Fish abundances in shoreline habitats and submerged aquatic vegetation in a tidal freshwater embayment of the Potomac River

Submerged aquatic vegetation (SAV) is considered an important habitat for juvenile and small forage fish species, but many long-term recruitment surveys do not effectively monitor fish communities in SAV. To better understand the impact of recent large increases of SAV on the fish community in tidal freshwater reaches of the Potomac River, we compared traditional seine sampling from shore with drop ring sampling of SAV beds (primarily Hydrilla) in a shallow water (depths, <1.5 m) embayment, Gunston Cove. To accomplish this, we developed species-specific catch efficiency values for the seine gear and calculated area-based density in both shoreline and SAV habitats in late summer of three different years (2007, 2008, and 2009). For the dominant species (Fundulus diaphanus, Lepomis macrochirus, Etheostoma olmstedi, Morone americana, Lepomis gibbosus, and Fundulus heteroclitus), density was nearly always higher in SAV, but overall, species richness was highest in shoreline habitats sampled with seines. Although historical monitoring of fish in Gunston Cove (and throughout Chesapeake Bay) is based upon seine sampling (and trawl sampling in deeper areas), the high densities of fish and larger areal extent of SAV indicated that complementary sampling of SAV habitats would produce more accurate trends in abundances of common species. Because drop ring samples cover much less area than seines and may miss rare species, a combination of methods that includes seine sampling is needed for biodiversity assessment. The resurgence of SAV in tidal freshwater signifies improving water quality, and methods we evaluated here support improved inferences about population trends and fish community structure as indicators of ecosystem condition.     

Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing

The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The spectral library is used to automate the processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV (Myriophyllum spicatum and Vallisneria americana). Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. The algorithms and databases developed in this study will be useful with the current and forthcoming space-based hyperspectral remote sensing systems.     

Influence of anthropogenic transformations of river bed on plant and macrozoobenthos communities

This study describes the influence of urban area on plant communities and benthic invertebrates inhabiting the S?upia River (northern Poland). Ten plant communities and 37 macrozoobenthos taxa were determined during four seasonal samplings at 25 sampling sites (October 2005 and January, April, and August 2006). The obtained data set was statistically evaluated in order to reveal the influence of anthropogenic transformations on the investigated communities against the background of other abiotic factors. Multivariate regression tree (MRT) method was used for vegetation, while for benthic fauna, both MRT and artificial neural network (ANN) methods were applied. The following explanatory variables were used: season, water temperature, and salinity; location of a sampling site; degree of human impact on the riverbed; microhabitat; and substrate type. MRT analyses showed significant differences in plant community structure depending on the location of a sampling site, indicating the influence of anthropogenic pressure, while macrozoobenthos composition differed significantly only between seasons. The overall ANN model proved the importance of type and location of a sampling site for the approximation of benthic fauna density. Additionally, influence of the explanatory variables on the consecutive macrozoobenthos taxa was analyzed on the basis of separate ANN.     

A Multivariate Analysis of Biophysical Parameters of Tallgrass Prairie Among Land Management Practices and Years

Six treatments of eastern Kansas tallgrass prairie – native prairie, hayed, mowed, grazed, burned and untreated – were studied to examine the biophysical effects of land management practices on grasslands. On each treatment, measurements of plant biomass, leaf area index, plant cover, leaf moisture and soil moisture were collected. In addition, measurements were taken of the Normalized Difference VegetationIndex (NDVI), which is derived from spectral reflectance measurements. Measurements were taken in mid-June, mid-July and late summer of 1990 and 1991. Multivariate analysis of variance was used to determine whether there were differences in the set of variables among treatments and years. Follow-up tests included univariate t-tests to determine whichvariables were contributing to any significant difference. Results showed a significant difference (p < 0.0005) among treatments in the composite of parameters during each of the months sampled. In most treatment types, there was asignificant difference between years within each month. The univariate tests showed, however, that only some variables, primarily soil moisture, were contributing to this difference. We conclude that biomass and % plant cover show the best potential to serve as long-term indicators of grassland condition as they generally were sensitive to effects ofdifferent land management practices but not to yearlychange in weather conditions. NDVI was insensitive to precipitation differences between years in July for most treatments, but was not in the native prairie. Choice of sampling time is important for these parameters to serve effectively as indicators.     

