The measurement of place attachment: Personal,community, and environmental connections

Place attachment has been researched extensively in the social and behavioural sciences over the past two decades. However, it is challenging for researchers to assimilate the mixed messages presented in the place attachment literature and to understand the multiple place attachment terms. In this study, a four-dimensional model of rural landholder attachments to their natural resource management region was conceptually and empirically developed with the aim of developing an integrated approach to the measurement of place attachment that clearly distinguishes between different elements of place scholarship. A 29-item place attachment scale with the dimensions of place identity, place dependence, nature bonding, and social bonding was tested on a random sample of rural landholders in the Adelaide and Mount Lofty Ranges in South Australia (N = 320). The majority of respondents were male (69.3%) and the average age was 59 years. The scale was reduced to 20-items and then administered simultaneously and in the same response format to rural landholders in two other areas of South Australia: the Northern and Yorke region (N = 664) and South Australian Murray-Darling Basin region (N = 659). In both studies, the majority of respondents were male (85%) and the average age was 55 years. Exploratory factor and reliability analyses of Adelaide and Mount Lofty Ranges and Northern and Yorke datasets produced a five-dimensional model of place attachment with high reliabilities. Social bonding divided into the constructs of family bonding and friend bonding. The refined five-dimensional model was then examined for convergent validity, with moderate but significant correlations found between individual attachment constructs and dependent variables expected to be related to the construct, such as place identity and length of residence, and nature bonding and time currently spent in nature. We used confirmatory factor analysis to test the goodness-of-fit of the South Australian Murray-Darling Basin (SAMDB) dataset to the proposed five-dimensional model and then compared its fit to the traditional two-dimensional model of place identity and place dependence. The five-dimensional model provided moderate fit for the SAMDB data. We conclude with a discussion of the validity and reliability of the five-dimensional model and its future role in place attachment research.     

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: The case study of Denmark

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME = 29.5%; N = 54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME = 31.5%; N = 14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME = 30%; N = 39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas.     

An Object-Based Image Analysis of Pinyon and Juniper Woodlands Treated to Reduce Fuels

Mechanical and prescribed fire treatments are commonly used to reduce fuel loads and maintain or restore sagebrush steppe rangelands across the Great Basin where pinyon (Pinus) and juniper (Juniperus) trees are encroaching and infilling. Geospatial technologies, particularly remote sensing, could potentially be used in these ecosystems to (1) evaluate the longevity of fuel reduction treatments, (2) provide data for planning and designing future fuel-reduction treatments, and (3) assess the spatial distribution of horizontal fuel structure following fuel-reduction treatments. High-spatial resolution color-infrared imagery (0.06-m pixels) was acquired for pinyon and juniper woodland plots where fuels were reduced by either prescribed fire, tree cutting, or mastication at five sites in Oregon, California, Nevada, and Utah. Imagery was taken with a Vexcel UltraCam X digital camera in June 2009. Within each treatment plot, ground cover was measured as part of the Sagebrush Steppe Treatment Evaluation Project. Trimble eCognition Developer was used to classify land cover classes using object-based image analysis (OBIA) techniques. Differences between cover estimates using OBIA and ground-measurements were not consistently higher or lower for any land cover class and when evaluated for individual sites, were within ±5 % of each other. The overall accuracy and the K _hat statistic for classified thematic maps for each treatment were: prescribed burn 85 % and 0.81; cut and fell 82 % and 0.77, and mastication 84 % and 0.80. Although cover assessments from OBIA differed somewhat from ground measurements, they are sufficiently accurate to evaluate treatment success and for supporting a broad range of management concerns.     

