Effect of Classification Procedure on the Performance of Numerically Defined Ecological Regions

Ecological regionalizations define geographic regions exhibiting relative homogeneity in ecological (i.e., environmental and biotic) characteristics. Multivariate clustering methods have been used to define ecological regions based on subjectively chosen environmental variables. We developed and tested three procedures for defining ecological regions based on spatial modeling of a multivariate target pattern that is represented by compositional dissimilarities between locations (e.g., taxonomic dissimilarities). The procedures use a “training dataset” representing the target pattern and models this as a function of environmental variables. The model is then extrapolated to the entire domain of interest. Environmental data for our analysis were drawn from a 400 m grid covering all of Switzerland and consisted of 12 variables describing climate, topography and lithology. Our target patterns comprised land cover composition of each grid cell that was derived from interpretation of aerial photographs. For Regionalization 1 we used conventional cluster analysis of the environmental variables to define 60 hierarchically organized levels comprising from 5 to 300 regions. Regionalization 1 provided a base-case for comparison with the model-based regionalizations. Regionalization 2, 3 and 4 also comprised 60 hierarchically organized levels and were derived by modeling land cover composition for 4000 randomly selected “training” cells. Regionalization 2 was based on cluster analysis of environmental variables that were transformed based on a Generalized Dissimilarity Model (GDM). Regionalization 3 and 4 were defined by clustering the training cells based on their land cover composition followed by predictive modeling of the distribution of the land cover clusters using Classification and Regression Tree (CART) and Random Forest (RF) models. Independent test data (i.e. not used to train the models) were used to test the discrimination of land cover composition at all hierarchical levels of the regionalizations using the classification strength (CS) statistic. CS for all the model-based regionalizations was significantly higher than for Regionalization 1. Regionalization 3 and 4 performed significantly better than Regionalization 2 at finer hierarchical levels (many regions) and Regionalization 4 performed significantly better than Regionalization 3 for coarse levels of detail (few regions). Compositional modeling can significantly increase the performance of numerically defined ecological regionalizations. CART and RF-based models appear to produce stronger regionalizations because discriminating variables are able to change at each hierarchic level.     

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.     

Decision Tree Algorithm for Detection of Spatial Processes in Landscape Transformation

The conversion of landscapes by human activities results in widespread changes in landscape spatial structure. Regardless of the type of land conversion, there appears to be a limited number of common spatial configurations that result from such land transformation processes. Some of these configurations are considered optimal or more desirable than others. Based on pattern geometry, we define ten processes responsible for pattern change: aggregation, attrition, creation, deformation, dissection, enlargement, fragmentation, perforation, shift, and shrinkage. A novelty in this contribution is the inclusion of transformation processes causing expansion of the land cover of interest. Consequently, we propose a decision tree algorithm that enables detection of these processes, based on three parameters that have to be determined before and after the transformation of the landscape: area, perimeter length, and number of patches of the focal landscape class. As an example, the decision tree algorithm is applied to determine the transformation processes of three divergent land cover change scenarios: deciduous woodland degradation in Cadiz Township (Wisconsin, USA) 1831–1950, canopy gap formation in a terra firme rain forest at the Tiputini Biodiversity Station (Amazonian Ecuador) 1997–1998, and forest regrowth in Petersham Township (Massachusetts, USA) 1830–1985. The examples signal the importance of the temporal resolution of the data, since long-term pattern conversions can be subdivided in stadia in which particular pattern components are altered by specific transformation processes.     

