How Communicative Planning Can Help Counties Reduce the Impact of Land Use Change on Biodiversity, While Other Planning Frameworks Fall Short: A Conceptual Blueprint for the California Biodiversity Project

Why we need Communicative Planning -------------------------------------------------



GIS-based modeling is stimulating changes in the fields of ecological research, 

resource management, and even ecologically-inspired politics. Within ecological 

research, the analytic and representational abilities of GIS have facilitated the 

introduction of a host of new ideas, including habitat fragmentation, wildlife corridors, 

and the patterns and periodicity of disturbances like fire, storms, and pest outbreaks. 

Within resource management, GIS technology and associated digital databases has 

expanded the power of managers by making it possible to keep track of the location and 

status of timber, water resources, and wildlife over wide areas. Within the realm of 

ecopolitics, data integration and mapping within GIS has facilitated the development of 

new concepts for managing nature at a scale variously called 'bioregional' or 

'ecosystem' or 'landscape' (Miller 1996). Small wonder that one particularly 

enthusiastic promoter, the director of the Great Barrier Reef Marine Park Authority, has 

said, "Nature conservation is best served when there are adequate databases of 

biological, geological and pedological information, linked through a sound cadastral 

base.� (Bridgewater 1993).



However, despite the availability of powerful statistical techniques, suitable data 

sources, and unprecedented computing capability, there have only been a scattering of 

efforts to employ GIS-based modeling platforms to address complex policy issues. A 

few promising attempts have been made in special places such as the Greater 

Yellowstone Ecosystem (Goldstein 1992) and a some effort has been made to couple 

GIS to a legislative mandate, such as multi-species Habitat Conservation Plans under 

Section 10a of the Endangered Species Act (Beatley 1994). However, GIS modeling 

has not been widely adopted to mediate environmental disputes between 

environmentalists, industry and agriculture, government, and the other participants in 

regional land and resource politics. Technological complexity, novelty, and cost 

certainly have a role in explaining this neglect, as well as the difficulty involved in 

creating empirically rigorous models that combine ecological and economic variables. 

But the greatest obstacle to widespread adoption is neither technical nor logistical. Time 

and time again, complex GIS-based models have been developed in isolation from the 

planning and policy-making environment, only to be ignored or scrutinized with great 

suspicion by key stakeholders. 



The solution to this divide between modeling and policy isn't more precise and accurate 

models, more user-friendly interfaces, or even a more sophisticated implementation 

strategy, utilizing techniques from marketing research and social psychology to 

overcome the resistance of comfortable old habits (Rogers 1995). Instead, we have to 

abandon the habit of designing the GIS first and only later thinking about model 

implementation. This approach violates the simple principle that, unlike a model 

intended purely for scientific research or efficient management, an effective planning 

model must be compatible with the values and knowledge of its users, as well as the 

way they interact politically. With this principle in mind, our question becomes, "How 

do we create an scientifically credible model that is integrated into the procedures 

through which communities actually form opinions and make decisions?" 



This is a tricky hybrid question, neither wholly about empirical modeling nor simply 

about public policy. Fortunately, research within the discipline of Urban and Regional 

Planning provides both an insightful critique of the failures of past GIS approaches and 

an exciting new set of theories and methods, which form the basis of the modeling 

strategy of University of California at Santa Cruz's California Biodiversity Project 

(CBP). Accordingly, this paper will attempt to demonstrate how many of the flawed 

implementation strategies adopted by GIS modelers recapitulate lessons learned over 

the last century in American planning theory and practice. These lessons are then 

consolidated with a new planning approach, called 'communicative planning', that 

could provide GIS modelers with the ability to make a significant contribution to policy 

and planning, and perhaps even catalyze changes that have long been forecast as a 

result of the GIS 'spatial revolution' but are rarely realized, such as bioregional and 

ecosystem management. This paper will conclude with a description of our attempt to 

apply the concept of communicative planning to the design of the ecological sub-model 

of the California Biodiversity Project, a three-year effort to help participants in county 

land-use planning understand the implications of changing land-use and development 

trends on regional biological diversity and mobilize effective policy responses to these 

impacts.



