A New Agent-Based Model Provides Insight Into Assumptions in Modeling Forest Management Under Deep Uncertainty Article Swipe
Garry Sotnik
,
Brooke A. Cassell
,
Matthew J. Duveneck
,
Robert M. Scheller
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-192142/v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-192142/v1
ContextExploratory modeling in forestry uses a variety of approaches to study forest management questions. One key assumption that every approach makes is about the degree of deep uncertainty—the lack of knowledge required for making an informed decision—that future forest managers will face. This assumption can strongly influence simulation results and the conclusions drawn from them, but is rarely studied.ObjectivesOur objective was to measure the degree of deep uncertainty within a forest management simulation to compare alternative modeling approaches and improve understanding of when a specific approach should be applied.MethodsWe first developed a method for measuring the degree of deep uncertainty assumed by approaches to modeling forest management. Next, we developed a new extension to the LANDIS-II model, the SOSIEL Harvest Extension, which simulates alternative approaches to modeling forest management. Finally, we applied the new method and extension to comparing three alternative approaches to modeling forest management in Michigan.ResultsThe degrees of deep uncertainty varied substantially among the three modeling approaches. There is also an overall negative relationship between the degree of deep uncertainty an approach assumes a forest manager will face and the level of flexibility the approach assumes a manager will have in responding to forest change.ConclusionsQuantifying the deep uncertainty inherent in simulated forest management and comparing it across models provides an opportunity to better understand its sources and investigate differences in the assumptions made by alternative modeling approaches.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-192142/v1
- https://www.researchsquare.com/article/rs-192142/v1.pdf?c=1631888854000
- OA Status
- gold
- References
- 98
- Related Works
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- OpenAlex ID
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https://doi.org/10.21203/rs.3.rs-192142/v1Digital Object Identifier
- Title
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A New Agent-Based Model Provides Insight Into Assumptions in Modeling Forest Management Under Deep UncertaintyWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-02-15Full publication date if available
- Authors
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Garry Sotnik, Brooke A. Cassell, Matthew J. Duveneck, Robert M. SchellerList of authors in order
- Landing page
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https://doi.org/10.21203/rs.3.rs-192142/v1Publisher landing page
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https://www.researchsquare.com/article/rs-192142/v1.pdf?c=1631888854000Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.researchsquare.com/article/rs-192142/v1.pdf?c=1631888854000Direct OA link when available
- Concepts
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Computer science, Forest management, Artificial intelligence, Management science, Forestry, Economics, GeographyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| abstract_inverted_index.informed | 36 |
| abstract_inverted_index.inherent | 201 |
| abstract_inverted_index.managers | 40 |
| abstract_inverted_index.modeling | 2, 77, 105, 127, 144, 158, 228 |
| abstract_inverted_index.negative | 165 |
| abstract_inverted_index.provides | 211 |
| abstract_inverted_index.required | 32 |
| abstract_inverted_index.specific | 85 |
| abstract_inverted_index.strongly | 46 |
| abstract_inverted_index.LANDIS-II | 116 |
| abstract_inverted_index.comparing | 139, 207 |
| abstract_inverted_index.developed | 91, 110 |
| abstract_inverted_index.extension | 113, 137 |
| abstract_inverted_index.influence | 47 |
| abstract_inverted_index.knowledge | 31 |
| abstract_inverted_index.measuring | 95 |
| abstract_inverted_index.objective | 60 |
| abstract_inverted_index.simulated | 203 |
| abstract_inverted_index.simulates | 123 |
| abstract_inverted_index.Extension, | 121 |
| abstract_inverted_index.approaches | 9, 78, 103, 125, 142 |
| abstract_inverted_index.assumption | 17, 44 |
| abstract_inverted_index.management | 13, 72, 146, 205 |
| abstract_inverted_index.questions. | 14 |
| abstract_inverted_index.responding | 194 |
| abstract_inverted_index.simulation | 48, 73 |
| abstract_inverted_index.understand | 216 |
| abstract_inverted_index.alternative | 76, 124, 141, 227 |
| abstract_inverted_index.approaches. | 159, 229 |
| abstract_inverted_index.assumptions | 224 |
| abstract_inverted_index.conclusions | 52 |
| abstract_inverted_index.differences | 221 |
| abstract_inverted_index.flexibility | 185 |
| abstract_inverted_index.investigate | 220 |
| abstract_inverted_index.management. | 107, 129 |
| abstract_inverted_index.opportunity | 213 |
| abstract_inverted_index.uncertainty | 68, 100, 152, 172, 200 |
| abstract_inverted_index.relationship | 166 |
| abstract_inverted_index.substantially | 154 |
| abstract_inverted_index.understanding | 81 |
| abstract_inverted_index.decision—that | 37 |
| abstract_inverted_index.applied.MethodsWe | 89 |
| abstract_inverted_index.uncertainty—the | 28 |
| abstract_inverted_index.ContextExploratory | 1 |
| abstract_inverted_index.Michigan.ResultsThe | 148 |
| abstract_inverted_index.studied.ObjectivesOur | 59 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| abstract_inverted_index.change.ConclusionsQuantifying | 197 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5054699537 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I27837315 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.0139403 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |