A Bayesian strategy for combining predictions from empirical and process-based models

We present a strategy for using an empirical forest growth model to reduce uncertainty in predictions made with a physiological process-based forest ecosystem model. The uncertainty reduction is carried out via Bayesian melding, in which information from prior knowledge and a deterministic computer model is conditioned on a likelihood function. We used predictions from an empirical forest growth model G-HAT in place of field observations of aboveground net primary productivity (ANPP) in a deciduous temperate forest ecosystem. Using Bayesian melding, priors for the inputs of the process-based forest ecosystem PnET-II were propagated through the model, and likelihoods for the PnET-II output ANPP were calculated using the G-HAT predictions. Posterior distributions for ANPP and many PnET-II inputs obtained using the G-HAT predictions largely matched posteriors obtained using field data. Since empirical growth models are often more readily available than extensive field data sets, the method represents a potential gain in efficiency for reducing the uncertainty of process-based model predictions when reliable empirical models are available but high-quality data are not.     

Generalized site occupancy models allowing for false positive and false negative errors

Site occupancy models have been developed that allow for imperfect species detection or "false negative" observations. Such models have become widely adopted in surveys of many taxa. The most fundamental assumption underlying these models is that "false positive" errors are not possible. That is, one cannot detect a species where it does not occur. However, such errors are possible in many sampling situations for a number of reasons, and even low false positive error rates can induce extreme bias in estimates of site occupancy when they are not accounted for. In this paper, we develop a model for site occupancy that allows for both false negative and false positive error rates. This model can be represented as a two-component finite mixture model and can be easily fitted using freely available software. We provide an analysis of avian survey data using the proposed model and present results of a brief simulation study evaluating the performance of the maximum-likelihood estimator and the naive estimator in the presence of false positive errors.     

Aphid population response to agricultural landscape change: A spatially explicit,individual-based model

A spatially explicit individual-based simulation model has been developed to represent aphid population dynamics in agricultural landscapes. The application of the model to Rhopalosiphum padi (L.) population dynamics is detailed, including an outline of the construction of the model, its parameterisation and validation. Over time, the aphids interact with the landscape and with one another. The landscape is modified by varying a simple pesticide regime, and the multi-scale spatial and temporal implications for a population of aphids is analysed. The results show that a spatial modelling approach that considers the effects on the individual of landscape properties and factors such as wind speed and wind direction provides novel insight into aphid population dynamics both spatially and temporally. This forms the basis for the development of further simulation models that can be used to analyse how changes in landscape structure impact upon important species distributions and population dynamics.     

Integrity of Tailings Infrastructure and Information Management: A GIS-Based Conceptual Model

Managing the integrity of tailings infrastructure is an important aspect of handling mine tailings. Unfortunately, little research is directed towards its efficient modeling. This paper presents salient aspects of tailings management. It proposes an integrated geographic information systems (GIS)-based conceptual model for efficient handling of these aspects. The paper also discusses the various integrated modules and comments on the systematic implementation of the model to achieve desired results. The modules include: structural integrity management (SIM), release impact assessment (RIA), and hazardous risk assessment and control (HRAC).     

Intermittent agitation of liquid manure: effects on methane,microbial activity,and temperature in a farm-scale study

Liquid manure storages are a significant source of methane (CH₄) emissions. Farmers commonly agitate (stir) liquid manure prior to field application to homogenize nutrients and solids. During agitation, manure undergoes mechanical stress and is exposed to the air, disrupting anaerobic conditions. This on-farm study aimed to better understand the effects of agitation on CH₄ emissions, and explore the potential for intentional agitation (three times) to disrupt the exponential increase of CH₄ emissions in spring and summer. Results showed that agitation substantially increased manure temperature in the study year compared to the previous year, particularly at upper- and mid-depths of the stored manure. The temporal pattern of CH₄ emissions was altered by reduced emissions over the subsequent week, followed by an increase during the second week. Microbial analysis indicated that the activity of archaea and methanogens increased after each agitation event, but there was little change in the populations of methanogens, archaea, and bacteria. Overall, CH₄ emissions were higher than any of the previous three years, likely due to warmer manure temperatures that were higher than the previous years (despite similar air temperatures). Therefore, intermittent manure agitation with the frequency, duration, and intensity used in this study is not recommended as a CH₄ emission mitigation practice.

Implications: The potential to mitigate methane emissions from liquid manure storages by strategically timed agitation was evaluated in a detailed farm-scale study. Agitation was conducted with readily-available farm equipment, and targeted at the early summer to disrupt methanogenic communities when CH₄ emissions increase exponentially. Methane emissions were reduced for about one week after agitation. However, agitation led to increased manure temperature, and was associated with increased activity of methanogens. Overall, agitation was associated with similar or higher methane emissions. Therefore, agitation is not recommended as a mitigation strategy.     

