PREDICTION OF MEAN ANNUAL FLOWS IN NORTH AND CENTRAL FLORIDA1

ABSTRACT: A frequency analysis approach for the prediction of flow characteristics at ungaged locations is applied to a region of high annual precipitation and low topography in north and central Florida. Stationary time series of annual flows are fitted with the lognormal distribution and estimated parameters of the distribution are fitted by third order trend surfaces. These explain 65 and 74 percent of the observed variances in the mean and standard deviation, respectively. Predictions of parameters are then made for several locations previously unused in the study and they are used to estimate the return periods of various flows from the lognormal distribution. Application of the Kolmogorov-Smirnov goodness-of-fit test suggests that only one of the five test stations can be considered significantly different from the observed data, confirming the applicability of this technique.     

Emergence cues of a mayfly in a high-altitude stream ecosystem: potential response to climate change.

To understand the consequences of human accelerated environmental change, it is important to document the effects on natural populations of an increasing frequency of extreme climatic events. In stream ecosystems, recent climate change has resulted in extreme variation in both thermal and hydrological regimes. From 2001 to 2004, a severe drought in western United States corresponded with earlier emergence of the adult stage of the high-altitude stream mayfly, Baetis bicaudatus. Using a long-term database from a western Colorado stream, the peak emergence date of this mayfly population was predicted by both the magnitude and date of peak stream flow, and by the mean daily water temperature, suggesting that Baetis may respond to declining stream flow or increasing water temperature as proximate cues for early metamorphosis. However, in a one-year survey of multiple streams from the same drainage basin, only water temperature predicted spatial variation in the onset of emergence of this mayfly. To decouple the effects of temperature and flow, we separately manipulated these factors in flow-through microcosms and measured the timing of B. bicaudatus metamorphosis to the adult stage. Mayflies emerged sooner in a warmed-water treatment than an ambient-water treatment; but reducing flow did not accelerate the onset of mayfly emergence. Nonetheless, using warming temperatures to cue metamorphosis enables mayflies to time their emergence during the descending limb of the hydrograph when oviposition sites (protruding rocks) are becoming available. We speculate that large-scale climate changes involving warming and stream drying could cause significant shifts in the timing of mayfly metamorphosis, thereby having negative effects on populations that play an important role in stream ecosystems.     

Building phenological models from presence/absence data for a butterfly fauna.

Species phenology is increasingly being used to explore the effects of climate change and other environmental stressors. Long-term monitoring data sets are essential for understanding both patterns manifest by individual species and more complex patterns evident at the community level. This study used records of 78 butterfly species observed on 626 days across 27 years at a site in northern California, USA, to build quadratic logistic regression models of the observation probability of each species for each day of the year. Daily species probabilities were summed to develop a potential aggregate species richness (PASR) model, indicating expected daily species richness. Daily positive and negative contributions to PASR were calculated, which can be used to target optimum sampling time frames. Residuals to PASR indicate a rate of decline of 0.12 species per year over the course of the study. When PASR was calculated for wet and dry years, wet years were found to delay group phenology by up to 17 days and reduce the maximum annual expected species from 32.36 to 30. Three tests to determine how well the PASR model reflected the butterfly fauna dynamics were all positive: We correlated probabilities developed with species presence/absence data to observed abundance by species, tested species' predicted phenological patterns against known biological characteristics, and compared the PASR curve to a spline-fitted curve calculated from the original species richness observations. Modeling individual species' flight windows was possible from presence/absence data, an approach that could be used on other similar records for butterfly communities with seasonal phenologies, and for common species with far fewer dates than used here. It also provided a method to assess sample frequency guidelines for other butterfly monitoring programs.     

Assessing Conservation Value Using Centers of Population Density

We present an index of centers of density for identifying areas of high conservation value. This index represents the average importance of an area to species occurring there as measured by comparisons of relative densities of each species among areas. We evaluated the index using collections of stream fishes from the Clinch River system above Norris Reservoir in Virginia and Tennessee (U.S.A.). A strong correlation between index values measured at the same sites at different times suggested that the index could be applied to sites without replicated samples in the region and still allow centers of density to be distinguished from noncenters. Species richness showed no relationship to the index, suggesting that conservation priorities based solely on species richness can be inadequate. A species-accumulation curve based on the index performed nearly as well as one based on an algorithm for identifying the minimum number of sites in which all species in the region are represented. This pattern reflected the tendency of the index to weight regionally rare species more heavily than common species. But sites with high index values were not necessarily those selected by the algorithm because the algorithm used only presence/absence, whereas the index used the additional information present in relative densities. Our index represents an additional tool for identifying "hot spots" of diversity, but conservation of biodiversity over the long term will also require that the ecological integrity of regional landscape be maintained.     

The importance of spatial autocorrelation,extent and resolution in predicting forest bird occurrence

Concerns about declines in forest biodiversity underscore the need for accurate estimates of the distribution and abundance of organisms at large scales and at resolutions that are fine enough to be appropriate for management. This paper addresses three major objectives: (i) to determine whether the resolution of typical air photo-derived forest inventory is sufficient for the accurate prediction of site occupancy by forest birds. We compared prediction success of habitat models using air photo variables to models with variables derived from finer resolution, ground-sampled vegetation plots. (ii) To test whether incorporating spatial autocorrelation into habitat models via autologistic regression increases prediction success. (iii) To determine whether landscape structure is an important factor in predicting bird distribution in forest-dominated landscapes. Models were tested locally (Greater Fundy Ecosystem [GFE]) using cross-validation, and regionally using an independent data set from an area located ca. 250 km to the northwest (Riley Brook [RB]). We found significant positive spatial autocorrelation in the residuals of at least one habitat model for 76% (16/21) of species examined. In these cases, the logistic regression assumption of spatially independent errors was violated. Logistic models that ignored spatial autocorrelation tended to overestimate habitat effects. Though overall prediction success was higher for autologistic models than logistic models in the GFE, the difference was only significantly improved for one species. Further, the inclusion of spatial covariates did little to improve model performance in the geographically discrete study area. For 62% (13/21) of species examined, landscape variables were significant predictors of forest bird occurrence even after statistically controlling for stand-level variability. However, broad spatial extents explained less variation than local factors. In the GFE, 76% (16/21) of air photo and 81% (17/21) of ground plot models were accurate enough to be of practical utility (AUC > 0.7). When applied to RB, both model types performed effectively for 55% (11/20) of the species examined. We did not detect an overall difference in prediction success between air photo and ground plot models in either study area. We conclude that air photo data are as effective as fine resolution vegetation data for predicting site occupancy for the majority of species in this study. These models will be of use to forest managers who are interested in mapping species distributions under various timber harvest scenarios, and to protected areas planners attempting to optimize reserve function.     

Effect of alum addition on the performance of submerged membranes for wastewater treatment.

The effect of aluminum sulfate (alum) addition on membrane performance was investigated, with a particular focus on membrane fouling. During initial operation, alum was added and the performance monitored. After terminating alum addition, the transmembrane pressure (TMP), which is indicative of membrane resistance to flow or fouling, increased. Accompanying the increase in TMP was an increase in the organic nonsettleable fraction (colloidal + dissolved) content of the mixed liquor and deterioration of permeate quality and floc strength. Permeate polysaccharide concentrations increased significantly, suggesting a preferential binding of solution polysaccharides by alum. Upon reinitiating alum addition, the TMP only partially recovered, indicating some irreversible fouling, while mixed liquor nonsettleable organic material, permeate quality, and floc strength returned to initial levels. These results suggest that direct alum addition to membrane bioreactors can improve membrane performance by reducing the organic fouling material and improving floc structure and strength. It appears that bulk liquid polysaccharides may contribute to irreversible membrane fouling, and this fraction can be efficiently controlled through the alum addition.     

Determination of Endosulfans in Soil/Sediment Samples from Point Mugu, Oxnard, California Using Capillary Gas Chromatography/Mass Selective Detection (GC/MSD)

The extent of contamination by endosulfans in soil samples collected from the Point Mugu watershed near Oxnard, California was determined using capillary gas chromatography/mass selective detection (GC/MSD). The study was designed to detect three organochlorinated pesticides: endosulfan , endosulfan and endosulfan sulfate. Thirteen sets of two soil samples each were taken from various sites in the region. Our results show that the endosulfan levels in these soils range from trace amounts to nearly 30 ppm, with endosulfan being the most abundant and endosulfan sulfate the least. Two sites of the study, Hueneme and Revolon and Farm and Revolon, showed high amounts of endosulfans and , with concentrations between 20 and 30 ppm. The majority of the other sites studied in this research produced concentrations of less than 10 ppm for each of the three endosulfans monitored. At five areas in particular, Pleasant Valley and Creek, Laguna and Creek, Etting and Creek, Road and Creek and Hueneme and Creek, less than 2 ppm or only trace amounts of endosulfans , and sulfate were detected.     