The application of local measures of spatial autocorrelation for describing pattern in north Australian landscapes

This paper tests the use of a spatial analysis technique, based on the calculation of local spatial autocorrelation, as a possible approach for modelling and quantifying structure in northern Australian savanna landscapes. Unlike many landscapes in the world, northern Australian savanna landscapes appear on the surface to be intact. They have not experienced the same large-scale land clearance and intensive land management as other landscapes across Australia. Despite this, natural resource managers are beginning to notice that processes are breaking down and declines in species are becoming more evident. With future declines of species looking more imminent it is particularly important that models are available that can help to assess landscape health, and quantify any structural change that takes place. GIS and landscape ecology provide a useful way of describing landscapes both spatially and temporally and have proved to be particularly useful for understanding vegetation structure or pattern in landscapes across the world. There are many measures that examine spatial structure in the landscape and most of these are now available in a GIS environment (e.g. FRAGSTATS* ARC, r.le, and Patch Analyst). All these methods depend on a landscape described in terms of patches, corridors and matrix. However, since landscapes in northern Australia appear to be relatively intact they tend to exist as surfaces of continuous variation rather than in clearly defined homogeneous units. As a result they cannot be easily described using entity-based models requiring patches and other essentially cartographic approaches. This means that more appropriate methods need to be developed and explored. The approach examined in this paper enables clustering and local pattern in the data to be identified and forms a generic method for conceptualising the landscape structure where patches are not obvious and where boundaries between landscape features are difficult to determine. Two sites are examined using this approach. They have been exposed to different degrees of disturbance by fire and grazing. The results show that savanna landscapes are very complex and that even where there is a high degree of disturbance the landscape is still relatively heterogeneous. This means that treating savanna landscapes as being made up of homogeneous units can limit analysis of pattern, as it can over simplify the structure present, and that methods such as the autocorrelation approach are useful tools for quantifying the variable nature of these landscapes.     

Directions of Change in Land Cover and Landscape Patterns from 1957 to 2000 in Agricultural Landscapes in NW Spain

The aim of this work is the analysis of the dynamics in cultural landscapes, focused on the spatial distribution of changes in land cover and landscape patterns, and their possible linkages. These dynamics have been analyzed for the years 1957 and 2000 in a sector of the north of Galicia (NW Spain) characterized with diverse landscapes. Afforestation processes linked to agriculture abandonment and forestry specialization were the main processes observed in the study area, with the exception of the southern mountainous sector that was dominated by ploughing of scrubland for conversion into grassland, reflecting a specialization in livestock production. The structural changes that have taken place in most of the study area were related to the heterogeneity aspects, although the mountainous sectors were characterized by changes in heterogeneity and fragmentation. According to the tests performed, the comparison of the spatial distribution of both dynamics showed a certain statistical significance, reflecting the interrelationship between patterns and processes. This approach could be useful for the identification of areas with similar characteristics in terms of spatial dynamics so as to define more effective and targeted landscape planning and management strategies.     

Representative Landscapes in the Forested Area of Canada

Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada’s land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative—or “exemplar”—from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada’s ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada’s forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach.     

From Forest Landscape to Agricultural Landscape in the Developing Tropical Country of Malaysia: Pattern,Process, and Their Significance on Policy

Agricultural expansion and deforestation are spatial processes of land transformation that impact on landscape pattern. In peninsular Malaysia, the conversion of forested areas into two major cash crops—rubber and oil palm plantations—has been identified as driving significant environmental change. To date, there has been insufficient literature studying the link between changes in landscape patterns and land-related development policies. Therefore, this paper examines: (i) the links between development policies and changes in land use/land cover and landscape pattern and (ii) the significance and implications of these links for future development policies. The objective is to generate insights on the changing process of land use/land cover and landscape pattern as a functional response to development policies and their consequences for environmental conditions. Over the last century, the development of cash crops has changed the country from one dominated by natural landscapes to one dominated by agricultural landscapes. But the last decade of the century saw urbanization beginning to impact significantly. This process aligned with the establishment of various development policies, from land development for agriculture between the mid 1950s and the 1970s to an emphasis on manufacturing from the 1980s onward. Based on a case study in Selangor, peninsular Malaysia, a model of landscape pattern change is presented. It contains three stages according to the relative importance of rubber (first stage: 1900–1950s), oil palm (second stage: 1960s–1970s), and urban (third stage: 1980s–1990s) development that influenced landscape fragmentation and heterogeneity. The environmental consequences of this change have been depicted through loss of biodiversity, geohazard incidences, and the spread of vector-borne diseases. The spatial ecological information can be useful to development policy formulation, allowing diagnosis of the country’s “health” and sustainability. The final section outlines the usefulness of landscape analysis in the policy-making process to prevent further fragmentation of the landscape and forest loss in Malaysia in the face of rapid economic development.

