Rechazo del régimen de guarda y custodia compartida

Recently there has been a revolution in the availability of information and in the development and application of tools for managing information and undertaking ecological assessment using Geographic Information Systems (GIS). These have enabled users, including ecologists, to organize information gathered across broad geographic regions in a spatial database and to perform analyses at a scale that was previously problematic to achieve (Miller & Wu, 2000). This tool has proved to be effective in accommodating large varieties of spatial attribute data. Additionally, it is beneficial to handle many layers of map information relating to one area. Generally, each layer describes a different aspect of its geography. One layer might hold data on geology, another on soils. Subsequent layers might include data on land cover, in a particular area, species distributions, or the socio-economic characteristics of the human population in the area. Thus, the power of GIS lies in the fact that data from any combination of these layers might be used to solve a particular problem. Furthermore, as problems change, the data can be processed in various ways to address different issues in a highly flexible way. Moreover, not only the ability to handle spatial information in the form of maps is important, GIS can also hold nonspatial attribute information, which can be associated with the various map features in a database management system of some kind (Miller & Wu, 2000).

As an example, the information embedded in a GIS could be used to target surveys and monitoring schemes. Data on species and habitat distribution from different dates allow monitoring of the location and the extent of change (Powell, Accad, & Shapcott, 2005; Salem, 2003). Another example of how GIS is used in the study conducted by Green and Baker (2003) about urbanisation impacts on avian habitat. In their research, they used a GIS to measure habitat structure and species

composition at each sample point, and a variety of landscape –habitat metrics were measured from aerial photographs and their location recorded (Miller & Wu, 2000).

Increasingly, ecologists are also using new technologies to collect field data. Remote sensing from aircraft and satellites has allowed them to collect data at various scales that can include many interacting ecosystems and even whole biomes. Remote sensing is the measurement of reflected, emitted, or back-scattered electromagnetic radiation from the earth’s surface, using instruments

placed at a distance, most often on a satellite, and occasionally aircraft are also used (Southwood & Henderson, 2000). Hence, the multispectral data provided by such on-board sensors led to an improved understanding of crops, forests, soils, urban growth, land changes and many other earth features and processes (Peres & Terborgh, 1995).

The integration of GIS and remotely sensed image analysis have indicated that a combination of data sources and techniques may provide more information about environmental change. A review by Wilkinson (1996) identifies three ways in which remote sensing and GIS technologies are

complementary: (a) remote sensing techniques can be used to acquire GIS data sets; (b) GIS data can be incorporated as additional information to improve remote sensing products; and (c) remote sensing data and GIS data can be used in conjunction for environmental modelling and impact analysis. A diagram as shown in Figure 3.5 shows how GIS plays an important role in land cover and impact assessment.

In conjunction with spatial metrics applied in fragmentation assessment, many GIS and image analysis software packages (e.g. IDRISI or GRASS) include landscape metric algorithms or other landscape metric software. Packages such as FRAGSTATS (McGarigal & Marks, 1995) and Patch Analyst (Elkie, Rempel, & Carr, 1999) have been developed to operate in conjunction with a GIS. FRAGSTATS is a computer software program designed to compute a wide variety of landscape metrics for categorical map patterns. It is a stand-alone program written in Microsoft Visual C++ for use in the Windows operating system. Alternatively, Patch Analyst works as an extension within ArcGIS and contains a more recent update of software code relative to FRAGSTATS. Either of these two programs can compute various indices of hierarchy.

The integration of GIS, remote sensing, and landscape metric software provides the opportunity for advanced analysis of landscape changes and disturbances. As an example, Tinker et al. (1998) used FRAGSTATS to calculate spatial pattern metrics to compare the effects of clear cutting and road building on the landscape pattern of the Bighorn National Forest, Wyoming. A principal components analysis was conducted to group the FRAGSTATS metrics into three uncorrelated components. Based on the results, the authors suggested the effects of timber harvesting and road construction may be easily monitored by the analysis of a few key metrics: patch core area, patch size and number of patches, edge density, and patch shape. Each of these metrics reported the highest loadings or scores across the three different principal components. Measures of inter-patch distance, such as mean nearest neighbour distance (MNN) and the mean proximity index (MPI), were also included in the Tinker et al. (1998) study. Results showed that either the MNN or MPI or inter-patch distance measures could contain unique information about landscape structure based on low correlations with the other metrics.