Before I describe the new approach of communicative planning that we have adopted in 

the design of the California Biodiversity Project, I will review the two most common 

approaches that GIS modelers take when they try to build a bridge from their technical 

knowledge to planning efforts. It is my intent to demonstrate that these two planning 

alternatives are inappropriate for the California Biodiversity Project, the first 

(comprehensive rational planning) because it is based on erroneous assumptions about 

both modeling and politics and the second (policy analysis) because biodiversity 

planning cannot be defined without controversy or confined within a public or private 

institution that can act without outside interference. Despite these limitations these two 

approaches are almost universally relied upon, because the only widely recognized 

alternative, 'advocacy planning' or 'social mobilization' is generally associated with the 

work of social activists, a role usually thought inappropriate for government agencies 

or universities conducting government-funded research (our work is funded by the 

National Biological Service, a branch of the United States Geological Survey). As I 

will show, communicative planning provides a way out of this conceptual 

straightjacket.



The Comprehensive Rational Planning Approach to Planning ------------------------------



Simply put, comprehensive rational planning is a form of social engineering, a 

replacement for politics and political participation. It flowered in the U.S. during the 

early part of this century, when public opinion reacted to the political corruption and 

Social Darwinism of the gilded age, and burgeoning industrialism and urbanization 

were accompanied by new levels of social coordination and control. Planning was 

offered as an alternative to politics, a means of employing a 'calculus of consent' to 

objectively measure the impacts of different public policies and choose the one that 

most efficiently served the public interest. Comprehensive rational planning demanded 

an end to politics, superseding the elected leader with the social technician, who 

measures collective values and develops collective plans outside of democratic control.



This approach reached its high water mark during the Great Depression, when 

Roosevelt's 'New Deal' brought about an unprecedented surrender of authority to the 

planning bureaucracy by the demoralized citizenry. Some comprehensive planning 

advocates had even greater ambitions, such as Rexford Tugwell's 'superpolitical' 

societal coordination by a fourth branch of government operating outside of politics. 

Tugwell envisioned a revolution of rationality, abolishing freedom of markets and other 

arenas of conflict in favor of consensual social coordination from the top. While these 

ideas stood little chance of implementation, they stand as a pure expression of the spirit 

of comprehensive rational planning. Post-war inheritors of this tradition were more 

conciliatory to democratic practices. Some, like Amitai Etzioni, searched for ways to 

incorporate public participation within controlled conditions established by scientific 

planning specialists within a rational planning process (Friedmann 1987). 



A key feature of post-war comprehensive rational planning was the use of 

comprehensive information systems and economic and social indicators, combining 

concepts from macroeconomics and macrosociology with complex quantitative 

analysis. The burgeoning power of computers increased the capacity of planners to 

develop ambitious social analyses, and lent greater scientific legitimacy to 

comprehensive rational planning, which had been criticized for demonstrating an 

inadequate understanding of social and economic forces. One example of computer-

assisted social analysis are the sophisticated macroeconomic analyses conducted by the 

Federal Reserve Board, which are a primary justification of the devolution of political 

authority to an appointed committee of bankers to regulate interest rates. The recent 

development of expert systems and artificial intelligence has also facilitated the 

incorporation of social values into decision making outside of a political process1. 



The possibility of explicit incorporation of social values into a GIS is quite enticing to 

an modeler who wants their work to benefit society. GIS can make it possible to 

measure the preferences of people in different locations and link these preferences to the 

disposition of the goods at different sites (e.g. zoning, infrastructure investment). GIS 

has the capability not only to calculate an optimal outcome in the present, but also to run 

series of simulations of the impact of different decisions, whose merits can be judged 

relative to a social optimization calculated by the modeler/planner. One GIS application 

that demonstrates this approach is Robert Costanza's Patuxent landscape model 

(Costanza and Wanger 1993). This model combines economic and ecological sub-

models, modeling changing sediment and nutrient loads in a watershed as farmers 

change land use practices in response to market conditions.



Simulating the entire range of societal preferences is beyond the capabilities of most 

modelers. However, there is one example of a modeling system that has many features 

of a GIS, that incorporates social preferences, simulates societal development through 

time, permits the modeler a great diversity of opportunities to influence social 

development through nearly the entire range of urban and rural land use and 

infrastructure decisions, and costs about $49, delivered in a colorful box with a good 

manual. This remarkable product is SimCity, a spatial simulation package from the 

MAXIS Corporation that has sold over a million copies to budding comprehensive 

rational planners throughout the world. The power of SimCity software to combine 

social choice with spatially-explicit simulations of land use and landscape change 

presents a clear embodiment of the comprehensive rational planning ideal. Behavior of 

'Sims' (the simulated citizens) varies depending on the opportunities and constraints 

controlled by the Mayor/model user (and the occasional random generation of a fire, 

riot, or rampaging monster). However, the illusions of democracy vanish when you 

consider how the economic and social preferences of the 'Sims' are calculated: only 

SimCity's programmers take individual and collective values into account to determine 

the suitability of particular social arrangements (and reward the user for creating these 

arrangements with simulated popularity, population growth and the financial means to 

grow the city). 