Effects of Mowing and Prescribed Fire on Plant Community Structure and Function in Rare Coastal Sandplains,Nantucket Island,MA, USA

Coastal sandplains provide habitat for a suite of rare and endangered plant and wildlife species in the northeastern United States. These early successional plant communities were maintained by natural and anthropogenic disturbances including salt spray, fire, and livestock grazing, but over the last 150 years, a decrease in anthropogenic disturbance frequency and intensity has resulted in a shift towards woody shrub dominance at the expense of herbaceous taxa. This study quantified the effects of more than a decade of dormant season disturbance-based vegetation management (mowing and prescribed fire) on coastal sandplain plant community composition on Nantucket Island, Massachusetts, USA. We used time-series plant cover data from two similar sites to evaluate the effectiveness of disturbance management for restoring herbaceous species cover and reducing woody shrub dominance. Our results indicate that applying management outside of the peak of the growing season has not been effective in maintaining or increasing the cover of herbaceous species. While management activities resulted in significant (P < 0.01) increases in herbaceous species immediately after treatment, woody species recolonized and dominated treated sites within 3-years post treatment at the expense of graminoids and forbs. These results highlight the difficulties associated with directing ecological succession using disturbance-based management to maintain rare, herbaceous species in coastal sandplain systems that were once a prevalent landscape component under historically chronic anthropogenic disturbance. Further experimentation with growing season disturbance-based management and different combinations of management techniques could provide insights into management alternatives for maintaining herbaceous conservation targets in coastal sandplains.     

Mesoscale survey of western and northwestern Irish lakes – Spatial and aestival patterns in trophic status and phytoplankton community structure

Inland water bodies are considered as integrated parts of the landscape and the monitoring of water quality and aquatic resources need to be addressed on a regional basis for optimal assessment and management. In this study, a simple stratified sampling scheme was applied to a mesoscale survey of western and northwestern Irish lakes, which was carried out to identify, based on the distribution patterns of phytoplankton biomass, potential associations between lake trophic state and land cover attributes. Phytoplankton community analysis was also performed to determine whether taxa associations reflected meteorology-linked aestival succession or specific spatial distributions. The assessment was based on the typology of hydrogeomorphological and land cover attributes of river catchments through ArcGIS analysis. Sampling was carried out in 50 lakes and during a 15-week period in summer 2009. Results showed a general longitudinal gradient in the trophic status of the lakes sampled, with a greater frequency of mesotrophic lakes in the eastern part of the study area where land cover is dominated by agricultural surfaces. Significant relationships (p < 0.010) were found between chlorophyll-a concentration and the proportion of river catchment surface covered by agriculture land and wetlands, findings which might be considered further as proxies for developing an eutrophication risk index. Multivariate analysis of phytoplankton community data clustered the sampled lakes into three assemblages, with ordination along axis 1 being significantly correlated to time and temperature (p < 0.006). There was greater frequency of occurrence of diatoms in lakes from cluster III (Kruskal–Wallis, p < 0.05, H = 6.34, df = 2, n = 49), concomitant to lower chlorophyll-a concentrations, lake surface temperatures and Secchi depths, reflecting meteorological conditions dominated by precipitations. Those results support the potential of mesoscale surveys to assess water quality variables and detect environmental patterns at regional scales.     

Determining Relative Contributions of Vegetation and Topography to Burn Severity from LANDSAT Imagery

Fire is a dominant process in boreal forest landscapes and creates a spatial patch mosaic with different burn severities and age classes. Quantifying effects of vegetation and topography on burn severity provides a scientific basis on which forest fire management plans are developed to reduce catastrophic fires. However, the relative contribution of vegetation and topography to burn severity is highly debated especially under extreme weather conditions. In this study, we hypothesized that relationships of vegetation and topography to burn severity vary with fire size. We examined this hypothesis in a boreal forest landscape of northeastern China by computing the burn severity of 24 fire patches as the difference between the pre- and post-fire Normalized Difference Vegetation Index obtained from two Landsat TM images. The vegetation and topography to burn severity relationships were evaluated at three fire-size levels of small (<100 ha, n = 12), moderate (100–1,000 ha, n = 9), and large (>1,000 ha, n = 3). Our results showed that vegetation and topography to burn severity relationships were fire-size-dependent. The burn severity of small fires was primary controlled by vegetation conditions (e.g., understory cover), and the burn severity of large fires was strongly influenced by topographic conditions (e.g., elevation). For moderate fires, the relationships were complex and indistinguishable. Our results also indicated that the pattern trends of relative importance for both vegetation and topography factors were not dependent on fire size. Our study can help managers to design fire management plans according to vegetation characteristics that are found important in controlling burn severity and prioritize management locations based on the relative importance of vegetation and topography.     

