The article A framework for teaching socio-environmental problem-solving, written by Cynthia A. Wei, Michael L. Deaton, Teresa J. Shume, Ramiro Berardo and William R. Burnside was originally published electronically on the publisher’s internet portal on 11 April 2020 without open access.

Feedback dynamics refers to the time-varying behavior of a system that is created by a particular class of causal forces referred to as feedback loops—circular chains of cause and effect among system traits or actors. Such chains create a bidirectional flow of causality: changes or movement at one point influence system behavior in such a way that propagates through the chain to eventually reinforce or mitigate the original change. Feedback comes in two forms: balancing (negative) and reinforcing (positive). As the names imply, balancing feedback balances or mitigates movement away from equilibrium, while reinforcing feedback reinforces and accelerates such movement. The history of feedback thought as an emerging concept in systems theory is documented in references under Historical Roots of Feedback Dynamics. Feedback loops and the dynamic behavior they create are evident at all scales, from the molecular to the global—and they are ubiquitous. Their presence and role in the natural world is discussed under Feedback Dynamics in the Biosphere. Because of limitations in human reasoning and the significant role of feedback dynamics in socio-ecological systems, the presence of feedback poses special problems for exercising judicious management of environmental resources. The literature in Effects of Feedback on Human Decision Making describes the limits of human decision making in the presence of feedback and points to the role of feedback modeling to augment the decision-making process. Building on this thread of reasoning, the literature under Modeling Feedback Dynamics and all its subsections describes both qualitative and quantitative approaches to modeling feedback and discusses the limitations and advantages of each approach. The works in Feedback Dynamics in Socio-ecological Problems provide a summary of several instances of studies involving feedback in socio-ecological systems and highlight that some of the most influential feedback dynamics involve the interacting influences of the natural environment and the humans that depend on that environment for survival. Hence, scientists employing a feedback view of the world and who work on socio-ecological problems have increasingly recognized the need to engage stakeholders in jointly creating models of system feedback dynamics in order to build consensus and a common vision for addressing problems involving human interactions with the environment. Key works describing approaches to engaging stakeholders in feedback modeling are discussed under Group Modeling: Engaging Stakeholders in Feedback Analysis.

Portable metabolic units afford a practical utility for field measurements of energy expenditure (EE). This methodology has proven useful to assess EE related to terrain, intensity, and duration during a single event. Similarly, system dynamics (SD) modeling has been used to describe the relationship between exercise and obesity as it relates to EE. However, there is paucity of literature that report SD to predict EE in real time. PURPOSE: To compare actual EE from a portable metabolic unit to predicted EE from a System Dynamics model. METHODS: Seven subjects (4 males, 3 females; 24.4 +/- 1.71) walked selected routes of varied terrain paced by a metronome at 2.7 mph. EE was measured using a Cosmed K4b2 portable metabolic unit with each subject completing four trials per route. An integrated GPS receiver recorded latitude and longitude coordinates of each route. The modeling software STELLA was used to design the SD model which incorporates subjects’ weight, walking pace, route elevation profile and distance. Pandolf’s et al (1977)) prediction equation for EE was run in the model to compare with the real-time K4b2 data. RESULTS: In simulation modeling parameters (stocks and flows) are adjusted to increase accuracy. Model parameters were adjusted to provide agreement for EE to within +/- 1% of the actual total EE as measured by the Cosmed K4b2 unit. A paired t-test comparing the actual versus the SD model predictions of total EE were not significantly different (p = .034). CONCLUSION: It appears that SD modeling can be an effective tool to predict EE of individuals walking on varied terrain. Once user parameters have been entered, simulation modeling can provide feedback on EE with suitable accuracy of a selected route. Compared to a single event measurement, SD allow users to compare EE of multiple defined routes simultaneously. Feedback has been identified as a critical component of adherence and motivation for physical activity. In this case of SD modeling, accurate feedback and route selection may encourage users to engage in regular physical activity. Funded by James Madison University Office of Public Safety.

Radical apocalypticism (RADAP) is a belief system, usually religious, that provides a logical framework for violent action in order to help usher in a new world order. Leaders with RADAP thinking h...

