Assessing the capacity of different urban forms to preserve the connectivity of ecological habitats
Graphical abstract
Highlights
► Forty simulations of compact or fractal residential development are compared. ► Comparison addresses the functional connectivity of the remaining forest habitat. ► Either fractal or compact urban forms best preserve forest habitat connectivity. ► Interest of an urban form depends on the intensity of residential development. ► It also depends on the dispersal distances of animals considered.
Introduction
Managing urban sprawl is a major concern in urban planning since it has marked negative environmental (air pollution, noise, and destruction of natural resources) and socio-economic (higher housing and commuting costs leading to social segregation and social inequity) effects. Yet urban development is a real necessity in many countries owing to the growing numbers of inhabitants and households. Consequently, land consumption is a major planning issue. Given that new residential buildings often require only moderate amounts of land compared to the associated road infrastructures (Camagni, Gibelli, & Rigamonti, 2002), the recurring question is where might urban expansion be located without worsening the effects of urban sprawl?
One major impact of urban sprawl on natural ecosystems is the fragmentation of wildlife habitats (Forman, 1995). The spread of artificial surfaces reduces available habitats through the loss of favorable areas and the break-up of the remaining habitat areas into separate patches. The viability of a species in a fragmented habitat depends on the ability of individuals to reach one patch from another by crossing unsuitable habitat. Consequently, landscape connectivity, combined with the size and the quality of habitat patches, proves to be a key notion for the conservation of animal species. Alongside structural connectivity, functional connectivity is recognized as being ecologically relevant (Taylor, Fahrig, & With, 2006). Functional connectivity may be defined as the interaction between a given species and the elements of a landscape. Methods for evaluating functional connectivity often use landscape metrics (Magle, Theobald, & Crooks, 2009) or spatial simulation models (Tischendorf & Fahrig, 2000). In order to set up tools that are easy for planners and landscape managers to use, we turn to graph theory, which provides a happy compromise between the need for intensive measurement as part of a biological approach and the constraints associated with data acquisition (Calabrese and Fagan, 2004, Fall et al., 2007). Moreover, graph theory is a preferable alternative to spatially explicit population models for species conservation in heterogeneous landscapes (Minor & Urban, 2007).
While numerous studies have analyzed responses of animals to anthropogenic habitat fragmentation, little research has addressed the relationship between habitat fragmentation and form of urban patterns (Bierwagen, 2005, Bierwagen, 2007). The limited transfer of knowledge between the eco-physical and spatial planning domains, underlined by Termorshuizen, Opdam, and van den Brink (2007), may partly explain the lack of knowledge about the relationship between urban forms and ecological systems. As Alberti (2005) points out, we do not know how clustered versus dispersed and monocentric versus polycentric urban structures differently affect environmental conditions, nor how urban development patterns influence ecological systems along the gradient of decreasing density from urban center to its periphery. Alberti (2005) also remarks that ecological studies dealing with urbanization simplify the consideration of urban structures to such an extent that the results are no longer useful to urban planners and managers. For example, Tratalos, Fuller, Warren, Davies, and Gaston (2007) compare and contrast several urban density measures with a series of measures of environmental quality and biodiversity potential. Their study yields no conclusive results and shows that similar urban forms may induce a varying environmental quality. Conversely, Bierwagen (2005) shows that urban areas that differ visually may nonetheless have similar ecological connectivity scores. Her study also shows that ecological connectivity declines with the increasing size of the urban area. However, it cannot be inferred from such a statistical relationship that there is any functional relationship between certain characteristics of urban forms and the ecological system. Urban forms are highly complex, which may account for the difficulty in identifying key variables for use as a lever for wildlife conservation. To overcome this difficulty, it may be helpful to work on simulated rather than real-world urban forms, since their morphological characteristics can be controlled. For instance, Geurs and van Wee (2006) use a system called Environment Explorer in which land-use and transport modules are dynamically interconnected to simulate scenarios of urban development. The 500 m resolution of the land-use cells, however, was too coarse for precise measurements of environmental impacts at local level.
