Historical Groundwater Trends in Northern New England and Relations with Streamflow and Climatic Variables

Water‐level trends spanning 20, 30, 40, and 50 years were tested using month‐end groundwater levels in 26, 12, 10, and 3 wells in northern New England (Maine, New Hampshire, and Vermont), respectively. Groundwater levels for 77 wells were used in interannual correlations with meteorological and hydrologic variables related to groundwater. Trends in the contemporary groundwater record (20 and 30 years) indicate increases (rises) or no substantial change in groundwater levels in all months for most wells throughout northern New England. The highest percentage of increasing 20‐year trends was in February through March, May through August, and October through November. Forty‐year trend results were mixed, whereas 50‐year trends indicated increasing groundwater levels. Whereas most monthly groundwater levels correlate strongly with the previous month's level, monthly levels also correlate strongly with monthly streamflows in the same month; correlations of levels with monthly precipitation are less frequent and weaker than those with streamflow. Groundwater levels in May through August correlate strongly with annual (water year) streamflow. Correlations of groundwater levels with streamflow data and the relative richness of 50‐ to 100‐year historical streamflow data suggest useful proxies for quantifying historical groundwater levels in light of the relatively short and fragmented groundwater data records presently available.     

The transition of a line plume to round plume

Environmental Fluid Mechanics - Buoyant turbulent plumes are often categorized by their geometry and described as either round plumes, issuing from a point source, or line/planar plumes, issuing...     

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.     

Factors Influencing the Effectiveness of Wildlife Underpasses in Banff National Park, Alberta, Canada

Abstract: Wildlife crossing structures are intended to increase permeability and habitat connectivity across roads. Few studies, however, have assessed the effectiveness of these mitigation measures in a multispecies or community level context. We used a null model to test whether wildlife crossing structures serve large mammal species equally or whether such structures limit habitat connectivity across roads in species-specific ways. We also modeled species responses to 14 variables related to underpass structure, landscape features, and human activity. Species performance ratios (observed crossing frequency to expected crossing frequency) were evaluated for four large carnivore and three ungulate species in 11 underpass structures in Banff National Park, Alberta, Canada. Observed crossing frequencies were collected in 35 months of underpass monitoring. Expected frequencies were developed from three independent models: radio telemetry, pellet counts, and habitat-suitability indices. The null model showed that species responded to underpasses differently. In the presence of human activity carnivores were less likely to use underpasses than were ungulates. Apart from human activity, carnivore performance ratios were better correlated to landscape variables, and ungulate performance ratios were better correlated to structural variables. We suggest that future underpasses designed around topography, habitat quality, and location will be minimally successful if human activity is not managed.     

Exploitation of a single-cohort fishery under risk: A simulation-optimization approach

A numerical approach involving dynamic programming and computer simulation is used to examine the socially optimal exploitation of a single-cohort fishery under risk, with specific reference to the Exmouth Gulf Prawn Fishery in Western Australia. Best management strategies for given investment levels are sought before optimizing investment. The results for this industry show that time of year is much more important then level of biomass in determining best fishing policies, and that the timing of the catch is sensitive to natural fluctuations in some biological variables. Employing a “closed season” policy for part of the year appears an attractive way of reconciling private and social objectives under commonality. Under or overcapitalization does not reduce benefits markedly.     

Flow regulation and fragmentation imperil pelagic-spawning riverine fishes.

