The role of the spatial dimension within the framework of sustainable landscapes and natural capital

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Abstract

A new paradigm of Natural Capital and Sustainable Landscapes has been suggested. It implies the integration of economic, environmental and social-cultural qualities in a physical setting while focusing on functions in terms of goods and services for people. Due to its anthropocentric perspective it pays less attention to landscape structure and spatial arrangement compared to the widely applied patch-matrix concept. The matrix of land use elements provides the key to understanding land use systems and land use changes and it can play an important role in understanding land use pattern and their dynamics. But one of the remaining constraints for a direct application of landscape ecological concepts in practice is the lack of agreed ways to combine environmental, socio-economic and societal/cultural views. This paper examines both paradigms, asking: does the spatial arrangement of land use types add specific qualities beyond statistical measures of their existence and quantity? For instance, can a landscape be sustainable, as long as 20% of the land use is extensive, 10% is protection area, etc., no matter where the respective patches are, which typical size and shape they have, how connected patches are and how often incompatible land use types are adjacent? This paper elucidates spatial concepts for sustainable landscapes with an emphasis on the role of GIS.

Introduction

Landscape ecology as a discipline has, in part, focussed on the description of structure and pattern, especially through the use of Geographic Information Systems (GIS). These pattern descriptions are the basis for the exploration of ecological mosaics (Turner, 1990, Forman, 1995, Wiens, 1995, Turner et al., 2001) and the foundation of a spatially explicit consideration of space based on relatively homogeneous patches as basic spatial entities (Wiens, 1995, Gustafson, 1998). It is generally believed that an area dissected into patches can be analysed and modelled more efficiently than dealing with a complex system as a whole. Environmental management has predominantly focused on individual ecosystems but is increasingly confronted with the problem of managing and planning entire landscapes which often consist of complex, interacting mosaics of different habitat patches and ecosystems (Potschin and Haines-Young, 2001). Generally, a complex entity is composed of different elements that interact and combine in a way that may not be obvious at first. Planners and environmentalists break down complex problems into compartments (sectoral approach) or themes (object-oriented or theme-oriented) accounting for the fact that landscapes are spatially and functionally heterogeneous, more so than ecosystems. Recently, models have been applied to the observed patterns and processes and research gradually moves from description to statistical interference (Turner et al., 2001, Bissonette, 2003). Planners offer guidelines for future developments, informing the decision making process (Botequilha Leitao and Ahern, 2002).

Nature is complex. To partition complexity is defining a typical human behaviour (Simon, 1962, Koestler, 1967). For example, structural complexity may refer to the compositional diversity and configurational intricacy of a system; functional complexity emphasizes the heterogeneity and non-linearity in system dynamics; and self-organizing complexity hinges on the emergent properties of systems co-evolving with their environment primarily through local interactions and feedbacks at different spatiotemporal scales (Wu and Marceau, 2002). We can observe a shift of systems thinking in complex ecology (Peterson and Parker, 1998): research increasingly deals with emergent properties of non-linear adaptive landscape system, spatio-temporal complexity and chaos, scale (scale invariance and covariance), hierarchy, cross-scale dynamics, and non-linear physics based holistic landscape ecology. New methods such as coupled map lattice, non-linear thermodynamics-based Markovian model, multiscale entropy analysis, self-assembling of networks, and detecting noise-induced structures in spatiotemporal data have been introduced (Brown et al., 2002). The idea that the concept of complexity is inseparable from perception depends on the scale of observation under study. There is no scale for observing all phenomena as illustrated in Fig. 1.

In order to understand complex systems, it is often convenient to consider a simpler system that exhibits the type of behaviour of interest (Simon, 1962). In sustainable landscape management we are mainly concerned with the notion of long term stability/resilience and the fact that the domain of attraction of a stable equilibrium may depend upon slowly varying biophysical parameters and fast changing human-induced disturbance (Botequilha Leitao and Ahern, 2002, Antrop, 2003). This task is extremely difficult and we have to look for easier approximations of these processes. Ludwig et al. (1997) demonstrated the complexity of the task to clarify the concepts of sustainability and resilience even for the subset of natural systems. Brown et al. (2002) describe recent progress and future prospects for understanding the mechanisms of complex systems as power laws which express empirical scaling relationships that are emergent quantitative features of biodiversity. One of the major issues of this paper is the ability to take into account the multiplicity of (spatial) scales of study so that each phenomenon studied at its specific level can be integrated through hierarchically organised spatial concepts.

