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Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change

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Abstract

Context

Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest products at regional, landscape and global scales.

Objectives

LINKAGES 2.2 was revised to create LINKAGES 3.0 and used it to evaluate tree species growth potential and total biomass production under alternative climate scenarios. This information is needed to understand species potential under future climate and to parameterize forest landscape models (FLMs) used to evaluate forest succession under climate change.

Methods

We simulated total tree biomass and responses of individual tree species in each of the 74 ecological subsections across the central hardwood region of the United States under current climate and projected climate at the end of the century from two general circulation models and two representative greenhouse gas concentration pathways.

Results

Forest composition and abundance varied by ecological subsection with more dramatic changes occurring with greater changes in temperature and precipitation and on soils with lower water holding capacity. Biomass production across the region followed patterns of soil quality.

Conclusions

Linkages 3.0 predicted realistic responses to soil and climate gradients and its application was a useful approach for considering growth potential and maximum growing space under future climates. We suggest Linkages 3.0 can also can used to inform parameter estimates in FLMs such as species establishment and maximum growing space.

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References

  • Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Kitzberger T, Rigling A, Breshears DD, Hogg EH, Gonzalez P, Fensham R, Zhang Z, Castro J, Demidova N, Lim J-H, Allard G, Running SG, Semerci A, Cobb N (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag 259:660–684

    Article  Google Scholar 

  • Arner SL, Woudenber S, Waters S, Vissage J, MacLean C, Thompson M, Hansen M (2001) National algorithms for determining stocking class, stand size class, and forest type for forest inventory and analysis plots. http://www.fs.fed.us/fmsc/ftp/fvs/docs/gtr/Arner2001.pdf

  • Botkin DB (1993) Forest dynamics an ecological model, 1st edn. Oxford University Press, New York

    Google Scholar 

  • Botkin DB, Janak JF, Wallis JR (1972) Some ecological consequences of a computer model of forest growth. J Ecol 60(3):849

    Article  Google Scholar 

  • Braun EL (1950) Deciduous forests of eastern North America. Blakiston CO., Philadelphia, Toronto, pp 596

  • Brown SL, Schroeder P, Birdsey R (1997) Aboveground biomass distribution of US eastern hardwood forests and the use of large trees as an indicator of forest development. For Ecol Manag 96:37–47

    Article  Google Scholar 

  • Brown SL, Schroeder P, Kern JS (1999) Spatial distribution of biomass in forests of the eastern USA. For Ecol Manag 123:81–90

    Article  Google Scholar 

  • Burns RM, Honkala BH (1990) Silvics of North America: 1. Conifers; 2. Hardwood. Agriculture Handbook 654, USDA Forest Service, Washington, DC

    Google Scholar 

  • Cleland DT, Freeouf JA, Keys JE, Nowacki GJ, Carpenter C, McNab WH (2007) Ecological subregions: sections of the coterminous United States. USDA forest service, Gen Tech Rep WO-76, Washington DC

    Google Scholar 

  • Delworth TL, Broccoli AJ, Rosati A, Stouffer RJ, Balaji V, Beesley JA (2006) GFDL’s CM2 global coupled climate models. Part I: formulation and simulation characteristics. J Clim 19:643–674

    Article  Google Scholar 

  • Federer CA (1995) BROOK90: a simulation model for evaporation, soil water, and streamflow, Version 3.1. USDA Forest Service

  • Federer CA (2015) The BROOK90 hydrologic model for evapotranspiration, soil water and streamflow. http://www.ecoshift.net/brook/brook90.html

  • Fralish JS (2003) The central hardwood forest: its boundaries and physiographic provinces, Proceedings 13th central hardwoods conference. In: Van Sambeek JW, Dawson JO, Ponder F, Lowenstein EF, Fralish JS (eds) USDA Forest Service, North Central Research Station, Gen Tech Rep NC-234, St. Paul

  • Gu L, Pallardy SG, Hosman KP, Sun Y (2015) Drought influenced mortality of tree species with different predawn leaf water dynamics in a decade-long study of a central US forest. Biogeosciences 12:2831–2845

    Article  Google Scholar 

  • Gustafson EJ, Keene R (2014). Predicting changes in forest composition and dynamics—landscape-scale process models. U.S. Department of Agriculture, Forest Service, Climate Change Resource Center

  • Gustafson EJ, Shinneman DJ (2015) Approaches to modeling landscape-scale drought-induced forest mortality. In: Perera AH, Sturtevant BR, Buse LJ (eds) Simulation modeling of forest landscape disturbances, Chap 3. Springer, New York, pp 45–71

