Prioritizing Wetland Restoration for Sediment Yield Reduction: A Conceptual Model

In a climate of limited resources, it is often necessary to prioritize restoration efforts geographically. The synoptic approach is an ecologically based tool for geographic prioritization of wetland protection and restoration efforts. The approach was specifically designed to incorporate best professional judgment in cases where information and resources are otherwise limited. Synoptic assessments calculate indices for functional criteria in subunits (watersheds, counties, etc.) of a region and then rank the subunits. Ranks can be visualized in region-scale maps which enable managers to identify areas where efforts optimize functional performance on a regional scale. In this paper, we develop a conceptual model for prioritizing watersheds whose wetlands can be restored to reduce total sediment yield at the watershed outlet. The conceptual model is designed to rank watersheds but not individual wetlands within a watershed. The synoptic approach is valid for applying the sediment yield reduction model because there is high demand for prioritizing disturbed wetlands for restoration, but there is limited, quantitative, accurate information available with which to make decisions. Furthermore, the cost of creating a comprehensive database is prohibitively high. Finally, because the model will be used for planning purposes, and, specifically, for prioritizing based on multiple decisions rather than optimizing a single decision, the consequence of prioritization errors is low. Model results cannot be treated as scientific findings. The conclusions of an assessment are based on judgement, but this judgement is guided by scientific principles and a general understanding of relevant ecological processes. The conceptual model was developed as the first step towards prioritizing of wetland restoration for sediment yield reduction in US EPA Region 4.     

Enrichment and isolation of endosulfan-degrading microorganisms

Endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,3,4-benzo-dioxathiepin-3-oxide) is a cyclodiene organochlorine currently used as an insecticide all over the world and its residues are posing a serious environmental threat. This study reports the isolation and identification of enriched microorganisms, capable of degrading endosulfan. Enrichment was achieved by using the insecticide as either the sole source of carbon or sulfur in parallel studies. Two strains each of fungi (F1 and F4) and bacteria (BF2 and B4) were selected using endosulfan as a sole carbon source. A Pandoraea species (Lin-3) previously isolated in our laboratory using lindane (gamma-HCH) as a carbon source was also screened for endosulfan degradation. F1 and F4 (Fusarium ventricosum) degraded alpha-endosulfan by as much as 82.2 and 91.1% and beta-endosulfan by 78.5 and 89.9%, respectively, within 15 d of incubation. Bacterial strains B4 and Lin-3 degraded alpha-endosulfan up to 79.6 and 81.8% and beta-endosulfan up to 83.9 and 86.8%, respectively, in 15 d. Among the bacterial strains isolated by providing endosulfan as a sulfur source, B4s and F4t degraded alpha-endosulfan by as much as 70.4 and 68.5% and beta-endosulfan by 70.4 and 70.8%, respectively, after 15 d. Degradation of the insecticide occurred concomitant with bacterial growth reaching an optical density (OD600) of 0.366 and 0.322 for B4 and Lin-3, respectively. High OD600 was also noted with the other bacterial strains utilizing endosulfan as a sulfur source. Fungal and bacterial strains significantly decreased the pH of the nutrient culture media while growing on endosulfan. The results of this study suggest that these novel strains are a valuable source of potent endosulfan-degrading enzymes for use in enzymatic bioremediation.     

A factor analytic study of attitudinal structure and its impact on rural landowners' access policies

Previous research has shown that rural landowners' hunter access policies are determined in large part by their attitudes towards hunters, legal liability, conservation, and economic incentives. The results of this study support this research and indicate that East Texas, USA, landowners' decisions to allow or restrict access are based, in part, on attitudes toward hunter behavior, hunting as a social activity, leasing as a management practice, and a perceived obligation toward wildlife stewardship. Attitude-based profiles of landowners who adopted one of four access policies are compared.     

