State-and-transition simulation modeling to compare outcomes of alternative management scenarios under two natural disturbance regimes in a forested landscape in northeastern Wisconsin, USA

Amanda Swearingen; Jessica Price; Janet Silbernagel; Randy Swaty; Nicholas Miller; Amanda Swearingen; Jessica Price; Janet Silbernagel; Randy Swaty; Nicholas Miller

doi:10.3934/environsci.2015.3.737

AIMS Environmental Science

2015, Volume 2, Issue 3: 737-763. doi: 10.3934/environsci.2015.3.737

Previous Article Next Article

Research article Special Issues

State-and-transition simulation modeling to compare outcomes of alternative management scenarios under two natural disturbance regimes in a forested landscape in northeastern Wisconsin, USA

1.
University of Wisconsin at Madison, The Nelson Institute, 550 North Park Street, Madison, WI 53706, USA;
2.
The Nature Conservancy, LANDFIRE Team, 101 South Washington Street, Marquette, MI 49855, USA;
3.
The Nature Conservancy, Wisconsin Field Office, 633 West Main Street, Madison, WI 53703, USA

Comparisons of the potential outcomes of multiple land management strategies and an understanding of the influence of potential increases in climate-related disturbances on these outcomes are essential for long term land management and conservation planning. To provide these insights, we developed an approach that uses collaborative scenario development and state-and-transition simulation modeling to provide land managers and conservation practitioners with a comparison of potential landscapes resulting from alternative management scenarios and climate conditions, and we have applied this approach in the Wild Rivers Legacy Forest (WRLF) area in northeastern Wisconsin. Three management scenarios were developed with input from local land managers, scientists, and conservation practitioners: 1) continuation of current management, 2) expanded working forest conservation easements, and 3) cooperative ecological forestry. Scenarios were modeled under current climate with contemporary probabilities of natural disturbance and under increased probability of windthrow and wildfire that may result from climate change in this region. All scenarios were modeled for 100 years using the VDDT/TELSA modeling suite. Results showed that landscape composition and configuration were relatively similar among scenarios, and that management had a stronger effect than increased probability of windthrow and wildfire. These findings suggest that the scale of the landscape analysis used here and the lack of differences in predominant management strategies between ownerships in this region play significant roles in scenario outcomes. The approach used here does not rely on complex mechanistic modeling of uncertain dynamics and can therefore be used as starting point for planning and further analysis.
- landscape scenarios,
- state-and-transition simulation modeling,
- scenario analysis,
- forest landscape modeling,
- expert knowledge,
- working forest conservation easements
Citation: Amanda Swearingen, Jessica Price, Janet Silbernagel, Randy Swaty, Nicholas Miller. State-and-transition simulation modeling to compare outcomes of alternative management scenarios under two natural disturbance regimes in a forested landscape in northeastern Wisconsin, USA[J]. AIMS Environmental Science, 2015, 2(3): 737-763. doi: 10.3934/environsci.2015.3.737

Related Papers:

Abstract

Comparisons of the potential outcomes of multiple land management strategies and an understanding of the influence of potential increases in climate-related disturbances on these outcomes are essential for long term land management and conservation planning. To provide these insights, we developed an approach that uses collaborative scenario development and state-and-transition simulation modeling to provide land managers and conservation practitioners with a comparison of potential landscapes resulting from alternative management scenarios and climate conditions, and we have applied this approach in the Wild Rivers Legacy Forest (WRLF) area in northeastern Wisconsin. Three management scenarios were developed with input from local land managers, scientists, and conservation practitioners: 1) continuation of current management, 2) expanded working forest conservation easements, and 3) cooperative ecological forestry. Scenarios were modeled under current climate with contemporary probabilities of natural disturbance and under increased probability of windthrow and wildfire that may result from climate change in this region. All scenarios were modeled for 100 years using the VDDT/TELSA modeling suite. Results showed that landscape composition and configuration were relatively similar among scenarios, and that management had a stronger effect than increased probability of windthrow and wildfire. These findings suggest that the scale of the landscape analysis used here and the lack of differences in predominant management strategies between ownerships in this region play significant roles in scenario outcomes. The approach used here does not rely on complex mechanistic modeling of uncertain dynamics and can therefore be used as starting point for planning and further analysis.

