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Conefor Sensinode 2.2: A software package for quantifying the importance of habitat patches for landscape connectivity

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Abstract

Maintaining and restoring landscape connectivity is currently a central concern in ecology and biodiversity conservation, and there is an increasing demand of user-driven tools for integrating connectivity in landscape planning. Here we describe the new Conefor Sensinode 2.2 (CS22) software, which quantifies the importance of habitat patches for maintaining or improving functional landscape connectivity and is conceived as a tool for decision-making support in landscape planning and habitat conservation. CS22 is based on graph structures, which have been suggested to possess the greatest benefit to effort ratio for conservation problems regarding landscape connectivity. CS22 includes new connectivity metrics based on the habitat availability concept, which considers a patch itself as a space where connectivity occurs, integrating in a single measure the connected habitat area existing within the patches with the area made available by the connections between different habitat patches. These new metrics have been shown to present improved properties compared to other existing metrics and are particularly suited to the identification of critical landscape elements for connectivity. CS22 is distributed together with GIS extensions that allow for directly generating the required input files from a GIS layer. CS22 and related documentation can be freely downloaded from the World Wide Web.

Introduction

Landscape connectivity facilitates the movement of organisms, genetic interchange and other ecological flows that are critical for the viability and survival of species and for the conservation of biodiversity in general (e.g. Crooks and Sanjayan, 2006). Maintaining or restoring landscape connectivity is currently a central concern in ecology and land conservation planning. In addition, connectivity is particularly crucial in the current challenge of alleviating the effects of climate change on species and ecosystems, since it may allow species to accommodate to the shifts in their natural ranges resulting from the changing environmental conditions (Opdam and Wascher, 2004). The study of connectivity is also important for the control of invasive species and diseases (e.g. Russell et al., 2006).

There is a wide consensus in the literature that connectivity is species-specific and should be measured from a functional perspective. That is, not only the spatial arrangement of the habitat (structural connectivity) but also the dispersal distances and/or the behavioral response of the focal species to the physical structure of the landscape (functional connectivity) should be taken into account (e.g. Adriaensen et al., 2003, Theobald, 2006). Although many different metrics have been proposed and used in this context, there is still a lack of tools for assessing connectivity in real-world planning problems. On the other hand, metrics and methodologies developed for landscape connectivity analysis may fail to become widespread in practice. This may be because they are too complex, too data intensive, not transparent enough or difficult to understand by land managers, or simply because they are not available or easy to implement in operational tools for real-world landscape planning (Sarkar et al., 2006). They may just remain as theoretical developments in the academic arena, having no real impact on actual landscape planning or on improved biodiversity conservation. More effort is required from the research community to provide end-user applications and practical recommendations for integrating connectivity considerations in landscape planning with a sound basis.

Recent comparative analyses (Pascual-Hortal and Saura, 2006, Saura and Pascual-Hortal, 2007) have shown the weaknesses of different commonly used connectivity metrics for prioritizing the most important habitat patches for the maintenance of landscape connectivity. Most of the examined metrics did not match up to all the desirable properties for decision-making, with the exception of two new landscape connectivity metrics, the integral index of connectivity and the probability of connectivity, which are based on graph structures and on the habitat availability concept (Pascual-Hortal and Saura, 2006, Saura and Pascual-Hortal, 2007). These new metrics are adequately sensitive to the loss of the different types of landscape elements and are effective in identifying the most critical habitat patches for conservation. In addition, they meet the need for the development of topoecological indices (Ricotta et al., 2000), which allow quantifying purely topological characteristics in combination with the relevant differences in the ecological characteristics of the habitat patches and links.

Here we describe the new Conefor Sensinode 2.2 (CS22) software, which allows quantifying the importance of individual habitat patches for the maintenance of functional landscape connectivity, as well as evaluating the connectivity improvement provided by new potential habitat sites that may be added in the landscape through habitat creation or restoration. CS22 differs from other popular software for landscape pattern analysis such as Fragstats (McGarigal et al., 2002) or APACK (Mladenoff and DeZonia, 2004) in that it does not only provide descriptive values of the landscape but rather is conceived as a tool for decision support in landscape planning and habitat conservation through the identification of critical landscape elements for connectivity. CS22 complements other already existing graph-based software for the analysis of network connectivity, such as LQGraph (Fuller and Sarkar, 2006), Pajek (Batagelj and Mrvar, 1996) or UCINET (Borgatti et al., 1999), proving a valuable addition to the toolbox of conservationists and planners through the new improved habitat availability metrics and other features. CS22 can be used free of charge and directly downloaded from the World Wide Web.

Section snippets

Landscape graphs

A landscape mosaic and its intricate network of functional connections are described and analysed in CS22 within the graph theory approach. The type of graph considered here is a set of nodes (or vertices) and links (or edges) such that each link connects two nodes (Fuller and Sarkar, 2006, Urban and Keitt, 2001). Nodes here represent units of suitable habitat (patches, cells, protected areas, etc.) surrounded by inhospitable habitat (non-habitat) while links symbolize the potential ability of

Graphs and connection models in CS22

CS22 implements undirected and weighted graphs, in which attributes can be attached both to habitat nodes and links. Two different connection models can be used within CS22, the binary and the probabilistic connection model (Saura and Pascual-Hortal, 2007), which affects the way links are characterized and the graph implementation itself. In the binary model two nodes are just either connected or not, with no intermediate modulation of the strength or feasibility of the connection between two

Conclusions and further development

The need for maintaining ecological fluxes in the landscape and the natural dispersal routes for the movement and survival of wildlife species call for a more integrated management of the land in which connectivity considerations should be necessarily incorporated. CS22 and the methodology in which it is based (graph structures, habitat availability concept, and the new improved metrics) may be a helpful decision support tool for integrating connectivity in landscape planning. It presents

Acknowledgments

Conefor Sensinode 2.2 has been and funded by the Spanish Ministry of Science and by European FEDER funds through the CONEFOR (REN2003-01628) and IBEPFOR (CGL2006-00312) projects. Sensinode 1.0 (Landgraphs package, MS-DOS command prompt) was developed by Dean Urban (Duke University, USA), and was the seminal software and starting point for CS22. CS22 has been developed by modifying, reprogramming and including new metrics and features in Sensinode 1.0. Dr. Dean Urban generously provided the

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