Contaminant mass flux and forensic assessment of polycyclic aromatic hydrocarbons: Tools to inform remediation decision making at a contaminated site in Canada

Polycyclic aromatic hydrocarbons (PAHs) and metal(loid) mass flux estimates and forensic assessment using PAH diagnostic ratios were used to inform remediation decision making at the Sydney Tar Ponds (STPs) and Coke Ovens cleanup project in eastern Canada. Environmental effects monitoring of surface marine sediments in Sydney Harbor indicated significantly higher PAH concentrations during the first year of remediation monitoring compared to baseline. This was equivalent to PAH loadings of ～2,000 kg over a 15‐month period. Increases in sediment PAH concentrations raised serious concerns for regulators, who requested cessation of remediation activities early in the $400 M (CAD) project. Historically, the STPs were reported as the primary source of PAH contamination in Sydney Harbor with estimated discharges of 300 to 800 kg/year between 1989 and 2001. Mass flux estimates of PAHs and metal(loid)s and PAH diagnostic ratios were used to evaluate if increases in PAH concentrations in marine sediments were the result of the STPs remediation activities. PAH mass flux estimates approximated that 17 to 97 kg/year were discharged from the STPs during three years of remediation and were corroborated by an independent PAH flux estimate of 119 kg in year 1. PAH fluxes to the Sydney Harbor were mostly surface water derived, with groundwater contributing negligible quantities (0.002–0.005 kg/year). Fluxes of metal(loid)s to harbor sediments were stable or declining across all years and were mirrored in sediment metal(loid) concentrations, which lacked temporal variation, unlike total PAH concentrations. Flux results were also corroborated using PAH diagnostic ratios, which found a common source of PAHs. Coal combustion was likely the principal source of PAHs and not migration from the STPs during remediation. Although short‐term residual sediment PAH increases during onset of remediation raised concerns for regulators, calls for premature cessation of remediation early in the project were unwarranted based on only one year of monitoring data. Mass flux estimates and forensic assessments using PAH diagnostic ratios proved useful tools to inform remediation decision making that helped environmental protection and reduced costs associated with lost cleanup time.     

Re-use of remediated soils for the bioremediation of waste oil sludge

We investigated the possibility of re-using remediated soils for new bioremediation projects by spiking these soils with waste oil sludge in laboratory based microcosms. The level of Total Petroleum Hydrocarbon (TPH) reduction was high (>80%) in naturally attenuated microcosms and was not significantly improved by biostimulation, bioaugmentation and the combined treatment of bioaugmentation and biostimulation by week 12. This indicated that the observed TPH reduction might have been related to the soil's inherent hydrocarbon-degrading potential. Microbial community analysis (16S rDNA and ITS-based Denaturing Gradient Gel Electrophoresis fingerprints) confirmed the dominance of hydrocarbon degrading genera such as Alcanivorax and Scedosporium. Cluster and Shannon diversity analysis revealed similar but stable bacterial and fungal communities in naturally attenuated and amended microcosms indicating that rapid reduction in TPH may not always be accompanied by changes in soil microbial communities. This study has therefore shown that soils previously used for bioremediation can have an improved hydrocarbon degrading potential which was successfully re-harnessed for new projects. This ability to re-harness this potential is attractive because it substantially reduces operational costs as no additional bioremediation treatments are needed. It can also extend a landfill's lifespan as soils can be re-used again before landfill disposal.     

Confronting socially generated uncertainty in adaptive management

As more and more organizations with responsibility for natural resource management adopt adaptive management as the rubric in which they wish to operate, it becomes increasingly important to consider the sources of uncertainty inherent in their endeavors. Without recognizing that uncertainty originates both in the natural world and in human undertakings, efforts to manage adaptively at the least will prove frustrating and at the worst will prove damaging to the very natural resources that are the management targets. There will be more surprises and those surprises potentially may prove at the very least unwanted and at the worst devastating. We illustrate how acknowledging uncertainty associated with the natural world is necessary but not sufficient to avoid surprise using case studies of efforts to manage three wildlife species; Hector's Dolphins, American Alligators and Pallid Sturgeon. Three characteristics of indeterminism are salient to all of them; non-stationarity, irreducibility and an inability to define objective probabilities. As an antidote, we recommend employing a holistic treatment of indeterminism, that includes recognizing that uncertainty originates in ecological systems and in how people perceive, interact and decide about the natural world of which they are integral players.