In this paper, we aim to better understand how different patterns of residential development may impact the shape of animal habitats, and therefore affect their connectivity. Two categories of built patterns are considered: compact built patterns characterized by high built densities, uniformity, and sharp (i.e. non-sprawling) boundaries (Geurs & van Wee, 2006); fractal built patterns that are intrinsically nonuniform across scales, and exhibit longer and more sinuous boundaries (Frankhauser, 2004). In urban planning, the compact city model is the common answer to the problem of urban sprawl. But the model's limitations have been pointed out, especially the congested roads, reduced access to green and natural areas, higher housing prices, and reduced living space (Breheny, 1992, Burton, 2000). Accordingly an alternative urban model has come to the fore combining reasonable densification, as in the “wisely compact city” (Camagni et al., 2002), and a polycentric urban organization (Davoudi, 2003). The fractal city model, in keeping with this tendency, appears promising since several commentators have suggested that the fractal city could satisfy people who consume various urban and rural amenities by improving access to both built and nonbuilt spaces (Cavailhès et al., 2004, Frankhauser, 2004).
In this paper, we adopt a two-step method. First, we generate 40 theoretical scenarios of residential development using a repeatable procedure that explicitly takes into account fractal or nonfractal urban development models. Then we compare the scenarios in terms of the functional connectivity of the remaining habitat using a graph-based approach. Our aim is to identify the urban form that best preserves habitat connectivity.
Section snippets
Study area and data
The study area includes the city of Besançon and its metropolitan area in eastern France (Fig. 1). With a surface area of 116 827 ha, the study area numbers about 234 000 inhabitants. Except for the urban core, the study area is not densely urbanized but urbanization is tending to grow. This provides considerable scope for simulating numerous scenarios of residential development.
Forested zones, threatened by urban sprawl, dominate the landscape. They provide a suitable ecological habitat for
Generation of scenarios of residential development
Forty scenarios of residential development were created using MUP-City 0.5.3 software (Tannier, Vuidel, Houot, & Frankhauser, in press). MUP-City can be used to generate residential development scenarios starting from an existing built pattern. The creation of new residential locations is simulated, but not the creation of new roads that often accompanies them. MUP-City requires two types of data as its input: detailed road network (lines) and buildings (polygons). As its output, MUP-City
Defining the landscape map
Starting from the raster map of forest habitat, forest patches were identified using the Morphological Spatial Pattern Analysis (MSPA) available in the free software package GUIDOS (http://forest.jrc.ec.europa.eu/biodiversity/GUIDOS/). MSPA uses mathematical morphology to classify structural patterns on a binary map of land cover (Vogt et al., 2007). The input map is composed of a foreground, which is the focal habitat (here the forest land cover), and a complementary background. The method
Analysis of the MSPA maps
We obtained five series of eight synthetic maps exhibiting the same proportion p of the landscape covered by forest habitat. Table 2 shows a marked increase in the number of new built cells with an increasing value of Nmax. The proportion of forest is initially high (43%) and remains quite high (at least 30%) even for the scenarios characterized by the highest amount of built area. Although Gardner and Urban (2007) suggest focusing inferential studies on landscapes with low p values because the
Reliability and interest of the methodology for urban planning and design
We proposed a simple and repeatable method requiring little in the way of data and parameters:
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Create residential development scenarios using MUP-City software;
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Use the MSPA method for identifying habitat patches;
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Calculate basic spatial indexes of habitat fragmentation;
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Calculate the PC index for assessing the global habitat connectivity.
We systematically explored the effect of two urban models, two planning rules, and a varying intensity of urbanization on certain structural and functional
Conclusion
In this paper, we have explored the relationship between urban forms and ecological processes. We showed that the decrease in habitat connectivity caused by fractal or nonfractal scenarios of residential development is almost the same when urbanization is not intense. In this case, a fractal residential development may be as helpful as a wisely compact development in maintaining biodiversity. With more intense residential development, nonfractal scenarios are better than fractal scenarios
Acknowledgements
The software application MUP-City has been developed in the framework of the French program PREDIT (research program on innovation in transport), funded by the French Ministry of Ecology, Energy, Sustainable Development and Sea. The graph analysis was conducted using the software ‘Graphab’, developed by Gilles Vuidel (UMR 6049 ThéMA), in the framework of the Graphab project of the USR 3124 MSHE Ledoux, funded by the French Ministry of Ecology, Energy, Sustainable Development and Sea.
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