerial photography (e.g. 4-inch pixel spatial resolution) (Fig. 3). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSoil samples were taken during the fall of 2016 from four Lawn, six Parks, four Garden, and two Forest sites in the Salisbury University Arboretum (Fig. 3). \u0026nbsp;At each sample site, four composite samples (of four 2 cm diameter cores) were collected with a soil corer to a depth of 20 cm. \u0026nbsp;The soils were dried at 35\u0026deg; C, and ground to 2 mm. \u0026nbsp; Tests for soil chemical properties (pH, %OM, and extractableFig macro- and micronutrients) were conducted at AgroLabs, Milford DE following procedures for the Northeastern United States (NEC-67 1995). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePhysical and chemical properties for surrounding agricultural soils in the same soil series were obtained using an identical methodology during prior published research (Geleta et al. 2014). Baseline soil series properties were also downloaded from Soil Characterization Lab Data provided by the National Cooperative Soil Survey (https://ncsslabdatamart.sc.egov.usda.gov/). The soil series identified in the campus area prior to University founding included Klej, Fort Mott, Evesboro and Rockawalkin. Klej, with the minor components of Fort Mott and Evesboro, formed the wooded habitat (i.e., Forest) in the current campus arboretum while Fort Mott soil dominated the Lawn habitat and Rockawalkin soils is now urban soils within the Gardens (Table 3) (Hall, 1970). While soil series classification criteria have changed somewhat since 1970 and archival soil series were tested in the surrounding region not including actual soil samples on campus, we believe our comparisons are valid given the relative homogeneity of the region\u0026rsquo;s physical environment. Although soil mapping units have changed names and criteria with survey updates, the soil properties examined in a specific sampling location have not changed. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo determine the degree to which soil properties varied within and between the sampled campus environments, Cluster Analysis was performed on the aggregate soil sample data to determine the variation in soil properties between campus land uses?: individual land uses? should show similar soil properties changes due to individual management schemes. Clustering was performed using Ward\u0026rsquo;s linkage and squared Euclidean distance to delineate soil groups by properties and their linkage to campus arboretum environments. The resultant clusters were used as independent variables in Principal Components Analysis (PCA) by using a correlation matrix to standardize the variables. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne-way ANOVA and Tukey multiple comparison tests were done on both the individual variables and the coefficients of PC 1, 2 and 3 to evaluate collinearity and independent variable relationships. \u0026nbsp;A Kruskal-Wallis test followed by Dunn\u0026rsquo;s multiple comparisons test was used when data could not be normalized. \u0026nbsp;Bayesian ANOVA was also used to check the strength of the evidence for the alternative hypothesis. \u0026nbsp;Bayes factor (BF\u003csub\u003e10\u003c/sub\u003e) interpretation follows Wagenmakers et al. (2018). \u0026nbsp; Pearson Correlation Coefficients were calculated between all individual variables. \u0026nbsp;Data analyses were performed using Minitab 17 (Minitab 17 Statistical Software 2010), IBM SPSS Statistics 23 (IBM Corp. 2015) and JASP (JASP Team 2018).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFive clusters were identified that closely matched our anthropogenically derived ecosystem classification based on management (Fig. 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Lawn Cluster contained 81.3% of the lawn samples and the Park Cluster contained 90% of the park samples. Interestingly, the second Forest area we identified clustered with the Park samples, so this area was reclassified solely as park. There were two Garden Clusters. \u0026nbsp;Garden Cluster 1 was made up of 92% of the samples from Gardens 1-3, while Garden Cluster 2 contained all of the samples from Garden 4. \u0026nbsp;The remaining Forest Cluster contained all the natural forest samples. Average values of the soil chemistry variables, by cluster, are shown in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrincipal components analysis was used to understand variation in soil chemical characteristics across the aggregated soil samples. \u0026nbsp;The first three principal components accounted for 72.2% of the total variance. The remaining principal components each accounted for \u0026lt; 6 % of the variance. Bartlett\u0026rsquo;s test of sphericity (\u0026chi;2 = 838.1, DF = 105, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) indicated that correlations among the variables were sufficient for PCA, while the Kaiser-Meyer-Olkin measure verified sampling adequacy (KMO = 0.811; \u0026lsquo;great\u0026rsquo; according to Field 2009). PC1 explained 47.3% of the total variance. \u0026nbsp;There were high positive loadings for pH, the macronutrients Ca, N, P, K and the micronutrients B, Cu, Fe and Zn (Table 2). \u0026nbsp; PC1 represents the majority (60%) of the soil chemistry parameters measured which is consistent with Joimel et al.\u0026rsquo;s (2016) study of multiple land uses in a French landscape, suggesting decreased acidity and OM enrichment in anthropomorphic soils. \u0026nbsp;From the plot of PC2 vs. PC1 (Fig. 5) and the one-way ANOVA of the PC1 scores (Fig. 6), one can see that Garden cluster 2, had the highest overall levels of soil nutrients, followed by the Forest cluster and Garden cluster 1. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Lawn and Park clusters had the lowest levels of soil nutrients. \u0026nbsp;These results are confirmed by one-way ANOVA on individual nutrients, indicating that within highly anthropomorphic soils basic cations and OM increase with increasing management (Table. 1). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePC2 explained 15.7% of the total variance. \u0026nbsp;There were high positive loadings for %OM, the macronutrients Mg and S, and the micronutrient Mn (Table 2). \u0026nbsp;There was little variation among the clusters (Fig. 7) with regards to PC2, except the Park cluster which had lower values than the other four clusters. \u0026nbsp;These results are confirmed by one-way ANOVA on individual nutrients (Fig. 7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePC3 explained 9.1% of the total variance. \u0026nbsp;There was a high negative loading for Al (Table 2). The Garden and Lawn clusters had relatively high values (Fig. 8), indicative of relatively low levels of Al. In comparison, the Park and Forest clusters exhibited lower values, indicative of higher levels of Al, consistent with lower pH. \u0026nbsp;This is confirmed by the one-ANOVA for Al (Fig. 8).