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.