ConsNet - Advanced Software for Systematic Conservation Planning

Software Overview

ConsNet is a comprehensive software package for the design and analysis of conservation area networks (CANs) to represent biodiversity. The conservation area network design problem has many variations which depend on the specific goals of the planner but the basic problem assumes a common structure. The study region is partitioned into "cells." For each cell, there are data on the expected presence or abundance of appropriate biodiversity surrogates, the potential costs (or benefits) of placing each cell under a conservation plan, and the spatial properties of the cell. A conservation area network is assembled as a collection of cells which best meets the goals of the planner (Margules & Sarkar, 2007).

ConsNet contains new search techniques for designing conservation area networks using multiple criteria. In particular, ConsNet can also handle a variety of spatial criteria including size, compactness, connectivity, replication, and alignment. These spatial criteria are integral to the planning process, but have been difficult to address in the past due to the computational and modeling difficulties of including them. Additionally, ConsNet allows users to introduce an arbitrary number of other criteria, including socio-economic criteria.

ConsNet is built on the Modular Abstract Self-Learning Tabu Search (MASTS) framework (Ciarleglio, 2008). Tabu search is a metaheuristic that relies on memory structures to organize and navigate the search space intelligently. In MASTS, parallelized search algorithms can take advantage of multiprocessor machines with shared memory, such as dual core or quad core processors. MASTS also supports innovative tabu search strategies such as rule based objectives (RBO) and dynamic neighborhood selection (DNS). These techniques can improve search performance by directing the search to promising regions and reducing the number of required evaluations.

Beyond the considerable search capabilities, ConsNet also functions as a general decision support tool that enables ongoing interactive analysis; planners design their own searches, analyze the results in real time, create portfolios of preferred solutions, and save their progress. Users may explore the problem from a variety of different perspectives, which enhances problem understanding.

Credits

ConsNet was developed by Michael Ciarleglio as part of a dissertation project at The University of Texas at Austin. ConsNet was designed as a collaboration between several programs at the University of Texas at Austin:

Funding for this research was made possible by the National Science Foundation (NSF) and the Air Force Office of Scientific Research (AFOSR).

Downloads

Installation

ConsNet requires a minimum of 1GB of RAM and a 1.0GHz processor. The installation files require less than 10MB of hard drive space, but subsequent storage may require hundreds of megabytes. Larger datasets will require at least 2GB of RAM and additional hard drive space. Users with large datasets should refer to the section in the manual, "Configuring ConsNet for Large Problems". For extremely large datasets, it is possible that a 64-bit machine will be required due to memory limitations on a 32-bit system.

ConsNet can take advantage of multiple processor machines with shared memory, such as dual core or quad core processors. ConsNet has only been tested with the Windows XP-Pro and Windows XP-Pro x64 operating systems.

ConsNet requires a Java Runtime Environment (JRE) compatible with Java 6.0. Many free JREs are available. This software was tested with the JRE from Sun Microsystems, which can be downloaded for free at this website:

http://www.java.com/en/download/index.jsp

If you already have an older version of the JRE from Sun Microsystems, please check to make sure that this version is JRE 6 update 1 (6u1) or later. Otherwise, ConsNet will not run.

Unzip the ConsNet files onto your hard drive (any location that has the available space). All of the files used by ConsNet will be stored in this directory. ConsNet can be completely un-installed by deleting this directory. To start the program, double click "consnet_client.bat".

Disclaimer and License

Although the ConsNet software package has been tested and run successfully on computer systems at the University of Texas at Austin The software, data, and related materials contained therein are provided “AS IS,” without warranty of any kind, either expressed or implied, including, but not limited to, the implied warranties of merchantability and fitness for a particular task.

The use of ConsNet and any original ConsNet source code is restricted to Research Use and other Non-Commercial Use. "Research Use" means research, evaluation, or development for the purpose of advancing knowledge, teaching, learning, or customizing the software for personal use. "Non-Commercial Use" expressly excludes use or distribution for direct or indirect commercial (including strategic) gain or advantage. Proper attribution is required for both Research Use and Non-Commercial Use. All other rights are reserved by the copyright holders.

Discussion Group

We encourage ConsNet users to subscribe to the Google discussion group in order to:

ConsNet References

preferred citation - please use this source as a reference for ConsNet

Ciarleglio, M., Barnes, J. W., & Sarkar, S. (2009). ConsNet: new software for the selection of conservation area networks with spatial and multi-criteria analyses. 32(2), 205-209.

Other References

Ciarleglio, M. (2008). Modular Abstract Self-Learning Tabu Search (MASTS): Metaheuristic Search Theory and Practice [dissertation]. University of Texas at Austin, Texas.

Margules, C. R., & Sarkar, S. (2007). Systematic Conservation Planning. Cambridge, UK: Cambridge University Press.


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