Spatial and temporal variation of microbial properties in the water column of Florida Bay

Physical and biological properties of the water column of Florida Bay were examined at seven study sites over an eighteen month period. The results indicated seasonality in some parameters, but was not evident in others. The data displayed statistically significant (P < 0.05) differences between study sites indicating spatial variation. The presence of seagrass affected the overlying water column, especially with respect to the biological parameters: those areas overlying seagrass beds displayed statistically significantly higher values than those over sparsely covered or barren areas. During the period of the study, Florida Bay experienced a seagrass die-off event: microbial activity and numbers were statistically significantly higher over areas of dying seagrass than over healthy or dead areas. The results of this study pointed to phosphorus being the controlling, or limiting factor, for microbial activity in the water column of Florida Bay.

On the accuracy of nonsurvey regional input-output multipliers: An empirical study

Correct specification of the simple location quotients in regionalizing the national direct requirements table is essential to the accuracy of regional input-output multipliers. The purpose of this research is to examine the relative accuracy of these multipliers when earnings, employment, number of establishments, and payroll data specify the simple location quotients.^ For each specification type, I derive a column of total output multipliers and a column of total income multipliers. These multipliers are based on the 1987 benchmark input-output accounts of the U.S. economy and 1988-1992 state of Florida data.^ Error sign tests, and Standardized Mean Absolute Deviation (SMAD) statistics indicate that the output multiplier estimates overestimate the output multipliers published by the Department of Commerce-Bureau of Economic Analysis (BEA) for the state of Florida. In contrast, the income multiplier estimates underestimate the BEA's income multipliers. For a given multiplier type, the Spearman-rank correlation analysis shows that the multiplier estimates and the BEA multipliers have statistically different rank ordering of row elements. The above tests also find no significant different differences, both in size and ranking distributions, among the vectors of multiplier estimates. ^