Raúl Macchiavelli

Estimating preferential flow in karstic aquifers using statistical mixed models.

Karst aquifers are highly productive groundwater systems often associated with conduit flow. These systems can be highly vulnerable to contamination, resulting in a high potential for contaminant exposure to humans and ecosystems. This work develops statistical models to spatially characterize flow and transport patterns in karstified limestone and determines the effect of aquifer flow rates on these patterns. A laboratory-scale Geo-HydroBed model is used to simulate flow and transport processes in a karstic limestone unit. The model consists of stainless steel tanks containing a karstified limestone block collected from a karst aquifer formation in northern Puerto Rico. Experimental work involves making a series of flow and tracer injections, while monitoring hydraulic and tracer response spatially and temporally. Statistical mixed models (SMMs) are applied to hydraulic data to determine likely pathways of preferential flow in the limestone units. The models indicate a highly heterogeneous system with dominant, flow-dependent preferential flow regions. Results indicate that regions of preferential flow tend to expand at higher groundwater flow rates, suggesting a greater volume of the system being flushed by flowing water at higher rates. Spatial and temporal distribution of tracer concentrations indicates the presence of conduit-like and diffuse flow transport in the system, supporting the notion of both combined transport mechanisms in the limestone unit. The temporal response of tracer concentrations at different locations in the model coincide with, and confirms the preferential flow distribution generated with the SMMs used in the study.

Recognition of Instars and Adult Trap Catches of Cosmopolites sordidus (Coleoptera: Curculionidae) from Plantains in Puerto Rico

Abstract On the basis of head capsule widths of field-collected larvae, Cosmopolites sordidus (Germar) (Coleoptera: Curculionidae) was found to have five instars. Mean head capsule widths were 0.44, 0.71, 1.04, 1.48, and 1.85 mm for the first to fifth instars, respectively. The greatest growth ratio was recorded between the first and second instar. Adult C. sordidus densities reached a peak in January with 2.4 adults per trap, and the lowest density recorded was during April with 0.7 adults per trap. Adult captures seems to be influenced by precipitation with higher captures after precipitation events.

Potential of trees, grasses, and turf legumes for restoring eroded soils

The performance and development potential of seven trees, two grasses and five turf legumes were evaluated in three highly eroded landscapes of Puerto Rico. Species development during the first year of establishment was adequate at the Corozal site, intermediate in Vega Baja and poor at the Orocovis location. Tree species Albicia procera and Leucaena leucocephala K 636 grew particularly well at Corozal and Vega Baja. At the Corozal site, grasses and turf legumes were significantly better for reducing soil erosion than trees and bare ground. Brachiaria decumbens did not allow sediment losses during a highly rainy period at this locale; it was significantly (P<0.01) superior to all tree species, one cover legume and bare ground. Soil dissolved organic carbon (SDOC) estimates were significantly (P<0.01) higher for ground cover species than for tree species and bare ground. Soil chemical composition of all eroded soil sites under consideration did not explain the changes in performance and development of the evaluated germplasm.

Center for Resources in General Education (CIVIS): Towards student success in General and STEM education

Researchers at the University of Puerto Rico-Mayaguez (UPRM) have conducted an analysis of student needs and have identified strategies to respond to the General and STEM education challenges at UPRM. A Center for Resources in General Education (CIVIS) has been established to deal with these challenges by providing students and professors a new, integrated perspective (focused on General and STEM skills) of the curriculum, and by enabling student academic success through various learning opportunities. CIVIS brings together faculty from Agricultural Sciences, Arts and Sciences, Business Administration and Engineering in order to develop activities that provide interdisciplinary and global perspectives to UPRMs General Education. The Center focuses on two main activities: (1) Paths to Student Success, and (2) Sustainable Context with the use of student learning modules tying the activities together. All initiatives of the Center are supported by a recent grant from the U.S. Department of Education, and are based on the success of initiatives that have been previously tested at a smaller scale at UPRM. CIVIS provides resources to expand the reach of those initiatives and will ensure sustainability by the institutionalization of those initiatives.

MODEL SELECTION TECHNIQUES FOR REPEATED MEASURES COVARIANCE STRUCTURES

A parsimonious covariance structure of repeated measures is often sought for purposes of increased power for testing hypotheses about the means, and for insight into the stochastic processes governing the repeated measures. For normal data, model selection is often based upon likelihood ratio tests or information criteria derived from the likelihood, sometimes supplemented with graphical plots of correlations and partial correlations. We exploit the ordered nature of repeated measures to decompose the likelihood ratio goodness-of-fit test statistic, and display graphical fingerprints associated with the covariance structures to help detect covariance structure misspecification, in order to provide guidance in choosing an appropriate structure for the data. The proposed methodology is illustrated with simulated repeated measures data and then applied to an experiment to compare tillage methods of pasture establishment.

The influence of hydrogeological and anthropogenic variables on phthalate contamination in eogenetic karst groundwater systems

This study investigates the occurrence of six phthalates and distribution of the three most-detected phthalates in the karst region of northern Puerto Rico (KRNPR) using data from historical records and current field measurements. Statistical data analyses, including ANOVA, Chi-Square, and logistic regression models are used to examine the major factors affecting the presence and concentrations of phthalates in the KRNPR. The most detected phthalates include DEHP, DBP, and DEP. At least one phthalate specie is detected above DL in 7% of the samples and 24% of the sampling sites. Concentrations of total phthalates average 5.08 ± 1.37 μg L-1, and range from 0.093 to 58.4 μg L-1. The analysis shows extensive spatial and temporal presence of phthalates resulting from dispersed phthalate sources throughout the karst aquifers. Hydrogeological factors are significantly more important in predicting the presence and concentrations of phthalates in eogenetic karst aquifers than anthropogenic factors. Among the hydrogeological factors, time of detection and hydraulic conductivities larger than 300 m d-1 are the most influential factors. Persistent presence through time reflects continuous sources of phthalates entering the aquifers and a high capacity of the karst aquifers to store and slowly release contaminants for long periods of time. The influence of hydraulic conductivity reveals the importance of contaminant fate and transport mechanisms from contamination sources. This study improves the understanding of factors affecting the spatial variability and fate of phthalates in karst aquifers, and allows us to better predict their occurrence based on these factors.

NONLINEAR MODELS WITH REPEATED MEASURES FOR ANALYZING DISEASE PROGRESS IN PLANT EPIDEMIOLOGY

Nonlinear models are commonly used in plant disease epidemiology to model temporal changes in the proportion of diseased plants (disease index). Most of the times they are fit using linearizing transformations or nonlinear least squares. These approaches assume that the disease index has a normal distribution, that they are independent and that they have constant variance. None of these assumptions can be justified in disease indices. In this paper we apply different strategies to model the progress of papaya ring spot virus in papaya. Using the logistic model we compare different strategies using the SAS System. Marginal (population average) and subjectspecific interpretations of the models are discussed.