Why Comprehensive Rational Planning is a Failure -----------------------------------------



While comprehensive rational planning has undeniable appeal (I confess to owning the 

latest version of SimCity), it does not provide a planning template for the California 

Biodiversity Project. For one thing, the programmers of SimCity do not have to reckon 

with three basic limitations on comprehensiveness that we face: 



1. The data may not be available to represent biodiversity or land use change. Many of 

the government data series available at the county and regional scale are gathered 

opportunistically to satisfy environmental impact review, and other sources are gathered 

to satisfy traditional agency objectives in ways that might not pertain to new concerns 

such as biodiversity. For example, when the Pacific Northwest spotted owl 

controversy was heating up in the late 1980�s, the Forest Service had great difficulty 

identifying the boundaries of old-growth forest because they had always classified 

forest type by stand volume and tree diameter-at-breast-height, instead of coarse woody 

debris, presence of indicator species, and other dimensions of an old growth forest. 



2. Modeling components may not articulate because they operate at different temporal 

and spatial  scales. Many of the socioeconomic processes associated with 

environmental variation are more rapid than ecological processes at the county scale 

(Doke 1995), and process dynamics are governed by constraints operating at different 

scales (Allen and Hoekstra 1992). Resolution disparity is compounded by 

irreconcilable spatial data. Ecological data is usually aggregated at scales that have some 

functional relationship to the process in question, while socioeconomic data is 

aggregated by administrative or jurisdictional metrics. For example, the U.S. census 

data is aggregated by census zones, spatially irregular aggregations of houses that bear 

only a secondary relationship to the underlying terrain (Martin and Bracken 1993). 



3. There are few approaches, concepts and features that are useful to bridge between 

ecological and socioeconomic phenomena. We know that ecological elements that 

comprise biodiversity are sensitive to human disturbance, and that people are drastically 

altering their environment through habitat conversion, resource extraction, and a 

multitude of other activities both on and off-site. Yet there are no empirically-derived 

algorithms to calculate the ecological impact of changing human population density, or 

good general rules for predicting which biological elements can coexist with forestry or 

agriculture, or adjacent to a road. Even framing problems like these may face daunting 

theoretical and methodological obstacles. Recent inquiry into the philosophy and 

sociology of science has replaced the notion of a steady and seamless accumulation of 

knowledge with the idea that scientific disciplines develop knowledge in isolation from 

each other, relying on fundamentally different paradigms, research methods, and 

technical languages (Kuhn 1970).



In addition to these limitations, comprehensive rational planning requires a number of 

unsupported assumptions about society. First of all, calculation of an "optimal" state of 

society using comprehensive rational planning models relies on the assumption that 

social systems are equilibrial and human preferences are static. For example, SimCity's 

'Sims' do not change in the way they respond to the provision of infrastructure or 

economic incentives, and are immune to social and economic change from outside their 

domain. Needless to say, social and economic relations in California's counties hardly 

exhibit such stability, and their residents are notoriously susceptible to changes in 

opinion. Most good spatial models of land use change (e.g. Zhang and Landis 1995) 

use logistic regression equations to extrapolate on the basis of past growth trends, 

which can only approximate the present because of variation in the economy, rapid 

spatial restructuring of industrial location in the 1990's, variation in population growth, 

and a myriad of other variables that impact human distribution patterns.



Furthermore, comprehensive rational planning presumes that policy making can be 

modeled as a rational process, that political agents are endowed with unbounded 

rationality, and that there are no legal or institutional constraints on policy 

implementation (Friedmann 1973). The actual policy context of the CBP is about as far 

as you can get from these assumptions - political authority in California counties is 

fragmented and subject to passion and ideology, county land use policy is bounded by 

a host of legal and institutional constraints, and any single institutional actor holds 

limited knowledge about ecological and social change, whether they are a county 

supervisor, director of a regional environmental advocacy group, or a real estate 

developer. And there are few planners left who would argue that this inefficient and 

sometimes inequitable process should be discarded in favor of rational comprehensive 

planning. Advocates of this position are called 'technocrats', and scorned for their lack 

of respect for the institutions and practices of representative democracy (Fischer 1990). 



The Policy Analysis Approach to Planning -------------------------------------------------



After W.W.II planners carved out a more modest role for their craft. Because of their 

inability to either derive or justify reliance on a single rational comprehensive model, 

planners were urged to address specific social grievances and allow themselves be 

subject to the political process (Popper 1959). Charles Lindblom suggested that no 

single individual or institution could possibly predict, let alone implement, the policies 

that result from competition and conflict between political actors (Lindblom 1959). 

Instead, Lindblom advised that planners devote their efforts to making decision analysis 

widely available, enhancing the autonomy of individuals, and improving the ability of 

people to communicate among themselves. Other planners, such as Saul Alinsky, 

learned to act as advocates for less powerful interests rather than social engineers 

working for an abstract public interest. These advocacy planners anticipated resistance 

instead of conformity in response to their suggestions and innovations (Friedmann 

1987). There are a few examples of an advocacy planning GIS. In South Africa, 

Trevor Harris and his colleagues sought to empower politically marginal black 

township people (Harris et.al 1995). Harris focused on incorporating local knowledge 

into the database, enhancing access to the technology, and using the model to change 

the practices of local land use planners. The process wasn't easy: Harris had great 

difficulty defining how people should participate, given the complex power relations in 

the community.



However, because of the expense and complexity of GIS modeling efforts, the great 

majority were developed either to support a particular position (evidenced by the 

proliferation of 'hired gun' research and policy consultants), or focus on technical 

analyses intended to increase government and industry efficiency and reliability, leaving 

determination of social value to elected officials. A widely acclaimed example of the 

latter approach is the GIS-based National Gap Analysis Program, intended to identify 

gaps in the representation of biological diversity within protected areas (Scott et.al. 

1994). GAP analysis is firmly circumscribed by scientifically validated procedures, and 

scrupulously excludes any overt mention of human values, environmental politics, or 

the perception of communities living on the lands that it encompasses. As the lead Gap 

Analysis researchers wrote, "Gap Analysis is a powerful and efficient first step toward 

setting land management priorities."(Scott 1994).



The Limits of Policy Analysis ------------------------------------------------------------------



Adopting an open advocacy position is clearly inappropriate for the California 

Biodiversity project, a government-funded, university-run effort to help communities 

develop an understanding of the cumulative impact of development and land use 

practices on biodiversity. A natural choice would be the other alternative, a policy 

science approach that demonstrates how communities can efficiently allocate 

development in way that preserves as much biodiversity as possible. The great majority 

of GIS applications adopt this strategy. Sadly, this approach is as infeasible and 

misguided as the comprehensive rational planning model. Land use planning and 

biological conservation are not topics that are amenable to rational and efficient 

solutions followed by implementation by the private sector or a government agency. 

Instead, they are hotly contested fields in which stakeholders engage in conflict within a 

host of different political venues and cannot even reach agreement on common terms of 

reference, let alone an optimal solution. At most, the policy analysis approach would 

provide ammunition for one side to lambaste their opponents, a result that would not 

accomplish CBP's goal of encouraging creative county-level growth management 

activities by fostering an understanding of the relationship between environment and 

development.



Not all fields within GIS modeling are contested, of course. Sometimes private 

enterprise holds a reasonable monopoly over decision making, such as in deciding 

where is the most profitable place to site a new facility, or what the rotation schedule 

for timber should be on private land. Some areas in the public domain are similarly 

uncontested, such as determining the fastest way for emergency services to reach an 

accident site, or topographic mapping. Also, some policy arenas where there are a 

variety of possible ways to conceptualize or interpret a problem are still dominated by a 

single problem definition. In these cases, expert analysis may reinforce a dominant 

view, keep the issue confined to institutions where special interests can best be served, 

and restrict who can participate in the discussion by using arguments about issue 

complexity or the neutrality or inevitability of social impacts (Baumgartner and Jones 

1993). The military-industrial complex enjoys this sort of dominant position over 

defense policy, as does the medical establishment over many aspects of health care.



Environmental issues are rarely amenable to dominance by a single stakeholder, 

although advocates of different positions have frequently tried to evade controversy by 

defining problems in narrow terms. For example, state agencies commonly use GIS to 

locate a hazardous waste disposal site, attempting to focus efforts on identification of 

the most economically efficient site, rather than consideration of the relative benefits of 

source reduction or recycling. However, though agencies and corporations prefer to 

solve the hazardous waste question in this way, local residents often mobilize to reject 

their assigned role in the social welfare model. Similarly, property owners and 

corporate interests have proven that they can mobilize to undermine scientifically-based 

biodiversity management efforts, either by commissioning their own expert analysis or 

through legal action. There are usually plenty of avenues for different stakeholders to 

intervene in an environmental debate, including different levels of government (e.g. 

local, state, federal), different stages of the policy process (e.g. agenda setting, policy 

implementation), and different government institutions (e.g. the legislative and 

executive branches, the courts). 



