MultCSync: a software package for incorporating multiple criteria in conservation planning

doi:10.1016/j.envsoft.2004.10.001

Environmental Modelling & Software

Volume 20, Issue 10, October 2005, Pages 1315-1322

https://doi.org/10.1016/j.envsoft.2004.10.001 Get rights and content

Abstract

MultCSync is a software package designed to aid incorporation of multiple criteria into conservation planning though it can be used in other similar contexts. During such planning, conservation area networks are selected primarily to represent biodiversity but must: (i) incorporate spatial design criteria such as size, dispersion, and connectivity of individual areas; and (ii) negotiate competing social claims on land use including recreation, resource extraction, and development. The social claims can also usually be modeled as (potentially incompatible) criteria to be simultaneously optimized along with the spatial design criteria. MultCSync enables the prioritization of alternative networks on the basis of such criteria after all biodiversity representation targets are satisfied. It begins by computing the set of non-dominated alternatives. If this set is sufficiently small, these alternatives can be presented to political decision makers. However, if this set is intractably large, further prioritization among the non-dominated alternatives is necessary. MultCSync accomplishes this prioritization using the Analytic Hierarchy Process (AHP) as well as a modification of the AHP in accordance with multi-attribute value theory (MAVT). MultCSync is freely downloadable via the world wide web and can be used in conjunction with different place prioritization software packages.

Introduction

A standard strategy for biodiversity conservation consists of the selection of conservation area networks (CANs): sets of places such as national parks and reserves at which conservation plans are implemented (Margules and Pressey, 2000). CANs are selected to represent desired features of biodiversity such as species (generically called “biodiversity surrogates”) at least up to specified targets, for instance, 10% of a species' range (Margules et al., 1988). Additionally, well-designed CANs incorporate spatial criteria such as the size and shape of individual areas, their dispersion over the landscape, and their connectivity. Moreover, CAN selection occurs in the context of many other social claims on land use besides biodiversity conservation. These include use for recreation, habitat transformation for agricultural or industrial development, biological and industrial resource extraction, etc. CANs are typically initially selected as economically as possible, that is, by representing biodiversity surrogates up to their targets in the smallest possible total area (Sarkar et al., 2004b). A central task of systematic conservation planning is to find a CAN that not only adequately represents surrogates but: (i) incorporates the spatial design criteria; and (ii) performs as optimally as possible with respect to the social claims on land use.

In what follows, each CAN that satisfies the biodiversity representation targets constitutes a “feasible alternative” or, in short, an “alternative”. Given a set of feasible alternatives, both the spatial design criteria and the competing social claims on land use can be modeled as criteria each of which assigns at least an ordinal rank, and preferably a quantitative value, to every such alternative. These criteria are often incompatible in the sense that they cannot all be fully optimized simultaneously. For instance, preserving land for its wilderness value is incompatible with converting it for agricultural use. Selecting the “best available” alternative involves computing “trade-offs” between all the spatial design and social criteria.

A wide variety of techniques exist for such computations ranging from heuristic multi-dimensional optimization algorithms to the well-developed multi-attribute value and utility theories (MAUT and MAVT) (Dyer et al., 1992, Keeney and Raiffa, 1993, Dyer, 2004). The MultCSync software package implements three of these techniques for use in conjunction with place prioritization software packages that ensure biodiversity surrogate representation. These packages include ResNet (Kelley et al., 2002, Sarkar et al., 2002), Marxan (Ball and Possingham, 2000), and C-Plan (Pressey, 1999). Each of these packages implements a different set of algorithms for selecting a CAN.

MultCSync begins by computing the subset of “non-dominated” alternatives in the set of feasible alternatives. An alternative, α_j, dominates another alternative, α_i, if α_j is better than α_i by at least one criterion, and no worse than α_i by any of the criteria. An alternative is “non-dominated” if no other alternative dominates it. Non-dominated alternatives are thus straightforwardly preferable to the dominated ones (Arrow and Raynaud, 1986): there is no criterion by which any dominated alternative is better than any non-dominated alternative. The set of non-dominated alternatives corresponds to the Pareto optimal sets of traditional economic analysis (Keeney and Raiffa, 1993). If the number of non-dominated alternatives is small, the non-dominated alternative set can be presented to political decision makers who can then select between them on the basis of considerations beyond those that have been modeled.

However, typically, the cardinality of the non-dominated alternative set increases rapidly with the number of criteria (Sarkar and Garson, in press). In this circumstance, the non-dominated alternative set may be intractably large for use during decision-making process. It then becomes imperative to refine the non-dominated alternative set, that is, rank the non-dominated alternatives, so that some of them can be eliminated. This requires establishing preferences between the criteria and compounding this information with the rankings of the alternatives according to the criteria.

MultCSync provides three refinement protocols: (i) it allows less important criteria to be dropped sequentially, leading to either (a) a new revised non-dominated set or (b) the elimination of some alternatives from the existing non-dominated set; (ii) it allows the use of the Analytic Hierarchy Process (AHP) (Saaty, 1980) to produce a ranking of all the criteria and uses it to rank the non-dominated alternatives; and (iii) it provides a modification of the AHP which brings it in accordance with multi-attribute value theory (MAVT) (Kamenetzky, 1982, Belton, 1986, Dyer, 1990, Salo and Hämäläinen, 1997). The AHP has routinely been used in the context of CAN design and selection, though without first excluding dominated members of the feasible alternative set (Anselin et al., 1989, Kangas, 1993, Li et al., 1999, Mendoza and Prabhu, 2000, Schmoldt et al., 2001, Clevenger et al., 2002, Villa et al., 2002, Hill et al., in press, Ananda and Herath, 2003). However, as will be noted in Section 2, the standard AHP has the counter-intuitive property of allowing rank reversal of existing alternatives when new alternatives are introduced (Kamenetzky, 1982, Dyer, 1990). MultCSync's method (iii) avoids this problem. The initial explicit computation of the non-dominated alternative set as well as methods (i) and (iii) mentioned above make MultCSync unique among existing software packages for multi-criteria decision making that are generally accessible. (For a review, see Belton and Stewart (2002).) Past software packages that also allow the explicit computation of non-dominated sets include VISPA (Colorni and Laniado, 1986) but this package is not generally accessible.