    Chapter  Google Scholar 

  • Gustafson EJ, Shvidenko AZ, Sturtevant BR, Scheller RM (2010) Predicting global change effects on forest biomass and composition in south-central Siberia. Ecol Appl 20:700–715

    Article  PubMed  Google Scholar 

  • Guyette R, Kabrick JM (2000) The legacy and continuity of forest disturbance, succession, and species at the MOFEP sites. In: Shifley SR, Kabrick JM (eds) Proceedings of the second Missouri Ozark forest ecosystem project symposium: post treatment results of the landscape experiment. U.S. Department of Agriculture, Forest Service, GTR NC-227 26-44

  • He HS (2008) Forest landscape models, definition, characterization, and classification. For Ecol Manag 254:484–498

    Article  Google Scholar 

  • He HS, Mladenoff DJ (1999) Spatially explicit and stochastic simulation of forest landscape fire disturbance and succession. Ecology 80:81–99

    Article  Google Scholar 

  • He HS, Mladenoff DJ, Crow TR (1999) Linking an ecosystem model and a landscape model to study forest species response to climate warming. Ecol Model 114:213–233

    Article  Google Scholar 

  • IPCC (2013) Annex III: glossary [Planton S. (ed.)]. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, **a Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge

  • Iverson LR, Prasad AM, Matthews SN, Peters M (2008) Estimating potential habitat for 134 eastern US tree species under six climate scenarios. For Ecol Manag 254:390–406

    Article  Google Scholar 

  • Iverson LR, Thompson FR III, Mathews S, Peters M, Prasad A, Dijak WD, Fraser JS, Wang WJ, Hanberry B, He HS, Janowiak M, Butler P, Brandt L, Swanston C (2016) Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models. Landscape. doi:10.1007/s10980-016-0404-8

    Google Scholar 

  • Jenkins JC, Birdsey RA, Pan Y (2001) Biomass and NPP estimation for the mid-Atlantic region (USA) using plot-level forest inventory data. Ecol Appl 11:1174–1193

    Article  Google Scholar 

  • Johnson PS, Shifley SR, Rogers R (2009) The ecology and silviculture of oaks, 2nd edn. CAB International, Oxfordshire

    Book  Google Scholar 

  • Kabrick JM, Jensen RG, Shifley SR, Larsen (2002) Woody vegetation following even-aged, uneven-aged and no-harvest treatments on the Missouri Ozarks forest ecosystem project sites. USDA General Technical Report NC-227

  • Li X, Niu J, **e B, Johnson SJ (2013) Study on hydrological functions of litter layers in North China. PLoS ONE 8(7):e70328

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lischke H, Loffler TJ, Fischlin A (1998) Forest succession models: capturing variability with height structured, random, spatial distributions. Theor Popul Biol 54:213–226

    Article  CAS  PubMed  Google Scholar 

  • Lischke H, Zimmermann NE, Bolliger J, Rickebusch S, Loffler TJ (2006) TreeMig: a forest-landscape model for simulating spatio-temporal patterns from stand to landscape scale. Ecol Model 199:409–420

    Article  Google Scholar 

  • Little EL Jr (1971) Atlas of United States trees, volume 1, conifers and important hardwoods: U.S. Department of Agriculture Miscellaneous Publication 1146, 200 maps

  • Little EL Jr (1977) Atlas of United States trees, volume 4, minor Eastern hardwoods: U.S. Department of Agriculture Miscellaneous Publication 1342, 230 maps

  • Livneh B, Rosenberg EA, Lin C, Nijssen B, Mishra V, Andreadis KM, Maurer EP, Lettenmaier DP (2013) A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States: update and extensions. J Clim 26:9384–9392

    Article  Google Scholar 

  • MacCleery DW. (1992) American forests: a history of resilience and recovery. USDA forest Service FS-540

  • McGarvey JC, Thompson JR, Epstein HE, Shugart HH Jr (2015) Carbon storage in old-growth forests of the Mid-Atlantic: toward better understanding the eastern forest carbon sink. Ecology 96:311–317

    Article  PubMed  Google Scholar 

  • Morin X, Thuiller W (2009) Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change. Ecology 90:1301–1313

    Article  PubMed  Google Scholar 

  • Morin X, Viner D, Chuine I (2008) Tree species range shifts at a continental scale: new predictive insights from a process-based model. J Ecol 96(4):784–794

    Article  Google Scholar 

  • Niinemets U, Valladares F (2006) Tolerance to shade, drought and waterlogging of temperate northern hemisphere trees and shrubs. Ecol Monogr 76:521–547