Not only are there a myriad of opportunities for participation in environmental issues 

(many of which provide effective veto power over a proposed action), but 

environmental issues are open to multiple interpretations. Biodiversity is one of the 

most flexible environmental terms. Over the past decade, biodiversity has replaced 

species diversity as the focal point of conservation, increasing conservationist's ability 

to introduce different ecological subdisciplines into conservation policy, while 

remaining ambiguous about the relative weight applied to its constituent elements. In 

the Global Biodiversity Strategy, a widely disseminated document, biodiversity 

emphasizes genetics, species and ecosystems, gives second billing to the subdisciplines 

of community and population ecology, and mentions human cultural diversity in 

passing (World Resources Institute 1991). The ability to define and weight the term in a 

myriad of ways, and their implicit relationship to other widely held social values 

(including cultural diversity and wilderness conservation), makes biodiversity a term 

that resists definitive expert definition. Because of this ambiguity, biodiversity has to be 

actively defined each time it is used.



The Right Choice: Communicative Planning ------------------------------------------------



The communicative planning approach that the California Biodiversity Project has 

adopted is an method to deal with these conditions of uncertainty and conflict. The three 

main components of this approach are; (1) examining problems from the perspective of 

community stakeholders as well as empirical experts; (2) basing the model on the 

concept of negotiated, rather than received knowledge, and (3) emphasizing dialogue 

within small groups as the ideal environment for social learning. 

The communicative approach is particularly appropriate for cases in which no single 

stakeholder can implement policy without coordinating with others, and where the 

definition as well as the solution to the problem is contested. The communicative 

approach overcomes the partiality of policy analysis by relying on techniques developed 

in the practice of conflict mediation and alternative dispute resolution. Rather than 

providing stakeholders with intellectual ammunition to engage in conventional political 

struggles, communicative planning strives to bring stakeholders together under 

conditions where there is a lack of coercion and domination between participants, an 

equality of access to information, and representation of all relevant interests. Under 

these conditions, people with different values may be able to build a common problem 

definition, as well as build the foundation for understanding and trust.  



In addition, by engaging all of the stakeholders in a process of mutual accommodation, 

communicative planning also corrects for the fatal drawbacks of comprehensive rational 

planning. In a recent paper, planning theorist Judy Innes describes how this works; (1) 

Instead of attempting to scientifically determine the public interest, communicative 

planning fosters the formation of political will between representatives of the 

community by promoting dialogue; (2) Rather than trying to set collective goals in 

isolation from political interaction, communicative planning encourages stakeholders 

who have knowledge of the way decisions are made to develop a strategy that can be 

implemented through the political process; (3) Modelers are relieved of the 

responsibility of making political choices, confining their efforts to providing analytic 

and regulatory expertise and facilitating the process; (4) Instead of assuming that 

stakeholders will cooperate to reach common goals, communicative planning provides a 

process for stakeholders to enhance their capacity to cooperate; (5) Rather than 

requiring integration of all the details of a comprehensive plan, the communicative 

planning process yields a set of general guidelines and strategies that can be fleshed out 

through the conventional decision making process; (6) Communicative planning does 

not produce a single plan, which would threaten the desire of stakeholders to maintain 

their influence over the policy process and address individual topics as they arise; (7) 

The planning procedure allows stakeholders to build on small agreements, rather than 

requiring them to vote up or down on a complex package they are unfamiliar with 

(Innes 1996).



Applying Communicative Planning to the California Biodiversity Project ------------------