Respiratory morbidity (particularly COPD and asthma) can be influenced by short-term weather fluctuations that affect air quality and lung function. We developed a model to evaluate meteorological conditions associated with respiratory hospital admissions in the Shenandoah Valley of Virginia, USA. We generated ensembles of classification trees based on six years of respiratory-related hospital admissions (64,620 cases) and a suite of 83 potential environmental predictor variables. As our goal was to identify short-term weather linkages to high admission periods, the dependent variable was formulated as a binary classification of five-day moving average respiratory admission departures from the seasonal mean value. Accounting for seasonality removed the long-term apparent inverse relationship between temperature and admissions. We generated eight total models specific to the northern and southern portions of the valley for each season. All eight models demonstrate predictive skill (mean odds ratio = 3.635) when evaluated using a randomization procedure. The predictor variables selected by the ensembling algorithm vary across models, and both meteorological and air quality variables are included. In general, the models indicate complex linkages between respiratory health and environmental conditions that may be difficult to identify using more traditional approaches.

PURPOSE:Several small proteomic studies suggest that the prosecretory tear protein lacritin may be selectively downregulated in dry eye syndrome and in blepharitis, yet little information is available about normal baseline levels. This study assessed lacritin levels in tears from healthy individuals and addressed whether they differ according to sex, age, or time of day.METHODS:Rabbit antibodies against lacritin N-terminal peptide EDASSDSTGADPAQEAGTS (Pep Lac N-Term) were generated and characterized against human recombinant lacritin and N-65 truncation mutant. Basal tears were collected from 66 healthy individuals ranging in age from 18 to 52 years, and at four times during one 24-hour period from 34 other individuals. Lacritin levels were then analyzed by ELISA and Western blotting.RESULTS:Anti-Pep Lac N-Term bound lacritin, but not truncation mutant N-65 that lacks the N-terminal antigenic site. Tear lacritin levels followed a normal distribution with a mean of 4.2 ± 1.17 ng/100 ng total tear protein. Levels differed little by age or sex, and decreased slightly between 4 and 8 hours in a 24-hour cycle. Tear-blocking effects were minimal, as suggested by spiking of tears with recombinant lacritin.CONCLUSIONS:Anti-Pep Lac N-Term-detectable lacritin comprises ~4.2 ng/100 ng total tear protein in healthy individuals, with no significant differences between males and females or among individuals between 18 and 52 years old. Levels decrease slightly in the late afternoon. These findings provide a baseline for future immunodiagnostic studies of lacritin in dry eye and other ocular diseases.

The physical activity recommendation for U.S. adults is to engage in a minimum of 150 minutes per week of moderate-intensity activities. Pedometer use supports this recommendation by estimating daily physical activity through step counts. Recently it was reported that walking 3000 steps in 30 minutes would meet the definition of moderate exercise intensity. To date, this suggestion has yet to be implemented over an extended length of time. PURPOSE: To evaluate changes in cardiorespiratory fitness, body composition, blood pressure, lipids, blood glucose, HbA1c, and CRP from 150 minutes of free living weekly exercise compared to pedometer measured 3000 steps in 30 minutes for five days per week. METHODS: Subjects were randomly divided into two intervention groups (free-living and supervised) for 12 weeks. The free-living (FL) group (8 females, 45.6 ± 12.9 yrs; 90.36 ± 31.91 kg) was asked to accumulate 150 minutes of moderate-intensity exercise a week. The pedometer (P) group (8 females, 3 males, 44.7 ± 14.7 yrs; 86.66 ± 20.32 kg) attended three 30 minute supervised walking sessions and walked two 30 minute walking sessions independently. During supervised sessions, the P group employed a digital metronome set at 110 steps per minute. Metabolic parameters were measured pre- and post-intervention. RESULTS: Exercise compliance was 77.9% and 93.6% in FL and P groups, respectively. Mean pre/post values of SBP and HbA1c were significantly lower in the P group (SBP: -8.24 ± 11.3 mmHg; HbA1c: -0.78 ± 0.83%, p < 0.05). Mean change (p>.05) in CRP (-1.6 ± 2.4mg/dl) and VO2max (1.6 ± 2.4ml/kg/min) improved in P group only. In contrast, FL pre to post measurements did not significantly differ for any parameter. Notable average improvement occurred in GLU for P (-7.2 ±11.8mg/dl) and slightly for the FL (-1.8 ± 8.1mg/dl) group but was not significant. CONCLUSION: These results indicate the dose response of 3000 steps in 30 minutes yield improvement in several important metabolic variables compared with the general recommendation of 150 weekly minutes of moderate-intensity activities. Additionally, the potential use of metronomes to maintain step pace and therefore walking intensity may serve as a suitable proxy for exercise intensity during walking.