\u003c/p\u003e\n\u003cp\u003eResults from the principal components analysis reveal where soil management has been most intensive in the arboretum, in the Garden and Forest clusters. Soil amendments have significantly increased pH in these campus environments as well as a suite of macro- and micronutrients especially in the Garden sites, where rotating annual plantings require high soil fertility. Alternately, Lawns encompass a large arboretum area and are solely managed to ensure turfgrass growth. This monoculture requires a less extensive array of soil amendments and therefore soil management minimizes their application given their expense. \u0026nbsp;While Parks form a distinct and varied campus ecosystem, the land cover is extensive in the University arboretum and is primarily composed of turfgrass some combination of shrubbery and trees. \u0026nbsp; Given the areal extent and plantings, nutrient management likely mimics that of Lawn environments as indicated by soil chemistry results. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eArboreta cluster soil properties were next compared to soil chemistry data in the regional agricultural soils to evaluate differences resulting from long-term campus arboretum management. Agricultural soil properties utilized in this comparison were obtained from two sources: soil series standards defined by the National Cooperative Soil Survey\u0026rsquo;s Soil Characterization Lab and 216 soil samples collected and processed by study co-authors from five surrounding Wicomico County farms. \u0026nbsp;Soil series in the campus arboretum were identified for comparisons from the 1970 Wicomico County Soil Survey. \u0026nbsp;These agricultural soil series analogous to campus soils prior to University founding include Klej, Evesboro, Rockwalkin and Fort Mott (Table 3). \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eComparisons indicate significant soil chemistry changes, especially in macro- and micronutrient levels in the arboretum, resulting from long-term landscape management. In most cases, Arboretum soil pHs were far higher than values measured in the agricultural analogs. Given the pre-campus agricultural soil\u0026rsquo;s acidity, and even greater natural acidity of pre-settlement eastern U.S. soils, large amounts of lime and/or dolomite have been applied to campus landscapes for years to raise pH to support robust vegetative across planting types. By the late 18\u003csup\u003eth\u003c/sup\u003e century, German American farmers had introduced gypsum, commonly known as plaster of Paris, as a fertilizer. The United States imported large quantities of gypsum from Nova Scotia quarries during the late 18\u003csup\u003eth\u003c/sup\u003e and early 19\u003csup\u003eth\u003c/sup\u003e centuries (Halm 2020; Stone 1920). \u003c/p\u003e\n\n\u003cp\u003eThe long-term input of carbonates to manage soil acidity is especially important for the apparent historic trend on much of our site. This soil management practice continues in the Lawn and Garden clusters on campus. Enrichment in organic matter (OM) and high pH levels, particularly in Garden soils, was evident. While OM is normally acidifying, the basic response of the Garden soils has been likely intensified by the addition of organic matter (OM) which can increase CEC resulting in increased capacity for adsorption of basic ions, Ca and Mg raising pH. The negative relationship between OM amounts and pH is an example of both technopedogenesis and metapedogenesis. In the highly leached soils of the eastern United States, intensive liming supersedes the influence of OM enrichment, and is evidence of heavy-handed management. Prairie soils (i.e., Mollisols) are extensive in areas with more limited precipitation and also have high OM and pH levels. This result suggests a fundamental change in campus soil processes and the ongoing addition of generously applied OM by student workers continues to be witnessed by this study\u0026rsquo;s authors. The forested Fort Mott, Klej and Evesboro soils had 10 to 40 times less Ca than other land uses on site (Table 4). Still the Forest habitat soil, while less acid than Garden or Lawn sites, were much higher than archival wooded soil\u0026rsquo;s pH. Along with grooming, such as leaf removal and plantings, and treatment of exotics around the forested area, our Forest site\u0026rsquo;s proximity to extensive landscaping has elevated most basic cation concentrations to a lesser degree than other habitants but much more than forest sites near agricultural lands (Table 4).\u003c/p\u003e\n\u003cp\u003eWe next compared arboreta soil chemistry to soil characteristics obtained from prior research in Wicomico County in a Fort Mott soil (Geleta et al. 2014). Soil pH across the arboreta vegetation habitats was significantly higher than the sampled agricultural soils as was organic matter percentage, and calcium, iron, magnesium and zinc (Table 5). Arboretum soils have been consistently amended with lime and/or dolomite since management began increasing pH and also increasing calcium and magnesium levels in these soils in comparison with the surrounding region. Iron amounts are also far greater in campus habitats likely the result of continuing soil amendments but perhaps a relic of manure additions prior to University founding. Zinc quantities are also much higher in the arboretum land covers, strongly suggesting their addition through management given the native sandy, acidic soils and high precipitation amounts in the climate leading to leaching. Boron amounts in the arboretum are also much higher, especially in the Garden clusters, than the surrounding environment likely due to the addition of large amounts of organic material in soil management. Organic matter additions also likely explain the increased the amounts of nitrogen, phosphorus and sulfur in arboretum habitats. Aluminum amounts on campus were in most cases lower than the amounts found in agricultural sites which is consistent with high pH levels; a benefit of enrichment of OM and liming. Aluminum toxicity is a significant concern for many of the ornamental plants and non-native tree species found in arboretum planting. Interestingly, Garden Cluster 2 levels across almost all soil chemistry measures far exceeded other campus vegetation zones and measurements in nearby agricultural soils the result of intensive management for the bedded plantings. \u003c/p\u003e\n"},{"header":"Conclusion","content":"\u003cp\u003eOur results reveal the fundamental transformation of inherent soil chemistry properties through long-term anthropogenic management of the Salisbury University arboretum\u0026rsquo;s varied landscapes. Gardening for aesthetic sensibility seems to greatly modify soil chemistry enriching soil water nutrients. Because pH is a function of the many different soil processes, the negative relationship between pH and OM in garden soils may indicate a major short-circuiting of geochemical cycling with little understood long-term and short-term effects. Current soil properties in no way reflect parent material native characteristics or even the soil properties found in nearby heavily utilized agricultural land uses. Fewer studies looked at the effect of differing urban land uses (within variation); most studies tend to clump urban as one land use category. Our results align with similar findings in European and Asian greenspaces (Chupina \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Joimel et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Scharenbroch at al. 2005). We believe that the soil management processes observed in our arboretum likely reflect similar management strategies employed in many urban greenspaces, including public parks, schoolyards, community gardens, athletic fields, and plazas and even cemeteries, thereby radically altering native landscapes through nutrient over enrichment. Even suburb landholders attempt to create an idealized natural environment; one so ingrained in the societal psyche that resultant ecologic shortcomings are not considered.