Vegetation And Soil Characteristics Of Pine Plantations And Naturally Regenerated Hardwood Forests On The Hoosier National Forest

During the 1930s there was widespread erosion on farmland and subsequent land abandonment. As a result, Pinus strobus L. (white pine), P. resinosa Aiton (red pine), and P. echinata Mill. (shortleaf pine) were planted in the Midwest to prevent erosion and rehabilitate sites. These species were selected due to their wide availability at the time. Currently, it is the goal of the U.S. Forest Service to provide a more natural and sustainable landscape, in part by removing these non-native Pinus stands and by replacing them with native hardwood species. The ultimate success of hardwood restoration depends, in part, on the lasting influence of Pinus stands on the soil where they were planted. This is worthy of concern because species of the family Pinaceae have a noted impact on nutrient availability, organic matter cycling, soil acidity, and soil buffering capacity compared to mesophytic hardwood species. This study investigates the impact that Pinus plantations have had on soil and vegetation communities compared to hardwood stands. I sampled old-field sites on mesic ridges and bottoms in the Hoosier National Forest that were planted to P. echinata and P. strobus, or naturally regenerated to mixed hardwood species. I measured overstory and understory vegetation, including saplings, seedlings and herbaceous-layer species. I measured environmental variables including soil, litter depth, and canopy openness. Soils were sampled and analyzed for macronutrients, micronutrients, pH, organic matter, exchange capacity, and Al. I used Non-metric multidimensional scaling (NMS) ordination and two-way ANOVA with Tukey multiple comparisons post hoc tests (a = 0.05) to statistically analyze data. Species composition under Pinus stands was distinctly different from that of hardwood stands. Pinus stands had lower concentrations of organic matter (OM; -21%), total carbon (TC; -29%), total nitrogen (TN; -30%), manganese (Mn; -37%), calcium (Ca; -24%), Zinc (Zn; -13%), and boron (B; -24%). Pinus stands had 2-5 times greater litter depth and 17% greater concentrations of Al compared to naturally regenerated hardwoods. As a result, Pinus stands displayed lower herbaceous-layer cover, species richness, and diversity. Hardwood stands contained a greater number of plant functional groups and had greater cover of graminoids, perennials, invasive species, and other mesophytic woody species including Acer saccharum Marshall (sugar maple), Lindera benzoin L. (spicebush) and Cornus florida L. (flowering dogwood). Herbaceous functional groups were more dominant on bottoms, while seedlings and saplings were more dominant on ridges. Ridge hardwood stands contained more mesophytic woody species, whereas ridge P. echinata stands contained a greater density of understory Quercus spp. and Fagus grandifolia Ehrh. (American beech). Soil fertility proved to be a driving factor in understory communities in my study. Infertile soil with deep litter hosted lower plant cover, but a greater density of Quercus spp., whereas more nutrient rich soils hosted mesophytic species. Bottomland soil was better buffered, allowing Acer spp. to ascend to the overstory with Pinus. The result was that, in bottoms, Pinus did not have as large an impact on soil or vegetation communities, resulting in greater similarity to hardwood stands

Successional Vegetation in the Jocassee Gorges, South Carolina

Multifactor ecosystem classification systems provide a three-pronged approach to identifying site units across the landscape based on repeating patterns of vegetation, soil, and geomorphology. Ecosystem classification models have been developed for a diversity of forest landscapes throughout North America, and are beneficial as an ecosystem management tool because the outcome yields data models that can be utilized by scientists and natural resource managers alike. In contrast to the enormous amount of classification studies undertaken in relatively stable, older-aged forests in eastern North America, there have been few studies that have employed multifactor classification techniques across a successional gradient, or heavily disturbed forests of the same region. The 17,500-ha Jocassee Gorges tract in upstate South Carolina represents an ideal landscape to examine both spatial and temporal variability in vegetation-environment relationships due to its myriad of landforms and long history of intense forest management over the past century. Successional vegetation patterns across this heavily disturbed, spatially heterogeneous landscape were examined using a multifactor landscape ecosystem classification (LEC) framework developed from ecosystem types described from older-aged (\u3e 75 years) stands. Ecosystem types for three age-classes of stand development post-timber harvest (10-25, 26-50, and 51-75 years) were determined by using environmental discriminants identified in the previous older-aged (reference) stand classification, and a total of 63 plots were established in previously logged stands between April 2003 and October 2004. Composition of ground flora and woody stem species, along with landform and soil datasets, was compared across age-classes within and among ecosystem types using non-metric multidimensional scaling, non-metric multi-response permutation procedures, and indicator species analysis. Woody stem composition remained similar between age-classes of xeric oak-blueberry and mesic hardwood-bloodroot ecosystem types, while woody stem composition was drastically different on early successional age-classes of the xeric chestnut oak-mountain laurel, submesic oak-mixed flora, and mesic hemlock-rhododendron ecosystem types. Ground flora composition differed between successional and reference age-class for each ecosystem type. Comparisons of ecosystem types across age-classes revealed the following trends: woody stem and ground flora species composition was similar between mesophytic ecosystem types, but differed between xerophytic types; by middle succession age-class (26-50 years) ground flora composition was distinct between all ecosystem types, except the submesic oak-mixed flora type which contained species diagnostic of all others; and by late succession age-class (51-75 years), both ground flora and woody stem composition differed between all ecosystem types. When ground flora and woody stems were placed into ecological species groups, canonical correlation analysis revealed similar trends in middle to late age-classes to those exhibited in reference age-classes. Overall, forest management has not had a severe effect on the disturbance regime across the Jocassee Gorges landscape to cause a significant shift in species composition within any ecosystem type. Although composition and diversity change across temporal gradients of each type, this is to be expected in a highly disturbed landscape of the southern Appalachian Mountains due to past natural and anthropogenic factors interrupting the process towards steady-state forests. Ecological classification systems are most effective in guiding ecosystem management processes when they are designed to document successional variation, as well as spatial heterogeneity, across landscapes. Adding a fourth (time-series) component to the LEC framework allows for a more accurate approach to documenting the biological diversity within a region, and serves as a more robust management tool because of its ability to predict vegetation across successional land units

Mapping the physiography of Michigan with GIS

Abstract: We present a new physiographic map of Michigan, that is also available interactively, online. Only four, small-scale physiographic maps of Michigan had been previously published. Our mapping project made use of a wide variety of spatial data, in a GIS environment, to visualize and delineate the physical landscape in more detail than has been done previously. We also examined many of the unit boundaries in the field, using a GIS running on a GPS-enabled laptop. Unlike previous physiographic maps, the online version of the map enables users to query the criteria used to define each of the 224 boundaries of its 10 major and 91 minor physiographic units. The interactive nature of the online version of the map is a unique enhancement to physiographic maps and mapping. Our study also provides data on the number and types of criteria used to define each of the 224 unit boundaries within the map. Most of our unit boundaries are based on data derived from 10-m raster elevation data and NRCS soils data, e.g., relief, soil wetness, escarpments, landscape fabric, and parent material characteristics. Data gleaned from NRCS SSURGO county-scale soil maps were a strength of the project