Landscape refers to a common perceivable part of Earth's surface (Zonneveld, 1995). Land use is the most dynamic aspect. Crop rotation and changing land use year after year is a ‘normal’ change and is not considered as a disturbance that breaks continuity. Changing land use in this manner seldom changes the whole landscape and may even be a specific character of it. Landscape change does happen when gradually the land cover transforms to a new dominant type and also causes structural change (Antrop, 2003). Another landscape will be formed when the new forms of land use demand larger fields, special treatment of the soil, terrain levelling, removal of hedgerows and new enlarged roads. Change and continuity are related to speed and magnitude of the overall land use and land organization. The use of aerial photography after the Second World War stimulated the study of landscape in a broader multidisciplinary field (Forman and Godron, 1986, Zonneveld, 1995). Theories about changes were developed and the human impact on the natural environment is considered as the most important factor of change nowadays, acting more and more at a global scale (Goudie, 2000). It is widely agreed that people living in the landscape must be actively integrated in the landscape planning process (Forman and Collinge, 1997, Volker, 1997, Botequilha Leitao and Ahern, 2002). If the residents do not have satisfying opportunities to influence the development of their landscape they might no longer fulfil their needs and identify themselves with their everyday landscape (Buchecker et al., 2003). Social problems can be a direct consequence (and cause) of environmental problems (Saunders and Briggs, 2002). Concepts, therefore, for sustainable landscapes should not only focus on sustaining the physical landscape resources, but they should also ensure quality of life of the people living in the landscape.

For particular situations, examples exist to model consequences in the form of scenarios and impact maps for a particular scale. The impacts of economic forces and environmental policies are difficult to forecast spatially due to the highly variable ecologies across regions (Webster, 1997) but ample studies demonstrate the possibility to combine both a local and regional perspective using a spatial framework (Dramstad et al., 1996, Hermann and Osinski, 1999, Botequilha Leitao and Ahern, 2002). A good example is land abandonment in Europe which is due to severe changes in agricultural economics. This process is ongoing in large parts of Europe but it is expected to be escalating over the next years. The spatial patterns of these expected severe land use changes, affecting millions of hectares of land, are important. The combination of GIS and spatial modelling tools will support research questions like: “where will land abandonment happen if no policy actions are set” or “which areas will be more or less affected if subsidies are increased or decreased”? The identification of risk zones may help planners at local, regional and national levels, to focus their activities on problem areas and to differentiate strategies between low-potential and high-potential areas. The example of modelling land abandonment certainly includes both ecological and economic aspects. Risk and potential are typically envisaged through additive models which indicate areas of superimposition of factors such as recent and historic land use, areas of legal restriction, environmental parameters on topography, soil, vegetation, or land use. Usually, they do not take into account the quality of life of the residents.

This paper puts an emphasis on spatial representations in the context of sustainable landscapes, namely maps and representations incorporating temporality and dynamic modelling which are important tools for the analysis of landscape ecological processes, and for the visualization of alternative land-use scenarios. Many social and economic data are only available for certain administrative levels. The availability of spatial data in digital form is a prerequisite in landscape analysis, to monitor landscape change and to evaluate landscape functions. GIS offer powerful tools for spatial analysis (Openshaw and Clark, 1996, Longley et al., 2001) but are not exclusive to model complex systems spatially. GIS is both a toolbox and methodology at the same time (Pickles, 1997). It needs methodologies to integrate qualitative and quantitative information across spatial and temporal scales. The sophistication and usefulness of GIS is not necessarily proportional to complexity but it is hypothesized that they are in principle codifying and empowering human understanding of nature.

Haines-Young (2000) suggested a new paradigm for landscape ecology based on the concept of natural capital: sustainable landscapes. It reflects the increased human influence on landscapes and the increasing demand to reveal the human population as part of the landscape. Haines-Young claims that current landscape models are mainly science-based and that these models cannot define in any complete sense an optimal or sustainable landscape. He argues that in order to deal with landscape sustainability we must recognise that in any situation there is a whole set of landscapes that are more or less sustainable, in terms of the outputs of goods and services that are important to people. In this paper, I critically discuss this concept, the underlying ideas of ecosystem functions and their valuation and I take up the challenge to juxtapose it to the spatially explicit patch-matrix concept (Forman and Godron, 1986).

