Effect of leaf-cutting ant nests on plant growth in an oligotrophic Amazon rain forest

This study examined whether high nutrient concentrations associated with leaf-cutting ant nests influence plant growth and plant water relations in Amazon rain forests. Three nests of Atta cephalotes were selected along with 31 Amaioua guianensis and Protium sp. trees that were grouped into trees near and distant (>10 m) from nests. A 15N leaf-labelling experiment confirmed that trees located near nests accessed nutrients from nests. Trees near nests exhibited higher relative growth rates (based on stem diameter increases) on average compared with trees further away; however this was significant for A. guianensis (near nest 0.224 y−1 and far from nest 0.036 y−1) but not so for Protium sp. (0.146 y−1 and 0.114 y−1 respectively). Water relations were similarly species-specific; for A. guianensis, near-nest individuals showed significantly higher sap flow rates (16 vs. 5 cm h−1), higher predawn/midday water potentials (−0.66 vs. −0.98 MPa) and lower foliar δ13C than trees further away indicating greater water uptake in proximity to the nests while the Protium sp. showed no significant difference except for carbon isotopes. This study thus shows that plant response to high nutrient concentrations in an oligotrophic ecosystem varies with species. Lower seedling abundance and species richness on nests as compared with further away suggests that while adult plants access subterranean nutrient pools, the nest surfaces themselves do not encourage plant establishment and growth.

Using soil profiles of seeds and molecular markers as proxies for sawgrass and wet prairie slough vegetation in Shark Slough, Everglades National Park

We measured the abundance of Cladium jamaicense (Crantz) seeds and three biomarkers in freshwater marsh soils in Shark River Slough (SRS), Everglades National Park (ENP) to determine the degree to which these paleoecological proxies reflect spatial and temporal variation in vegetation. We found that C. jamaicense seeds and the biomarkers Paq, total lignin phenols (TLP) and kaurenes analyzed from surface soils were all significantly correlated with extant aboveground C. jamaicense biomass quantified along a vegetation gradient from a C. jamaicense to a wet prairie/slough (WPS) community. Our results also suggest that these individual proxies may reflect vegetation over different spatial scales: Paq and kaurenes correlated most strongly (R 2 = 0.88 and 0.99, respectively) with vegetation within 1 m of a soil sample, while seeds and TLP reflected vegetation 0–20 m upstream of soil samples. These differences in the spatial scale depicted by the different proxies may be complementary in understanding aspects of historic landscape patterning. Soil profiles of short (25 cm) cores showed that downcore variation in C. jamaicense seeds was highly correlated with two of the three biomarkers (Paq, R 2 = 0.84, p<0.005; TLP, R 2 = 0.97, p<0.0001), and all four of the proxies indicated a recent increase in C. jamaicense biomass at the site. Using a preliminary depth-to-age relationship based on matching charcoal peaks with available ENP fire records (1980-present) specific to our coring site, we found that peak-depths in C. jamaicense seed concentration appeared to correspond to recent minimum water levels (e.g., 1989 and 2001), and low seed abundance corresponded to high water levels (e.g., 1995), consistent with the known autecology of C. jamaicense. In summary, the combination of C. jamaicense seeds and biomarkers may be useful for paleoecological reconstruction of vegetation change and ultimately in guaging the success of ongoing efforts to restore historic hydrologic conditions in the South Florida Everglades.

Tool cutting force modeling and wear estimation of micro -end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. ^ The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc. ^

Cutting through paradise: A political history of the Cross -Florida Barge Canal

The Cross-Florida Barge Canal, synonymous with boondoggle and waste, became the cause celebre of environmental activism in Florida of the late 1960s. Dramatic changes in Florida's and the nation's politics doomed the CFBC to failure. My purpose is to place in national context the important developments and personalities of Florida's most important environmental controversy. ^ The methodology involved a series of interviews with the most important actors in the canal drama and the environmental movement. Also utilized were regional collections in Florida Public Libraries, the Florida State Archives, personal papers housed at the University of Florida and Corps of Engineers documents. Results showed a clear connection between Florida activism and national environmental policy through the influence of key individuals. I concluded that the CFBC acted as a catalyst to Florida's environmental movement, serving as an indicator of a larger political change from the New Deal coalition to the Republican realignment of 1968. ^

Tool cutting force modeling and wear estimation of micro-end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc.