Geology topics

B. R. Gray

Publications and source records attributed to B. R. Gray.

11 recordsLinked to original sources

USGS2011

Treating floodplain lakes of large rivers as study units for variables that vary within lakes; an evaluation using chlorophyll a and inorganic suspended solids data from floodplain lakes of the Upper Mississippi River

Contiguous floodplain lakes ('lakes') have historically been used as study units for comparative studies of limnological variables that vary within lakes. The hierarchical nature of these studies implies that study variables may be correlated within lakes and that covariate associations may differ not only among lakes but also by spatial scale. We evaluated the utility of treating lakes as study units for limnological variables that vary within lakes based on the criteria of important levels of among-lake variation in study variables and the observation of covariate associations that vary among lakes. These concerns were selected, respectively, to ensure that lake signatures were distinguishable from within-lake variation and that lake-scale effects on covariate associations might provide inferences not available by ignoring those effects. Study data represented chlorophyll a (CHL) and inorganic suspended solids (ISS) data from lakes within three reaches of the Upper Mississippi River. Sampling occurred in summer from 1993 through 2005 (except 2003); numbers of lakes per reach varied from 7 to 19, and median lake area varied from 53 to 101 ha. CHL and ISS levels were modelled linearly, with lake, year and lake x year effects treated as random. For all reaches, the proportions of variation in CHL and ISS attributable to differences among lakes (including lake and lake x year effects) were substantial (range: 18%-73%). Finally, among-lake variation in CHL and ISS was strongly associated with covariates and covariate effects that varied by lakes or lake-years (including with vegetation levels and, for CHL, log(ISS)). These findings demonstrate the utility of treating floodplain lakes as study units for the study of limnological variables and the importance of addressing hierarchy within study designs when making inferences from data collected within floodplain lakes.

Illinois;Iowa;Minnesota;Missouri;Wisconsin↗

USGS2011

Cumulative effects of restoration efforts on ecological characteristics of an open water area within the Upper Mississippi River

Ecological restoration efforts in large rivers generally aim to ameliorate ecological effects associated with large-scale modification of those rivers. This study examined whether the effects of restoration efforts-specifically those of island construction-within a largely open water restoration area of the Upper Mississippi River (UMR) might be seen at the spatial scale of that 3476ha area. The cumulative effects of island construction, when observed over multiple years, were postulated to have made the restoration area increasingly similar to a positive reference area (a proximate area comprising contiguous backwater areas) and increasingly different from two negative reference areas. The negative reference areas represented the Mississippi River main channel in an area proximate to the restoration area and an open water area in a related Mississippi River reach that has seen relatively little restoration effort. Inferences on the effects of restoration were made by comparing constrained and unconstrained models of summer chlorophyll a (CHL), summer inorganic suspended solids (ISS) and counts of benthic mayfly larvae. Constrained models forced trends in means or in both means and sampling variances to become, over time, increasingly similar to those in the positive reference area and increasingly dissimilar to those in the negative reference areas. Trends were estimated over 12- (mayflies) or 14-year sampling periods, and were evaluated using model information criteria. Based on these methods, restoration effects were observed for CHL and mayflies while evidence in favour of restoration effects on ISS was equivocal. These findings suggest that the cumulative effects of island building at relatively large spatial scales within large rivers may be estimated using data from large-scale surveillance monitoring programs. Published in 2010 by John Wiley & Sons, Ltd.

River Research and Applications↗

USGS2011

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

River Research and Applications↗

USGS2011

Estimating site occupancy rates for aquatic plants using spatial sub-sampling designs when detection probabilities are less than one

Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.

Aquatic Botany↗

USGS2011

An evaluation of the Bayesian approach to fitting the N-mixture model for use with pseudo-replicated count data

The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.

Journal of Statistical Computation and Simulation↗

USGS2009

Effect of imperfect detectability on adaptive and conventional sampling: Simulated sampling of freshwater mussels in the upper Mississippi River

Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.