Greenery on residential buildings: Does it affect preferences and perceptions of beauty?

Recently there has been a surge in the number of green roofs and façades (vegetation on the roofs & walls of a building) installed in the UK, with advocation of their use by policy-makers and claims that they are aesthetically pleasing and promote restoration. But these claims rely on generalisations from different landscapes, raising concerns about validity. The present study examined whether houses with vegetation would be more preferred than those without, be perceived as more beautiful and restorative, and have a more positive affective quality. Differences between types of building-integrated vegetation were also examined. Two studies were conducted: an online survey in which participants (N = 188) rated photographs of houses with and without vegetation on each of these measures, and interviews (N = 8) which examined preference and installation concerns. Results showed that houses with (some types of) building-integrated vegetation were significantly more preferred, beautiful, restorative, and had a more positive affective quality than those without. The ivy façade and meadow roof rated highest on each. These findings are consistent with other areas of landscape research and the claims of those in the industry, and suggest that building-integrated vegetation would be a valuable addition to the urban environment.     

Seeking knowledge of traditional Indigenous burning practices to inform regional bushfire management

ABSTRACT

A transdisciplinary review of the current academic knowledge of Indigenous traditional fire management is presented for the Mt Lofty Ranges in South Australia. For a long time, the roles of Indigenous management of the landscape have either been overlooked or discounted within environmental studies. That situation is beginning to change in many parts of Australia. However, this review of knowledge of traditional Indigenous burning practices specifically for the Mt Lofty Ranges suggests that there is very little formalised, academic knowledge available that could be utilised to inform prescribed burning practices in the region. Perhaps Indigenous peoples’ use of fire was strongly governed by individual choices, or perhaps established regimes demarcated roles across groups; perhaps some areas were burnt regularly and others were left unaltered – there is still no clear evidence from the academic literature to provide even limited understandings of such elements of pre-colonial fire regimes. That gap in knowledge will become increasingly problematic as the need for appropriate, sophisticated burning practices to respond to risk in peri-urban Adelaide increases with a changing climate. To learn from traditional Indigenous land management: (a) formal knowledge needs to be generated on past regional burning practices; and (b) understanding needs to be developed as to whether past burning practices could lead to effective hazard management and biodiversity outcomes within contemporary landscapes. Such an integration of Indigenous knowledge for effective environmental management will only be possible if the injustices of past exclusions of the importance of Indigenous biocultural practices are recognised.     

Norwegian farmers ceasing certified organic production: Characteristics and reasons

This article examines the characteristics of and reasons for Norwegian farmers’ ceasing or planning to cease certified organic production. We gathered cross-sectional survey data in late 2007 from organic farmers deregistering between January 2004 and September 2007 (n = 220), and similar data from a random sample of farmers with certified organic management in 2006 (n = 407). Of the respondents deregistering by November 2007, 17% had quit farming altogether, 61% now farmed conventionally, and 21% were still farming by organic principles, but without certification. Nearly one in four organic farmers in 2007 indicated that they planned to cease certification within the next 5–10 years. From the two survey samples, we categorised farmers who expect to be deregistered in 5–10 years into three groups: conventional practices (n = 139), continuing to farm using organic principles (uncertified organic deregistrants, n = 105), and stopped farming (n = 33). Of the numerous differences among these groups, two were most striking: the superior sales of uncertified organic deregistrants through consumer-direct marketing and the lowest shares of organic land among conventional deregistrants. We summarised a large number of reasons for deregistering into five factors through factor analysis: economics, regulations, knowledge-exchange, production, and market access. Items relating to economics and regulations were the primary reasons offered for opting out. The regression analysis showed that the various factors were associated with several explanatory variables. Regulations, for example, figured more highly among livestock farmers than crop farmers. The economic factor strongly reflected just a few years of organic management. Policy recommendations for reducing the number of dropouts are to focus on economics, environmental attitudes, and the regulatory issues surrounding certified organic production.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

