MODELING THE IMPACT OF MULTICOMPONENT VOCs ON GROUND WATER USING THE STEFAN‐MAXWELL EQUATION1

ABSTRACT: Computer programs that model the fate and transport of organic contaminants through porous media typically use Fick's first law to calculate vapor phase diffusion. Fick's first law, however, is limited to the case of a single, dilute species diffusing into a stagnant, high concentration, bulk vapor phase. When dealing with more than one diffusing species and at higher concentrations, the multicomponent coupling effects on vapor phase diffusion and advection of the various constituents become significant. VLEACH, a one‐dimensional finite difference model developed for the U.S. Environmental Protection Agency (USEPA), is typical of the models using Fick's first law to model vapor‐phase diffusion. The VLEACH model was modified to accommodate up to 10 components and to calculate the binary diffusion coefficients for each of the components based on molecular weight, molecular volume, temperature and pressure, and to address the coupling effects on multiple component vapor phase diffusion and its impact on ground water. The resulting model was renamed MC‐CHEMSOIL. At low vapor phase concentrations, MC‐CHEMSOIL predicts identical ground water impacts (dissolved phase loading) to those from VLEACH 2.2a. At higher vapor phase concentrations, however, the relative difference between the models exceeded 20 percent.     

CHEMISTRY OF COALBED METHANE DISCHARGE WATER INTERACTING WITH SEMI‐ARID EPHEMERAL STREAM CHANNELS1

ABSTRACT: The objective of this study was to examine the chemistry of Coalbed Methane (CBM) discharge water reacting with semi‐arid ephemeral stream channels in the Powder River Basin, Wyoming. The study area consisted of two ephemeral streams: Burger Draw and Sue Draw. These streams are tributaries to the perennial Powder River. Samples were collected bimonthly from three CBM discharge points and seven channel locations in Burger Draw and Sue Draw. Samples were also collected bimonthly from the Powder River above and below the confluence of Burger Draw. Before sample collection, the pH and electrical conductivity (EC) were measured in the field. Samples were transported to the laboratory and analyzed for alkalinity, major cations, and anions. From the measurement of sodium (Na), calcium (Ca), and magnesium (Mg), practical sodium adsorption ratio (SARp) and true sodium adsorption ratio (SARt) were calculated. Results suggest pH and EC of CBM discharge water was 7.1 and 4.3 dS/m, respectively. The CBM discharge water consisted of higher concentrations of sodium and alkalinity compared to other components. The pH of CBM discharge water increased significantly (p = 0.000) in the downstream channel of Burger Draw from 7.1 to 8.84 before it joined with the Powder River. Dissolved calcium concentration of CBM discharge water decreased significantly (p = 0.000) in the downstream channel water. Subsequently, SARp increased approximately from 24 to 29. The SARt also increased significantly (p = 0.001) in the downstream channel water. For instance, SARt of CBM discharge water increased from 32.93 to 45.5 downstream channels after the confluence of Sue Draw with the Burger Draw. The only significant difference in water chemistry above and below the confluence of Burger Draw with the Powder River was pH, which increased from 8.36 to 8.52. The significant increase in SAR values of CBM discharge water in Burger Draw and Sue Draw tributaries suggest a careful monitoring of salinity and sodicity is needed if CBM discharge water is used for irrigation in semi‐arid environments. Results discussed in this study will be useful to downstream water users who depend on water for irrigation.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

GEOMORPHOLOGY OF STEEPLAND HEADWATERS: THE TRANSITION FROM HILLSLOPES TO CHANNELS1

Headwater streams comprise 60 to 80 percent of the cumulative length of river networks. In hilly to mountainous terrain, they reflect a mix of hillslope and channel processes because of their close proximity to sediment source areas. Their morphology is an assemblage of residual soils, landslide deposits, wood, boulders, thin patches of poorly sorted alluvium, and stretches of bedrock. Longitudinal profiles of these channels are strongly influenced by steps created by sediment deposits, large wood, and boulders. Due to the combination of small drainage area, stepped shallow gradient, large roughness elements, and cohesive sediments, headwater streams typically transport little sediment or coarse wood debris by fluvial processes. Consequently, headwaters act as sediment reservoirs for periods spanning decades to centuries. The accumulated sediment and wood may be episodically evacuated by debris flows, debris floods, or gully erosion and transported to larger channels. In mountain environments, these processes deliver significant amounts of materials that form riverine habitats in larger channels. In managed steepland forests, accelerated rates of landslides and debris flows resulting from the harvest of headwater forests have the potential to seriously impact the morphology of headwater streams and downstream resources.     