Section snippets

Background

MultCSync uses two distinct structures: (i) a set of feasible alternatives, A = {α_j: j = 1, 2,…, m}; and (ii) a set of criteria, K = {κ_i: i = 1, 2,…, n}. Each α_j must be assigned a value, ν_ij, indicating the performance of the α_j relative to each κ_i. The values ν_ij can indicate: (a) only an ordinal ranking of the α_j relative to each κ_i; or (b) a definite quantitative value on the basis of some metric for each criterion. In the following discussion it will be assumed that lower values are preferred to

Program description

MultCSync 1.0 consists of a single executable file (MultCSync.exe) that can be downloaded anywhere onto the user's hard drive. The program is opened by double clicking on the executable file. Graphic output requires the prior instillation of Gnuplot (http://www.ncftpd.com/download/). The MultCSync interface is composed of a main interface containing eight menu options along with a progress window that informs the user about the options that are currently activated. Functions are performed by

An example

The use of MultCSync in conservation planning will be illustrated by an example describing the application of the software to the evaluation of CANs in continental Ecuador (a more detailed treatment of this example is found in Sarkar et al. (2004a)).

Final notes

MultCSync makes three innovations relevant to the selection of CANs during systematic conservation planning:

(i)
MultCSync is the only generally accessible software package that allows the explicit computation of the non-dominated set Δ. While Rothley (1999) and others (e.g., Sarkar et al., 2000) have advocated the use of non-dominated sets to incorporate multiple criteria into CAN selection, those software packages that explicitly compute them (for instance, VISPA) are not yet generally accessible.

Acknowledgments

We thank Jim Dyer for discussions.

References (39)

J. Ananda et al.
The use of the Analytic Hierarchy Process to incorporate stakeholder preferences into regional forest planning
Forest Policy and Economics
(2003)
A. Anselin et al.
Multicriteria techniques in ecological evaluation: an example using the Analytic Hierarchy Process
Biological Conservation
(1989)
V. Belton
A comparison of the Analytic Hierarchy Process and a simple multi-attribute value function
European Journal of Operational Research
(1986)
J. Kangas
A multi-attribute preference model for evaluating the reforestation chain alternatives of a forest stand
Forest Ecology and Management
(1993)
W. Li et al.
Designing the buffer zone of a nature reserve: a case study in Yancheng biosphere reserve, China
Biological Conservation
(1999)
C.R. Margules et al.
Selecting networks of reserves to maximize biological diversity
Biological Conservation
(1988)
G. Mendoza et al.
Multiple criteria decision making approaches to assessing forest sustainability using criteria and indicators: a case study
Forest Ecology and Management
(2000)
J. Mustajoki et al.
Participatory multicriteria decision support with Web-HIPRE: a case of lake regulation policy
Environmental Modelling and Software
(2004)
K.J. Arrow et al.
Social Choice and Multicriterion Decision-Making
(1986)
I.R. Ball et al.
MARXAN (V 1.8.2) User's Manual
(2000)

V. Belton et al.

Multiple Criteria Decision Analysis: An Integrated Approach

(2002)

A. Clevenger et al.

GIS-generated, expert-based models for identifying wildlife habitat linkages and planning mitigation passages

Conservation Biology

(2002)

A. Colorni et al.

A software package for environmental impact assessment

J. Dyer

Remarks on the Analytic Hierarchy Process

Management Science

(1990)

J. Dyer

MAUT-multiattribute utility theory

J.S. Dyer et al.

Multiple criteria decision making, multiattribute utility theory: the next ten years

Management Science

(1992)

Expert Choice

Expert Choice 2000 2nd Edition for Groups

(2000)

J. Garson et al.

ResNet Ver 1.2 Manual

(2002)

Hill, M., Braaten, R., Veitch, S., Lees, B., Sharma, S., 2004. Multi-criteria decision analysis in spatial decision...

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MultCSync: a software package for incorporating multiple criteria in conservation planning

Abstract

Introduction

Section snippets

Background

Program description

An example

Final notes

Acknowledgments

Forest Policy and Economics

Biological Conservation

European Journal of Operational Research

Forest Ecology and Management

Biological Conservation

Biological Conservation

Forest Ecology and Management

Environmental Modelling and Software

Social Choice and Multicriterion Decision-Making

MARXAN (V 1.8.2) User's Manual

Multiple Criteria Decision Analysis: An Integrated Approach

GIS-generated, expert-based models for identifying wildlife habitat linkages and planning mitigation passages

Conservation Biology

A software package for environmental impact assessment

Remarks on the Analytic Hierarchy Process

Management Science

MAUT-multiattribute utility theory

Multiple criteria decision making, multiattribute utility theory: the next ten years

Management Science

Expert Choice 2000 2nd Edition for Groups

ResNet Ver 1.2 Manual