References

[1]	Fairfax S, Gwin L, King M, et al. (2005) Buying nature: the limits of land acquisition as a conservation strategy, 1780-2004. Cambridge, Massachusetts: MIT Press, 379.
[2]	Hobbs R (2007) Setting effective and realistic restoration goals: key directions for research. Restor Ecol 15: 354-357. doi: 10.1111/j.1526-100X.2007.00225.x
[3]	Turner M, Gardner R, O'Neill R (2001) Landscape ecology in theory and practice: pattern and process. New York: Springer.
[4]	Boutin S, Herbert D (2002) Landscape ecology and forest management: developing an effective partnership. Ecol Appl 12: 390-397.
[5]	Cissel B, Swanson F, Mckee W, et al. (1994) Using the past to plan the future in the Pacific Northwest. J Forest 92: 30-31.
[6]	Franklin J, Forman R (1987) Creating landscape patterns by forest cutting: ecological consequences and principles. Landsc Ecol 1: 5-18. doi: 10.1007/BF02275261
[7]	Li H, Franklin J, Swanson F, et al. (1993). Developing alternative forest cutting patterns: a simulation approach. Landscape Ecol 8: 63-75.
[8]	Silbernagel J, Price J, Swaty R, et al. (2011) The next frontier: projecting the effectiveness of broad-scale forest conservation strategies. In C. Li, R. Lafortezza, & J. Chen Eds., Landscape Ecology in Forest Management and Conservation: Challenges and Solutions in a Changing Globe, New York: Springer, 209-230.
[9]	Coreau A, Pinay G, Thompson J, et al. (2009) The rise of research on futures in ecology: rebalancing scenarios and predictions. Ecol Lett 12: 1277-1286. doi: 10.1111/j.1461-0248.2009.01392.x
[10]	Wollenberg E, Edmunds D, Buck L (2000) Using scenarios to make decisions about the future: anticipatory learning for the adaptive co-management of community forests. Landscape Urban Plan 47: 65-77. doi: 10.1016/S0169-2046(99)00071-7
[11]	Gustafson E, Lytle D, Swaty R, et al. (2006) Simulating the cumulative effects of multiple forest management strategies on landscape measures of forest sustainability. Landsc Ecol 22: 141-156.
[12]	Provencher L, Forbis T, Frid L, et al. (2007) Comparing alternative management strategies of fire, grazing, and weed control using spatial modeling. Ecol Model 209: 249-263. doi: 10.1016/j.ecolmodel.2007.06.030
[13]	Frid L, Holcombe T, Morisette J, et al. (2013) Using state-and-transition modeling to account for imperfect detection in invasive species management. Invas Plant Sci Mana 6: 36-47 doi: 10.1614/IPSM-D-11-00065.1
[14]	Kurz W, Beukema B, Klenner W, et al. (2000) TELSA: the tool for exploratory landscape scenario analyses. Comput Electron Agr 27: 227-242. doi: 10.1016/S0168-1699(00)00109-5
[15]	Beukema S, Kurz W, Pinkham C, et al. (2003) Vegetation Dynamics Development Tool: user's guide version 4.4c. Vancouver: ESSA Technologies Ltd.
[16]	Evers L, Miller R, Doescher P, et al. (2013) Simulating Current Successional Trajectories in Sagebrush Ecosystems With Multiple Disturbances Using a State-and-Transition Modeling Framework. Rangel Ecol Manag 66: 313-329. doi: 10.2111/REM-D-11-00220.1
[17]	Provencher L, Anderson T (2011) Climate Change Revisions to Nevada's Wildlife Action Plan: Vegetation Mapping and Modeling Report to the Nevada Department of Wildlife.
[18]	Halofsky J, Hemstrom M, Conklin D, et al. (2013) Assessing potential climate change effects on vegetation using a linked model approach. Ecol Modell 266: 131-143. doi: 10.1016/j.ecolmodel.2013.07.003
[19]	Yospin G, Bridgham S, Neilson R, et al. (2015) A new model to simulate climate-change impacts on forest succession for local land management. Ecol Appl 25: 226-242. doi: 10.1890/13-0906.1
[20]	Nowacki G, Abrams M (2014) Is climate an important driver of post-European vegetation change in the Eastern United States? Glob Change Biol 21: 314-334.
[21]	Costanza J, Terando A, McKerrow A, et al. (2015) Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S. J Environ Manage 151: 186-199. doi: 10.1016/j.jenvman.2014.12.032
[22]	Price J, Silbernagel J, Miller N, et al. (2012) Eliciting expert knowledge to inform landscape modeling of conservation scenarios. Ecol Modell 229: 76-87. doi: 10.1016/j.ecolmodel.2011.09.010
[23]	Janowiak M, Iverson L, Mladenoff D, et al. (2014) Forest ecosystem vulnerability assessment and synthesis for northern Wisconsin and western Upper Michigan: a report from the northwoods climate change response framework project. Gen Tech Rep NRS-136.
[24]	WICCI, Forestry Working Group Report. Madison, Wisconsin: Nelson Institute for Environmental Studies, University of Wisconsin-Madisonand the Wisconsin Department of Natural Resources, 2011. Available from: http://www.wicci.wisc.edu/report/Forestry.pdf.
[25]	Turner M (1989) Landscape Ecology: The Effect of Pattern on Process. Annu Rev Ecol Syst 20:171-197. doi: 10.1146/annurev.es.20.110189.001131
[26]	LANDFIRE, LANDFIRE National Vegetation Dynamics Models. U.S. Department of Agriculture, Forest Service; U.S. Department of Interior, 2007. Available from http://www.landfire.gov/index.php.
[27]	TNC, Adapting LANDFIRE vegetation dynamics models manual v.1. Tallahassee, FL: TNC Global Fire Initiative, 2009. Available from: http://www.tncfire.org/documents/Aug12pluslinksFINAL_003.pdf.
[28]	Ryan KC, Opperman TS (2013) LANDFIRE-A national vegetation/fuels data base for use in fuels treatment, restoration, and suppression planning. Forest Ecol Manage 294: 208-216. doi: 10.1016/j.foreco.2012.11.003
[29]	Rollins M (2009) LANDFIRE: A nationally consistent vegetation, wildland fire, and fuel assessment. Int J Wildl Fire 18: 235-249. doi: 10.1071/WF08088
[30]	Wisconin Department of Natural Resources, Wisconsin's managed forest law: a program summary. Wisconsin Department of Natural Resources. PUB-FR-295, 2013. Available from: http://dnr.wi.gov/files/pdf/pubs/fr/FR0295.pdf
[31]	Cleland D, Crow T, Saunders S, et al. (2004) Characterizing historical and modern fire regimes in Michigan (USA): a landscape ecosystem approach. Landsc Ecol 19: 311-325. doi: 10.1023/B:LAND.0000030437.29258.3c
[32]	Schulte L, Mladenoff D, Crow T, et al. (2007) Homogenization of northern U.S. Great Lakes forests due to land use. Landsc Ecol 22: 1089-1103.
[33]	Drever C, Bergeron Y, Drever M, et al. (2009) Effects of climate on occurrence and size of large fires in a northern hardwood landscape: historical trends, forecasts, and implications for climate change in Temiscamingue, Quebec. Appl Veg Sci 12: 261-272. doi: 10.1111/j.1654-109X.2009.01035.x
[34]	Drobyshev I, Goebel P, Bergeron Y, et al. (2012) Detecting changes in climate forcing on the fire regime of a North American mixed-pine forest: A case study of Seney National Wildlife Refuge, Upper Michigan. Dendrochronologia 30: 137-145. doi: 10.1016/j.dendro.2011.07.002
[35]	Flannigan M, Stocks B, Turetsky M, et al. (2009) Impacts of climate change on fire activity and fire management in the circumboreal forest. Glob Chang Bio 15: 549-560. doi: 10.1111/j.1365-2486.2008.01660.x
[36]	Overpeck J, Rind D, Goldberg R (1990) Climate-induced changes in forest disturbance and vegetation. Nature 343: 51-53. doi: 10.1038/343051a0
