Buckwheat as a Cover Crop in Florida: Mycorrhizal Status, Soil Analysis, and Economic Assessment

This thesis analyses buckwheat as a cover crop in Florida. The study was designed to demonstrate: soil enrichment with nutrients, mycorrhizal arbuscular fungi interactions, growth in different soil types, temperature limitations in Florida, and economic benefits for farmers. Buckwheat was planted at the FIU organic garden (Miami, FL) in early November and harvested in middle December. After incorporation of buckwheat residues, soil analyses indicated the ability of buckwheat to enrich soil with major nutrients, in particular, phosphorus. Symbiosis with arbuscular mycorrhizal fungi increased inorganic phosphorus uptake and plant growth. Regression analysis on aboveground buckwheat biomass weight and soil characteristics showed that high soil pH was the major limiting factor that affected buckwheat growth. Spatial analysis illustrated that buckwheat could be planted in South Florida throughout the year but might not be planted in North and Central Florida in winter. An economic assessment proved buckwheat to be a profitable cover crop.

Knowledge discovery using multiple sources of biological data

The primary aim of this dissertation is to develop data mining tools for knowledge discovery in biomedical data when multiple (homogeneous or heterogeneous) sources of data are available. The central hypothesis is that, when information from multiple sources of data are used appropriately and effectively, knowledge discovery can be better achieved than what is possible from only a single source. ^ Recent advances in high-throughput technology have enabled biomedical researchers to generate large volumes of diverse types of data on a genome-wide scale. These data include DNA sequences, gene expression measurements, and much more; they provide the motivation for building analysis tools to elucidate the modular organization of the cell. The challenges include efficiently and accurately extracting information from the multiple data sources; representing the information effectively, developing analytical tools, and interpreting the results in the context of the domain. ^ The first part considers the application of feature-level integration to design classifiers that discriminate between soil types. The machine learning tools, SVM and KNN, were used to successfully distinguish between several soil samples. ^ The second part considers clustering using multiple heterogeneous data sources. The resulting Multi-Source Clustering (MSC) algorithm was shown to have a better performance than clustering methods that use only a single data source or a simple feature-level integration of heterogeneous data sources. ^ The third part proposes a new approach to effectively incorporate incomplete data into clustering analysis. Adapted from K-means algorithm, the Generalized Constrained Clustering (GCC) algorithm makes use of incomplete data in the form of constraints to perform exploratory analysis. Novel approaches for extracting constraints were proposed. For sufficiently large constraint sets, the GCC algorithm outperformed the MSC algorithm. ^ The last part considers the problem of providing a theme-specific environment for mining multi-source biomedical data. The database called PlasmoTFBM, focusing on gene regulation of Plasmodium falciparum, contains diverse information and has a simple interface to allow biologists to explore the data. It provided a framework for comparing different analytical tools for predicting regulatory elements and for designing useful data mining tools. ^ The conclusion is that the experiments reported in this dissertation strongly support the central hypothesis.^

Forest Resource Islands in a Sub-tropical Marsh: Soil–Site Relationships in Everglades Hardwood Hammocks

Spatial heterogeneity in soils is often characterized by the presence of resource-enriched patches ranging in size from a single shrub to wooded thickets. If the patches persist long enough, the primary constraint on production may transition from one limiting environmental factor to another. Tree islands that are scattered throughout the Florida Everglades basin comprise nutrient-enriched patches, or resource islands, in P-limited oligotrophic marshes. We used principal component analysis and multiple regressions to characterize the belowground environment (soil, hydrology) of one type of tree island, hardwood hammocks, and examined its relationship with the three structural variables (basal area, biomass, and canopy height) indicative of site productivity. Hardwood hammocks in the southern Everglades grow on two distinct soil types. The first, consisting of shallow, organic, relatively low-P soils, is common in the seasonally flooded Marl Prairie landscape. In contrast, hammocks on islands embedded in long hydroperiod marsh have deeper, alkaline, mineral soils with extremely high P concentrations. However, this edaphic variation does not translate simply into differences in forest structure and production. Relative water depth was unrelated to all measures of forest structure and so was soil P, but the non-carbonate component of the mineral soil fraction exhibited a strong positive relationship with canopy height. The development of P-enriched forest resource islands in the Everglades marsh is accompanied by the buildup of a mineral soil; however, limitations on growth in mature islands appear to differ substantively from those that dominate incipient stages in the transformation from marsh to forest. Key words: resource island; tree

Soil carbon dynamics in primary and secondary tropical forests in Colombia

Soils play a central role in the dynamics of biospheric carbon and in climate change. They contain the largest carbon stock of terrestrial ecosystems and return to the atmosphere a significant proportion of carbon fixed by photosynthesis. Soils of tropical forests are tremendously important in the carbon cycle because they receive the largest organic matter inputs, they have the largest respiration rates, and they are among the largest carbon reservoirs among world soils. This research assesses the main components of the soil carbon dynamics in primary (PF) and secondary (SF) tropical forests in Colombia. I evaluated the production, stocks, and decomposition rates of aboveground detritus as well as the stocks, growth, mortality, and decomposition of fine roots in these two forest types. Soil carbon outputs were evaluated as total soil, heterotrophic, and root respiration. The stocks of soil organic carbon down to 4 m deep in these two cover types and in degraded pastures (PAS) were also evaluated. ^ Soil inputs of organic carbon from above and belowground sources were lower in SF than in PF. Litterfall in SF was 58% and production of fine root detritus was 60% of that in PF. When production of woody detritus and palm fronds was considered, the difference between these forest types was even larger. However, outputs of mineral carbon through heterotrophic soil respiration were similar; in SF they equaled 97% of those in PF. As a result, soil carbon balance was positive in PF and negative in SF. Despite that soil carbon balances suggest that soils of SF are losing carbon, soil carbon stocks of SF were higher than of degraded pastures, suggesting that they have already started to recover soil carbon stocks lost under degraded pastures. This discrepancy can be partially explained by the effect of drier conditions on heterotrophic soil respiration as a consequence of a moderate El Niño event during the period of soil respiration measurements. The positive carbon balance in soils of PF despite the El Niño event, suggests that soils of PF accumulated about 664 Kg C ha−1 yr−1. Therefore, soil carbon dynamics mainly depended on successional status of vegetation and on climatic conditions. ^

Effect of Water Management on Interannual Variation in Bulk Soil Properties from the Eastern Coastal Everglades

We examined interannual variation in soil properties from wetlands occurring in adjacent drainage basins from the southeastern Everglades. Triplicate 10-cm soil cores were collected, homogenized, and analyzed during the wet season 2006–2010 from five freshwater sawgrass wetland marshes and three estuarine mangrove forests. Soil bulk density from the Taylor Slough basin ranged from 0.15 gm-cm−3 to 0.5 gm-cm−3, was higher than from the Panhandle basin every year, and generally increased throughout the study period. Organic matter as a percent loss on ignition ranged from 7 % to 12 % from freshwater marshes and from 13 % to 56 % from estuarine mangroves. Extractable iron in soils was similar among drainage basins and wetland types, typically ranging from 0.6 to 2.0 g Fe kg−1. In contrast, inorganic sulfur was on average over four times higher from estuarine soils relative to freshwater, and was positively correlated with soil organic matter. Finally total soil phosphorus (P) was lower in freshwater soils relative to estuarine soils (84 ± 5 versus 326 ± 32 mg P kg−1). Total P from the freshwater marshes in the Panhandle basin rose throughout the study period from 54.7 ± 8.4 to 107 ± 17 mg P kg−1, a possible outcome of differences in water management between drainage basins.