Wetlands mitigation: Partnership between an electric power company and a federal wildlife refuge

Nine hectares (23 acres) of a degraded section of Patuxent Research Refuge in Laurel, Maryland, USA, were converted to wetland habitat by the Baltimore Gas and Electric Company in 1994. The wetlands were created as mitigation for 5.7 ha (14 acres) of wetlands that were impacted as part of the construction of an 8.5-km (5.3-mile) 500-kV overhead transmission line on the refuge. The area consists of a created forested wetland of 5.5 ha (13.5 acres), a seasonally inundated green-tree reservoir of 7.6 ha (6.5 acres), and an impounded pond wetland of 1.2 ha (3 acres). Construction included the planting of 6131 trees, 4276 shrubs, and 15,102 emergent plants. Part of the site has been studied intensively since completion and survival of trees and shrubs after two years was 88%. Measurements of these transplants have shown growth greater than on other created sites in Maryland. Grasses and other herbaceous vegetation were dominant plants in the meter-square plots in the first two years of sampling of the created forested wetland. Wildlife surveys for birds, mammals, amphibians, and reptiles have revealed diverse communities. Although these communities represent species consistent with open habitat, more typical forest species should colonize the area as it undergoes succession into a more mature forested wetland. The creation, management, and research of this mitigation site represents an excellent example of a partnership between a private electric power company and a federal wildlife refuge. This partnership has increased local biodiversity and improved regional water quality of the Patuxent River and the Chesapeake Bay.     

SOIL EROSION AND GROUND WATER POLLUTION TRADEOFFS FOR NONIRRIGATED FARMING SYSTEMS1

ABSTRACT: Traditional focus on reducing one environmental externality may cause another externality to increase. This article examines the environmental and economic costs of abating soil loss and (or) nitrate leaching through alternative optimal production systems in the nonirrigated farming systems of Northeastern Oregon. Models estimating soil loss and nitrate‐nitrogen leaching rates associated with current production processes, are linked to a Multi‐Objective Programming (MOP) model. The results show that site specific conditions influence the level of abatement expenditures and optimal production strategies to reduce soil loss and leaching rates. Moreover, while existing production strategies are effective in reducing soil loss at little cost, no strategies could be identified to reduce nitrate leaching rate on some soils.     

Effect of mixed liquor suspended solids concentration on the biodegradation of nitrilotriacetic acid in the activated sludge process

The biodegradation of nitrilotriacetic acid in laboratory simulations of the activated sludge process has been studied at two different concentrations of mixed liquor suspended solids. Responses to changes in the influent nitrilotriacetic acid concentration such as those which might be associated with a “wash day” have been examined.     

Efficient Markov chain Monte Carlo sampling for hierarchical hidden Markov models

Traditional Markov chain Monte Carlo (MCMC) sampling of hidden Markov models (HMMs) involves latent states underlying an imperfect observation process, and generates posterior samples for top-level parameters concurrently with nuisance latent variables. When potentially many HMMs are embedded within a hierarchical model, this can result in prohibitively long MCMC runtimes. We study combinations of existing methods, which are shown to vastly improve computational efficiency for these hierarchical models while maintaining the modeling flexibility provided by embedded HMMs. The methods include discrete filtering of the HMM likelihood to remove latent states, reduced data representations, and a novel procedure for dynamic block sampling of posterior dimensions. The first two methods have been used in isolation in existing application-specific software, but are not generally available for incorporation in arbitrary model structures. Using the NIMBLE package for R, we develop and test combined computational approaches using three examples from ecological capture–recapture, although our methods are generally applicable to any embedded discrete HMMs. These combinations provide several orders of magnitude improvement in MCMC sampling efficiency, defined as the rate of generating effectively independent posterior samples. In addition to being computationally significant for this class of hierarchical models, this result underscores the potential for vast improvements to MCMC sampling efficiency which can result from combinations of known algorithms.     

The fire frequency analysis branch of the pyrostatistics tree: sampling decisions and censoring in fire interval data

Statistical characterization of past fire regimes is important for both the ecology and management of fire-prone ecosystems. Survival analysis—or fire frequency analysis as it is often called in the fire literature—has increasingly been used over the last few decades to examine fire interval distributions. These distributions can be generated from a variety of sources (e.g., tree rings and stand age patterns), and analysis typically involves fitting the Weibull model. Given the widespread use of fire frequency analysis and the increasing availability of mapped fire history data, our goal has been to review and to examine some of the issues faced in applying these methods in a spatially explicit context. In particular, through a case study on the massive Cedar Fire in 2003 in southern California, we examine sensitivities of parameter estimates to the spatial resolution of sampling, point- and area-based methods for assigning sample values, current age surfaces versus historical intervals in generating distributions, and the inclusion of censored (i.e., incomplete) observations. Weibull parameter estimates were found to be roughly consistent with previous fire frequency analyses for shrublands (i.e., median age at burning of ~30–50 years and relatively low age dependency). Results indicate, however, that the inclusion or omission of censored observations can have a substantial effect on parameter estimates, far more than other decisions about specifics of sampling.