\u003c/p\u003e \u003cp\u003eGiven the mobility of many of the over-enriched soil nutrients, these landscapes\u0026rsquo; contributions to stormwater runoff is an overlooked consequence of commonly employed and intensive soil management practices. The contribution of these environments to changes in the water chemistry of retention features and piping feeding into local waterways and into surficial groundwater aquifers may also be as impactful than the frequently noted agricultural contributions. Additional research quantifying the areal extent of these landscapes within urban environments, and direct measurements of these areas\u0026rsquo; impact on water chemistry during stormwater runoff events is increasingly important as urban populations grow and intensively managed greenspace incorporation into urban designs increase. The magnitude of the observed soil chemistry changes in our case study of a small University arboretum highlights the importance of understanding how these environments impact soil nutrient and hydrologic cycles within urban settings.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe only financial assistance provided for this research was obtained from the authors\u0026rsquo; academic institution in the form of an internal grant to support undergraduate student research. The authors received no compensation, including consulting fees, equity and/or stock ownership nor non-financial support related to this research within the last three years. The authors hold no patents or copyrights relevant to the work described within the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics, Consent to Participate, and Consent to Publish declarations: not applicable.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eEach author contributed substantially to this research. S. G. and C. B. supervised data collection. C. B. , M. F., S. G. and D. H. provided input on data analysis, figure creation, and manuscript preparation/writing.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eSoil chemistry data utilized in this research is available upon request from the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAllen Co. (1899). W.F. Allen Jr. \u003cem\u003eStrawberry Catalogue 1899\u003c/em\u003e. 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Part II:: Example applications with JASP. \u003cem\u003ePsychometric Bulletin and Review\u0026nbsp;\u003c/em\u003e25:58-76. https://doi.org/10.3758/s13423-017-1323-7 \u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/li\u003e\n \u003cli\u003eWhitney, G. G., Adams, S. D. (1980). Man as a maker of new plant communities. Journal of \u003cem\u003eApplied Ecology\u003c/em\u003e 17:431\u0026ndash;448. http://www.jstor.org/stable/2402338\u003c/li\u003e\n \u003cli\u003eZhou, Y., Wang, T., Zou, M., Yin, Q., Jia, Z., Su, B., Zhang, Q., Chen, L., and Zhou, S. (2023). Trends in the occurrence and accumulation of microplastics in urban soil of Nanjing and their policy implications, \u003cem\u003eScience of The Total Environment\u003c/em\u003e, Volume 903, 66144,\u003c/li\u003e\n \u003cli\u003eISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2023.166144.\u003c/li\u003e\n \u003cli\u003eZukswert, J. M., Hallett, R., Bailey, S. W., and Sonti, N. F. (2021).\u003c/li\u003e\n \u003cli\u003eUsing regional forest nutrition data to inform urban tree management in the northeastern United States, \u003cem\u003eUrban Forestry \u0026amp; Urban Greening\u003c/em\u003e, Volume 57, 126917, ISSN 1618-8667,https://doi.org/10.1016/j.ufug.2020.126917.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTable 1. Mean\u003csup\u003e1\u003c/sup\u003e values for soil chemical properties across soil clusters in the Salisbury University Arboretum.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eLawn cluster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003ePark cluster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003eGarden\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ecluster 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003eGarden\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ecluster 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eForest cluster\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7.45 a\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e6.05 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e7.10 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e7.10 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e6.40 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e% OM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.50 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e2.00 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e4.55 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e7.90 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e3.20 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eAl (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e552 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e557 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e481 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e463 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e570 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eB (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.323 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.233 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e0.510 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e0.928 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.485 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eCa (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1645 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e705 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e2662 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e4183 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1539 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eCu (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2.92 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e2.18 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e2.85 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e18.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e4.21 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eFe (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e155 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e148 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e212 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e240 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e410 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMg (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e153 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e96.