Vegetation and hydrologic influences on carbon and nitrogen in subsurface water of a forested riparian wetland

Vegetation communities affect carbon and nitrogen dynamics in the subsurface water of mineral wetlands through the quality of their litter, their uptake of nutrients, root exudation and their effects on redox potential. However, vegetation influence on subsurface nutrient dynamics is often overshadowed by the influences of hydrology, soils and geology on nutrient dynamics. The effects of vegetation communities on carbon and nitrogen dynamics are important to consider when managing land that may change vegetation type or quantity so that wetland ecosystem functions can be retained. This study was established to determine the magnitude of the influences and interaction of vegetation cover and hydrology, in the form of water table fluctuations, on carbon and nitrogen dynamics in a northern forested riparian wetland. Dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), nitrate (NO3-) and ammonium (NH4+) concentrations were collected from a piezometer network in four different vegetation communities and were found to show complex responses to vegetation cover and water table fluctuations. Dissolved organic carbon, DIC, NO3- and NH4+ concentrations were influenced by forest vegetation cover. Both NO3- and NH4+ were also influenced by water table fluctuations. However, for DOC and NH4+ concentrations there appeared to be more complex interactions than were measured by this study. The results of canonical correspondence analysis (CCA) and analysis of variance (ANOVA) did not correspond in relationship to the significance of vegetation communities. Dissolved inorganic carbon was influenced by an interaction between vegetation cover and water table fluctuations. More hydrological information is needed to make stronger conclusions about the relationship between vegetation and hydrology in controlling carbon and nitrogen dynamics in a forested riparian wetland.

Modeling and classifying variable width riparian zones utilizing digital elevation models, flood height data, digital soil data and national wetlands inventory : a new approach for riparian zone delineation

Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

Landscape and forest structure at moose mortality sites on Isle Royale National Park. A LiDAR based assessment

Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

EXPLORING CHANGES IN DETRITAL FLOCCULENT LAYER DYNAMICS DUE TO SHIFTS IN MACROPHYTE COMMUNITIES IN THE NORTHERN EVERGLADES

A shift in plant communities of the Water Conservation Areas (WCAs) within the Everglades has been linked to changes in hydrology and high levels of nutrient loading from surrounding agicultural areas. This has resulted in the encroachment of dense cattail stands (Typha domingensis) into areas that had previously been a ridge and slough landscape populated primarily by native sawgrass (Cladium jamaicense). In order to study ecological management solutions in this area, WCA-2A was broken into study plots; several of which became open water areas through the application of herbicide and burning regimens. The open water areas allowed for Chara spp (a submersed algal species) to replace Typha domingensis as the dominant macrophyte. This study investigated the polymer and ionic profiles of Chara spp, Typha domingensis and Cladium jamaicense and their contributions to detrital flocculent (floc) in the study plots where they are the dominant macrophytes. Floc is not only an important food source for aquatic species; it also supports many algal, fungal and bacterial communities. Data gathered in this study indicated that the floc sample from a phosphorus enriched open water study plot (EO1) where Chara spp was the dominant macrophyte may contain cell wall polymers from sources other than Chara spp (most likely Typha domingensis), while the chemical and polymeric profile of the floc of the study plot where Typha domingensis is the dominant macrophyte (EC1) suggests that the floc layer has contributions from algal sources as well as Typha domingensis. Additionally, monoclonal antibodies to Arabinoglalactan protein (AGP) and (1,4)-β-D galactan were identified as possible biomarkers for distinguishing algal dominated floc layers from layers dominated by emergent vegetation. Calcium labeling could be a useful tool for this as well because of the high amount of Ca2+ associated with Chara spp cell walls. When looking into the soluble phosphorus content of the macrophytes and paired floc samples of WCA-2A, it was found that Chara spp may be contributing a greater amount of Ca-bound phosphorus to floc layers where it is the dominant macrophyte when compared to floc layers from study plots dominated by emergent macrophytes. Floc layers also appear to be acting as a nutrient sink for soluble phosphorus. The findings of this study support the overall hypothesis that the shift from native emergent macrophyte communities to submersed macrophyte communities in study sites of the northern Everglades is affecting the polymeric/chemical profile and ionic content of detrital floc layers. The effects of this shift may contribute to changes in complex flocculent community dynamics.

MIGRATION PATTERNS AMONG YOUNG ADULTS IN THE UNITED STATES: ENVIRONMENTAL, SOCIAL, AND ECONOMIC EXPLANATIONS

Young adult migration is a key factor in community development. The goal of this paper is to study what kinds of places attract young adults and what kinds are losing them. Linear regression is conducted to analyze what place-specific factors explain migration patterns among young adults. These factors include economic, social, and environmental variables. This study finds that social and environmental factors are just as important as economic ones. Specifically, employment in the arts increases young adult net migration. Environmental variables, for example, natural amenities and protected federal lands are particularly important in rural settings in attracting young adults. These findings suggest that policy makers interested in attracting and retaining young adults should pay closer attention to social and environmental factors and consider creating more opportunities for arts employment in general. For rural areas, improving the attractiveness of natural amenities and better protection of federal lands is also recommended.