Environmental Monitoring and Assessment↗

USGS2007

Effects of methylmercury exposure on the immune function of juvenile common loons (Gavia immer)

We conducted a dose-response laboratory study to quantify the level of exposure to dietary Hg, delivered as methylmercury chloride (CH3HgCl), that is associated with suppressed immune function in captive-reared common loon (Gavia immer) chicks. We used the phytohemagglutinin (PHA) skin test to assess T-lymphocyte function and the sheep red blood cell (SRBC) hemagglutination test to measure antibody-mediated immunity. The PHA stimulation index among chicks receiving dietary Hg treatment did not differ significantly from those of chicks on the control diet (p = 0.15). Total antibody (immunoglobulin [Ig] M [primary antibody] + IgG [secondary response]) production to the SRBC antigen in chicks treated with dietary methylmercury (MeHg), however, was suppressed (p = 0.04) relative to chicks on control diets. Analysis indicated suppression of total Ig production (p = 0.025 with comparisonwise ?? level = 0.017) between control and 0.4 ??g Hg/g wet food intake treatment groups. Furthermore, the control group exhibited a higher degree of variability in antibody response compared to the Hg groups, suggesting that in addition to reducing the mean response, Hg treatment reduced the normal variation attributable to other biological factors. We observed bursal lymphoid depletion in chicks receiving the 1.2 ??g Hg/g treatment (p = 0.017) and a marginally significant effect (p = 0.025) in chicks receiving the 0.4 ??g Hg/g diet. These findings suggest that common loon chick immune systems may be compromised at an ecologically relevant dietary exposure concentration (0.4 ??g Hg/g wet wt food intake). We also found that chicks hatched from eggs collected from low-pH lakes exhibited higher levels of lymphoid depletion in bursa tissue relative to chicks hatched from eggs collected from neutral-pH lakes. ?? 2007 SETAC.

Environmental Toxicology and Chemistry↗

USGS2007

Breeding bird territory placement in riparian wet meadows in relation to invasive reed canary grass, Phalaris arundinacea

Invasive plants are a growing concern worldwide for conservation of native habitats. In endangered wet meadow habitat in the Upper Midwestern United States, reed canary grass ( Phalaris arundinacea ) is a recognized problem and its prevalence is more widespread than the better-known invasive wetland plant purple loosestrife ( Lythrum salicaria ). Although resource managers are concerned about the effect of reed canary grass on birds, this is the first study to report how common wet meadow birds use habitat in relation to reed canary grass cover and dominance. We examined three response variables: territory placement, size of territories, and numbers of territories per plot in relation to cover of reed canary grass. Territory locations for Sedge Wren ( Cistothorus platensis ) and Song Sparrow ( Melospiza melodid ) were positively associated with reed canary grass cover, while those for Common Yellowthroat ( Geothlypis trichas ) were not. Only Swamp Sparrow ( M. georgiana ) territory locations were negatively associated with reed canary grass cover and dominance (which indicated a tendency to place territories where there was no reed canary grass or where many plant species occurred with reed canary grass). Swamp Sparrow territories were positively associated with vegetation height density and litter depth. Common Yellowthroat territories were positively associated with vegetation height density and shrub cover. Song Sparrow territories were negatively associated with litter depth. Reed canary grass cover within territories was not associated with territory size for any of these four bird species. Territory density per plot was not associated with average reed canary grass cover of plots for all four species. Sedge Wrens and Song Sparrows may not respond negatively to reed canary grass because this grass is native to wet meadows of North America, and in the study area it merely replaces other tall lush plants. Avoidance of reed canary grass by Swamp Sparrows may be mediated through their preference for wet areas where reed canary grass typically does not dominate.

Wetlands↗

USGS2005

Selecting a distributional assumption for modelling relative densities of benthic macroinvertebrates