Communicative planning radically alters the role of California Biodiversity Project 

researchers. Instead of deciding on the components of each sub-model and determining 

parameter weighting through expert consultation or a literature review, we are 

convening two workshops. One workshop will bring together local and regional 

ecological experts,  and the other representatives from the principle county 

stakeholders. We will employ dispute resolution and consensus building techniques to 

develop a consensus on the three fundamental features of our ecological sub-model; (1) 

a basis for comparison and weighting between biodiversity elements(e.g. importance 

ranking or weighting coefficients of different elements of biodiversity to permit 

assessment of cumulative impact of different development scenarios); (2) the 

relationship between biodiversity elements and different types and intensities of land 

use (e.g. the thresholds at which housing density impairs and destroys the ecological 

value of an Oak Woodland patch); and (3) recognition and evaluation of landscape-scale 

ecological features, such as corridors or patch area. While this approach relieves us of 

the burden of establishing and defending one particular formulation of biodiversity, we 

have to have to mediate between the expert knowledge of the ecologists and planners 

and the knowledge of each stakeholder, since acceptance of the output of the combined 

model by the stakeholders is crucial to our efforts to provide a framework for 

community discussion of biodiversity. We will also use our workshops to foster 

dialogue about policy initiatives that can be derived from the trends revealed by the 

analysis. 



In contrast to a comprehensive rational planning effort, the CBP will not create a map 

of a single county development pattern that purports to minimize impact on 

biodiversity. Instead, model users will be able to alter the definition of biodiversity to 

explore how different development patterns influence different combinations of 

ecological resources. The choice of how to weight biodiversity will be influenced by 

the ecological questions being asked, the expertise available to conduct the weighting, 

the policy environment (including time frame, policy issues, and constraints) and the 

regulatory tools available of the model user. For example, if a county was attempting to 

avoid biodiversity 'train-wrecks' such as an endangered species listing this would 

suggest weighting the presence of at-risk species, such as State-designated Species of 

Special Concern. Alternatively, if the county were interested in integrating their 

protected area and open space lands with state-wide conservation priorities, they might 

select a more holistic definition of biodiversity, systematically combining species and 

habitat criteria. This flexibility is crucial, since stakeholders in each county will be 

motivated to participate in this modeling effort because of their inability to solve 

different sets of biodiversity and development policy issues.



After we integrate the ecological and socioeconomic sub-models and develop a user 

interface that allows users to alter model assumptions and derive results in a readily 

understood format, we intend to convene a third workshop in which we will assist the 

same stakeholders who helped develop the model to explore the ecological impact of 

different growth scenarios and discuss what policy actions they might undertake to 

improve growth control measures in the county. Possibilities include a published report 

with model results and analysis, a combined initiative to amend habitat protection 

ordinances to take cumulative impacts into account, recommendations to improve GIS 

capability within the county planning, and distribution of a CD-ROM with a variety of 

development scenarios developed for educational purposes. Regardless of the direction 

chosen, we think that one of the most important benefits of this modeling process will 

be improvements in the level of communication and collaboration among stakeholders 

between players, as a result of greater agreement on both basic facts (e.g. what is 

biodiversity, how does development impact it) and on appropriate policy responses 

(Innes 1994).



Conclusion -------------------------------------------------------------------------------------



The California Biodiversity Project is intended to enable participants in county land-use 

planning to design protected areas, craft regulatory strategies and zoning schemes to 

protect biodiversity, or conduct a wide range of other activities. The emphasis is on 

flexibility, accommodating a wide range of planning needs and growth scenarios. Our 

modeling design will offer interested parties the capacity to vary factors systematically, 

allowing them to overlay a community-generated vision of biodiversity with 

socioeconomic scenarios constructed by economists and regional planners working at 

the county scale. A communicative planning model provides a superior foundation for 

this modeling strategy, extracting many of the worthwhile features of comprehensive 

rational planning and policy analysis while helping to attract the interest and 

commitment of the important stakeholders in our pilot counties. We hope that our work 

will demonstrate a cure for the frustration that many modelers feel after they develop 

sophisticated GIS-based models, only to have them ignored by planners and 

policymakers. We also hope that our work can contribute toward overcoming the 

ideological, organizational, and intellectual obstacles that have prevented communities 

from addressing the terrifying social and ecological consequences of the gradual loss of 

regional biodiversity.





Acknowledgements:



I appreciate the efforts of Michael Soule, Jim Estes, Steven Minta, Pete Stine, and Chris

Cogan in designing and collaborating on the California Biodiversity Project.





EndNotes:



1 Expert systems are a method of querying a population (generally of technical 

specialists) in a way that reduces their capability to personally influence one another's 

opinion, creating a statistically defensible summary of their collective judgment. 

Artificial intelligence takes this one step further, determining the steps by which experts 

formulate judgment and systematically organizing these steps. For example, an expert 

system could provide you with the combined judgment of a panel of heart surgeons of 

the risk of a particular procedure, while an artificial intelligence system (combined with 

a good robot) could conduct the procedure, making the appropriate adjustments in 

response to a client's medical condition.





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