The potential of biomonitoring of air quality using leaf characteristics of white willow (Salix alba L.)

In this study, we assess the potential of white willow (Salix alba L.) as bioindicator for monitoring of air quality. Therefore, shoot biomass, specific leaf area, stomatal density, stomatal pore surface, and stomatal resistance were assessed from leaves of stem cuttings. The stem cuttings were introduced in two regions in Belgium with a relatively high and a relatively low level of air pollution, i.e., Antwerp city and Zoersel, respectively. In each of these regions, nine sampling points were selected. At each sampling point, three stem cuttings of white willow were planted in potting soil. Shoot biomass and specific leaf area were not significantly different between Antwerp city and Zoersel. Microclimatic differences between the sampling points may have been more important to plant growth than differences in air quality. However, stomatal pore surface and stomatal resistance of white willow were significantly different between Zoersel and Antwerp city. Stomatal pore surface was 20% lower in Antwerp city due to a significant reduction in both stomatal length (?11%) and stomatal width (?14%). Stomatal resistance at the adaxial leaf surface was 17% higher in Antwerp city because of the reduction in stomatal pore surface. Based on these results, we conclude that stomatal characteristics of white willow are potentially useful indicators for air quality.     

Organochlorine Contaminants in Herring Gull Eggs from the Great Lakes, 1974-1995: Change Point Regression Analysis and Short-Term Regression

The temporal trends (1974-1995) of 11 organochlorine contaminants in herring gull eggs from 13 colonies throughout the Great Lakes were statistically analyzed using two regression methods on logarithmically transformed data. Change point analysis was used to determine if there had been significant year to year fluctuations in contaminant levels and/or changes in long-term trends. Short-term regressions were conducted on 6 major compounds for two time periods (early 1990s and early 1980s) to compare the rates of decline. Overall, change point analyses indicated that for most of the comparisons (75%) there had been significant year to year fluctuations in contaminant levels. They also indicated that for most of the comparisons (67%) the rate of decline after the change point was as fast as or faster than before the change point, this pattern was most common for dieldrin and heptachlor epoxide at certain locations. In 19% of the comparisons the rates of decline had slowed or stabilized, this was most common for PCB and pentachlorobenzene. In 14% of the comparisons there were no significant temporal trends, this was most common for photomirex and mirex. Results for short-term regression showed that out of 78 comparisons for each time period, 5 (6%) were declining significantly in the early 1990s and 11 (14%) were declining significantly in the early 1980s. Both types of regression indicated that, for most of the herring gull egg contaminant database, recent logarithmic rates of decline were similar to those seen previously in the sampling period. For PCB 1254:1260, a group of compounds of particular toxicological importance, change point analyses indicated that the logarithmic rates of decline in herring gull eggs from western Lake Ontario were slower from 1987-1995 than they were from 1974-1986. At both Lake Superior colonies and the Niagara River colony PCB 1254:1260 concentrations ceased to decline in the mid-1980s. At the colony in Green Bay, Lake Michigan, PCB 1254:1260 levels have shown no significant temporal trend since 1976. At the remaining 8 colonies, PCB 1254:1260 levels continue a logarithmic decline in recent years at the same rate as or faster than previously.     

A comparison of techniques to sample salamander assemblages along highland streams of Maryland

Amphibians may be useful indicators of biological condition in small streams so determining which sampling technique maximizes encounters at the least cost and at the optimal time of year is important. Area constrained surveys (ACS), used by the Maryland Biological Stream Survey, were tested against cover board surveys, drift fences with pitfall and funnel traps, quadrat leaf litter searches, and leaf litter bags. Sixteen, 100 m-long sites were established in headwater streams in the Savage River State Forest in Garrett County, Maryland. Each technique was randomly assigned to a 25 m stream section within each overall sampling site, and sites were sampled once each month from May to October (2005) with additional sampling in March and April (2006). Area constrained surveys yielded means of 2.7 taxa and 14.9 total individuals per sampling visit, which was significantly higher than the yield of all other methods in all months except October and March, when yields were low for all techniques. Area constrained surveys were also significantly more cost-effective per taxon and per individual compared to all other methods. September produced the most taxa and individuals, October and March produced the least, and yields for April through August were similar to September. We employed removal sampling at four sites in April 2006, but abundance could not be estimated because a significant linear decrease in the accumulated catch versus catch per unit effort did not occur for three of the sites.     

The Influence of Linear Elements on Plant Species Diversity of Mediterranean Rural Landscapes: Assessment of Different Indices and Statistical Approaches

This paper mainly aims to study the linear element influence on the estimation of vascular plant species diversity in five Mediterranean landscapes modeled as land cover patch mosaics. These landscapes have several core habitats and a different set of linear elements -habitat edges or ecotones, roads or railways, rivers, streams and hedgerows on farm land- whose plant composition were examined. Secondly, it aims to check plant diversity estimation in Mediterranean landscapes using parametric and non-parametric procedures, with two indices: Species richness and Shannon index.Land cover types and landscape linear elements were identified from aerial photographs. Their spatial information was processed using GIS techniques. Field plots were selected using a stratified sampling design according to relieve and tree density of each habitat type. A 50×20 m² multi-scale sampling plot was designed for the core habitats and across the main landscape linear elements. Richness and diversity of plant species were estimated by comparing the observed field data to ICE (Incidence-based Coverage Estimator) and ACE (Abundance-based Coverage Estimator) non-parametric estimators.The species density, percentage of unique species, and alpha diversity per plot were significantly higher (p < 0.05) in linear elements than in core habitats. ICE estimate of number of species was 32% higher than of ACE estimate, which did not differ significantly from the observed values. Accumulated species richness in core habitats together with linear elements, were significantly higher than those recorded only in the core habitats in all the landscapes. Conversely, Shannon diversity index did not show significant differences.     

Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran)

Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.     

What do qualitative rapid assessment collections of macroinvertebrates represent? A comparison with extensive quantitative sampling

It is a fundamental tenet of Rapid Biological Assessments (RBA) that the samples collected reflect the community from which they are drawn. As with any biological sampling, RBA collections are subject to sampling error resulting in the omission of some taxa. The aim of this study is to compare the composition of RBA samples with an estimate of community structure based on extensive quantitative sampling. We used logistic regression to explore the relationships between the frequency of a taxon being collected in an RBA sample and its biological and ecological traits, namely its abundance, distribution, body size and habit. RBA samples and quantitative estimates of community structure were made in riffles in the Kangaroo and Nepean Rivers, New South Wales, Australia. Single RBA samples may collect up to 63% of the taxa that are collected by extensive quantitative sampling at a site. The frequency of a taxon being recorded in an RBA sample was significantly and positively related to all traits tested indicating a bias in the collection methods towards large, abundant and widely distributed taxa. Accordingly, taxa missed by RBA sampling were generally small, narrowly distributed or rare. These findings enhance our understanding of what RBA samples represent, and the bias and source of errors associated with RBA sampling. This study also quantifies the utility of RBA methods for biodiversity assessment.     

Bootstrapping to investigate the effect of number of macroinvertebrate samples on confidence limits of the mean

A resampling technique (bootstrapping) was used to evaluate the effects of increasing sample number on the confidence limits of mean density and the mean number of taxa (Families) in addition to the performance of four different sampling devices used to collect macroinvertebrates in three streams of contrasting anthropogenic impact. The four sampling devices were a Hess sampler, a modified Hess sampler equipped with an internal water pump, a Surber sampler, and a two-pole kick-net. In general, confidence limits decreased predictably as the number of samples increased, most notably with the addition of a third sample. The density of organisms captured with the Surber sampler was significantly lower than that of the Hess sampler but greater than that of the kick-net sampler. No significant difference in the number of Families was found among sampling devices. Based upon a minimal 10% reduction in confidence limits compared to the previous sample, a minimum of four replicates was suggested when using the Surber sampler. In general, other methods required a greater number of replicates that the Surber to adequately represent density, but this did not hold when applied to the number of taxa. Despite the inconvenience of having to bend down to use the Surber sampler, this study found no evidence to reject its apparent popularity as a sampling method for macroinvertebrates.     