The selection of a distributional assumption suitable for modelling macroinvertebrate density data is typically challenging. Macroinvertebrate data often exhibit substantially larger variances than expected under a standard count assumption, that of the Poisson distribution. Such overdispersion may derive from multiple sources, including heterogeneity of habitat (historically and spatially), differing life histories for organisms collected within a single collection in space and time, and autocorrelation. Taken to extreme, heterogeneity of habitat may be argued to explain the frequent large proportions of zero observations in macroinvertebrate data. Sampling locations may consist of habitats defined qualitatively as either suitable or unsuitable. The former category may yield random or stochastic zeroes and the latter structural zeroes. Heterogeneity among counts may be accommodated by treating the count mean itself as a random variable, while extra zeroes may be accommodated using zero-modified count assumptions, including zero-inflated and two-stage (or hurdle) approaches. These and linear assumptions (following log- and square root-transformations) were evaluated using 9 years of mayfly density data from a 52 km, ninth-order reach of the Upper Mississippi River (n = 959). The data exhibited substantial overdispersion relative to that expected under a Poisson assumption (i.e. variance:mean ratio = 23 ??? 1), and 43% of the sampling locations yielded zero mayflies. Based on the Akaike Information Criterion (AIC), count models were improved most by treating the count mean as a random variable (via a Poisson-gamma distributional assumption) and secondarily by zero modification (i.e. improvements in AIC values = 9184 units and 47-48 units, respectively). Zeroes were underestimated by the Poisson, log-transform and square root-transform models, slightly by the standard negative binomial model but not by the zero-modified models (61%, 24%, 32%, 7%, and 0%, respectively). However, the zero-modified Poisson models underestimated small counts (1 ??? y ??? 4) and overestimated intermediate counts (7 ??? y ??? 23). Counts greater than zero were estimated well by zero-modified negative binomial models, while counts greater than one were also estimated well by the standard negative binomial model. Based on AIC and percent zero estimation criteria, the two-stage and zero-inflated models performed similarly. The above inferences were largely confirmed when the models were used to predict values from a separate, evaluation data set (n = 110). An exception was that, using the evaluation data set, the standard negative binomial model appeared superior to its zero-modified counterparts using the AIC (but not percent zero criteria). This and other evidence suggest that a negative binomial distributional assumption should be routinely considered when modelling benthic macroinvertebrate data from low flow environments. Whether negative binomial models should themselves be routinely examined for extra zeroes requires, from a statistical perspective, more investigation. However, this question may best be answered by ecological arguments that may be specific to the sampled species and locations. ?? 2004 Elsevier B.V. All rights reserved.

Ecological Modelling↗

USGS2004

Agricultural ponds support amphibian populations

In some agricultural regions, natural wetlands are scarce, and constructed agricultural ponds may represent important alternative breeding habitats for amphibians. Properly managed, these agricultural ponds may effectively increase the total amount of breeding habitat and help to sustain populations. We studied small, constructed agricultural ponds in southeastern Minnesota to assess their value as amphibian breeding sites. Our study examined habitat factors associated with amphibian reproduction at two spatial scales: the pond and the landscape surrounding the pond. We found that small agricultural ponds in southeastern Minnesota provided breeding habitat for at least 10 species of amphibians. Species richness and multispecies reproductive success were more closely associated with characteristics of the pond (water quality, vegetation, and predators) compared with characteristics of the surrounding landscape, but individual species were associated with both pond and landscape variables. Ponds surrounded by row crops had similar species richness and reproductive success compared with natural wetlands and ponds surrounded by nongrazed pasture. Ponds used for watering livestock had elevated concentrations of phosphorus, higher turbidity, and a trend toward reduced amphibian reproductive success. Species richness was highest in small ponds, ponds with lower total nitrogen concentrations, tiger salamanders ( Ambystoma tigrinum ) present, and lacking fish. Multispecies reproductive success was best in ponds with lower total nitrogen concentrations, less emergent vegetation, and lacking fish. Habitat factors associated with higher reproductive success varied among individual species. We conclude that small, constructed farm ponds, properly managed, may help sustain amphibian populations in landscapes where natural wetland habitat is rare. We recommend management actions such as limiting livestock access to the pond to improve water quality, reducing nitrogen input, and avoiding the introduction of fish.

Minnesota↗

USGS2004

Flow cytometry used to assess genetic damage in frogs from farm ponds

Flow cytometry (FC) is a laboratory method used to detect genetic damage induced by environmental contaminants and other stressors in animals, including amphibians. We tested FC methods on three species of ranid frogs collected from farm ponds and natural wetlands in southeastern Minnesota. We compared FC metrics for Rana clamitans between ponds with direct exposure to agricultural contaminants and reference (unexposed) ponds. Concentrations of atrazine in water from our farm ponds ranged from 0.04 to 0.55 ppb. We found that R. clamitans from exposed ponds had DNA content similar to frogs from unexposed ponds. Pond-averaged C-values (a measure of DNA content) ranged from 6.53 to 7.08 for R. pipiens (n . 13), 6.55 to 6.60 for R. clamitans (n . 40) and 6.74 for R. palustris (n . 5). Among all species, the mean sample CVs ranged from 1.91 (R. palustris) to 6.31 (R. pipiens). Deformities were observed in only 2 of 796 individuals among all species and occurred in both reference and exposed ponds. Although we did not detect evidence of DNA damage associated with agriculture in our study, we demonstrated the potential of FC for screening amphibian populations for genetic damage. Metrics from a variety of amphibian species and locations as well as laboratory studies are needed to further assess the value of FC for monitoring amphibian genetic integrity in contaminated sites.

Journal of the Iowa Academy of Science↗