Assessing the restorative components of environments

We used a direct rating approach based on definitions of each construct to measure the four components of a restorative environment proposed by attention restoration theory (ART): being away, extent, fascination, and compatibility. We used the same approach to measure two criterion variables, perceived restorative potential (PRP) of a setting and preference for the setting, as well as four additional predictor variables (openness, visual access, movement ease, and setting care). Each participant rated 70 settings, 35 each from urban and natural environments, for only one of the variables. Mean ratings were higher for the natural than the urban settings for both criterion variables and all four restorative components, with differences significant in all cases except for fascination. Correlations across settings generally followed the predictions of ART, but collinearity appeared among several sets of variables, most notably being away and setting category, PRP and preference, and extent and fascination. Despite these problems, regression analysis showed that being away and compatibility predicted PRP and that the pattern of prediction for PRP and preference was somewhat different.     

Environmental preference and restoration: (How) are they related?

Does the widely documented tendency to prefer natural over built environments owe to the perception of greater restorative potential in natural environments? In the present experimental study we tested the mediating role of restoration in environmental preferences. Participants viewed a frightening movie, and then were shown a video of either a natural or a built environment. We used two examples of each type of environment. Participants’ mood ratings were assessed before and after they viewed the frightening movie, and again after viewing the environmental video. Participants also rated the beauty of the environment shown (to indicate preference) and performed a test of concentration after viewing the environmental video. The results indicate that participants perceived the natural environments as more beautiful than the built environments. In addition, viewing natural environments elicited greater improvement in mood and marginally better concentration than viewing built environments. Mediational analyses revealed that affective restoration accounted for a substantial proportion of the preference for the natural over the built environments. Together, these results help substantiate the adaptive function of people's environmental preferences.     

峨眉山野生黄连资源研究与评价

通过对峨眉山地区的野生黄连资源状况研究，加深对当地有关资源生态学与资源价值的认识。通过野外生境调查和伴生种恒有度分析和资源经济性与稀有性评价，指出当地2个野生黄连种类极其伴生种具有明显的岩生性，它们的分布生境及其伴生植物区系存在较大的区别，其中峨眉野连（Coptis omeiensis（Chen）C．Y．cheng）垂直分布幅较宽，喜中性土壤和阴湿环境；古蔺黄连（C．gtdinensis T．Z．Wang）分布海拔较高且局限，立地土壤呈强酸性，稍喜阳。目前广泛栽培的黄连（C．chinensis Franch）具有更好的综合经济性状，而当地的2个野生黄连类型具有明显的资源稀有性。其中值得注意的是，峨眉野连根茎及叶部的有效成份小檗碱的含量高于其它各种，具有值得重视的资源保护与利用价值。     

Development of the PRCQ: A measure of perceived restorative characteristics of zoo attractions

This study describes the development of the Perceived Restorative Characteristics Questionnaire (PRCQ), a measure of perceived restorative characteristics of zoo attractions. The questionnaire was administered in two zoo attractions. The hypothesized five factor structure of the PRCQ, and relations between perceived restorative characteristics and experienced pleasure in and preference for the attractions were examined. In Study 1, 137 visitors of a Dutch zoo evaluated perceived restorative characteristics of a butterfly garden; In Study 2, 158 visitors evaluated those of a baboon attraction. In Study 1 three factors emerged (fascination, escape and coherence); In Study 2 four factors could be distinguished (fascination, novelty, escape, coherence). Compatibility did not appear as a separate factoring either study. Perceived fascination and escape were significant predictors of experienced pleasure and preference in both attractions. The implications of the findings are discussed.     

Children's appreciation of outdoor places in a poor neighborhood

Children 7–12 years of age, living in a poor neighborhood, photographed outdoor places where they liked to go in their neighborhood. In individual interviews, they discussed their photos, selected their favorite place, and discussed the places they disliked. Children identified parks and playgrounds most often both as liked and disliked places, and spaces near an acquaintance's home as their favorite place. Liked places varied according to children's age and degree of vegetation. Children's negative perceptions of places were centered on safety threats. Children distinguish favorite places from liked places only by the greater number of positive characteristics and activities they offer children. The study highlights how positive and negative features coexist in places of importance to these children.     