A Multi‐Scale Analysis of Single‐Family Residential Water Use in the Phoenix Metropolitan Area

Studies that evaluate determinants of residential water demand typically use data from a single spatial scale. Although household‐scale data are preferred, especially when econometric models are used, researchers may be limited to aggregate data. There is little, if any, empirical analysis to assess whether spatial scale may lead to ecological fallacy problems in residential water use research. Using linear mixed‐effects models, we compare the results for the relationship of single‐family water use with its determinants using data from the household and census tract scales in the city of Phoenix. Model results between the household and census tract scale are similar suggesting the ecological fallacy may not be significant. Common significant determinants on these two spatial scales include household size, household income, house age, pool size, irrigable lot size, precipitation, and temperature. We also use city/town scale data from the Phoenix metropolitan area to parameterize the linear mixed‐effects model. The difference in the parameter estimates of those common variables compared to the first two scales indicates there is spatial heterogeneity in the relationship between single‐family water use and its determinants among cities and towns. The negative relationship between single‐family house density and residential water use suggests that residential water consumption could be reduced through coordination of land use planning and water demand management.     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Considering the needs of indigenous and local populations in conservation programs

Local rural and indigenous communities have assumed increasing responsibility for conservation within and between areas buffering the impacts of agricultural or resource‐extraction zones and protected areas. Empowering local communities as central partners in conservation and climate‐change mitigation has allowed many people to gain access to land and citizenship rights but has provided limited improvements in access to social services and economic opportunities even as expectation about their role as environmental stewards grows. These expectations, however, are inconsistent with reality. We conducted multiple field studies in Brazil since the mid‐1980s to illustrate the discrepancies between conservation programs and local conditions and expectations. We suggest that public policies and conservation programs should not delegate responsibility for managing protected areas to local and indigenous communities without considering local needs and expectations and locals’ attitudes toward conservation. In other words, behavior that maintains or improves the environment should not be treated as traditional based on the expectations of outsiders. Framing local populations as traditional environmentalists creates contradictions and frustrations for local populations and for conservation professionals and policy makers.     

Level of environmental threat posed by horticultural trade in Cactaceae

Ornamental horticulture has been identified as an important threat to plant biodiversity and is a major pathway for plant invasions worldwide. In this context, the family Cactaceae is particularly challenging because it is considered the fifth most threatened large taxonomic group in the world; several species are among the most widespread and damaging invasive species; and Cactaceae is one of the most popular horticultural plant groups. Based on the Convention on International Trade in Endangered Species of Wild Flora and Fauna and the 11 largest online auction sites selling cacti, we documented the international cactus trade. To provide an in‐depth look at the dynamics of the industry, we surveyed the businesses involved in the cactus trade in South Africa (a hotspot of cactus trade and invasions). We purchased seeds of every available species and used DNA barcoding to identify species to the genus level. Although <20% of this trade involved threatened species and <3% involved known invasive species, many species were identified by a common name. However, only 0.02% of the globally traded cacti were collected from wild populations. Despite a large commercial network, all South African imports (of which 15% and 1.5% were of species listed as threatened and invasive, respectively) came from the same source. With DNA barcoding, we identified 24% of the species to genus level. Based on our results, we believe that if trade restrictions are placed on the small proportion of cacti that are invasive and there is no major increase in harvesting of native populations, then the commercial trade in cactus poses a negligible environmental threat. However, there are currently no effective methods for easily identifying which cacti are traded, and both the illicit harvesting of cacti from the wild and the informal trade in invasive taxa pose on‐going conservation challenges.     

The difficulties of systematic reviews

The need for robust evidence to support conservation actions has driven the adoption of systematic approaches to research synthesis in ecology. However, applying systematic review to complex or open questions remains challenging, and this task is becoming more difficult as the quantity of scientific literature increases. We drew on the science of linguistics for guidance as to why the process of identifying and sorting information during systematic review remains so labor intensive, and to provide potential solutions. Several linguistic properties of peer‐reviewed corpora—including nonrandom selection of review topics, small‐world properties of semantic networks, and spatiotemporal variation in word meaning—greatly increase the effort needed to complete the systematic review process. Conversely, the resolution of these semantic complexities is a common motivation for narrative reviews, but this process is rarely enacted with the rigor applied during linguistic analysis. Therefore, linguistics provides a unifying framework for understanding some key challenges of systematic review and highlights 2 useful directions for future research. First, in cases where semantic complexity generates barriers to synthesis, ecologists should consider drawing on existing methods—such as natural language processing or the construction of research thesauri and ontologies—that provide tools for mapping and resolving that complexity. These tools could help individual researchers classify research material in a more robust manner and provide valuable guidance for future researchers on that topic. Second, a linguistic perspective highlights that scientific writing is a rich resource worthy of detailed study, an observation that can sometimes be lost during the search for data during systematic review or meta‐analysis. For example, mapping semantic networks can reveal redundancy and complementarity among scientific concepts, leading to new insights and research questions. Consequently, wider adoption of linguistic approaches may facilitate improved rigor and richness in research synthesis.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.