Maintaining the Conservation Value of Shifting Cultivation Landscapes Requires Spatially Explicit Interventions

Fallow vegetation within landscapes dominated by shifting cultivation represents a woody species pool of critical importance with considerable potential for biodiversity conservation. Here, through the analysis of factors that influence the early stages of fallow vegetation regrowth in two contrasting forest margin landscapes in Southern Cameroon, we assessed the impact of current trends of land use intensification and expansion of the cultivated areas, upon the conservation potential of shifting cultivation landscapes. We combined the analysis of plot and landscape scale factors and identified a complex set of variables that influence fallow regrowth processes in particular the characteristics of the agricultural matrix and the distance from forest. Overall we observed a decline in the fallow species pool, with composition becoming increasingly dominated by species adapted to recurrent disturbance. It is clear that without intervention and if present intensification trends continue, the potential of fallow vegetation to contribute to biodiversity conservation declines because of a reduced capacity, (1) to recover forest vegetation with anything like its original species composition, (2) to connect less disturbed forest patches for forest dependent organisms. Strategies to combat biodiversity loss, including promotion of agroforestry practices and the increase of old secondary forest cover, will need not only to operate at a landscape scale but also to be spatially explicit, reflecting the spatial pattern of species reservoirs and dispersal strategies and human usage across landscapes.     

A Multi-scale Spatial Analysis of Native and Exotic Plant Species Richness Within a Mixed-Disturbance Oak Savanna Landscape

Impacts of human land use pose an increasing threat to global biodiversity. Resource managers must respond rapidly to this threat by assessing existing natural areas and prioritizing conservation actions across multiple spatial scales. Plant species richness is a useful measure of biodiversity but typically can only be evaluated on small portions of a given landscape. Modeling relationships between spatial heterogeneity and species richness may allow conservation planners to make predictions of species richness patterns within unsampled areas. We utilized a combination of field data, remotely sensed data, and landscape pattern metrics to develop models of native and exotic plant species richness at two spatial extents (60- and 120-m windows) and at four ecological levels for northwestern Ohio’s Oak Openings region. Multiple regression models explained 37–77 % of the variation in plant species richness. These models consistently explained more variation in exotic richness than in native richness. Exotic richness was better explained at the 120-m extent while native richness was better explained at the 60-m extent. Land cover composition of the surrounding landscape was an important component of all models. We found that percentage of human-modified land cover (negatively correlated with native richness and positively correlated with exotic richness) was a particularly useful predictor of plant species richness and that human-caused disturbances exert a strong influence on species richness patterns within a mixed-disturbance oak savanna landscape. Our results emphasize the importance of using a multi-scale approach to examine the complex relationships between spatial heterogeneity and plant species richness.     

Examining Landscape Dynamics at a Watershed Scale Using Landsat TM Imagery for Detection of Wintering Hooded Crane Decline in Yashiro,Japan