Flow regulation and fragmentation of the world's rivers threaten the integrity of freshwater ecosystems and have resulted in the loss or decline of numerous fish species. Pelagic-spawning fishes (pelagophils) are thought to be particularly susceptible to river regulation because their early life stages (ichthyoplankton) drift until becoming free-swimming, although the extent of transport is largely unknown. Transport velocity and distance were determined for passively drifting particles, which mimicked physical properties of ichthyoplankton, in two large, regulated rivers (Rio Grande and Pecos River) of the arid Southwest United States. Particle drift data were incorporated into celerity-discharge equations (r2 > 0.90; P < 0.001), and reach-specific transport velocity was modeled as a function of discharge. Transport velocities of particles exceeded 0.7 m/s in all river reaches during typical spawning flows (i.e., reservoir releases or rainstorms) and were greatest in highly incised and narrow channel reaches. Mean transport distance of particles released in the Pecos River during sustained reservoir flows (141.1 km; 95% CI = 117.0-177.5 km) was significantly longer than during declining reservoir flows that mimicked a natural rainstorm (52.4 km; 95% CI = 48.8-56.5 km). Mean transport distance of particles in the Rio Grande during sustained reservoir flows was 138.7 km (95% CI = 131.0-147.2 km). There are 68 dams and 13 reservoirs that fragment habitats and regulate flow in the Rio Grande Basin (Rio Grande and Pecos River) in areas historically occupied by pelagophils. While the basin historically provided 4029 km of free-flowing riverine habitat, reservoir habitat now represents > 10% of the longitudinal distance. Only five unfragmented nonreservoir reaches > 100 km remain in the Rio Grande, and two remain in the Pecos River. Pelagophils were extirpated from all reservoirs and from nearly all short, fragmented reaches (< 100 km) of the Rio Grande Basin, but at least some fraction persisted in all longer reaches (> 100 km). The recovery and long-term persistence of pelagophils in regulated rivers, including those in this study, will likely depend on reestablishment and protection of long unfragmented reaches coupled with mimicry of the natural flow regime.     

The effects of regional angling effort, angler behavior, and harvesting efficiency on landscape patterns of overfishing

We used a coupled social-ecological model to study the landscape-scale patterns emerging from a mobile population of anglers exploiting a spatially structured walleye (Sander vitreus) fishery. We systematically examined how variations in angler behaviors (i.e., relative importance of walleye catch rate in guiding fishing site choices), harvesting efficiency (as implied by varying degrees of inverse density-dependent catchability of walleye), and angler population size affected the depletion of walleye stocks across 157 lakes located near Thunder Bay (Ontario, Canada). Walleye production biology was calibrated using lake-specific morphometric and edaphic features, and angler fishing site choices were modeled using an empirically grounded multi-attribute utility function. We found support for the hypothesis of sequential collapses of walleye stocks across the landscape in inverse proportionality of travel cost from the urban residence of anglers. This pattern was less pronounced when the regional angler population was low, density-dependent catchability was absent or low, and angler choices of lakes in the landscape were strongly determined by catch rather than non-catch-related attributes. Thus, our study revealed a systematic pattern of high catch importance reducing overfishing potential at low and aggravating overfishing potential at high angler population sizes. The analyses also suggested that density-dependent catchability might have more serious consequences for regional overfishing states than variations in angler behavior. We found little support for the hypotheses of systematic overexploitation of the most productive walleye stocks and homogenized catch-related qualities among lakes sharing similar access costs to anglers. Therefore, one should not expect anglers to systematically exploit the most productive fisheries or to equalize catch rates among lakes through their mobility and other behaviors. This study underscores that understanding landscape overfishing dynamics involves a careful appreciation of angler population size and how it interacts with the attributes that drive angler behaviors and depensatory mechanisms such as inverse density-dependent catchability. Only when all of these ingredients are considered and understood can one derive reasonably predictable patterns of overfishing in the landscape. These patterns range from self-regulating systems with low levels of regional fishing pressure to sequential collapse of walleye fisheries from the origin of angling effort.     

From expectation to experience: Graduates entering a large corporation

The paper reports a longitudinal study of new and recently recruited graduates to an oil company, to evaluate how initial expectations compared with experience, and how needs, interests and work activities changed over time post-entry. Results showed that new entrants had unrealistic expectations, especially of having more managerial job content than they were assigned initially, but this increased with subsequent experience to reach expected levels. Socialization effects were evident, especially by job function, but not by gender. The work orientations and job experiences of commercial and technical graduates developed on divergent paths over time, suggesting more positive personal growth over their early careers for the commercial graduates.