Selection Of Environmental Variables Research Articles

Generalizing Trends in Upstream American Eel Movements at Four East Coast Hydropower Projects

Abstract Dams impede the upstream migration of juvenile American Eel Anguilla rostrata, limiting their access to freshwater habitat and potentially contributing to population declines across their range. The implementation of fishways at large hydropower dams help restore access to upstream habitat and represents a long-term dataset of American Eel captures. We analyzed the relationships between eel captures and select environmental variables (river discharge, water temperature, and lunar illumination) at four hydropower projects on east coast rivers with a comparable decade of data and sampling techniques: Roanoke Rapids Dam on the Roanoke River in North Carolina, Conowingo Dam on the Susquehanna River in Maryland, Holyoke Dam on the Connecticut River in Massachusetts, and the Moses-Saunders Dam on St. Lawrence River in New York and Canada. The number of eels captured varied among projects, from year to year, and seasonally. American Eel are opportunistic in their upstream movements, with peak movement events associated with high flows, increased water temperature, and low lunar illumination. Our results suggest that systems altered by hydropower dams offer unique challenges to American Eel migrants and that a multitude of factors play a role in the timing of upstream movements.

Feasibility of High-Frequency Monitoring of the Home Environment and Health in Older Adults: Proof of Concept

Technology provides new opportunities to understand and optimize the relationship between the home indoor environmental quality and health outcomes in older adults. We aimed to establish proof-of-concept and feasibility of remote, real-time, high-frequency, and simultaneous monitoring of select environmental variables and outcomes related to health and wellbeing in older adults. Thirty-four participants (27 were female) with an average age (SD) of 81 years (±7.1) were recruited from community and supportive housing environments. Environmental sensors were installed in each home and participants were asked to use a wearable device on their finger and answer smartphone-based questionnaires on a daily basis. Further, a subgroup of participants were asked to complete tablet-based cognitive tests on a daily basis. Average compliance with the wearable (time worn properly/total time with device) was 81%. Participants responded to 69% of daily smartphone surveys and completed 80% of the prescribed cognitive tests. These results suggest that it is feasible to study the impact of the home thermal environment and air quality on biological rhythms, cognition, and other outcomes in older adults. However, the success of non-passive data collection elements may be contingent upon baseline cognition.

Abiotic and biotic drivers of endosymbiont community assembly in Jatropha curcas

AbstractWhile the endosymbiotic communities recruited by plants are known to vary among host species and across environmental gradients, the drivers of community assembly remain poorly understood. We tested the hypothesis that establishment of an endosymbiotic bacterial community is driven primarily by the influence of the abiotic environment on biotic interactions between plant and soil bacteria. We planted sterile Jatropha curcas seedlings at three field sites in Panama and in a greenhouse with soil from those sites. After allowing sufficient time for endosymbiont colonization, we sequenced bacterial 16S rRNA to study the endophytic bacterial community in root and leaf tissue. We compared the communities between field and greenhouse plants and examined associations among the endosymbionts, the soil microbial community, and local abiotic factors. We found that endosymbiont richness and community composition varied between the greenhouse and field, despite plants being grown in the same soil. Plants in each field site harbored a distinct bacterial community, determined by soil microbes and select environmental variables, particularly major plant nutrients. Jatropha curcas can harbor a wide variety of endosymbiotic communities, and the composition of these communities is a product of the local environment. Fertility and agricultural practices may determine the fate of plant symbionts and therefore plant properties modulated through those symbionts.

Analytical Modeling of Partially Shaded Photovoltaic Systems

As of today, the considerable influence of select environmental variables, especially irradiance intensity, must still be accounted for whenever discussing the performance of a solar system. Therefore, an extensive, dependable modeling method is required in investigating the most suitable Maximum Power Point Tracking (MPPT) method under different conditions. Following these requirements, MATLAB-programmed modeling and simulation of photovoltaic systems is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) systems. End results prove the reliability of the proposed model in replicating the aforementioned output characteristics in the prescribed setting. The proposed model is chosen because it can, conveniently, simulate the behavior of different ranges of PV systems from a single PV module through the multidimensional PV structure.

The relationship between carbon and nitrogen stable isotopes of zooplankton and select environmental variables in low-latitude reservoirs

Cyclopoids were collected from 18 reservoirs in southern China during August (a wet month) and December (a dry month) of 2010 for the analysis of carbon and nitrogen stable isotopes (δ13CZoo and δ15NZoo). The objectives of this study were to examine whether δ13CZoo and δ15NZoo can be better indicators of primary productivity and trophic state than the stable isotope composition of suspended particulate organic matter (POM), and to evaluate the relationship between δ13CZoo and δ15NZoo and select environmental variables. The δ13CZoo in these reservoirs was enriched in August and depleted in December, and varied significantly along the continuum of trophic levels. By contrast, δ15NZoo was depleted in August and enriched in December, and did not increase significantly with an increase in trophic state. Both δ13CZoo and δ15NZoo were more strongly correlated with environmental factors than δ13CPOM and δ15NPOM were. In addition, more environmental factors were significantly correlated with δ13CZoo and the δ15NZoo than with δ13CPOM and δ15NPOM. When data from two seasons were pooled, δ13CZoo was strongly correlated with dissolved inorganic nitrogen (DIN), soluble reactive phosphorus (SRP) and the DIN:SRP ratio, while δ15NZoo was weakly correlated with nutrient concentrations. This study indicates that, compared to the stable isotope composition of POM, δ13CZoo is a better indicator of primary productivity and trophic state, while δ15NZoo may be used as a proxy for nitrogen sources in aquatic ecosystems.

Auscultatory, echocardiographic, biochemical, nutritional, and environmental characteristics of mitral valve disease in Norfolk terriers

ObjectivesIn order to more fully understand degenerative mitral valve disease (DMVD) in the Norfolk terrier, we sought to characterize findings from the physical and echocardiographic examination; biochemical, biomarker, and nutritional profiles; and select environmental variables from a cohort of apparently healthy Norfolk terriers. Animals, materials and methodsOvertly healthy Norfolk terriers ≥6 yrs old were recruited by 3 different veterinary hospitals and underwent historical, physical, electrocardiographic (ECG), and 2D/color-flow Doppler echocardiographic examinations. Anterior mitral valve leaflet length, maximal thickness, area, and degree of prolapse were measured or calculated from two-dimensional images. Blood samples were obtained for serum biochemistry, serum serotonin, plasma NT-proBNP, amino acid profile, C-reactive protein, and cardiac troponin I. ResultsOf the 48 dogs entered into the study, 23 (48%) had murmurs, 2 (4%) had mid-systolic clicks, 11 (23%) had ECG P pulmonale, and 41 (85%) were deemed to have echocardiographic evidence of DMVD, including 18 Norfolk terriers without a murmur. Seven (15%), 28 (58%), and 13 (27%) dogs were classified as normal (stage 0), International Small Animal Cardiac Health Council (ISACHC) stage 1a, and 1b, respectively. Mean indexed echocardiographic mitral leaflet thickness (P = 0.017), area (P = 0.0002), prolapse (P = 0.0004), and left atrial to aortic diameter (P = 0.01) were significantly different between ISACHC 0, 1a, and 1b. ConclusionDMVD is relatively common in Norfolk terriers and echocardiographic changes consistent with mild DMVD can be seen in dogs without a heart murmur.

Water Chemistry and Landscape Patterns in the Distribution of Banded Sunfish (Enneacanthus obesus) in Streams of the Atlantic Coastal Plain in Maryland

Water chemistry and landscape data were analyzed from streams in the Atlantic Coastal Plain physiographic province in Maryland, USA, to identify patterns in the spatial distribution of the state rare Banded Sunfish (Enneacanthus obesus). Principal component analysis was used to assess patterns in the distribution of this species based on select environmental variables. Mantel tests were conducted to further assess the correlation of environmental variables with the distribution of Banded Sunfish in Maryland while accounting for spatial autocorrelation. The distribution of Banded Sunfish was correlated with acidic stream segments with high concentrations of dissolved organic carbon and higher proportions of forest and wetland landscapes in upstream catchments. Conservation of Banded Sunfish will require the preservation of acidic, blackwater habitats through the protection of natural forest and wetland landscapes and limiting of the potentially harmful impacts of agricultural practices and urbanization. Such practices would likely benefit other native fishes throughout the region as well.

Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network

Artificial neural networks (ANNs) and Bayesian belief networks (BBNs) utilizing select environmental variables were developed and evaluated, with the intent to model net ecosystem metabolism (a proxy for system trophic state) within a freshwater wetland. Network modeling was completed independently for distinct data subsets, representing periods of ‘low’ and ‘high’ water levels throughout in the wetland. ANNs and BBNs were ‘benchmarked’ against traditional parametric analyses, with network architectures outperforming regression models. ANNs delivered the greatest predictive accuracy for NEM and did not require expert knowledge about system variables for their development. BBNs provided users with an interactive diagram depicting predictor interaction and the qualitative/quantitative effects of variable dynamics upon NEM, thereby affording better information extraction. Importantly, BBNs accommodated the imbalanced nature of the dataset and appeared less affected (than ANNs) with variable auto-correlation traits that are typically observed within large and ‘noisy’ environmental datasets.

Detecting toxic diatom blooms from ocean color and a regional ocean model

[1] An apparent link between upwelling-related physical signatures, macronutrients, and toxic diatom blooms in the various “hotspots” throughout California has motivated attempts to forecast harmful algal blooms (HABs) as a function of select environmental variables. Empirical models for predicting toxic Pseudo-nitzschia blooms in one such region, the Santa Barbara Channel (SBC), are tested in a nowcast mode using predictions based on merging data from MODIS ocean color geophysical products and the Regional Ocean Modeling System (ROMS) applied to the Southern California Bight. Thresholds for each model generate event forecasts. Spatially-explicit, monthly HAB maps are compared to shipboard observations and California monitoring data, demonstrating that the models predict offshore events otherwise undetected by nearshore monitoring. The use of mechanistic hydrodynamic models in concert with empirical, biological models facilitates future process studies on the effects of coastal eutrophication and climate change on regional HAB dynamics.