Allocation of Biomass and Net Primary Productivity of Mangrove Forests along Environmental Gradients in the Florida Coastal Everglades, USA

Vegetation patterns of mangroves in the Florida Coastal Everglades (FCE) result from the interaction of environmental gradients and natural disturbances (i.e., hurricanes), creating an array of distinct riverine and scrub mangroves across the landscape. We investigated how landscape patterns of biomass and total net primary productivity (NPPT), including allocation in above- and below-ground mangrove components, vary inter-annually (2001–2004) across gradients in soil properties and hydroperiod in two distinct FCE basins: Shark River Estuary and Taylor River Slough. We propose that the allocation of belowground biomass and productivity (NPPB) relative to aboveground allocation is greater in regions with P limitation and permanent flooding. Porewater sulfide was significantly higher in Taylor River (1.2 ± 0.3 mM) compared to Shark River (0.1 ± 0.03 mM) indicating the lack of a tidal signature and more permanent flooding in this basin. There was a decrease in soil P density and corresponding increase in soil N:P from the mouth (28) to upstream locations (46–105) in Shark River that was consistent with previous results in this region. Taylor River sites showed the highest P limitation (soil N:P > 60). Average NPPT was double in higher P environments (17.0 ± 1.1 Mg ha−1 yr−1) compared to lower P regions (8.3 ± 0.3 Mg ha−1 yr−1). Root biomass to aboveground wood biomass (BGB:AWB) ratio was 17 times higher in P-limited environments demonstrating the allocation strategies of mangroves under resource limitation. Riverine mangroves allocated most of the NPPT to aboveground (69%) while scrub mangroves showed the highest allocation to belowground (58%). The total production to biomass (P:B) ratios were lower in Shark River sites (0.11 yr−1); whereas in Taylor River sites P:B ratios were higher and more variable (0.13–0.24 yr−1). Our results suggest that the interaction of lower P availability in Taylor River relative to Shark River basin, along with higher sulfide and permanent flooding account for higher allocation of belowground biomass and production, at expenses of aboveground growth and wood biomass. These distinct patterns of carbon partitioning between riverine and scrub mangroves in response to environmental stress support our hypothesis that belowground allocation is a significant contribution to soil carbon storage in forested wetlands across FCE, particularly in P-limited scrub mangroves. Elucidating these biomass strategies will improve analysis of carbon budgets (storage and production) in neotropical mangroves and understanding what conditions lead to net carbon sinks in the tropical coastal zone.

The impacts of trade policy reforms on the Sri Lankan economy

This dissertation presents an analysis of the impacts of trade policy reforms in Sri Lanka. A Computable General Equilibrium (CGE) model is constructed with detailed description of the domestic production structure and foreign trade. The model is then used to investigate the effects of trade policy reforms on resource allocation and welfare.^ Prior to 1977, Sri Lanka maintained stringent control over its imports through rigid quantitative restrictions. A new economic policy reform package was introduced in 1977, and it shifted Sri Lanka's development strategy toward an export oriented policy regime. The shift of policy focus from a restrictive trade regime toward a more open trade regime is expected to have a significant impact on the volume of external trade, domestic production structure, allocation of resources, and social welfare.^ Simulations are carried out to assess the effects of three major policy reforms: (1) a devaluation of the Sri Lanka rupee, (2) a partial or a complete elimination of export duties, and (3) a devaluation-cum-removal of export duties.^ Simulation results indicate that the macroeconomic impact of a devaluation-cum-removal of export duties can be substantial. They also suggest that the resource-pull effects of a devaluation and a devaluation-cum-export duty removal policy are significant. However, the model shows that a devaluation combined with an export duty reduction is likely to be a superior strategy. ^

Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

A Markov chain location-allocation meta-model for hurricane relief

An emergency is a deviation from a planned course of events that endangers people, properties, or the environment. It can be described as an unexpected event that causes economic damage, destruction, and human suffering. When a disaster happens, Emergency Managers are expected to have a response plan to most likely disaster scenarios. Unlike earthquakes and terrorist attacks, a hurricane response plan can be activated ahead of time, since a hurricane is predicted at least five days before it makes landfall. This research looked into the logistics aspects of the problem, in an attempt to develop a hurricane relief distribution network model. We addressed the problem of how to efficiently and effectively deliver basic relief goods to victims of a hurricane disaster. Specifically, where to preposition State Staging Areas (SSA), which Points of Distributions (PODs) to activate, and the allocation of commodities to each POD. Previous research has addressed several of these issues, but not with the incorporation of the random behavior of the hurricane's intensity and path. This research presents a stochastic meta-model that deals with the location of SSAs and the allocation of commodities. The novelty of the model is that it treats the strength and path of the hurricane as stochastic processes, and models them as Discrete Markov Chains. The demand is also treated as stochastic parameter because it depends on the stochastic behavior of the hurricane. However, for the meta-model, the demand is an input that is determined using Hazards United States (HAZUS), a software developed by the Federal Emergency Management Agency (FEMA) that estimates losses due to hurricanes and floods. A solution heuristic has been developed based on simulated annealing. Since the meta-model is a multi-objective problem, the heuristic is a multi-objective simulated annealing (MOSA), in which the initial solution and the cooling rate were determined via a Design of Experiments. The experiment showed that the initial temperature (T0) is irrelevant, but temperature reduction (δ) must be very gradual. Assessment of the meta-model indicates that the Markov Chains performed as well or better than forecasts made by the National Hurricane Center (NHC). Tests of the MOSA showed that it provides solutions in an efficient manner. Thus, an illustrative example shows that the meta-model is practical.

Dimensions of gender relations and reproductive health inequity perceived by female undergraduate students in the Mekong Delta of Vietnam: a qualitative exploration

Introduction Increasing evidence indicates that gender equity has a significant influence on women’s health; yet few culturally specific indicators of gender relations exist which are applicable to health. This study explores dimensions of gender relations perceived by female undergraduate students in southern Vietnamese culture, and qualitatively examines how this perceived gender inequity may influence females’ sexual or reproductive health. Methods Sixty-two female undergraduate students from two universities participated in eight focus group discussions to talk about their perspectives regarding national and local gender equity issues. Results Although overall gender gaps in the Mekong Delta were perceived to have decreased in comparison to previous times, several specific dimensions of gender relations were emergent in students’ discussions. Perceived dimensions of gender relations were comparable to theoretical structures of the Theory of Gender and Power, and to findings from several reports describing the actual inferiority of women. Allocation of housework and social paid work represented salient dimensions of labor. The most salient dimension of power related to women in positions of authority. Salient dimensions of cathexis related to son preference, women’s vulnerability to blame or criticism, and double standards or expectations. Findings also suggested that gender inequity potentially influenced women’s sexual and reproductive health as regards to health information seeking, gynecological care access, contraceptive use responsibility, and child bearing. Conclusion Further investigations of the associations between gender relations and different women’s sexual and reproductive health outcomes in this region are needed. It may be important to address gender relations as a distal determinant in health interventions in order to promote gender-based equity in sexual and reproductive health.

The effect of domestic credit in the economic *development process

A commonly held view is that creation of excessive domestic credit may lead to inflation problems, however, many economists uphold the possibility that, generous domestic credit under appropriate conditions will result in increases of output. This hypothesis is examined for Japan and Colombia for the period 1950-1993.^ Domestic credit theories are reviewed since the times of Thornton and Smith, until the recent times of Lewis, McKinnon, Stiglitz and of Japanese economists like K. Emi, Tachi R. and others. It is found that in Japan of the Post-War period, efficient financial markets and the decisive role of the government in orienting investment decisions seem to have influenced positively the effectiveness of domestic credit as an output-stimulating variable. On the contrary, in Colombia the absence of the above features seems to explain why domestic credit is not very effective as an output-stimulating variable.^ Multiple regression analyses show that domestic credit is a strong explanatory variable for output increases in Japan and a weak one for Colombia's case in the studied period. For Japan the correlation depicts a positive relationship between the two variables with a decreasing rate very similar to a typical production function. Moreover, the positive decreasing rate is confirmed if net domestic credit is used in the correlations. For Colombia a positive relationship is also found when accumulated domestic credit is used, but, if net domestic credit is the source of correlations, the positive decreasing rate is not obtained.^ Granger causality tests determined causality from domestic credit to output for Japan and no-causality for Colombia at the 1% significance level; the differences are explained by: (1) The low development level of the financial system in Colombia. (2) The nonexistence of consistent domestic credit policy to foster economic development. (3) The lack of an authoritative orientation in the allocation of financial resources and the nonexistence of long range industrialization programs in Colombia that could channel productively credit resources. For the system of equations relating domestic credit and exports, the Granger causality tests determined no-causality between domestic credit and exports for both Japan and Colombia also at the 1% significance level. ^