The bulk of previous research involving Nordic walking poles has been completed in laboratory settings on treadmills, limiting the practical applications as an outdoor activity for varied terrain. PURPOSE: This study compared selected physiological responses and ratings of perceived exertion (RPE) to walking with and without Nordic walking poles in a field setting. METHODS: Twenty six active adults (23 ± 4.5 years, 13 males and 13 females) meeting the current physical activity guidelines as defined by the Center for Disease Control and the American College of Sports Medicine participated in the study. Each subject completed a metronome paced Nordic Pole and no pole walk on a 3200 meter outdoor course of varied terrain (-14 to +20% grade) on separate days in a randomized order. Blood lactate was measured immediately before and after each walk. RPE was taken during and immediately after each walk. A Cosmed K4b2 portable metabolic unit was used to measure metabolic indices throughout each walk condition. The integrated GPS receiver of the K4b2 recorded distance and altitude during each walk trial. RESULTS: Average VE, VO2, VCO2, HR (125.9 ± 2.8 vs. 118.1 ±2.8 bpm), EE (199.6 ± 6.6 vs. 187.6 ± 6.3 kcal), and MET (5.1 ±0.2vs 4.7 ±0.2) levels during the Nordic pole walk were all significantly higher compared to the no pole walk condition (p ≤0.05) whereas RER was significantly lower for the Nordic pole walk (p ≤0.05). Changes in blood lactate from pre to post walk were not significantly different between walks (no poles 0.09 ± 0.1 vs. poles 0.23 ± 0.1 mM; p = 0.43) and RPE (11.8 ± 0.3 for poles and 12 ± 0.3 no poles) did not differ between walks (p ≥0.41). CONCLUSIONS: Nordic walking over a 3200 meter course of varied grade increases exercise intensity compared to normal walking without a corresponding increase in subjective feelings of effort. Moreover, blood lactate which is a marker for exercise intensity, tended to be lower during Nordic walking. Additionally, higher EE and MET levels combined with lower RER values during the Nordic pole walk favorably compliment weight loss conditions. The combination of these factors suggests that Nordic pole walking may facilitate exercise adherence and encourage individuals to engage in a walking activity for an extended duration.

Synoptic-scale air quality climatologies can often be categorized into trajectory methods based on air parcel movement or air mass approaches that are primarily dictated by thermal and moisture conditions. Here, we examine the relationship between these two essentially independent methods of synoptic-scale climate classification: 72-h Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model back-trajectories and the Spatial Synoptic Classification (SSC) of air masses for Martinsburg, West Virginia, located at the northern end of the Shenandoah Valley, from 1997 to 2006. Statistically significant differences exist between trajectory groups across the six SSC air mass types within each season and between seasons within each air mass type.Further examination of the trajectory distributions reveals a high degree of overlap between trajectories associated with different air mass types. In some cases, up to 50% of one air mass's trajectories are statistically closer to the trajectories of a different air mass type. Accordingly, air mass alone cannot be used to identify specific source regions of pollutants. This suggests that, while an air mass classification system can be used to identify general flow patterns, the integration of both thermodynamic and air-flow variables in a synoptic classification should provide information that is not discernible from either method independently. The inclusion of both back-trajectory and air mass information represents the suite of environmental conditions that may enhance or suppress pollutant concentrations in the Shenandoah Valley better than using either measure independently. Copyright (C) 2009 Royal Meteorological Society