Seagrass resource assessment using remote sensing methods in St. Joseph Sound and Clearwater Harbor,Florida, USA

In the event of a natural or anthropogenic disturbance, environmental resource managers require a reliable tool to quickly assess the spatial extent of potential damage to the seagrass resource. The temporal availability of the Landsat 5 Thematic Mapper (TM) imagery provided a suitable option to detect and assess damage of the submerged aquatic vegetation (SAV). This study examined Landsat TM imagery classification techniques to create two-class (SAV presence/absence) and three-class (SAV estimated coverage) SAV maps of the seagrass resource. The Mahalanobis Distance method achieved the highest overall accuracy (86%) and validation accuracy (68%) for delineating the seagrass resource (two-class SAV map). The Maximum Likelihood method achieved the highest overall accuracy (74%) and validation accuracy (70%) for delineating the seagrass resource three-class SAV map. The Landsat 5 TM imagery classification provided a seagrass resource map product with similar accuracy to the aerial photointerpretation maps (validation accuracy 71%). The results support the application of remote sensing methods to analyze the spatial extent of the seagrass resource.     

Changes in levels of organochlorines in woodcock wings from 1971 to 1975

Wings from woodcock (Philohela minor) were first monitored for organochlorine pesticides and polychlorinated biphenyls (PCBs) in the eastern U.S. in 1971. Regional differences in these compounds were clearly demonstrated and baseline residue levels were obtained for later comparisons. An expanded sampling of wings in 1972 revealed that residues in wings of adult woodcock may differ significantly from those in immatures, and that residues of several important agricultural insecticides and PCBs had declined significantly. More extensive sampling was undertaken in 1975 to determine if changes in residue levels had taken place in the intervening years. PCBs, mirex, and heptachlor epoxide increased significantly between 1972 and 1975 in adult woodcock wings. In immature woodcock wings mirex, dieldrin, and PCBs increased significantly between 1972 and 1975, but DDT residues decreased significantly.     

Mapping aboveground woody biomass using forest inventory,remote sensing and geostatistical techniques

Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m?×?31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10–40, 40–70 and >70 % of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m³ ha^?1. The total growing stock of the forest was found to be 2,024,652.88 m³. The AGWB ranged from 143 to 421 Mgha^?1. Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE)?=?42.25 Mgha^?1) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha^?1 respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha^?1. The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

Terrestrial snails as quantitative indicators of environmental metal pollution

Concentrations of cadmium, lead, copper and zinc were measured in individuals of Arianta arbustorum from different urban sampling sites. In comparison to snails from a reference site, the animals collected in the city showed higher concentrations of cadmium, lead, and copper, indicating elevated levels of metal pollution. The most pronounced difference in tissue concentrations between control animals and contaminated snails was observed for lead. Within the city, metal levels in snails differed significantly, even between adjacent populations. Arianta arbustorum is a suitable species for biomonitoring, because it is widespread, resident and easy to collect; it has a high capacity for metal accumulation and shows different concentrations depending on metal contamination of the sampling area. An interspecific comparison of metal concentrations in terrestrial gastropods was conducted to define background levels and classes of burden. Three pollution levels are distinguished on the basis of the snails' metal burden: no pollution (class 1: reference sites), moderate (class 2: traffic and other human activities in urban areas), and high pollution (class 3: mining and heavy industry).     

溪源水库蓄水前后冬春季水体营养盐和浮游植物特征研究

于2007—2008年溪源水库蓄水前,2014—2015年溪源水库蓄水后对溪源宫水源地水体进行采样,分析了冬春季水体的理化指标、浮游植物生物量及群落组成。蓄水前共鉴定出浮游植物6门26属43种,水体水质状况较好,浮游植物细胞密度平均为7.31×10~5cells/L,以硅藻、绿藻门为优势门类,两者占浮游植物总生物量的比例约为54.7%、32.2%,水体呈贫-中营养状态。蓄水后,水体氮、磷营养盐浓度分别约为蓄水前的2.4倍、3倍,浮游植物细胞密度平均为1.42×10~7cells/L,约为蓄水前的20倍,且群落结构发生改变,优势门类为硅藻、蓝藻、绿藻,所占比例分别为40.2%、38.7%、14.4%,蓝藻门比例有显著提高,约为蓄水前的5倍。说明建库蓄水对浮游植物的影响显著。     