It is usually inappropriate to define rectangular land areas or administrative units as the extent for quantifying landscapes that possess hierarchical structure. As a functional unit established by geophysical relationships, the watershed is one of many natural scales in the hierarchical landscape. We examined the dynamics of the Yashiro watershed of Japan at the landscape level using pattern metrics based on Landsat thematic mapper (TM) imagery from 1985 to 1998. This watershed provides important habitats for the hooded crane (Grus monachus), a vulnerable species. While its world population has remained stable, the number wintering at Yashiro has declined in recent years. Changes in landscape metrics reveal that the spatial pattern within the watershed underwent homogenization due to depopulation of local people and shifts in local energy requirements and forest management policy at Yashiro. Specific changes include: a decrease in bare land area from 6.2% to 1.0% of the landscape, increased forest cover from 69.2% to 76.1%, reduction in patch number from 1194 to 616 and enlarged mean patch size, and a decrease in total edge from 223,740 m to 158,040 m. The rate of change in landscape metrics indicates a rapid change towards homogeneity in the landscape since 1990. The temporal changes in hooded crane populations corresponded to the changes in landscape. An alternative explanation has been proposed that decline of the species is influenced by landscape dynamics affecting both habitat selection and food resources. Conservation at the watershed scale is suggested to be complementary to the current conservation measures of the species.     

Impacts of changes in land use and fragmentation patterns on Atlantic coastal forests in northern Spain

Changes in forested landscapes may have important consequences for ecosystem services and biodiversity conservation. In northern Spain, major changes in land use occurred during the second half of the 20th century, but their impacts on forests have not been quantified. We evaluated the dynamics of landscape and forest distribution patterns between 1957 and 2003 in Fragas do Eume Natural Park (northwestern Spain). We used orthoimages and a set of standard landscape metrics to determine transitions between land cover classes and to examine forest distribution patterns. Eucalypt plantations showed the greatest increase in area (197%) over time. Furthermore, transitions to eucalypt plantations were found in all major land cover classes. Forest showed a net decline of 20% in total area and represented 30% of the landscape area in 2003. Forest losses were mainly due to eucalypt plantations and the building of a water reservoir, while forest gains were due to increases in shrubland, meadows and cultivated fields which had been recolonised. Forest patch size and core area decreased, and edge length increased over time. In turn, increases were obtained in mean distance between forest patches, and in adjacency to eucalypt plantations and to a water reservoir. These results suggest an increase in forest fragmentation from 1957 to 2003, as well as a change in the nature of the habitat surrounding forest patches. This study shows that land use changes, mostly from eucalypt plantation intensification, negatively affected forested habitats, although some regeneration was ongoing through ecological succession from land abandonment.     

Simulating secondary succession of elk forage values in a managed forest landscape,western Washington

Modern timber management practices often influence forage production for elk (Cervus elaphus) on broad temporal and spatial scales in forested landscapes. We incorporated site-specific information on postharvesting forest succession and forage characteristics in a simulation model to evaluate past and future influences of forest management practices on forage values for elk in a commercially managed Douglas fir (Pseudotsuga menziesii, PSME)-western hemlock (Tsuga heterophylla, TSHE) forest in western Washington. We evaluated future effects of: (1) clear-cut logging 0, 20, and 40% of harvestable stands every five years; (2) thinning 20-year-old Douglas fir forests; and (3) reducing the harvesting cycle from 60 to 45 years. Reconstruction of historical patterns of vegetation succession indicated that forage values peaked in the 1960s and declined from the 1970s to the present, but recent values still were higher than may have existed in the unmanaged landscape in 1945. Increased forest harvesting rates had little short-term influence on forage trends because harvestable stands were scarce. Simulations of forest thinning also produced negligible benefits because thinning did not improve forage productivity appreciably at the stand level. Simulations of reduced harvesting cycles shortened the duration of declining forage values from approximately 30 to 15 years. We concluded that simulation models are useful tools for examining landscape responses of forage production to forest management strategies, but the options examined provided little potential for improving elk forages in the immediate future.     