a study of the temporal variability of atrazine in private well water. part i: study design, implementation, and database development

In 1988, the Iowa Department of Natural Resources, along withthe University of Iowa conducted the Statewide Rural WellWater Survey, commonly known as SWRL. A total of 686private rural drinking water wells was selected by use of aprobability sample and tested for pesticides and nitrates. Sixty-eight of these wells, the 10% repeat wells, were additionallysampled in October, 1990 and June, 1991. Starting inNovember, 1991, the University of Iowa, with sponsorshipfrom the United States Environmental Protection Agency,revisited these wells to begin a study of the temporalvariability of atrazine and nitrates in wells. Other wells, whichhad originally tested positive for atrazine in SWRL but werenot in the 10% repeat population, were added to the studypopulation. Temporal sampling for a year-long period beganin February of 1992 and concluded in January of 1993. Allwells were sampled monthly, one subset was sampled weekly,and a second subset was sampled for 14-day consecutiveperiods. Two unique aspects of this study were the use of animmunoassay technique to screen for triazines before gaschromatography/mass spectrometry (GC/MS) analysis andquantification of atrazine, and the use of well owners to samplethe wells. A total of 1771 samples from 83 wells are in thefinal data base for this study. This paper reviews the studydesign, the analytical methodologies, and development of thedata base. A companion paper (Pinsky et al., 1997) discussesthe analysis of the data from this survey.     

The creation of an historical meteorological database for environmental dose assessment

The focus of this study is to develop wind data for the SavannahRiver Site (SRS) between 1955 and 1961 to be used in an assessment of estimates of atmospheric dispersion and downwindrisk at the Savannah River Site. In particular, a study of theuncertainties of radioiodine dosimetry from the late 1950sprovides the underlying motivation for developing historicalwindroses at the Savannah River Site (SRS). Wind measurement towers did not exist at the SRS until theearly 1970s. Three relatively simple methods were used to createa 1955–1961 meteorological database for the SRS for a dosereconstruction project. The winds were estimated from onsitemeasurements in the 1990s and National Weather Service (NWS)observations in the 1990s and 1950s using (1) a linear regressionmethod, (2) a similarity theory approach, and (3) a simplestatistical differences method. The criteria for determining success were based on (1) howwell the mean values and standard deviations of the predictedwind speed agree with the known SRS values from the 1990s, (2) the shape of the predicted frequency distribution functions forwind speed, and (3) how closely the predicted windroses resembledthe SRS windrose for the 1990s. The linear regression model's wind speed distribution functionwas broad, flat, and skewed too much toward higher wind speeds.The similarity theory approach produced a wind speed distributionfunction that contained excess predicted speeds in the range 0–1.54 m s^-1 (0–3 kts) and had `excluded' bins caused bypredictions being made from integer values of knots in the NWSdata. The distribution function from the mean difference methodwas smooth with a shape like a Weibull distribution with a shapeparameter of 2 and appearedto resemble closely the SRS 1992–1996 distribution.The wind directions for all three methods of approach weresuccessfully based on the mean difference method. It wasdifficult to discern differences among the wind roses produced bythe three methods so the wind speed distribution functions needto be examined in order to make an informed choice for dose reconstruction.     

Plan integration for resilience scorecard: evaluating networks of plans in six US coastal cities

Planning for hazard mitigation is frequently detached from other planning activities that influence development patterns in hazardous areas. Consistent integration of mitigation reduces hazard vulnerability for people and the built environment. We apply a plan integration for resilience scorecard in six US coastal cities to evaluate the integration of local networks of plans and the degree to which they target areas most vulnerable to flooding hazards. We find that plan integration scores vary widely across the six cities, and that some plans actually increase vulnerability in hazard zones. Policies also frequently support mitigation in areas with low vulnerability, rather than in areas with high vulnerability. The plan integration for resilience scorecard can generate information to improve hazard planning by allowing planners to identify conflicts between plans, assess whether plans target areas that are most vulnerable, and better inform decision makers about opportunities to mainstream mitigation into multiple sectors of planning.