Evaluating the ecological benefits of wildfire by integrating fire and ecosystem simulation models

Fire managers are now realizing that wildfires can be beneficial because they can reduce hazardous fuels and restore fire-dominated ecosystems. A software tool that assesses potential beneficial and detrimental ecological effects from wildfire would be helpful to fire management. This paper presents a simulation platform called FLEAT (Fire and Landscape Ecology Assessment Tool) that integrates several existing landscape- and stand-level simulation models to compute an ecologically based measure that describes if a wildfire is moving the burning landscape towards or away from the historical range and variation of vegetation composition. FLEAT uses a fire effects model to simulate fire severity, which is then used to predict vegetation development for 1, 10, and 100 years into the future using a landscape simulation model. The landscape is then simulated for 5000 years using parameters derived from historical data to create an historical time series that is compared to the predicted landscape composition at year 1, 10, and 100 to compute a metric that describes their similarity to the simulated historical conditions. This tool is designed to be used in operational wildfire management using the LANDFIRE spatial database so that fire managers can decide how aggressively to suppress wildfires. Validation of fire severity predictions using field data from six wildfires revealed that while accuracy is moderate (30-60%), it is mostly dictated by the quality of GIS layers input to FLEAT. Predicted 1-year landscape compositions were only 8% accurate but this was because the LANDFIRE mapped pre-fire composition accuracy was low (21%). This platform can be integrated into current readily available software products to produce an operational tool for balancing benefits of wildfire with potential dangers.     

Modeling the population dynamics of cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) over a wide area in northern China

The cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) is one of the most serious crop pests in northern China, calling for accurate prediction of pest outbreaks and strategies for pest control. A computer model is developed to simulate the population dynamics of H. armigera over a wide area in northern China. The area considered covers 12 provinces where serious outbreaks of H. armigera have been observed. In this model, pest development is driven by local ambient temperature, and adults migrate long distances between regions and select preferred hosts for oviposition within a region. Six types of host including cotton, wheat, corn, peanut, soybean and a single category composed of all other minor hosts are considered in this model. Survival rates of eggs and larvae are based on life-table data, and simulated as a function of host type, host phenology and temperature. The incidence of diapause depends on temperature and photoperiod experienced during the larval stage. Survival rate of non-diapause pupae is a nonlinear function of rainfall, and overwinter survival rate is a nonlinear function of temperature. Insecticide is applied when population density exceeds the economic threshold on a host crop within a region. Comparisons of model output with light-trap data indicate that our model reflects the pest population dynamics over a wide area, and could potentially be used for testing novel pest control strategies in northern China.     

Emergy analysis using US economic input-output models with applications to life cycles of gasoline and corn ethanol

A commonly encountered challenge in emergy analysis is the lack of transformity data for many economic products and services. To overcome this challenge, emergy analysts approximate the emergy input from the economy via a single emergy/money ratio for the country and the monetary price of economic inputs. This amounts to assuming homogeneity in the entire economy, and can introduce serious uncertainties in the results. This paper proposes and demonstrates the use of a thermodynamically augmented economic input-output model of the US economy for obtaining sector-specific emergy to money ratios that can be used instead of a single ratio. These ratios at the economy scale are more accurate than a single economy-wide emergy/money ratio, and can be obtained quickly for hundreds of economic products and services. Comparing sector-specific emergy/money ratios with those from conventional emergy studies indicates that the input-output model can provide reasonable estimates of transformities at least as a stop-gap measure until more detailed analysis is completed. A hybrid approach to emergy analysis is introduced and compared with conventional emergy analysis using life cycles of corn ethanol and gasoline as examples. Emergy and transformity data from the hybrid approach are similar to those from conventional emergy analysis, indicating the usefulness of the proposed approach. In addition, this work proposes the metric of return on emergy investment for assessing product alternatives with the same utility such as transportation fuels. The proposed approach and data may be used easily via web-based software.     

Integration of a fish bioenergetics model into a spatially explicit water quality model: Application to menhaden in Chesapeake Bay

Although fish are usually thought of as victims of water quality degradation, it has been proposed that some planktivorous species may improve water quality through consumption of algae and sequestering of nutrients via growth. Within most numerical water quality models, the highest trophic level modeled explicitly is zooplankton, prohibiting an investigation of the effect a fish species may be having on its environment. Conversely, numerical models of fish consumption do not typically include feedback mechanisms to capture the effects of fish on primary production and nutrient recycling. In the present study, a fish bioenergetics model is incorporated into CE-QUAL-ICM, a spatially explicit eutrophication model. In addition to fish consumption of algae, zooplankton, and detritus, fish biomass accumulation and nutrient recycling to the water column are explicitly accounted for. These developments advance prior modeling efforts of the impact of fish on water quality, many of which are based on integrated estimates over an entire system and which omit the feedback the fish have through nutrient recycling and excretion. To validate the developments, a pilot application was undertaken for Atlantic menhaden (Brevoortia tyrannus) in Chesapeake Bay. The model indicates menhaden may reduce the algal biomass while simultaneously increasing primary productivity.     