A discussion to promote global sustainability techniques for motivating plastic waste to minimize carbon footprints

This paper emphasizes the significant challenges facing the sustainable environment, including managing and handling plastic waste and reducing carbon footprints. To tackle these challenges, it is essential to identify people's awareness levels of waste handling techniques and their pro-environmental behaviors. The study focuses on Guwahati, one of the most important cities in Northeast India, which generates increasing plastic waste daily. The paper aims to identify the factors contributing to the reduction of carbon footprints resulting from plastic waste management activities. The data collected from 1326 respondents was analyzed using factor analysis, and the reliability of the dataset was confirmed using Cronbach's alpha (0.84 for the awareness level of waste management techniques and 0.780 for the prevalent mode of plastic waste management techniques). KMO (0.796), Bartlett's test of sphericity (p < 0.001), and determinant score (0.019) were used to assess the data adequacy and factorability of the dataset, and the results were found to be satisfactory. Principal component analysis, exploratory factor analysis, and varimax orthogonal rotation method were used to identify high-loaded factors by reducing the number of variables. The results showed that two highly loaded components, namely awareness level of waste management techniques (AWMT) and prevalent mode of plastic waste management techniques (PWMT), explained 27.53% and 24.34% of the total variance, respectively, with eigenvalues of 3.35 and 2.88. The regression model confirmed the statistical significance of these factors (p < 0.001) and their relationship with the dependent variable, greenhouse reduction (GHGR). The study proposes that minimizing carbon footprints in the environment can be achieved by focusing on a limited number of controllable factors such as AWMT and PWMT. This study provides valuable insights to the authorities in controlling waste generation and achieving a pollution-free environment.     

Landscape--wildfire interactions in southern Europe: implications for landscape management

Every year approximately half a million hectares of land are burned by wildfires in southern Europe, causing large ecological and socio-economic impacts. Climate and land use changes in the last decades have increased fire risk and danger. In this paper we review the available scientific knowledge on the relationships between landscape and wildfires in the Mediterranean region, with a focus on its application for defining landscape management guidelines and policies that could be adopted in order to promote landscapes with lower fire hazard. The main findings are that (1) socio-economic drivers have favoured land cover changes contributing to increasing fire hazard in the last decades, (2) large wildfires are becoming more frequent, (3) increased fire frequency is promoting homogeneous landscapes covered by fire-prone shrublands; (4) landscape planning to reduce fuel loads may be successful only if fire weather conditions are not extreme. The challenges to address these problems and the policy and landscape management responses that should be adopted are discussed, along with major knowledge gaps.     

Evaluating Post-Fire Forest Resilience Using GIS and Multi-Criteria Analysis: An Example from Cape Sounion National Park,Greece

Forest fires are one of the major causes of ecological disturbance in the mediterranean climate ecosystems of the world. Despite the fact that a lot of resources have been invested in fire prevention and suppression, the number of fires occurring in the Mediterranean Basin in the recent decades has continued to markedly increase. The understanding of the relationship between landscape and fire lies, among others, in the identification of the system’s post-fire resilience. In our study, ecological and landscape data are integrated with decision-support techniques in a Geographic Information Systems (GIS) framework to evaluate the risk of losing post-fire resilience in Pinus halepensis forests, using Cape Sounion National Park, Central Greece, as a pilot case. The multi-criteria decision support approach has been used to synthesize both bio-indicators (woody cover, pine density, legume cover and relative species richness and annual colonizers) and geo-indicators (fire history, parent material, and slope inclination) in order to rank the landscape components. Judgments related to the significance of each factor were incorporated within the weights coefficients and then integrated into the multicriteria rule to map the risk index. Sensitivity analysis was very critical for assessing the contribution of each factor and the sensitivity to subjective weight judgments to the final output. The results of this study include a final ranking map of the risk of losing resilience, which is very useful in identifying the “risk hotspots”, where post-fire management measures should be applied in priority.     