[37]	Woolford D, Cao J, Dean C, et al. (1999) Signals in a region of the Canadian boreal forest. Environmetrics 21: 789-800.
[38]	Guyette RP, Thompson FR, Whittier J, et al. (2014). Future Fire Probability Modeling with Climate Change Data and Physical Chemistry. Forest Sci 60: 862-870. doi: 10.5849/forsci.13-108
[39]	Andresen J, Hilberg S, Kunkel K (2012) Historical Climate and Climate Trends in the Midwestern USA. U.S. Natl Clim Assess Midwest Tech Input Rep. 3-16.
[40]	Peterson C (2000) Catastrophic wind damage to North American forests and the potential impact of climate change. Sci Total Environ 262: 287-31. doi: 10.1016/S0048-9697(00)00529-5
[41]	Coniglio M, Stensrud D (2004) Interpreting the Climatology of Derechos. Weather Forecast 19: 95-605.
[42]	Dale V, Joyce L, McNulty S, et al. (2001) Climate Change and Forest Disturbances. Bioscience 51: 723-734. doi: 10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2
[43]	LANDFIRE, LANDFIRE National Vegetation Dynamics Models. U.S. Department of Agriculture, Forest Service; U.S. Department of Interior, 2007. Availble from: http://www.landfire.gov/national_veg_models_op2.php
[44]	ESRI (Environmental Systems Research Institute) (2008) ArcGIS: Release 9.3 software. Environmental Systems Research Institute, Redlands, California
[45]	McGarigal K, Cushman S, Neel M, et al. FRAGSTATS: Spatial pattern analysis program for categorical maps. University of Massachusetts, Amherst, 2002. Available from: http://www.umass.edu/landeco/research/fragstats/fragstats.
[46]	Li B, Archer S (1997) Weighted mean patch size: A robust index for quantifying landscape structure. Ecol Modell 102: 353-361. doi: 10.1016/S0304-3800(97)00071-9
[47]	Riitters K, O'Neill R, Hunsaker C, et al. (1995) A factor analysis of landscape pattern and structure metrics. Landsc Ecol 10: 23-39. doi: 10.1007/BF00158551
[48]	R Core Team, R: A language environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austira. 2013. Available from: http://www.R-project.org/.
[49]	Merenlender A, Huntsinger L, Guthey G, et al. (2004) Land trusts and conservation easements: Who is conserving what for whom? Conserv Biol 18: 65-75. doi: 10.1111/j.1523-1739.2004.00401.x
[50]	Scheller R, Mladenoff D (2007) An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems. Landsc Ecol 22: 491-505. doi: 10.1007/s10980-006-9048-4
[51]	Wear D, Turner M, Flamm R, et al. (1996) Ecosystem management with multiple owners: landscape dynamics in a Southern Appalachian watershed. Ecol Appl 6: 1173-1188. doi: 10.2307/2269600
[52]	Zollner P, Roberts L, Gustafson E, et al. (2008) Influence of forest planning alternatives on landscape pattern and ecosystem processes in northern Wisconsin, USA. Forest Ecol Management 254: 429-444. doi: 10.1016/j.foreco.2007.07.038
[53]	Levins R (1966) The strategy of model building in population biology. Ameri Scientist 54: 421-431.
[54]	Radeloff V, Mladenoff D, Gustafson E, et al. (2006) Modeling forest harvesting effects on landscape pattern in the Northwest Wisconsin Pine Barrens. Forest Ecol Management 236: 113-126. doi: 10.1016/j.foreco.2006.09.007
[55]	Peterson G (2002) Contagious disturbance, ecological memory, and the emergence of landscape pattern. Ecosystems 5: 329-338.56. Drescher M, Perera A, Buse L, et al. (2008) Uncertainty in expert knowledge of forest succession: A case study from boreal Ontario. For Chron 84: 194-209. doi: 10.5558/tfc84194-2

Reader Comments

Your name:*

Email:*
© 2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)