Underwater video as a monitoring tool to detect change in seagrass cover

To date seagrass monitoring has involved the removal of seagrass from its environment. In fragile or highly disturbed systems, monitoring using destructive techniques may interfere with the environment or add to the burden of disturbance. Video photography is a form of non-destructive monitoring that does not require the removal of seagrass or interference with the environment and has the potential to be a valuable tool in monitoring seagrass systems. This study investigated the efficacy of video photography as a tool for detecting change in seagrass cover, using the temperate Australian species Amphibolis antarctica (Labill.) Sonder ex Aschers. Using visual and random point estimates of seagrass cover from video footage, it was possible to determine the minimum sample size (number of random video frames) needed to detect change in seagrass cover, the minimum detectable change in cover and the probability of the monitoring design committing a Type II error. Video footage was examined at three scales: transects (m apart), sites (km apart) and regions (tens of km apart). Using visual and random point estimation techniques, a minimum sample size of ten quadrats per transect was required to detect change in uniform and variable seagrass cover. With ten quadrats it was possible to identify a minimum detectable change in cover of 15% for uniform and 30% for variable seagrass cover. Power analysis was used to determine the probability of committing a Type II error from the data. Region level data had low power, corresponding to a high risk of committing a Type II error. Site and transect level data had high power corresponding to a low risk of committing a Type II error. Based on this study's data, managers using video to monitor for change in seagrass cover are advised to use data from the smaller scale, for example, site and transect level data. By using data from the smaller scale, managers will have a low risk of incorrectly concluding there has not been a disturbance when one has actually occurred.     

SAMPLING FREQUENCY SELECTION FOR REGULATORY WATER QUALITY MONITORING1

ABSTRACT: The selection of sampling frequencies in order to achieve reasonably small and uniform confidence interval widths about annual sample means or sample geometric means of water quality constituents is suggested as a rational approach to regulatory monitoring network design. Methods are presented for predicting confidence interval widths at specified sampling frequencies while considering both seasonal variation and serial correlation of the quality time series. Deterministic annual cycles are isolated and serial dependence structures of the autoregressive, moving average type are identified through time series analysis of historic water quality records. The methods are applied to records for five quality constituents from a nine-station network in Illinois. Confidence interval widths about annual geometric means are computed over a range of sampling frequencies appropriate in regulatory monitoring. Results are compared with those obtained when a less rigorous approach, ignoring seasonal variation and serial correlation, is used. For a monthly sampling frequency the error created by ignoring both seasonal variation and serial correlation is approximately 8 percent. Finally, a simpler technique for evaluating serial correlation effects based on the assumption of AR(1) type dependence is examined. It is suggested that values of the parameter p₁, in the AR(1) model should range from 0.75 to 0.90 for the constituents and region studied.     

SALMONID SMOLT SURVIVAL RELATIVE TO TURBINE EFFICIENCY AND ENTRAINMENT DEPTH IN HYDROELECTRIC POWER GENERATION1

ABSTRACT: The hypotheses that fish survival probabilities may be lower (1) at less than peak operating turbine efficiency; (2) at deeper entrainment depth; and (3) with the deployment of extended‐length intake guidance screens, are not supported by results on yearling chinook salmon smolts (Oncorhynchus tshawytscha) at Lower Granite Dam, Snake River, Washington. Estimated 96 h survival probabilities for the six test conditions ranged from 0.937 to 0.972, with the highest survival at turbine operating towards the lower end of its efficiency. A blanket recommendation to operate all Kaplan type turbines within ± 1 percent of their peak efficiency appears too restrictive. Cavitation mode survival (0.946) was comparable to that at peak operating efficiency mode (0.937), as was the survival between upper (0.947) and mid depths (0.937). Survival differed only slightly among three turbine intake bays at the same depth (0.937 to 0.954), most likely due to differential flow distribution. Extended‐length intake fish guidance screens did not reduce survival. However, the sources of injury somewhat differed with depth; probable pressure and shear‐related injuries were common on fish entrained at mid‐depth, and mechanically‐induced injuries were common at upper depth. Operating conditions that reduce turbulence within the turbine environment may enhance fish survival; however, controlled experiments that integrate turbine flow physics and geometry and the path entrained fish traverse are needed to develop specific guidance to further enhance fish passage survival.     

Estimation of upper centile concentrations using historical atrazine monitoring data from community water systems

A survey sampling approach is presented for estimating upper centiles of aggregate distributions of surface water pesticide measurements obtained from datasets with large sample sizes but variable sampling frequency. It is applied to three atrazine monitoring programs of Community Water Systems (CWS) that used surface water as their drinking water source: the nationwide Safe Drinking Water Act (SDWA) data, the Syngenta Voluntary Monitoring Program (VMP), and the Atrazine Monitoring Program (AMP).The VMP/AMP CWS were selected on the basis of atrazine monitoring history (CWS having at least one annual average concentration from SDWA ≥ 1.6 ppb atrazine since 1997 in the AMP). Estimates of the raw water 95th, 99th, and 99.9th centile atrazine concentrations for the VMP/AMP CWS are 4.82, 11.85, and 34.00 ppb, respectively. The corresponding estimates are lower for the finished drinking water samples, with estimates of 2.75, 7.94, and 22.66 ppb, respectively. Finished water centile estimates for the VMP/AMP CWS using only the SDWA data for these sites are consistent with the results. Estimates are provided for the April through July period and for CWS based on surface water source type (static, flowing, or mixed). Requisite sample sizes are determined using statistical tolerance limits, relative SE, and the Woodruff interval sample size criterion. These analyses provide 99.9% confidence that the existing data include the 99.9th centile atrazine concentration for CWS raw and finished water in the Midwest atrazine high-use areas and in the nationwide SDWA dataset. The general validity of this approach is established by a simulation that shows estimates to be close to target quantities for weights based on sampling probabilities or time intervals between samples. Recommendations are given for suitable effective sample sizes to reliably determine interval estimates.     

EFFICIENCY OF HYDROLOGIC DATA COLLECTION SYSTEMS ROLE OF TYPE I AND II ERRORS1

ABSTRACT The efficiency of hydrologic data collection systems is relevant to solution of environmental problems, scientific understanding of hydrologic processes, model-building and management of water resources. Because these goals may be overlapping and non-commensurate, design of data networks is not simple. Identified are four elements of error or risk in such networks: (a) choice of variables and mathematical model for the same process, (b) accuracy of model parameter estimates, (c) acceptance of wrong hypothesis or rejection of correct hypothesis and (d) economic losses associated with error. Of these four, the classical hypothesis testing problem is specifically evaluated in terms of costs of type I and II errors for simple and composite hypotheses; mathematical models for these economic analyses also include costs of sample data and costs of waiting while new data is obtained. An illustrative computational example focuses on the hypothesis that natural recharge might be augmented by a system of pumping wells along an ephemeral channel. The relationship of the hypothesis testing problem to Bayesian decision theory is discussed; it is felt that the latter theory offers a more comprehensive framework for design and use of hydrologic data networks.     

Influence of Sampling Effort on the Estimated Richness of Road-Killed Vertebrate Wildlife

Road-killed mammals, birds, and reptiles were collected weekly from highways in southern Brazil in 2002 and 2005. The objective was to assess variation in estimates of road-kill impacts on species richness produced by different sampling efforts, and to provide information to aid in the experimental design of future sampling. Richness observed in weekly samples was compared with sampling for different periods. In each period, the list of road-killed species was evaluated based on estimates the community structure derived from weekly samplings, and by the presence of the ten species most subject to road mortality, and also of threatened species. Weekly samples were sufficient only for reptiles and mammals, considered separately. Richness estimated from the biweekly samples was equal to that found in the weekly samples, and gave satisfactory results for sampling the most abundant and threatened species. The ten most affected species showed constant road-mortality rates, independent of sampling interval, and also maintained their dominance structure. Birds required greater sampling effort. When the composition of road-killed species varies seasonally, it is necessary to take biweekly samples for a minimum of one year. Weekly or more-frequent sampling for periods longer than two years is necessary to provide a reliable estimate of total species richness.     

Modeling of power plant impacts on fish populations

A simulation model was developed for assessing the effects of power plant impacts on fish populations. The model was based on biomass changes in a fish population that divided into 4 life stages: eggs, larvae, juveniles, and adults. Metabolism of fish was included in the model as assimilation and respiration with the effects of temperature push-pull regulation. A cohort technique was used for life stage transfers in the young stages. Compensation was included in terms of density-dependent mortality of the young fish. Power plant impacts on a fish population included entrainment (eggs and larvae) and impingement (juveniles and adults).The model was applied to the gizzard shad (Dorosoma cepedianum) population in Pool 14 of the Mississippi River in Illinois and lowa. The nearby nuclear power plant, the Quad-Cities Station, is located on the Illinois side. The simulation of the model with the 1976 field data estimates of the power plant entrainment and impingement predicted a 10 percent potential reduction of the population over 30 years. The simulated reduction of the population with the effects of different river flows showed that the result with the 1976 river flow data gave 1.5 times higher reduction than the results with data of other plant operation years, 1972 through 1975. Because the 1976 data recorded low river flow, the 10 percent reduction quoted above may be high.     

MASS LOAD ESTIMATION ERRORS UTILIZING GRAB SAMPLING STRATEGIES IN A KARST WATERSHED1

ABSTRACT: Developing a mass load estimation method appropriate for a given stream and constituent is difficult due to inconsistencies in hydrologic and constituent characteristics. The difficulty may be increased in flashy flow conditions such as karst. Many projects undertaken are constrained by budget and manpower and do not have the luxury of sophisticated sampling strategies. The objectives of this study were to: (1) examine two grab sampling strategies with varying sampling intervals and determine the error in mass load estimates, and (2) determine the error that can be expected when a grab sample is collected at a time of day when the diurnal variation is most divergent from the daily mean. Results show grab sampling with continuous flow to be a viable data collection method for estimating mass load in the study watershed. Comparing weekly, biweekly, and monthly grab sampling, monthly sampling produces the best results with this method. However, the time of day the sample is collected is important. Failure to account for diurnal variability when collecting a grab sample may produce unacceptable error in mass load estimates. The best time to collect a sample is when the diurnal cycle is nearest the daily mean.     

PARAMETER IDENTIFICATION IN A TWO‐MULTIPLIER SEDIMENT YIELD MODEL1

ABSTRACT: A process based, distributed runoff erosion model (KINEROS2) was used to examine problems of parameter identification of sediment entrainment equations for small watersheds. Two multipliers were used to reflect the distributed nature of the sediment entrainment parameters: one multiplier for a raindrop induced entrainment parameter, and one multiplier for a flow induced entrainment parameter. The study was conducted in three parts. First, parameter identification was studied for simulated error free data sets where the parameter values were known. Second, the number of data points in the simulated sedigraphs was reduced to reflect the effect of temporal sampling frequency on parameter identification. Finally, event data from a small range‐land watershed were used to examine parameter identifiability when the parameter values are unknown. Results demonstrated that whereas unique multiplier values can be obtained for simulated error free data, unique parameter values could not be obtained for some event data. Unique multiplier values for raindrop induced entrainment and flow induced entrainment were found for events with greater than a two‐year return period (～25 mm) that also had at least 10 mm of rain in ten minutes. It was also found that the three‐minute sampling frequency used for the sediment sampler might be inadequate to identify parameters in some cases.     

Managing Water to Protect Fish: A Review of California’s Environmental Water Account, 2001–2005

The Sacramento-San Joaquin Delta, the landward reach of the San Francisco Estuary, provides habitat for threatened delta smelt, endangered winter-run Chinook salmon, and other species of concern. It is also the location of huge freshwater diversion facilities that entrain large numbers of fish. Reducing the entrainment of listed fishes into these facilities has required curtailment of pumping, reducing the reliability of water deliveries. We reviewed the first 5 years (2001–2005) of the Environmental Water Account (EWA), a program instituted to resolve conflicts between protecting listed fishes and providing a reliable water supply. The EWA provided fishery agencies with control over 0.2–0.4 km³ of water to be used for fish protection at no cost to users of exported water, and fish agencies guaranteed no disruption of water supply for fish protection. The EWA was successful in reducing uncertainty in water supply; however, its contribution to the recovery of listed fishes was unclear. We estimated the effectiveness of the EWA to be modest, increasing the survival of winter-run Chinook salmon by 0–6% (dependent on prescreen mortality), adult delta smelt by 0–1%, and juvenile delta smelt by 2–4%. Allocating EWA water for a single life stage of one species could provide larger gains in survival. An optimally allocated EWA of equal size to the median of the first 5 years could increase abundance of juvenile delta smelt up to 7% in the springs of dry years. If the EWA is to become a long-term program, estimates of efficacy should be refined. If the program is to be held accountable for quantitative increases in fish populations, it will be necessary to integrate scientific, possibly experimental, approaches.     

Detection and decision-making in environmental effects monitoring

The majority of environmental effects monitoring (EEM) frameworks that have been proposed compare selected indicator variables as a means of assessing whether significant changes in stressed ecosystems have occurred. Most are deterministic in nature and do not appropriately account for the natural variability and dynamics within the systems being comapred. This suggests that the comparative procedures should be statistically based and immediately raises the issue of whether the selected comparative procedures are to be used as decision-making tools or conclusive procedures. Conclusive procedures require a significant body of evidence before rejecting the postulated null hypothesis. The costs and time involved in environmental data collection accordingly bias action toward the maintenance of a status quo approach to environmental management. if, however, EEM is treated as a decision-making procedure, risk functions that include consideration of type I and II statistical error may be developed and combined with costs to select a minimum expected loss strategy for environemental management. Examples of the interpretative difficulties and conclusion reversal phenomena caused when EEM is used as a conclusive procedure are presented. In addition, risk functions appropriate for environmental management within an EEM context are constructed and applied. Only when such tools are fully developed and applied can EEM expect to have significant impacts on minimizing environmental degradation.     

THE INFLUENCE OF ENGINEERING DESIGN AND OPERATION AND OTHER ENVIRONMENTAL FACTORS ON RESERVOIR FISHERY RESOURCES1

The apparent effect of selected reservoir environmental variables-including surface area, mean depth, outlet depth, thermocline depth, water level fluctuation, storage ratio, shore development, total dissolved solids, growing season and age of reservoir–on fish standing crop in 140 large impoundments has been explored through partial correlation and multiple regression analyses. The sample was partitioned into 25 subsamples based on reservoir use type, water exchange rate, thermocline formation and water chemistry. Fish standing crops were estimated by summer rotenone sampling of coves or open water areas enclosed by blockoff net. Logarithmic partial correlation revealed highly significant (0.01 confidence shore development and dissolved solids on At the 0.20 confidence level, the crop of storage ratio and shore level) positive effects of outlet depth, total standing crop in the entire sample. all sport fishes is positively influenced by outlet depth, development and negatively by mean depth. In 54 hydropower reservoirs with a stable thermocline, positive effects of increased storage ratio and dissolved solids on t o t a l crop are evident at the 0.05 confidence interva. Increase in thermocline depth has a negative effect. In 25 hydropower reservoirs without a stable thermocline, clupeid (shad) crop is negatively correlated with surface area, mean depth and fluctuation. Reservoirs with a thermocline have higher standing crops than those without. At the species or species group level, partial correlation of nine environmental variables a t the 0.05 confidence interval reveals: Positive effect of surface area on pike and pickerel; buffalo-fishes, white crappie and total sport fish crop; positive effect of outlet depth on largemouth bass, catfishes, total sport fish crop and buffalofishes; a negative effect of water level fluctuation on pike and pickerel, redear sunfish and gizzard shad; a positive relationship between storage ratio and channel catfish and bull- heads and a negative one with flathead catfish and suckers; a positive effect of total dissolved solids on black and whit basses, catfishes, gizzard shad, carpsuckers and carp. A morphoedaphic expression, total dissolved solids divided by mean depth, provides a useful index t o reservoir fish production. The relationship is curvilinear, with maximum crops expected at index values of 5 t o 30.The index accounts for 62 percent of the variability in hydropower storage reservoir crops. Several multivariable regressions have been derived f o r predictive purposes. Examples are included, with R values of 35 t o 60.     

TWO PRACTICAL APPROACHES FOR DETERMINING THE CONFIDENCE INTERVAL OF RAINFALL DEPTH PERCENTILES1

ABSTRACT: A simple simulation type approach and a statistical method are proposed for determining the confidence interval of the T‐year frequency rainfall percentiles (or precipitation extremes) for generalized extreme value (GEV) distributions. The former method is based on the Monte Carlo testing procedure. To generate realizations, the covariance structure of the three parameters of GEV is investigated using an observed information matrix of the likelihood function. For distributions with realistic parameters, the correlation between the location and the scale parameters is practically constant when the shape parameter varies around values close to its optimal value. The latter method is based on likelihood ratio statistics. In the case where the joint confidence surface for shape parameters and estimates is plotted with lines of best estimates, the region where the estimated best percentile value can be chosen as a possible estimate is part of the joint confidence surface. The projection of this bounded region on axis of percentile is defined as the effective confidence interval in this research. The use of this effective interval as the confidence interval of the percentile of T‐year frequency rainfall is particularly recommended because it is stable for T and it reflects variations in all three parameters of GEV appropriately.     

A Comparison of Sampling Designs for Monitoring Recreational Trail Impacts in Rocky Mountain National Park

The dual goals of the Organic Act of 1916 and Wilderness Act of 1964 are to protect natural resources and provide quality visitor experiences. Park managers need metrics of trail conditions to protect park resources and quality of visitor experiences. A few methods of sampling design for trails have been developed. Here, we describe a relatively new method, spatially balanced sampling, and compare it to systematic sampling. We evaluated the efficiency of sampling designs to measure recreation-related impacts in Rocky Mountain National Park. This study addressed two objectives: first, it compared estimates of trail conditions from data collected from systematic versus spatially balanced sampling data; second, it examined the relationship between sampling precision and sampling efficiency. No statistically significant differences in trail condition were found between the 100-m interval and the spatially balanced datasets. The spatially balanced probability-based dataset was found to be a good estimate of trail conditions when analyses were conducted with fewer sample points. Moreover, spatially balanced probability-based sampling is flexible and allows additional sample points to be added to a sample.     

ESTIMATING IRRIGATION WATER USE THROUGH SELECTIVE MONITORING: A NORTH FLORIDA CASE STUDY1

ABSTRACT: Selective placement - under a rigorous statistical sampling design - of newly available monitoring equipment on irrigation systems may provide effective and economical estimates of total irrigation water use in areas where complete water use inventories are impractical. In 1979, a joint effort by the U.S. Geological Survey and Florida's Suwannee River Water Management District was launched to estimate the District's 1979 irrigation water use using a selective monitoring approach. Analysis of previous inventories of irrigation equipment and amounts of water applied in the District indicated that total 1979 water use estimates with six to nine percent sampling error could be obtained using selective monitoring, given the time and equipment limitations for the monitoring program. Restricting monitoring to a sample of farms can introduce systematic error to water use estimates if farmers' participation is related to their water use methods. Preliminary results of the 1979 study indicate tht declining participation rates, if unchecked, could lead to serious systematic eror in future North Florida selective monitoring studies.     

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 +/- 0.6 degrees C at the 95% confidence interval.     

Hemolysis,Fish Mortality,and LC-ESI-MS of Cultured Crude and Fractionated Golden Alga (Prymnesium parvum)1

Schug, Kevin A., Theodore R. Skingel, Sandra E. Spencer, Carlos A. Serrano, Cuong Q. Le, Christopher A. Schug, Theodore W. Valenti, Jr., Bryan W. Brooks, Laura D. Mydlarz, and James P. Grover, 2010. Hemolysis, Fish Mortality, and LC-ESI-MS of Cultured Crude and Fractionated Golden Alga (Prymnesium parvum). Journal of the American Water Resources Association (JAWRA) 46(1):33-44. DOI: 10.1111/j.1752-1688.2009.00389.x Abstract: Erythrocyte lysis and fish mortality assays, in combination with high performance liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) analysis, were investigated for bioassay-guided fractionation of cultured golden alga (Prymnesium parvum). Intracellular constituents from isolated cell pellets and extracellular supernatant growth medium were fractionated by a variety of common separation modes, including reversed phase and normal phase solid phase extraction step fractionation procedures. For reversed phase fractionation of extracellular growth medium, one fraction was obtained that displayed hemolytic activity and adversely affected fish survival. Effective dose concentrations for this sample were similar in both assays and the LC-ESI-MS analysis of the fraction showed a number of mass spectral signals which were distinct to this fraction. Fractions obtained from separation of an ethanol extract of the lyophilized cell pellet provided one sample that was highly hemolytic, but not toxic to fish. Discrepancies such as this, along with notable fish behavioral responses from other nonhemolytic cell pellet fractions, problems with the use of unbonded silica gel for fractionation, and misleading mass spectral signatures are interesting in the context of our current understanding of P. parvum toxicity and remain to be investigated further. This work provides an account of ongoing research aimed toward comprehensive elucidation of toxic constituents produced by golden alga for the purpose of providing a better understanding and means to potentially remediate the ecological impact of this harmful bloom organism.     

KALMAN FILTER CALCULATION OF SAMPLING FREQUENCY WHEN DETERMINING ANNUAL MEAN SOLUTE CONCENTRATIONS

ABSTRACT: A linear filter (Kalman filter) technique was used with a Streamflow-concentration model the minimize surface water quality sampling frequencies when determining annual mean solute concentrations with a predetermined allowable error. The Kalman filter technique used the stream discharge interval as a replacement for the more commonly used time interval. Using filter computations, the measurement error variance was minimized within the sample size constraints. The Kalman filter application proposed here is applicable only under several conditions including: monitoring is solely to estimate annual mean concentration; discharge measurement errors are negligible; the Streamflow-concentration model is valid; and monthly samples reflect the total variance of the solute in question.     

Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA

This paper presents a Data Envelopment Analysis (DEA) model combined with bootstrapping to assess performance in mining operations. Since DEA-type indicators based on nonparametric production analysis are simply point estimates without any standard error, we provide a methodology to assess the performance of strip mining operations by means of a DEA bootstrapping approach. This methodology is applied to a sample of fifteen Illinois strip coal mines using publicly available data (Thompson et al., 1995). The applied approach uses a mixed mine environmental performance indicator (MMEPI) that is derived by means of a VRS DEA environmental technology treating overburden as an undesirable output under the weak disposability assumption, and we compare this measure with a traditional output-oriented mine performance indicator (MPI) omitting overburden. Although omitting undesirable output results in biased performance estimates, these findings are based on sample specific results and indicate this bias is not statistically significant. The confidence intervals derived by the bootstrapping of the proposed MMEPI point estimates indicate that significant inefficiency has taken place in the analyzed sample of Illinois strip mines.