Studies report physical activity decreases inflammatory markers such as high sensitivity C-reactive protein (hsCRP). However, little research has been done on the effects of physical activity on hsCRP in a sedentary smoking population. PURPOSE: To determine if a walking program using walking poles and/or pedometers will show a decrease in hsCRP in sedentary smokers(S) and non- smokers(NS). METHODS: 17 female (40.5 + 8.7 yrs, 164.1 + 7.2 cm, 76.9 + 19.4 kg) and 2 male (53 yrs, 180.3 + 7.2 cm, 91.4 + 15.3 kg) subjects were chosen based on sedentary status determined by CDC/ACSM Physical Activity Guidelines. S and NS subjects were assigned to one of two exercise modes and accumulated at least 90 minutes of walking per week for 8 weeks. Volitional VO2 max, hsCRP, blood lipids, and body fat (%bf) were measured at orientation (Wk0) and week 8 (Wk8). Subjects recorded walking time and number of steps taken each week, and completed a 3-day diet record at Wk0 and Wk8. A repeated measures design was used to determine differences (p<0.05) between the S and NS groups at Wk0 and Wk8. An independent t-test was used to determine the difference in walking time and steps taken between S and NS. RESULTS: Overall hsCPR was significantly higher in S when compared to NS (p=0.008). There was a significant interaction between Wk0 and Wk8 for hsCRP in S and NS (p=0.027). HsCRP decreased in NS and increased in S after Wk8. There was a significant difference in overall TC/HDL ratio between S and NS (p=0.021) with NS having a lower TC/HDL Ratio. Total Cholesterol (TC), LDL, and %bf were higher in S overall. TC and LDL decreased in NS and increased in S over the 8 weeks. VO2max and HDL were higher in NS overall. Saturated fat intake increased after Wk8 for both S and NS, but NS tend to consume less. These trends were not statistically significant. There was no difference in walking time or steps taken between S and NS. CONCLUSIONS: HsCRP levels increased in the smoking population after wk8. Normally hsCRP levels lower after long term exercise but this has not been reported for smokers. This suggests that the activity for S may have elicited an inflammatory response for a sedentary (mean 27.01 + 5.1VO2 max) population. Future research should determine if hsCRP responds differently in a sedentary smoking population if a prescribed intensity level is monitored in a long term exercise program.

Trekking poles are used by hikers for improved stability and lowered leg fatigue due to increased upper body muscle involvement. However, the weight of the poles and exaggerated upper body movement when using poles may increase total energy expenditure at a given walking speed. Few studies have investigated the physiological responses of hiking with trekking poles outside the laboratory setting. The purposes of this study were to determine if trekking poles altered physiological responses to hiking on varied terrain, and whether responses between trials were dependent on the grade of the terrain. Fourteen recreational hikers completed four hiking trials over a course that included sustained sections of flat (0 +/- 1% grade), steep uphill (>10% grade), gradual uphill (5% grade), gradual downhill (-5% grade) and steep downhill (<-10% grade) terrain. Subjects walked at a self-selected speed that was matched across trials using time-splits and a metronome. Two trials were conducted with hiking poles and two without poles. [latin capital V with dot above]O2 was significantly elevated (p <0.05) during the pole trials (1502.9 +/- 510.7 ml/min) compared to the no-pole trials (1362.4 +/- 473.2 ml/min). Similarly, ventilatory efficiency ([latin capital V with dot above]E) (43.1 +/- 9.6; 38.3 +/- 10.1 L/min) and heart rate (HR) (112.1 +/- 9.7; 105.7 +/- 10.4 bt/min) were significantly higher during the pole trials than the no-pole trials. However, ratings of perceived exertion (RPE) was not altered by pole condition (8.5 +/- 0.7; 8.4 +/- 0.8). Comparisons within each grade revealed significantly higher physiological responses for [latin capital V with dot above]O2, [latin capital V with dot above]E and HR in the pole-condition at all grades, with no significant variable*grade interactions. RPE measures were not significantly different between pole trials at any grade. These data suggest that trekking poles may be a beneficial tool for increasing caloric expenditure, as energy production increased during exercise without increased perceptions of effort.