This paper discusses several leading issues in landscape science. Namely the importance of understanding concepts, research and applied approaches and methods with respect to their informational characteristics and the potentials for development provided by the recently emerged arena of multi-scale segmentation/object-relationship modelling. It makes a case for this, demonstrating the significance of the spatial, and the limitations of statistical approaches based mainly around a patch-matrix model. Throughout I aim to link these issues to ones of landscape policy planning and sustainable management, in particular the assessment approach of natural capital applied to sustainable landscape planning.

Section snippets

Landscape change: decoupling ‘sustainability’ and ‘development’

Humanity has influenced and dramatically changed at least 90% of Earth's landscape (Naveh, 2000, Sanderson et al., 2002). The influence of human beings on the planet has become so pervasive that it is hard to find adults in any country who have not seen the environment around them reduced in natural values during their lifetimes. This includes woodlots converted to agriculture, agricultural lands converted to suburban development, suburban development converted to urban areas (Sanderson et al.,

GIS

In the late 1980s and throughout the 1990s research frameworks and applications in various disciplines evolved which emphasize spatial relationships. Some of this growth has led to increased sophistication in the description of spatial patterns (McGarigal and Marks, 1994, Forman, 1995, Gustafson, 1998, Turner et al., 2001), aided by more powerful spatial statistics (Liebhold and Gurevitch, 2002), techniques for detecting patch boundaries (Fortin et al., 2000), Geographic Information Systems (

Spatial planning for sustainable landscapes

There are multiple dimensions to sustainability including, economic, social, ethical and spatial. Ahern (1999, p. 175) points out that landscape planning is most fundamentally linked with the latter, the spatial dimension and “predominantly at the scale of the landscape”. Despite the concerns of ecologists (see Section 2.4) it will not only pragmatically but also legally be the era of landscape planners. Although defined functionally and more precisely the ecosystem is by definition vulnerable

Sustainable landscapes: problems to be solved

More research is needed for a scientifically based framework to evaluate avoidance and compensation rules. Compensation should only be on option if degradation or harm cannot be prevented or compensated for to the required extent. According to the common understanding of sustainability, an intervention is balanced or equalized if, when it has ended, no major or persistent disruption of the balance of nature remains and the visual appearance of the landscape has been restored or reshaped in an

GIS integration

The premise of landscape ecology, that spatial context makes a difference in ecological patterns and processes does not hold for any case, but there are many studies and empirically validated facts underpinning the importance of the spatial (Wiens, 1995, Wrbka, 1998, Fjellstad, 2001, Turner et al., 2001, Bissonette, 2003). GIS is not a solution to environmental problems but a powerful analysis, integration and visualization tool for sustainable environmental management. Although the choice of

Acknowledgements

Special thanks are given to Dr. Charles Burnett for the critical discussion of the first version of the manuscript. Four anonymous reviewers and Dr. Denis Saunders as co-editor of the journal provided helpful detailed comments and constructive critique on earlier versions of this manuscript.

Thomas Blaschke holds a MSc in Geography and Applied Geoinformatics and a PhD in Geography from the University of Salzburg, Austria. He worked as GIS coordinator at the Bavarian Academy of Nature Conservation and Landscape Management, Laufen, Germany, as a senior research fellow in Manchester, UK, and as a professor for Geography and GIS at the University of Tubingen, Germany. Currently, he is associate director of Z_GIS, the Centre for Geoinformatics, University of Salzburg, Austria. His

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    Thomas Blaschke holds a MSc in Geography and Applied Geoinformatics and a PhD in Geography from the University of Salzburg, Austria. He worked as GIS coordinator at the Bavarian Academy of Nature Conservation and Landscape Management, Laufen, Germany, as a senior research fellow in Manchester, UK, and as a professor for Geography and GIS at the University of Tubingen, Germany. Currently, he is associate director of Z_GIS, the Centre for Geoinformatics, University of Salzburg, Austria. His research interests include methodological issues of the use of GIS, remote sensing and image processing in landscape and urban studies. He is involved in European-wide landscape ecological research projects, CIS and remote sensing projects and has edited several books on GIS and Remote Sensing related topics. One primary research question is on scales over which the relations and processes that we are seeking to model operate.

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