Using Multiple Antibiotic Resistance and land use characteristics to determine sources of fecal coliform bacterial pollution

Multiple Antibiotic Resistance (MAR) analysis and regression modeling techniques were used to identify surface water areas impacted by fecal pollution from human sources, and to determine the effects of land use on fecal pollution in Murrells Inlet, a small, urbanized, high-salinity estuary located between Myrtle Beach and Georgetown, South Carolina. MAR analysis was performed to identify areas in the estuary that are impacted by human-source fecal pollution. Additionally, regression analysis was performed to determine if an association exists between land use and fecal coliform densities over the ten-year period from 1989 to 1998. Land-use variables were derived using Geographic Information System (GIS) techniques and were used in the regression analysis.MAR analyses were conducted by comparing the frequency and patterns of antibiotic resistance found in Escherichia coli isolates derived from surface water samples and from sewage sources in the Murrells Inlet sewage collection system. The MAR results suggest that the majority of the fecal pollution detected in the Murrells Inlet estuary may be from non-human sources, including fecal coliforms isolated from areas in close proximity to high densities of active septic tanks.A MAR Index, which measures the frequency of antibiotic resistance, was calculated for each of twenty-three water samples and nine sewage samples. The antibiotic resistance pattern comparisons were performed using cluster analysis. Although the MAR indices indicated that several surface water sites had potential human-source contamination, the cluster analysis suggests that only one sampling site had MAR patterns that were similar to those found in the sewage samples. This site was in close proximity to several large pleasure boats as well as a sewage collection system lift station, but was not near areas with active septic tanks. The results of the regression analysis also suggest that sewage sources and rainfall runoff from urbanized areas may contribute to fecal pollution in the estuary.     

Impact of microcystin containing diets on physiological performance of Nile tilapia (Oreochromis niloticus) concerning detoxification

Nile tilapia (Oreochromis niloticus) were fed by diets supplemented with cyanobacteria containing in part the cyanotoxin microcystin-LR (MC-LR) to determine the potential impacts on detoxification. Four different diets were prepared based on a commercial diet: (1) control, (2) MC-5% (containing 5% dried Microcystis sp. biomass with 4.92 μg MC-LR g(-1) diet), (3) MC-20% (containing 20% dried Microcystis sp. biomass with 19.54 μg MC-LR g(-1) diet), and (4) Arthr-20% (containing 20% dried Arthrospira sp. biomass without MC-LR). Blood and liver samples were taken after one, 7, and 28 days and protein has been determined in plasma and liver. In the liver, impacts on detoxification were measured by glutathione-S-transferase (GST) activities and gene expression of multi drug resistance protein (MDRP). Plasma protein did not change between all four diets at any sampling time whereas liver protein was significantly elevated already after one day in Arthr-20% and after 28 days in both, MC-20% and Arthr-20%. Biochemical measurements of GST activities revealed no significant impact at any sampling time. In order to characterize the potential effect of MC-LR on MDRP, RT-qPCR method was established. However, as for GST activities no significant changes in MDRP gene expression have been observed. Thus, in summary, oral exposure of MC-LR containing cyanobacteria to Nile tilapia via feed ingestion did not impact significantly detoxification in liver concerning GST activities and MDRP expression despite biochemical composition concerning liver protein was significantly elevated by the diets containing 20% cyanobacteria biomass, regardless whether they contained MC-LR or not.     

洪泽湖藻类与环境因子逐步回归统计和蓝藻水华初步预测

以洪泽湖2008—2010年的连续监测资料为基础,运用多元逐步回归统计方法,选择水温等12项环境因子与藻类叶绿素a等5项生物因子进行逐步回归分析,找出与生物因子显著相关的因子,建立多元逐步回归方程,预测洪泽湖藻类密度的变化情况,初步进行了洪泽湖蓝藻水华的预测预报。结果显示,总磷、总氮、氨氮和水深为洪泽湖藻类密度的显著相关因子,透明度、水温、水深为蓝藻密度的显著相关因子。