Spatial resilience of forested landscapes under climate change and management
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Resilience, the ability to recover from disturbance, has risen to the forefront of scientific policy, but is difficult to quantify, particularly in large, forested landscapes subject to disturbances, management, and climate change.
Our objective was to determine which spatial drivers will control landscape resilience over the next century, given a range of plausible climate projections across north-central Minnesota.
Using a simulation modelling approach, we simulated wind disturbance in a 4.3 million ha forested landscape in north-central Minnesota for 100 years under historic climate and five climate change scenarios, combined with four management scenarios: business as usual (BAU), maximizing economic returns (‘EcoGoods’), maximizing carbon storage (‘EcoServices’), and climate change adaption (‘CCAdapt’). To estimate resilience, we examined sites where simulated windstorms removed >70% of the biomass and measured the difference in biomass and species composition after 50 years.
Climate change lowered resilience, though there was wide variation among climate change scenarios. Resilience was explained more by spatial variation in soils than climate. We found that BAU, EcoGoods and EcoServices harvest scenarios were very similar; CCAdapt was the only scenario that demonstrated consistently higher resilience under climate change. Although we expected spatial patterns of resilience to follow ownership patterns, it was contingent upon whether lands were actively managed.
Our results demonstrate that resilience may be lower under climate change and that the effects of climate change could overwhelm current management practices. Only a substantial shift in simulated forest practices was successful in promoting resilience.
KeywordsCarbon cycle Century Climate change adaptation Forest simulation model Forest management Wind disturbance
Funding was provided by USDA AFRI (2012-68002-19896) and USDA Forest Service Northern Research Station. We acknowledge substantial contributions by the Staff of the Chippewa National Forest, particularly Kelly Barrett, Jim Gries, Audrey Gustafson, Gary Swanson, Sharon Klinkhammer, Barb Knight, Rose Johnson and John Rickers. We thank Brian Miranda for coding the Linear Wind Extension. Drs. Louis Iverson, Matt Hurteau and Matthew Duveneck provided comments that helped us substantively improve the manuscript. We greatly benefited from Matthew Duveneck’s expertise in R and LANDIS-II parameterization. Thanks also for GIS assistance by Sue Lietz and John Richardson.
- Brand FS, Jax K (2007) Focusing the meaning(s) of resilience: resilience as a descriptive concept and a boundary object. Ecol Soc 12(1):23. http://www.ecologyandsociety.org/vol12/iss1/art23/ CrossRefGoogle Scholar
- D’Amato A, Bolton WR, Blinn CR, Ek AR (2008) Current status and long-term trends of silvicultural practices in Minnesota: a 2008 assessment. University of Minnesota, St. Paul, p 58Google Scholar
- EPA (2012) U.S. Environmental Protection Agency climate change adaption plan. Public review draft. http://www.epa.gov/climatechange/pdfs/EPA-climate-change-adaptation-plan-final-for-public-comment-2-713.pdf. Accessed 5 May 2015
- Grimm V, Calabrese JM (2011) What is resilience? A short introduction. In: Viability and resilience of complex systems. Springer, Berlin, p 3–13Google Scholar
- Gustafson EJ (2016) LANDIS-II Linear Wind Extension v1.0 extension user guide. Portland State University, PortlandGoogle Scholar
- Gustafson EJ, Sturtevant BR, Fall A (2006) A collaborative, iterative approach to transferring modeling technology to land managers. In: Perera AH, Buse LJ, Crow TR (eds) Forest landscape ecology: transferring knowledge to practice. Springer, New York, pp 43–64Google Scholar
- Haeussler S, Kneeshaw D (2003) Comparing forest management to natural processes. In: Towards sustainable management of the boreal forest. NRC Research Press, Ottawa, p 307–368Google Scholar
- Handler S, Duveneck MJ, Iverson L, Peters E, Scheller RM, Wythers KR. Brandt L. Butler P, Janowiak M. Shannon, PD (2014) Minnesota forest ecosystem vulnerability assessment and synthesis: a report from the Northwoods Climate Change Response Framework project. In: Minnesota forest ecosystem vulnerability assessment and synthesis: a report from the Northwoods Climate Change Response Framework project. Gen. Tech. Rep. NRS-129. USDA Forest Service. Newtown SquareGoogle Scholar
- Holling CS (1996) Engineering resilience versus ecological resilience. In: Schulze P (ed) Engineering within ecological constraints. National Academy, Washington, DC, pp 31–44Google Scholar
- Kimmins J (2004) Emulating natural forest disturbance: What does this mean? In: Perera AH, Buse LJ, Weber MG (eds) Emulating natural forest landscape disturbances: concepts and applications. Columbia University Press, New York, pp 8–28Google Scholar
- Kolbert E (2014) The sixth extinction: an unnatural history. Bloomsbury, LondonGoogle Scholar
- Lucash MS, Scheller RM (2015) LANDIS-II Climate Library v1.0 user guide. Portland State University, PortlandGoogle Scholar
- Miles PD, Heinzen D, Mielke ME, Woodall CW. Butler BJ. Piva RJ. Meneguzzo DM. Perry CH. Gormanson DD. Barnett CJ (2011) Minnesota’s forests 2008. Resource Bulletin NRS-50. US Department of Agriculture, Forest Service Northern Research Station, Newtown SquareGoogle Scholar
- Newton AC, Cantarello E (2015) Restoration of forest resilience: an achievable goal? N For 46(5–6):645–668Google Scholar
- Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2013) Vegan: community ecology package. R package version 2.0-3. http://CRAN.R-project.org/package=vegan. Accessed Nov 2014
- Parton WJ, Anderson DW, Cole CV, Steward JWB (1983) Simulation of soil organic matter formation and mineralization in semiarid agroecosystems. In: Lowrance RR, Todd RL, Asmussen LE, Leonard RA (eds) Nutrient cycling in agricultural ecosystems. The University of Georgia, College of Agriculture Experiment Stations, AthensGoogle Scholar
- PRISM Climate Group (2013) Oregon State University. http://www.prism.oregonstate.edu/. Accessed 20 May 2013
- R Development Core Team (2014) R: a S language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Scheller RM, Domingo JB (2003) LANDIS-II Base Wind v2.1 extension user guideGoogle Scholar
- Scheller RM, Domingo JB (2015) LANDIS-II Base Harvest v3.0 user guide. Portland State University, PortlandGoogle Scholar
- Scheller RM, Domingo JB (2016) LANDIS-II Leaf Biomass Harvest (v2.1) user guide. Portland State University, PortlandGoogle Scholar
- Scheller RM, Lucash MS, Creutzburg M, Loudermilk EL (2015) LANDIS-II Century Extension v4.0 User Guide. Portland State University, Portland, OR.Google Scholar
- USDA Forest Service (2007) Chippewa National Forest, national forest management plan. http://www.fs.usda.gov/detail/chippewa/landmanagement/planning/?cid=fsm9_016569. Accessed Mar 2014
- USDA Forest Service (2010) Chapter 2020, ecological restoration and resilience, interim directive 2020–2010. In: Forest service manual 2000, national forest research management. https://fs.usda.gov/FSI_Directives/wo_id_2020-2011-1.doc