Landscape Trends in Mid-Atlantic and Southeastern United States Ecoregions

Landscape pattern and composition metrics are potential indicators for broad-scale monitoring of change and for relating change to human and ecological processes. We used a probability sample of 20-km × 20-km sampling blocks to characterize landscape composition and pattern in five US ecoregions: the Middle Atlantic Coastal Plain, Southeastern Plains, Northern Piedmont, Piedmont, and Blue Ridge Mountains. Land use/land cover (LULC) data for five dates between 1972 and 2000 were obtained for each sample block. Analyses focused on quantifying trends in selected landscape pattern metrics by ecoregion and comparing trends in land cover proportions and pattern metrics among ecoregions. Repeated measures analysis of the landscape pattern documented a statistically significant trend in all five ecoregions towards a more fine-grained landscape from the early 1970s through 2000. The ecologically important forest cover class also became more fine-grained with time (i.e., more numerous and smaller forest patches). Trends in LULC, forest edge, and forest percent like adjacencies differed among ecoregions. These results suggest that ecoregions provide a geographically coherent way to regionalize the story of national land use and land cover change in the United States. This study provides new information on LULC change in the southeast United States. Previous studies of the region from the 1930s to the 1980s showed a decrease in landscape fragmentation and an increase in percent forest, while this study showed an increase in forest fragmentation and a loss of forest cover.     

Lakes,Wetlands, and Streams as Predictors of Land Use/Cover Distribution

The importance of the surrounding landscape to aquatic ecosystems has been well established. Most research linking aquatic ecosystems to landscapes has focused on the one-way effect of land on water. However, to understand fully the complex interactions between aquatic and terrestrial ecosystems, aquatic ecosystems must be seen not only as receptors of human modification of the landscape, but also as potential drivers of these modifications. We hypothesized that the presence of aquatic ecosystems influences the spatial distribution of human land use/cover of the nearby landscape (≤1 km) and that this influence has changed through time from the 1930s to the 1990s. To test this hypothesis, we compared the distribution of residential, agricultural, and forested land use/cover around aquatic ecosystems (lakes, wetlands, and streams) to the overall regional land use/cover proportion in an area in southeast Michigan, USA; we also compared the distribution of land use/cover around county roads/highway and towns (known determinants of many land use/cover patterns) to the regional proportion. We found that lakes, wetlands, and streams were strongly associated with the distribution of land use/cover, that each ecosystem type showed different patterns, and that the magnitude of the association was at least as strong as the association with human features. We also found that the area closest to aquatic ecosystems (<500 m) was more strongly associated with land use/cover distribution than areas further away. Finally, we found that the strength of the association between aquatic ecosystems and land use/cover increased from 1938 to 1995, although the overall patterns were similar through time. Our results show that a more complete understanding is needed of the role of aquatic ecosystems on the distribution of land use/cover.     

An approach based on spatial multicriteria analysis to map the nature conservation value of agricultural land

Knowledge of the nature conservation value of agricultural land provides a useful input to land-use planning. However, the scarcity of suitable data causes this component to rarely play a role. The paper proposes a methodology based on commonly available data to assess the nature conservation value of agricultural landscapes, and to generate cartographic results to be used as decision variables in planning. The approach relies on landscape ecological indicators and on the application of multicriteria analysis in a Geographical Information System (GIS) context. Four criteria were selected: the agricultural landscape type, the cover of vegetation remnants and marginal features, the length of forest-agriculture ecotones, and the proximity to nature reserves. These criteria were assessed directly or by means of specific indicators, generating maps that were subsequently aggregated through spatial multicriteria analysis. The approach was tested in an alpine area located in Trentino (northern Italy).     

Afforestation Planning and Biodiversity Conservation: Predicting Effects on Habitat Functionality in Lithuania

Habitat re-creation is one of the multiple faces of biodiversity restoration and encompasses the attempts to reconstruct an ecosystem on severely disturbed sites with little left to restore. Afforestation of abandoned or marginal agricultural land is an important tool for the re-creation of forest ecosystems and re-establishment of functional habitat networks for the maintenance of biodiversity. This study was performed in the context of the Danish-Lithuanian project ‘Afforestation of abandoned agricultural land based on sustainable land use planning and environmentally sound forest management’. The study assessed how habitat re-creation as designed in alternative afforestation plans for two administrative regions in Lithuania will affect the functionality of the landscapes for bird species of conservation concern. Spatial analysis of the forest cover was performed under existing and proposed conditions using general landscape ecological principles concerning core and edge habitats as well as nearest-neighbour metrics. The results show that the use of general criteria may result in proportionally negative changes in the availability of some forest habitats relative to changes in total forest cover, thus leading to less significant improvements in the habitats of many naturally occurring (and even protected) species compared to what would be expected from changes in forest cover alone. To solve this dilemma it is suggested that the requirements of focal species and quantitative conservation objectives should be considered in a spatially explicit – each main forest type. It is concluded that to ensure functionality of habitat networks, knowledge and experience from the fields of landscape ecology and conservation biology should be more commonly incorporated into afforestation planning.     