PURPOSE: The purpose of this study was to examine adherence to different walking assignments (Nordic walking plus pedometer or pedometer only) and to compare the physiological differences between the groups after 16 weeks of walking. METHODS: Thirty-four participants began the 16 week program. Participants were randomly assigned to a Nordic walking plus pedometer group (NP) or a pedometeronly (P) group, after being matched similar body composition between groups. For the first 7 weeks, participants were instructed to walk 90 minutes per week. By week 8, all participants were asked to meet a minimum goal of 150 minutes per week. Exercise duration was recorded after each walk, and step counts were recorded at the end of each week. Physical health assessments were performed prior to the program, and following 8 weeks, and 16 weeks. Three day diet records were also collected at these intervals. RESULTS: Eighteen women (48.8 ± 10.5yrs; 164.72 ± 6.8cm; 78.1 ± 14.7 kg) and 4 men (53 ± 5.6 yrs; 174.75 ± 6.7cm; 88.3 ± 21.8 kg) completed the program. Average median walk times and median step counts for NP were 120.7 ± 10.61 minutes per week and 13890 ± 1366.46 steps per week, respectively. Based on a 2-sample t-test, the NP values were not significantly different from P, which reported 141.6 ± 20.97 minutes per week (p=.361) and 16464 ± 2436.89 steps per week (p=.348). Based on a repeated measures analysis, significant changes in the mean in resting metabolic rate (189.9 ± 2.9 calories; p=.0172) and % body fat (1.75 ± .03; p=.0143) were observed over the 16 weeks, but these changes were not found to be associated with group assignment. There were no significant differences in caloric intake between groups. CONCLUSIONS: 16 weeks of walking with pedometers elicited small but statistically significant improvements in body composition and metabolic rate in previously sedentary subjects. Subjects using trekking poles obtained similar responses to those not using poles, despite walking approximately 20 fewer minutes per week, perhaps suggesting an increased metabolic cost of walking while using poles. Equipment support provided by LEKI USA

PURPOSE: The purpose of this study was to compare body fat losses and compliance to exercise in previously sedentary individuals who were randomly-assigned to a pedometer group or pedometer-Nordic walking pole group. METHODS: Twenty-three sedentary adults were recruited to participate in an 8-week walking program, beginning on a staggered schedule as recruits enlisted in the study. Subjects were told that the study would compare physiological changes between two walking groups. Body fat % measurements were obtained on each subject using a BodPod prior to the walking intervention, and following 8-weeks of walking. For the first six weeks, participants were instructed to walk at least 90 minutes per week with a goal of reaching 150 minutes per week by week 7. Participants completed walking logs each week, in which they recorded date, time spent walking, and the number of steps per week. RESULTS: As of the date of this writing, three males and six females (46.7 + 12.4 yr) completed the 8-week program. The Nordic pole group averaged walking 119.2 min/ week (± 51.0 min) and the pedometer group averaged 140.8 min/week (± 85.2 min). The difference is not statistically significant (p = 0.264). No significant changes were observed in pre versus post % fat, within group, nor when comparing the two groups. However, the average change in percent body fat in the hiking pole group was - 3.0%, (± 2.5%; p = 0.123) and the average change in the pedometer only group was −0.3% (± 1.2%, p = 0.372), suggesting that statistically significant differences may be observed in the Nordic walking pole group once all subjects have completed the study. CONCLUSIONS: The current study observed no signficant differences in compliance or body fat changes between the pedometer and pedometer-Nordic walking pole groups. However these results are preliminary and may change once the remaining 14 subjects complete the study and are analyzed to determine if the trend towards greater fat losses in the pole group are are practically significant.

An accident or a deliberate terrorism attack releasing hazardous chemicals will create chaos, confusion, and seeming unpredictability that complicates the emergency response. Clinicians are challenged to urgently treat patients needing care, even before a chemical is confirmed. Emergency response planning that focuses on preparing for predictable challenges to the health care system and applies basic toxicologic principles to clinical decision-making can bring a sense of order to the chaos and provide medical care that will be best for the most victims of an incident.

Since September 11, 2001, awareness of potential terrorist targets has increased greatly. Industrial chemicals, either in storage or transport, are now considered dangerously accessible materials that could be used to cause substantial harm. In response to this new threat, emergency organizations are beginning to plan for such possible chemical releases. Currently there is no tool that allows a community to track, analyze, query, and display data about these chemical "weapons of opportunity" and the readiness of the communities around them.Decision support systems are computer environments designed to assist decision makers within a particular problem-solving context. A particular type of DSS, environmental decision support systems (EDSS), assists environmental scientists and planners in making environmental management decisions. A hazardous materials decision support system called "FALCON" will assist emergency organizations by integrating information describing chemical inventories, security, health readiness, geography, and population into one information system. Emergency organizations will be able to assess response readiness of a community for chemical releases and prioritize antidote stockpiling, training, and security. Emergency organizations and first responders will use the FALCON DSS to simulate and prepare for real-time events, assess possible casualties, and receive emergency contact information. And with the help of FALCON, law enforcement and security personnel will be able to evaluate and augment protection of the most dangerous facilities. (c) 2006 Elsevier Ltd. All rights reserved.