The use of digital photos to assess visual cover for wildlife in rangelands

Grassland vegetation can provide visual cover for terrestrial vertebrates. The most commonly used method to assess visual cover is the Robel pole. We test the use of digital photography as a more accurate and repeatable method. We assessed the digital photography method on four forage grassland species (Pseudoroegneria spicata, Festuca campestris, Poa pratensis, Achnatherum richardsonii). Digital photos of 2-dimensional cutout silhouettes of three bird species sharp-tailed grouse, western meadowlark and savannah sparrow were used to model the impact of clipping (i.e., grazing) on visual cover. In addition, photos of artificial voles were used to model litter on cover available to small mammals. Nine sites were sampled and data were analyzed by the dominant grass species in each study plot. Regression analysis showed that digital photos (r² = 0.62) were a better predictor than the Robel pole (r² = 0.26) for assessment of cover. Clipping heights showed that clipping at less than 15 cm left the silhouettes 50% exposed. Digital photo analysis revealed that visual cover was affected by the type of grass species, with F. campestris > P. pratensis > A. richardsonii > P. spicata. Biomass and litter were both positively related to cover for small mammals.     

The role of parental behaviour for the development of behaviour specific environmental norms – The example of recycling and re-use behaviour

Based on the norm activation theory we developed assumptions about how parents may influence specific pro-environmental behaviours (i.e. re-use of paper and recycling) of their children (age 8–10). A sample of 206 parent-child-dyads were investigated using questionnaires recording norm activation model variables for children (i.e. awareness of need, awareness of consequences, personal norm, subjective norm, pro-environmental behaviour), as well as communication behaviour and actual behaviour of parents. For both behaviours (re-use and recycling) two separate structural equation models were tested (N = 206 and N = 194). Model fit statistics indicate a good fit of empirical data and model structure for both behaviours, supporting our assumption that the norm activation model can be applied to pro-environmental behaviour of young children. Communication behaviour of parents had a different influence on the two respective behaviours. While parents seemed to influence their children's recycling behaviour via sanctions and their own behaviour, re-use of paper was mainly influenced via communication of problem knowledge.     

Creating safe walkable streetscapes: Does house design and upkeep discourage incivilities in suburban neighbourhoods?

There is growing evidence that residents are more likely to walk in attractive neighbourhoods, and that negative visual cues can deter residents from engaging in physical activity. This study explored the premise that house design and upkeep could inhibit the incidence of physical disorder in suburban streets, thus contributing to a more pleasant walking environment for pedestrians. Street segments (n = 443) in new residential developments (n = 61) in Perth, Western Australia, were audited for house attributes that facilitate natural surveillance (e.g., porch/verandah) or indicate territoriality (e.g., garden/lawn upkeep), and physical incivilities. A composite index of street-level house attributes yielded highly significant associations with disorder (trend test p = 0.001) and graffiti (trend test p = 0.005), signifying that the cumulative effect of several key attributes had greater potential to discourage incivilities in the street than any single characteristic. The findings suggest house design and upkeep may contribute to the creation of safe, inviting streets for pedestrians.     

Implementing landscape fragmentation as an indicator in the Swiss Monitoring System Of Sustainable Development (Monet)

There is an increasing need and interest in including indicators of landscape fragmentation in monitoring systems of sustainable landscape management. Landscape fragmentation due to transportation infrastructure and urban development threatens human and environmental well-being by noise and pollution from traffic, reducing the size and viability of wildlife populations, facilitating the spread of invasive species, and impairing the scenic and recreational qualities of the landscape. This paper provides the rationale, method, and data for including landscape fragmentation in monitoring systems, using as an example the Swiss Monitoring System of Sustainable Development (Monet). We defined and compared four levels of fragmentation analysis, or fragmentation geometries (FGs), each based on different fragmenting elements, e.g., only anthropogenic, or combinations of anthropogenic and natural elements. As each FG has specific strengths and weaknesses, the most appropriate choice of FG depends on the context and objectives of a study. We present data on the current degree of landscape fragmentation for the five ecoregions and 26 cantons in Switzerland for all four FGs. Our results show that the degree of landscape fragmentation as quantified by the effective mesh size method is strongly supported by the postulates and indicator selection criteria of Monet, and we identify the most suitable FG focusing on the land area below 2100 m (e.g., excluding lakes) and allowing for an equitable comparison of fragmentation degrees among regions that differ in area covered by lakes and high mountains. For a more detailed analysis of landscape fragmentation in the context of environmental impact assessments and strategic environmental assessments, a combination of all four FGs may provide a more informative tool than any single FG.     

