Difference between revisions of "CLAMS"
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{{DSS, Name, responsible organisation and contact person | {{DSS, Name, responsible organisation and contact person | ||
|Has full name=Coastal Landscape Analysis and Modeling System | |Has full name=Coastal Landscape Analysis and Modeling System | ||
|Has acronym=CLAMS | |Has acronym=CLAMS | ||
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{{DSS, Software identification | {{DSS, Software identification | ||
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{{DSS, Description | {{DSS, Description | ||
|Has description=CLAMS is a multi-disciplinary research effort sponsored cooperatively through OSU's College of Forestry, the US Forest Service's Pacific Northwest Research Station, and the Oregon Department of Forestry. Our main goal is to analyze the aggregate ecological, economic, and social consequences of forest policies of different land owners in the Coast Range. | |Has description=CLAMS is a multi-disciplinary research effort sponsored cooperatively through OSU's College of Forestry, the US Forest Service's Pacific Northwest Research Station, and the Oregon Department of Forestry. Our main goal is to analyze the aggregate ecological, economic, and social consequences of forest policies of different land owners in the Coast Range. | ||
+ | The research project, titled the Coastal Landscape Analysis and Modeling | ||
+ | Study (CLAMS), was designed to develop and evaluate concepts and tools to understand pattern | ||
+ | and dynamics of provincial or subregional ecosystems such as the Coast Range and to analyze the | ||
+ | aggregate ecological and socioeconomic consequences of different forest policies and strategies | ||
+ | across multiple ownerships. CLAMS was also an experiment in ‘‘anticipatory assessments’’ in which | ||
+ | an independent group of scientists uses current and expected policy issues as the focus for research | ||
+ | that could help policy makers and stakeholders to see unintended consequences of current policies to | ||
+ | compare with consequences of new policies, and thereby possibly avoid future policy crises. | ||
+ | In this Invited Feature we present the major findings of this decade-long research effort. CLAMS | ||
+ | is a highly integrated effort in the sense that all of the studies focused on the same overall question: How might current and alternative policies and forest management activities affect ecological and socioeconomic conditions within and across ownerships at multiple spatial scales? To answer this question the studies shared the same spatial databases, simulation models, spatial resolution, time frame, and measures of forest structure and composition. | ||
+ | CLAMS was an experiment in anticipatory assessment for policy makers and other stakeholders. | ||
+ | Johnson et al. discuss the lessons learned from working at the interface of scientists, policy makers, and | ||
+ | the public. They conclude that CLAMS was successful in developing models and understanding policy | ||
+ | effects at multiple scales. They also find, however, that so far policy makers have shown relatively little | ||
+ | interest in independent evaluations of existing and alternative policies at broad scales. The reasons for | ||
+ | this are numerous. Not the least of these is the fact that policy institutions operating at this scale are | ||
+ | generally too weak or do not exist, and that interest in environmental policy analysis stems as much | ||
+ | from the pursuit of power as the pursuit of knowledge. Also, biodiversity problems often are framed at | ||
+ | finer or coarser scales than a subregion or province. Nevertheless, cross-boundary issues will not go | ||
+ | away: species and ecosystems do not respect lines on maps depicting ownership. | ||
+ | CLAMS clearly demonstrates that policy differences and variations in management practices | ||
+ | across owners can result in major differences in biological diversity and that there can be unintended | ||
+ | consequences as a result of uncoordinated policy development. Given the political constraints, | ||
+ | policy-focused science will have to be patient, but ecological research will be better able to contribute | ||
+ | in the future if it can develop better tools for understanding the complex mix of combined forest policy effects, both today and into the future. | ||
+ | |Has temporal scale=Short term (operational) | ||
+ | |Has spatial scale=Regional/national level | ||
+ | |Has objectives dimension=Multiple objectives | ||
+ | |Has forest management goal=economic evaluation, forest ecology | ||
}} | }} | ||
{{DSS, Concrete application | {{DSS, Concrete application | ||
+ | |Has user profile=public land managers (i.e. state-owned / federal / cantonal / communal forests), national forest administration | ||
|Has country=United States | |Has country=United States | ||
|Has number of users=N/A | |Has number of users=N/A |
Latest revision as of 14:58, 13 September 2024
Contents
Wiki quality control
Has flag | red |
---|
Name, responsible organisation and contact person
Has full name | Coastal Landscape Analysis and Modeling System |
---|---|
Has acronym | CLAMS |
Has wiki contact person | |
Has wiki contact e-mail |
Software identification
Has software | CLAMS |
---|
Description
Has description | CLAMS is a multi-disciplinary research effort sponsored cooperatively through OSU's College of Forestry, the US Forest Service's Pacific Northwest Research Station, and the Oregon Department of Forestry. Our main goal is to analyze the aggregate ecological, economic, and social consequences of forest policies of different land owners in the Coast Range.