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e192 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e209 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e144 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMn (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e27.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e15.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e21.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e29.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e24.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eN (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7.37 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5.78 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e7.24 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e14.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e9.84 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eP (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e62.9 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e61.0 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e101.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e226.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e163.1 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eK (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e57.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e44.6 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e62.9 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e78.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e70.3 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNa (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e7.86 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e21.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e24.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e15.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eS (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e10.7 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e14.1 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e16.8 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e16.5 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eZn (ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e5.27 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e7.01 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e13.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e48.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e23.0 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eCEC (meq 100g\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e10.1 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e5.34 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e15.7 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e23.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e10.1 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMedian values shown for Al\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eMeans (Tukey test) or medians (Dunn\u0026rsquo;s test) across clusters with different letters are significantly different (\u0026alpha; = 0.05).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTable 2. \u0026nbsp;Results of principle component analysis of soil chemical properties, excluding heavy metals (Rotation Method: Varimax with Kaiser normalization; rotation converged in 5 iterations). \u0026nbsp;Loadings of the first three components are shown (total variance explained = 72.2%).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 472px;\"\u003e\n \u003cp\u003eComponent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 157px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eAl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eCa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eFe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eMn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eNa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e-0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eZn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 618px;\"\u003e\n \u003cp\u003eTable 3. Salisbury University Arboretum Soil Series\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoil Series\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTaxonomy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eEvesboro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003eMesic, coated Lamellic Quartzipsamments\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eFort Mott\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003eLoamy, siliceous, semiactive, mesic Arenic Hapludults\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eKlej\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003eMesic, coated Aquic Quartzipsamments\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eRockawalkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 462px;\"\u003e\n \u003cp\u003eLoamy, mixed, semiactive, mesic Aquic Arenic Hapludults\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e: United States Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center, Kellogg Soil Survey Lab, Lincoln, Nebraska, 68508-3866\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTable 4. Arboreta Soil Cluster Properties Compared to Regional Soil Series (centimoles)\u0026nbsp;Hall, Richard L., 1970-. Soil Survey, Wicomico County, Maryland. [Washington] :U.S. Soil Conservation Service; [for sale by the Supt. of Docs., U.S. Govt. Print. Off.], 1970.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLawn cluster\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePark cluster\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGarden cluster 1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGarden cluster 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eForest cluster\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvesboro\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKlej\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRockawalkin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFort Mott Field\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFort Mott Forest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e8.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e20.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e7.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5.4/6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e3.1/3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e4.9/5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e5.9/6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e4.0/4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTable 5. Arboreta Soil Cluster Properties Compared to Wicomico County Studies (ppm). Geleta et al 2014.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLawn cluster\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePark cluster\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGarden cluster 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGarden cluster 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eForest cluster\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGraveyard (36)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRidge (36)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSlope (36)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite CP (27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite EM (27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite LR (27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite SD (27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e552.