Indicators of visual scale as predictors of landscape preference; a comparison between groups

Landscape change alters the visual scale of agricultural landscapes, as production units get larger and strips of taller vegetation are removed between smaller units. Visual scale, defined as the perceptual units reflecting the experience of landscape rooms, visibility and openness, is considered a key factor shaping landscape preference. The visual expression of landscapes affects people in many ways; aesthetic appreciation, health and well being. In order to understand how landscape changes alter the visual scale of landscapes, and hence its effect on human beings, it is important to establish efficient and practical ways of measuring visual scale and its relation to landscape preferences. This paper presents an empirical test of the ability to predict landscape preference of two photo-based indicators of visual scale; percentage open land in the view and size of landscape rooms. A preference survey was conducted with two groups of respondents; a student group from the Norwegian University of Life Sciences (UMB) and a public group. The student group was chosen to represent future landscape professionals. Photos of landscapes varying in the expression of visual scale were shown to survey respondents, who were asked to give scores according to how much they liked the landscapes. Both indicators were found to be predictors of preference for the student group, but not for the public group. The results demonstrate that student preferences do not reflect the landscape preferences of the wider public. The different appreciation of visual scale in the landscape of future landscape professionals and the public implies that experts wanting to reflect preferences of the wider public should be cautious when evaluating the visual impact of landscape change.     

Evaluation of the Environmentalist Dimension of Ecotourism at the Dadia Forest Reserve (Greece)

Environmental education and financial support of nature conservation are considered among the primary components of the environmentalist dimension of ecotourism. The potential of environmental education calls for enhancing visitor environmental knowledge and prompting change of visitor behavior. The present study addressed the evaluation of the environmentalist dimension of ecotourism in the Dadia Forest Reserve. The first objective of the research was to study the influence of variables determined prior to the visit, namely, visitor and visit characteristics, visitor environmental information sources, visitor pro-environmental behavior, and visitation goals, on variables determined during the visit, that is, visitor participation in and satisfaction from ecotourism activities. The second objective was to study the effect of selected variables on visitor knowledge and behavior intentions. Visitor participation in and satisfaction from ecotourism activities were primarily controlled by visit characteristics. Levels of visitor knowledge were quite satisfactory; however, coherence among knowledge items was rather loose. On the other hand, behavior intention items revealed the highest possible degree of coherence, which should be attributed to the pervasive influence of visitor satisfaction from watching birds at the Bird Observatory within the Dadia Forest Reserve. Ecotourism activities, during which the main part of environmental knowledge was offered, exerted no effect on visitor knowledge; all the same, they significantly influenced visitor behavior intentions. Overall, visitor behavior intentions revealed a considerable potential of financing environmental protection and providing voluntary work in the frame of the environmental management of the Dadia Forest Reserve.     

Factors affecting alkalinity generation by successive alkalinity-producing systems: regression analysis

Use of successive alkalinity-producing systems (SAPS) for treatment of acidic mine drainage (AMD) has grown in recent years. However, inconsistent performance has hampered widespread acceptance of this technology. This research was conducted to determine the influence of system design and influent AMD chemistry on net alkalinity generation by SAPS. Monthly observations were obtained from eight SAPS cells in southern West Virginia and southwestern Virginia. Analysis of these data revealed strong, positive correlations between net alkalinity generation and three variables: the natural log of limestone residence time, influent dissolved Fe concentration, and influent non-Mn acidity. A statistical model was constructed to describe SAPS performance. Subsequent analysis of data obtained from five systems in western Pennsylvania (calibration data set) was used to reevaluate the model form, and the statistical model was adjusted using the combined data sets. Limestone residence time exhibited a strong, positive logarithmic correlation with net alkalinity generation, indicating net alkalinity generation occurs most rapidly within the first few hours of AMD-limestone contact and additional residence time yields diminishing gains in treatment. Influent Fe and non-Mn acidity concentrations both show strong positive linear relationships with net alkalinity generation, reflecting the increased solubility of limestone under acidic conditions. These relationships were present in the original and the calibration data sets, separately, and in the statistical model derived from the combined data set. In the combined data set, these three factors accounted for 68% of the variability in SAPS systems performance.     

Patterns of television viewing and of perceptions of hazards to life

A previous study using respondents in a London regional audience appreciation diary panel showed that links existed between overall amounts of the viewing of television recorded across one week and levels of perception of risk of three hazards to life, namely lightning, flooding and terrorist bomb attacks. With a fourth hazard, cancer, there was an inverted U-shaped relationship between perceived risk level and amount of viewing. At the same time there were no relationships between amounts of viewing of news and documentary material and perceived risks of any of 12 hazards. Two new surveys were done, nearly three years after the previous one, asking people in widely different regions about their perceptions of nine various hazards, and linking these results with measures of attitudes towards certain adaptations of new technology (which could prove hazardous or beneficial according to points of view) and to patterns of television viewing. The two surveys agreed on a wide number of points with each other; they agreed with the previous study in finding no steady relationships between information programme viewing and hazard perception. Lightning and flooding were again related, this time more specifically with viewing of particular types of television programming. A new finding is that heavier viewing of television sport is associated with less perceived risk of cancer and of nuclear pollution. Interpretations are generally favoured along the lines of a selective process of viewers with certain predispositions choosing certain kinds of viewing patterns, rather than that programme contents provide an example for formulating perceptions and attitudes.     