Modeling the Landscape Drivers of Fire Recurrence in Sardinia (Italy)

Although recurrent fire events with very short return periods have the most dangerous effects on landscape degradation, only a few papers have explored the landscape ecological factors that drive the probability of fire recurrence. In this paper we apply a habitat suitability model for analyzing the spatial relationship between a selected set of landscape factors (mainly land use types) and fire recurrence in Sardinia (Italy) in the years 2005–2010. Our results point out that fire occurrence in already burned areas is lower than expected in natural and semi-natural land cover types, like forest and shrublands. To the contrary, like in all regions where human activity is the main source of fire ignitions, the probability of fire recurrence is higher at low altitudes and close to roads and to urban and agricultural land cover types, thus showing marked preference for those landscape factors denoting higher anthropogenic ignition risk.     

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to Central Plains stream conditions

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.     

The Influence of Landscape Features on Road Development in a Loess Region,China

Many ecologists focus on the effects of roads on landscapes, yet few consider how landscapes affect road systems. In this study, therefore, we quantitatively evaluated how land cover, topography, and building density affected the length density, node density, spatial pattern, and location of roads in Dongzhi Yuan, a typical loess region in China. Landscape factors and roads were mapped using images from SPOT satellite (Système Probatoire d’Observation de la Terre), initiated by the French space agency and a digital elevation model (DEM). Detrended canonical correspondence analysis (DCCA), a useful ordination technique to explain species–environment relations in community ecology, was applied to evaluate the ways in which landscapes may influence roads. The results showed that both farmland area and building density were positively correlated with road variables, whereas gully density and the coefficient of variation (CV of DEM) showed negative correlations. The CV of DEM, farmland area, grassland area, and building density explained variation in node density, length density, and the spatial pattern of roads, whereas gully density and building density explained variation in variables representing road location. In addition, node density, rather than length density, was the primary road variable affected by landscape variables. The results showed that the DCCA was effective in explaining road–landscape relations. Understanding these relations can provide information for landscape managers and transportation planners.     

Landscape Characterization Integrating Expert and Local Spatial Knowledge of Land and Forest Resources

In many developing countries, political documentation acknowledges the crucial elements of participation and spatiality for effective land use planning. However, operative approaches to spatial data inclusion and representation in participatory land management are often lacking. In this paper, we apply and develop an integrated landscape characterization approach to enhance spatial knowledge generation about the complex human–nature interactions in landscapes in the context of Zanzibar, Tanzania. We apply an integrated landscape conceptualization as a theoretical framework where the expert and local knowledge can meet in spatial context. The characterization is based on combining multiple data sources in GIS, and involves local communities and their local spatial knowledge since the beginning into the process. Focusing on the expected information needs for community forest management, our characterization integrates physical landscape features and retrospective landscape change data with place-specific community knowledge collected through participatory GIS techniques. The characterization is established in a map form consisting of four themes and their synthesis. The characterization maps are designed to support intuitive interpretation, express the inherently uncertain nature of the data, and accompanied by photographs to enhance communication. Visual interpretation of the characterization mediates information about the character of areas and places in the studied local landscape, depicting the role of forest resources as part of the landscape entity. We conclude that landscape characterization applied in GIS is a highly potential tool for participatory land and resource management, where spatial argumentation, stakeholder communication, and empowerment are critical issues.