The research project, titled the Coastal Landscape Analysis and Modeling Study (CLAMS), was designed to develop and evaluate concepts and tools to understand pattern and dynamics of provincial or subregional ecosystems such as the Coast Range and to analyze the aggregate ecological and socioeconomic consequences of different forest policies and strategies across multiple ownerships. CLAMS was also an experiment in ‘‘anticipatory assessments’’ in which an independent group of scientists uses current and expected policy issues as the focus for research that could help policy makers and stakeholders to see unintended consequences of current policies to compare with consequences of new policies, and thereby possibly avoid future policy crises. In this Invited Feature we present the major findings of this decade-long research effort. CLAMS is a highly integrated effort in the sense that all of the studies focused on the same overall question: How might current and alternative policies and forest management activities affect ecological and socioeconomic conditions within and across ownerships at multiple spatial scales? To answer this question the studies shared the same spatial databases, simulation models, spatial resolution, time frame, and measures of forest structure and composition. CLAMS was an experiment in anticipatory assessment for policy makers and other stakeholders. Johnson et al. discuss the lessons learned from working at the interface of scientists, policy makers, and the public. They conclude that CLAMS was successful in developing models and understanding policy effects at multiple scales. They also find, however, that so far policy makers have shown relatively little interest in independent evaluations of existing and alternative policies at broad scales. The reasons for this are numerous. Not the least of these is the fact that policy institutions operating at this scale are generally too weak or do not exist, and that interest in environmental policy analysis stems as much from the pursuit of power as the pursuit of knowledge. Also, biodiversity problems often are framed at finer or coarser scales than a subregion or province. Nevertheless, cross-boundary issues will not go away: species and ecosystems do not respect lines on maps depicting ownership. CLAMS clearly demonstrates that policy differences and variations in management practices across owners can result in major differences in biological diversity and that there can be unintended consequences as a result of uncoordinated policy development. Given the political constraints, policy-focused science will have to be patient, but ecological research will be better able to contribute in the future if it can develop better tools for understanding the complex mix of combined forest policy effects, both today and into the future. |
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Has modelling scope | |
Has temporal scale | Short term (operational) |
Has spatial context | |
Has spatial scale | Regional/national level |
Has objectives dimension | Multiple objectives |
Has related DSS | |
Has goods and services dimension | |
Has decision making dimension | |
Has forest management goal | economic evaluation, forest ecology |
Supports tree species | |
Supports silvicultural regime |
Concrete application
Has typical use case | |
---|---|
Has user profile | public land managers (i.e. state-owned / federal / cantonal / communal forests), national forest administration |
Has country | United States |
Has references about examples of application | |
Has number of users | N/A |
Has number of real-life applications | N/A |
Has utilisation in education | N/A |
Has research project reference | |
Has tool dissemination |
Decision support techniques used in the DSS
Has decision support techniques | CLAMS.Decision support techniques |
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Support of Knowledge Management
Has knowledge management processes | CLAMS.Knowledge management process |
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Support of social participation
Has support for social participation | CLAMS.Support of social participation |
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DSS development
Has DSS development | CLAMS.Description of DSS development |
---|
Documentation
Has website | www.fsl.orst.edu/clams |
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Has online demo | www.fsl.orst.edu/clams |
Has manual | No |
Has technical documentation | No |
Has reference |