DYNAMICS OF SIMULATED EFFECTS OF IRRIGATION OVER DRYLAND FARMING IN SASKATCHEWAN1

ABSTRACT: Irrigation development in Saskatchewan was initiated as an instrument to bring forth regional stability through drought proofing and diversification in the agricultural sector. This development has been surrounded by controversies. Particularly, some critics questioning its economic value to the farmer. In this study, irrigation on a farm is compared as a growth alternative to the expansion of dryland farming. Under relatively conservative machine replacement policies, modest family withdrawals, government subsidized irrigation loans, and relatively favorable gross operating margins, irrigation can be a profitable undertaking in the South Saskatchewan River Basin.     

Waste materials for activated carbon preparation and its use in aqueous-phase treatment: a review

Commercial activated carbon is a preferred adsorbent for the removal of micropollutants from the aqueous phase; however, its widespread use is restricted due to high associated costs. To decrease treatment costs, attempts have been made to find inexpensive alternative activated carbon (AC) precursors, such as waste materials. Some reviews report the use of waste materials for the preparation of AC; however, these studies are restricted to either type of wastes, preparation procedures, or specific aqueous-phase applications. The present work reviews and evaluates literature dedicated both to the preparation of AC by recycling different types of waste materials and also to its application in various aqueous-phase treatments. It is clear that conventional (from agriculture and wood industry) and non-conventional (from municipal and industrial activities) wastes can be used to prepare AC, that can be applied in various aqueous treatment processes, namely to remove organic pollutants, dyes, volatile organic compounds, and heavy metals. Moreover, high surface areas can be obtained using either physical or chemical activation; however, combined treatments might enhance the surface properties of the adsorbent, therefore increasing its adsorption capacity. It is evident from the revision made that AC prepared from both conventional and non-conventional wastes might effectively compete with the commercial ones. This happens mostly when the activation procedures are optimized considering both the raw material used to produce the carbons and the contaminants to be removed.     

Relationships between soil and runoff phosphorus in small Alberta watersheds

Field-scale relationships between soil test phosphorus (STP) and flow-weighted mean concentrations (FWMCs) of dissolved reactive phosphorus (DRP) and total phosphorus (TP) in runoff are essential for modeling phosphorus losses, but are lacking. The objectives of this study were (i) to determine the relationships between soil phosphorus (STP and degree of phosphorus saturation (DPS)) and runoff phosphorus (TP and DRP) from field-sized catchments under spring snowmelt and summer rainfall conditions, and (ii) to determine whether a variety of depths and spatial representations of STP improved the prediction of phosphorus losses. Runoff was monitored from eight field-scale microwatersheds (2 to 248 ha) for 3 yr. Soil test phosphorus was determined for three layers (0 to 2.5 cm, 0 to 5 cm, and 0 to 15 cm) in spring and fall and the DPS was determined for the surface layer. Average STP (0 to 15 cm) ranged from 3 to 512 mg kg(-1), and DPS (0 to 2.5 cm) ranged from 5 to 91%. Seasonal FWMCs ranged from 0.01 to 7.4 mg L(-1) DRP and from 0.1 to 8.0 mg L(-1) TP. Strong linear relationships (r2=0.87 to 0.89) were found between the site mean STP and the FWMCs of DRP and TP. The relationships had similar extraction coefficients, intercepts, and predictive power among all three soil layers. Extraction coefficients (0.013 to 0.014) were similar to those reported for other Alberta studies, but were greater than those reported for rainfall simulation studies. The curvilinear DPS relationship showed similar predictive ability to STP. The field-scale STP relationships derived from natural conditions in this study should provide the basis for modeling phosphorus in Alberta.     

REAL-TIME SNOW SIMULATION MODEL FOR THE MONONGAHELA RIVER BASIN1

ABSTRACT: The Pittsburgh District, U.S. Army Corps of Engineers, is responsible for operating two multipurpose reservoirs in the 7384 square mile (19198 square kilometer) Monongahela Basin. A third reservoir, presently under construction, will soon be operating. The real-time forecasting of runoff for operational purposes requires simulation of snow accumulation and snowmelt throughout the Basin during the winter season. This article describes capabilities of SNOSIM, a model being developed for performing such simulation. The application of this model as part of a comprehensive system of water control software, and some initial simulation results are presented.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.