Integrating Satellite Imagery with Simulation Modeling to Improve Burn Severity Mapping

Both satellite imagery and spatial fire effects models are valuable tools for generating burn severity maps that are useful to fire scientists and resource managers. The purpose of this study was to test a new mapping approach that integrates imagery and modeling to create more accurate burn severity maps. We developed and assessed a statistical model that combines the Relative differenced Normalized Burn Ratio, a satellite image-based change detection procedure commonly used to map burn severity, with output from the Fire Hazard and Risk Model, a simulation model that estimates fire effects at a landscape scale. Using 285 Composite Burn Index (CBI) plots in Washington and Montana as ground reference, we found that an integrated model explained more variability in CBI (R ² = 0.47) and had lower mean squared error (MSE = 0.28) than image (R ² = 0.42 and MSE = 0.30) or simulation-based models (R ² = 0.07 and MSE = 0.49) alone. Overall map accuracy was also highest for maps created with the Integrated Model (63 %). We suspect that Simulation Model performance would greatly improve with higher quality and more accurate spatial input data. Results of this study indicate the potential benefit of combining satellite image-based methods with a fire effects simulation model to create improved burn severity maps.     

Associations between forest characteristics and socio-economic development: a case study from Portugal

The integration of socio-economic and environmental objectives is a major challenge in developing strategies for sustainable landscapes. We investigated associations between socio-economic variables, landscape metrics and measures of forest condition in the context of Portugal. The main goals of the study were to 1) investigate relationships between forest conditions and measures of socio-economic development at national and regional scales, 2) test the hypothesis that a systematic variation in forest landscape metrics occurs according to the stage of socio-economic development and, 3) assess the extent to which landscape metrics can inform strategies to enhance forest sustainability. A ranking approach and statistical techniques such as Principal Component Analysis were used to achieve these objectives. Relationships between socio-economic characteristics, landscape metrics and measures of forest condition were only significant in the regional analysis of municipalities in Northern Portugal. Landscape metrics for different tree species displayed significant variations across socio-economic groups of municipalities and these differences were consistent with changes in characteristics suggested by the forest transition model. The use of metrics also helped inform place-specific strategies to improve forest management, though it was also apparent that further work was required to better incorporate differences in forest functions into sustainability planning.     

Resource Selection by Elk in an Agro-Forested Landscape of Northwestern Nebraska

In recent years, elk have begun recolonizing areas east of the Rocky Mountains that are largely agro-forested ecosystems composed of privately owned land where management of elk is an increasing concern due to crop and forage depredation and interspecific disease transmission. We used a Geographic Information System, elk use locations (n = 5013), random locations (n = 25,065), discrete-choice models, and information-theoretic methods to test hypotheses about elk resource selection in an agro-forested landscape located in the Pine Ridge region of northwestern Nebraska, USA. Our objectives were to determine landscape characteristics selected by female elk and identify publicly owned land within the Pine Ridge for potential redistribution of elk. We found distance to edge of cover influenced selection of resources by female elk most and that in areas with light hunting pressure, such as ours, this selection was not driven by an avoidance of roads. Female elk selected resources positioned near ponderosa pine cover types during all seasons, exhibited a slight avoidance of roads during spring and fall, selected areas with increased slope during winter and spring, and selected north- and east-facing aspects over flat areas and areas with south-facing slopes during winter months. We used our models to identified a potential elk redistribution area that had a higher proportion of landcover with characteristics selected by elk in our study area than the current herd areas and more landcover that was publicly owned. With appropriate management plans, we believe elk within the Potential Elk Redistribution Area would predominantly occupy publicly owned land, which would help minimize crop and forage damage on privately owned lands.