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e557.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e481.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e463.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e570.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e589.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e636.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e628.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e749.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e636.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e510.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e575.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e1645.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e705.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2662.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e4183.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e1539.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e211.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e288.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e236.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e400.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e135.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e204.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e241.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e155.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e148.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e212.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e240.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e410.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e90.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e102.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e92.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e125.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e117.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e63.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e73.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e57.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e44.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e62.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e78.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e70.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e74.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e70.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e112.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e37.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e66.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e153.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e96.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e192.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e209.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e144.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e27.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e47.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e39.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e77.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e7.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e5.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e7.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e9.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n 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\u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"arboretum, land use history, soil management, soil nutrients, urban soil","lastPublishedDoi":"10.21203/rs.3.rs-5448647/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5448647/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe impact of long-term institutional management on soil chemistry within urban greenspaces is important to recognize given the proliferation of these urban planning methods in our ever-increasing urban environments. Most research on urban soils primarily focuses upon heavy metal pollutant accumulation and its relationship to industrial history and current environmental quality. Far less research, especially in the United States, examines the impact of soil and landscape management practices aimed at providing greenspaces for the residents of the ever-expanding urban environments. Moreover, systematic studies detailing resultant soil chemistry changes in managed greenspaces rarely exist given the lack of a non-urban analogs by which to compare. Also, land use histories of urban sites are often ambiguous and through time soil management practices vary as managers seek to create varied \u0026ldquo;aesthetically pleasing\u0026rdquo; landscapes in these institutional environments. This study details soil chemistry differences within the varied landscapes of an urban greenspace, a University arboretum, following almost 100 years of institutional soil management as the University expanded into former agriculture soils. Soil series mapped on the University campus prior to arboretum establishment remain agriculturally active in the surrounding community enabling our analysis. Results indicate the widespread addition of lime throughout arboretum environments has elevated soil pH thereby increasing the availability of macro- and micronutrients in vegetative communities including lawns, gardens and woodlands. Of concern, organic matter amounts are also elevated in the arboretum, fundamentally changing its natural inverse relationship with pH. The over enrichment of nutrients in this greenspace likely represents the outcome of anthropogenic management practices across many types of urban greenspaces. These soil chemistry modifications likely result in significant changes in runoff water chemistry thereby impacting local surface and groundwater resources.\u003c/p\u003e \u003cp\u003e\u0026ldquo;Urban soils often become defined by human activities and land use histories at a particular location rather than by the continuum of geologic processes.\u0026rdquo; \u0026ndash; Solano \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u0026ldquo;Urban plant communities are as much a product of the cultural environment as they are a part of the physical landscape.\u0026rdquo; \u0026ndash; Whitney and Adams \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1980\u003c/span\u003e\u003c/p\u003e","manuscriptTitle":"Spatial variation of soil characteristics within an urban arboretum. A case study of the Salisbury University Arboretum, Maryland, U.S.A.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-25 01:15:46","doi":"10.21203/rs.3.rs-5448647/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"20c29b0a-d9fa-47cd-bff5-e526b5364e8d","owner":[],"postedDate":"December 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-22T11:28:04+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-25 01:15:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5448647","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5448647","identity":"rs-5448647","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}