Human Performance Cognitive-Behavioral Modeling: A Benefit for Occupational Safety

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex humanautomation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tool’s fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.     

Force-Velocity Characteristics of Individual Human Skeletal Muscles: TBCIat and TBCIong. Outline of the Method

The aim of the work is to outline a procedure of finding force-velocity (F–V) characteristics (F = f(V)) of individual skeletal muscles of the human locomotor system. The presentation is based on an example concerning extensors of the elbow joint: the lateral and long heads of triceps brachii (TBCIat and TBCIong). The experimental part of the procedure involves a natural movement of using the upper extremity to push an external object of variable, adjustable load, engaging both the elbow and shoulder joint.

Five men aged 23 took part in the experiment. Their task was to push the handle of a physical pendulum whose moment of inertia could be adjusted within the range of 58 kg m²-450 kg m², so as to give it maximum angular velocity. During each trial the movement of the trunk, of the upper extremity and of the pendulum was video recorded and the force applied with the hand to the handle of the pendulum was measured.

In order to find the F–V characteristics a simulation model SHOULDER was used, which is capable of solving the synergy problem for muscles of the arm and the shoulder girdle.

It was found that despite considerable dispersion of experimental points the respective regression lines revealed a clear tendency of decreasing muscle force for increased shortening velocity of the monoarticular head (TBCIat) and of increasing muscle force for increased lengthening velocity of the biarticular head (TBCIong) of the triceps brachii muscle.     

An optimal level of dust explosion risk management: Framework and application

The current research provides guidance on the prevention and mitigation of dust explosion using a Quantitative Risk Management Framework (QRMF). Using concepts drawn from previous studies, the framework consists of three main steps: (i) a new combined safety management protocol, (ii) the use of DESC (Dust Explosion Simulation Code) and FTA (Fault Tree Analysis) to assess explosion consequences and likelihood, respectively, and (iii) application of the hierarchy of controls (inherent, engineered and procedural safety). QRMF assessment of an industrial case study showed that the original process was at high risk. DESC simulations and Probit equations determined the destructive percentages. FTAs revealed high probabilities of explosion occurrence; in addition, detailed individual and societal risks calculations were made, before and after the framework was applied. Based on the hierarchy of controls technique, the framework showed significant risk reduction to the point where the residual risk was acceptable for the process.     

Worst-case identification of gas dispersion for gas detector mapping using dispersion modeling

To quickly and accurately quantify the material release in process units, gas detectors may be placed according to the results of gas dispersion modeling. DNV's PHAST software is one of the most useful and reliable tools for material dispersion modeling. In this software, fluid dispersion is modeled based on the process conditions, the weather conditions and the specifications of the material release point. However, varying weather conditions throughout the year and the exact determination of the release point on the plot plan and the release elevation are problematic; these issues cause the results to be non-exact and non-integrated. Choosing the most appropriate conditions is challenging. In this paper, a scheme was provided to select the most appropriate conditions for gas dispersion modeling. This scheme approaches modeling based on the worst-case scenario (the situation in which the dispersed gas reaches the detector later in comparison to the other cases). Therefore, different weather conditions, release elevations and release points on the plot plan were modeled for an absorber tower of the Gonbadli Dehydration Unit of the Khangiran Refinery. The worst case of each release condition was then chosen. Finally, gas detectors were placed using the gas dispersion modeling results based on the worst-case scenario.     

长株潭地区经济增长与工业污染变迁的实证研究

根据长株潭地区1990~2006年经济与工业污染数据,分析了经济发展与环境污染的相互关系,建立了二者之间的计量模型。研究表明：作为一个重化工业城市群,长株潭自20世纪90年代以来,在经济高速发展的情况下,其环境恶化程度逐步得到局部控制。其中,长沙市部分环境指标与人均GDP演替轨迹呈现显著的环境库兹涅茨曲线特征;而株洲市和湘潭市工业污染排放量与人均GDP呈“U”形特征,即随着经济的增长,环境污染先是有一定程度的缓解,但随即有较大幅度的反弹。为了进一步促进长株潭地区经济与环境的协调发展,三地政府一方面应采取措施加快产业结构调整和优化工业布局,另一方面,还应尝试实施"排污权交易"和"受益者支付"原则等积极的环保管理手段和政策。