Development and Comparison of Multiple Regression Models to Predict Bankfull Channel Dimensions for Use in Hydrologic Models

Channel dimensions are important input variables for many hydrologic models. As measurements of channel geometry are not available in most watersheds, they are often predicted using bankfull hydraulic geometry relationships. This study aims at improving existing equations that relate bankfull width, depth, and cross‐sectional area to drainage area (DA) without limiting their use to well‐gauged watersheds. We included seven additional variables in the equations that can be derived from data that are generally required by hydrologic models anyway and conducted several multiple regression analyses to identify the ideal combination of additional variables for nationwide and regional models for each Physiographic Division of the United States (U.S.). Results indicate that including the additional variables in the regression equations generally improves predictions considerably. The selection of relevant variables varies by Physiographic Division, but average annual precipitation (PCP) and temperature (TMP) were generally found to improve the models the most. Therefore, we recommend using regression equations with three independent variables (DA, PCP, and TMP) to predict bankfull channel dimensions for hydrologic models. Furthermore, we recommend using the regional equations for watersheds within regions from which data were used for model development, whereas in all other parts of the U.S. and the rest of the world, the nationwide equations should be given preference.     

Environmental attributes and the prediction of visual preferences for agrarian landscapes in Western Norway

This article reports findings from a study employing a number of environmental attributes in order to (a) describe agrarian landscapes in western Norway; and (b) predict preferences for the same landscapes. For these purposes three domains of attributes were chosen: informational variables; perception-based variables; and one single variable, perceived age of landscape. The most prominent characteristics of highly preferred human-influenced landscapes were their high degrees of Age and Mystery. On the other hand, highly preferred nature-dominated landscapes were characterized by high degrees of Coherence, Openness, Smoothness and Ease of Locomotion. In multiple regression analyses, informational variables were the most effective domain of preference predictors, although, in separate regression analyses, one perception-based variable, Openness, and Age also yielded significant results. The results suggest that attributes known to enhance preference are present to a markedly higher degree in traditional than in modern agrarian settings. However, that these attributes seem to function differently in human-influenced and nature-dominated settings is of theoretical interest.     

Engaging with the natural environment: The role of affective connection and identity

Research has shown pro-environmental behaviour to be positively associated with the strength of emotional connection towards the natural environment. The present study (N=199) investigated the predictive utility of an extended model of the theory of planned behaviour (TPB) [ Ajzen, I. (1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50, 179–211] for people's intentions to engage with the natural environment. It was hypothesised that both affective connection and identification with the natural environment would contribute significantly to the prediction of people's intentions. A secondary hypothesis was that participants who had grown up in rural areas would report more positive orientations towards engaging with the natural environment than would urban participants. The research found that affective connection was a significant independent predictor of intentions to engage with the natural environment. Environmental identity was only a significant predictor in the absence of affective connection in the regression model. As predicted, rural and urban participants differed significantly along the measured variables.     

Factors influencing farmers' concerns regarding bovine tuberculosis in wildlife and livestock around Riding Mountain National Park

Despite intensive efforts over the last century to eradicate bovine tuberculosis (TB) in North America, several hotspots of infected wildlife and livestock remain, raising concerns that the disease will never be eradicated. The stress and frustration for a farmer caused by having a herd test positive for TB or living in an infected region can be substantial. The goal of this study was to investigate the concerns of farmers around Riding Mountain National Park (RMNP) regarding the presence of TB in wildlife and livestock and conduct an exploratory analysis of causal factors. Data were collected from 786 farmers within 50 km of RMNP using a mail-back questionnaire. Overall, farmers indicated a high level of concern toward diseases in both wildlife and cattle relative to other concerns. The spatial variables that had the greatest influence on TB concern were both the distance of farms to the RMNP boundary and distance of farms to previous cases of TB. The most important aspatial factor associated with high TB concern was the frequency with which farmers observed elk on their land. These results underscore the important differences between 'objective' measures of risk, such as epidemiological estimates of disease prevalence, and subjective measures of disease concern, such as risk perception and acceptability of management actions. Written responses suggest that concerns regarding disease may affect how farmers view wildlife on their land and their relationship with neighbouring protected areas. Management activities that reduce the frequency of elk interactions with farms, but also recognize the complex relationship that farmers have with wildlife and protected areas, will be most effective in mitigating farmer concern regarding this important problem.     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Modelling the conversion of Colombian lowland ecosystems since 1940: drivers, patterns and rates

In biologically mega-diverse countries that are undergoing rapid human landscape transformation, it is important to understand and model the patterns of land cover change. This problem is particularly acute in Colombia, where lowland forests are being rapidly cleared for cropping and ranching. We apply a conceptual model with a nested set of a priori predictions to analyse the spatial and temporal patterns of land cover change for six 50-100 km(2) case study areas in lowland ecosystems of Colombia. Our analysis included soil fertility, a cost-distance function, and neighbourhood of forest and secondary vegetation cover as independent variables. Deforestation and forest regrowth are tested using logistic regression analysis and an information criterion approach to rank the models and predictor variables. The results show that: (a) overall the process of deforestation is better predicted by the full model containing all variables, while for regrowth the model containing only the auto-correlated neighbourhood terms is a better predictor; (b) overall consistent patterns emerge, although there are variations across regions and time; and (c) during the transformation process, both the order of importance and significance of the drivers change. Forest cover follows a consistent logistic decline pattern across regions, with introduced pastures being the major replacement land cover type. Forest stabilizes at 2-10% of the original cover, with an average patch size of 15.4 (+/-9.2)ha. We discuss the implications of the observed patterns and rates of land cover change for conservation planning in countries with high rates of deforestation.     

Global Warming and Global Dioxide Emission: An Empirical Study

In this paper, the dynamic relationship between global surface temperature (global warming) and global carbon dioxide emission (CO₂) is modelled and analyzed by causality and spectral analysis in the time domain and frequency domain, respectively. Historical data of global CO₂emission and global surface temperature anomalies over 129 years from 1860–1988 are used in this study. The causal relationship between the two phenomena is first examined using the Sim and Granger causality test in the time domain after the data series are filtered by ARIMA models. The Granger causal relationship is further scrutinized and confirmed by cross-spectral and multichannel spectral analysis in the frequency domain. The evidence found from both analyses proves that there is a positive causal relationship between the two variables. The time domain analysis suggests that Granger causality exists between global surface temperature and global CO₂emission. Further, CO₂emission causes the change in temperature. The conclusions are further confirmed by the frequency domain analysis, which indicates that the increase in CO₂emission causes climate warming because a high coherence exists between the two variables. Furthermore, it is proved that climate changes happen after an increase in CO₂emission, which confirms that the increase in CO₂emission does cause global warming.     

Estimating the benefits and costs to mountain bikers of changes in trail characteristics,access fees,and site closures: choice experiments and benefits transfer

Mountain biking is an increasingly popular leisure pursuit. Consequences are trail degradation and conflicts with hikers and other users. Resource managers often attempt to resolve these problems by closing trails to mountain biking. In order to estimate the impact of these developments, a model has been devised that predicts the effects of changes in trail characteristics and introduction of access fees, and correlates these with biker preference on trail selection. It estimates each individual's per-ride consumer's surplus associated with implementing different policies. The surplus varies significantly as a function of each individual's gender, budget, and interest in mountain biking. Estimation uses stated preference data, specifically choice experiments. Hypothetical mountain bike trails were created and each surveyed biker was asked to make five pair-wise choices. A benefit-transfer simulation is used to show how the model and parameter estimates can be transferred to estimate the benefits and costs to mountain bikers in a specific area.     

GIS As A Tool For Assessing The Influence Of Countryside Designations and Planning Policies On Landscape Change

The county of Bedfordshire is typical of landscape in lowland England with land cover dominant over land form and agriculture forming the major land use. Landscape change can be influenced by planning policies through their control of land use. A number of designated areas such as Areas of Great Landscape Value, Areas of Outstanding Natural Beauty and Green Belt have been defined where particular planning priorities for the conservation of the countryside apply. This paper reports work where an attempt has been made to measure the influence of these designations on landscape change using the tools of aerial photograph interpretation and Geographic Information Systems (GIS). Aerial photographs were available for the study area for 1968, 1981 and 1991. These were interpreted to a landscape classification scheme in terms of point, linear and area features such as trees, hedgerows and cultivated land, respectively. Field work was carried out to assess the accuracy of the interpretation. The resulting data were input to a GIS for each date of photography. Digital maps were created for the land cover features and tables were generated of lengths of linear features or counts of point features for each kilometre square in the study area. Spatial analysis tools provided by the GIS were used to describe the landscape character of each of the designated areas and then to measure the change that had taken place within them over the time period defined by the photography. Areas which were not designated for conservation of scenic beauty were shown to be poorer in traditional landscape features.