The production capacity of the biodiesel industry is experiencing exponential growth. Demand is driven by environmental, social, and economic factors and helped along by government mandates and incentives. Suppliers are having difficulty keeping up with demand. The U.S. production capacity has grown by a factor of ten in the past two years, and between thirty and forty new plants are currently in or near construction phase. Continued strong growth of biodiesel production capacity depends on producer/supplier profitability, which will be influenced by several factors such as biomass oil feedstock prices, product/co-product prices, production technologies, and government regulations/incentives. How, why, and to what extent will the growth of the biodiesel industry be influenced by these factors? To explore possible answers to these questions, we describe the formulation of a system dynamics model of the U.S. biodiesel marketplace. The construction and use of this model will provide a framework for understanding the causal-loop/feedback structure and dynamics of this industry and how changes in key variables (e.g. feedstock price or change in government incentives) impact growth. Using system dynamics modeling, we envision and put into perspective the possible growth behavior scenarios for this industry over the next decade

1717 The advent of portable metabolic units has extended energy expenditure measurement to field settings. However, relatively few studies have investigated the energetic demands of backpacking activities outside the laboratory. PURPOSE: To compare the metabolic responses of backpacking with and without trekking poles during section hiking on the Appalachian Trail. METHODS: The subject for this case study was a 51-year-old male backpacker (72 kg, 173cm, VO2peak 52.7ml.kg−1.min−1). Breath by breath respiratory data was measured using a portable metabolic unit during two hikes of a ten-mile section of the Appalachian Trail, walked at a self-selected pace with and without trekking poles. Energy expenditure (EE), ventilation (VE), breaths/min (BM), respiratory exchange ratio (RER), heart rate (HR) and changes in altitude were averaged over one minute intervals during both hikes. Altitude data was measured with integrated GPS software of the metabolic unit. Responses in dependent measures were compared between trials using ANCOVAs, with altitude change as the covariate. RESULTS: When comparing trekking poles versus no poles, all dependent measures showed parallel slopes between trials with respect to change in altitude (p > 0.05). The y-intercepts were not significantly different between poles and no-poles, respectively, for EE (5.86 vs 6.31 kcals.min−1; p = 0.162) and BM (27.5 vs 26.5; p = 0.254). Alternatively, the y-intercepts for HR (113.0 vs 120.7 beats/min; p < .0001), VE (35.8 vs 38.1 L/min; p = .0042), and RER (.81 vs .87; p <. 0001) were all significantly higher for the non-pole condition. Overall rating of perceived exertion was also lower during the pole condition. CONCLUSION: While overall energy expenditure did not differ between conditions, the use of poles positively affected various responses to backpacking. It is plausible that the use of poles altered the muscular distribution of work in a way that eased the perceived effort of the activity. In this case, portable metabolic units appear to have considerable utility for examining backpacking related research questions in the future. Moreover, using one-minute averages over varied terrain affords a coherent approach to accounting for the effects of gradient in the analysis thereby providing a more meaningful comparison Equipment Support Provided by: LEKI USA, COSMED USA (GPS Kit), GoLite

Chapter Objectives— After you finish this chapter, you should be able to: 1.  Describe various types of surface water pollution, their sources, and their impacts. 2.  Describe qualitatively and mathematically the concept of mass-balance, and apply this concept to solve mass-balance problems. 3  Describe the flow of oxygen into and out of water in an aquatic ecosystem, highlighting the reservoirs and flows of this oxygen. 4.  Construct a systems diagram that illustrates how oxygen may be depleted from an aquatic system due to inputs of organic matter. 5.  Through manipulation of a systems model, identify the driving variables of the DO-sag curve and describe this curve’s response to perturbations of those variables.