    Article  Google Scholar 

  • O’Connell, BM, LaPoint EB, Turner JA, Ridley T, Boyer D, Wilson AM, Waddell KL, Conkling BL (2013) The forest inventory and analysis database: database description and user guide for Phase 2 (version 6.0.2). http://www.fia.fs.fed.us

  • Pastor J, Post WM (1985) Development of a linked forest productivity-soil process model. In: ORNL/TM-9519. Oak Ridge National Laboratory, Oak Ridge

    Google Scholar 

  • Purves D, Pacala S (2008) Predictive models of forest dynamics. Science 320(5882):1452–1453

    Article  CAS  PubMed  Google Scholar 

  • Reclamation (2014) http://cmip-pcdmi.llnl.gov/cmip5/availability.html

  • Reich PB, Frelich LE (2001) Temperate deciduous forests. Encyclopedia of global change. Macmillan Reference USA, Biology for students

  • Saxton KE, Rawls WJ, Romberger JS, Papendick RI (1986) Estimating generalized soil-water characteristics from texture. Soil Sci Soc Am J 50:1031–1036

    Article  Google Scholar 

  • Scheller RM, Mladenoff DJ (2005) A spatially dynamic simulation of the effects of climate change, harvesting, wind, and tree species migration on the forest composition, and biomass in northern Wisconsin, USA. Glob Change Biol 11:307–321

    Article  Google Scholar 

  • Scheller RM, Van Tuyl S, Clark KL, Hayden NG, Hom J, Mladenoff DJ (2007) Simulation of forest change in the New Jersey Pine Barrens under current and pre-colonial conditions. For Ecol Manage 255:1489–1500

    Article  Google Scholar 

  • Schneiderman JE, He HS, Thompson FR, Dijak WD, Fraser JS (2015) Comparison of a species distribution model and a process model from a hierarchical perspective to quantify effects of projected climate change on tree species. Landscape Ecol 30(10):1879–1892

    Article  Google Scholar 

  • Schroeder P, Brown S, Mo JM, Birdsey R, Cieszewski C (1997) Biomass estimation for temperate broadleaf forests of the United States using inventory data. For Sci 42:424–434

    Google Scholar 

  • Schumacher S, Bugmann H, Mladenoff DJ (2004) Improving the formulation of tree growth and succession in a spatially explicit landscape model. Ecol Model 180:175–194

    Article  Google Scholar 

  • Seidl R, Rammer W, Scheller RM, Spies T (2012) An individual-based process model to simulate landscape-scale forest ecosystem dynamics. Ecol Model 231:87–100

    Article  Google Scholar 

  • Shifley SR, He HS, Lischke H, Wang W, ** W, Gustafson EJ, Thompson JR, Thompson FR III, Dijak WD, Wang J (in press) The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models. Landscape Ecology

  • Shugart HH, West DC (1980) Forest succession models. BioScience 30(5):308–313

    Article  Google Scholar 

  • Solomon AM (1986) Transient response of forest to CO2-induced climate change: simulation modeling experiments in eastern North America. Oecologia 68:567–579

    Article  PubMed  Google Scholar 

  • Taylor JA (1967) Growing season as affected by land aspect and soil texture. In: Taylor JA (ed) Weather and agriculture. Pergamon Press, Oxford, pp 15–36

    Chapter  Google Scholar 

  • Thompson JR, Foster DR, Scheller RM, Kittredge D (2011) The influence of land use and climate change on forest biomass and composition in Massachusetts, USA. Ecol Appl 21(7):2425–2444

    Article  PubMed  Google Scholar 

  • Thornton PE, Thornton MM, Mayer BW, Wilhelmi N, Wei Y, Deveraconda R, Cook RB (2016) Daymet: daily surface weather data on a 1 km grid for North America, 1980–2012. (http://daymet.ornl.gov/) Accessed 13 Jul 2016, Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge

  • United States Department of Agriculture, Natural Resources Conservation Service. (2006) Land Resource Regions and Major Land Resource Areas of the United States, the Caribbean, and the Pacific Basin. U.S. Department of Agriculture Handbook 296

  • Vanclay JK (1991) Aggregating tree species to develop diameter increment equations for tropical rainforests. For Ecol Manag 42:143–168

    Article  Google Scholar 

  • Vanderwel MC, Purves DW (2014) How do disturbances and environmental heterogeneity affect the pace of forest distribution shifts under climate change? Ecography 37:10–20

    Article  Google Scholar 

  • Wang WJ, He HS, Spetich MA, Shifley SR, Thompson FR III (2014) LANDIS PRO: a landscape model that predicts forest composition and structure changes at regional scales. Ecography 37:225–229

    Article  Google Scholar 

  • Wang WJ, He HS, Thompson FR III, Fraser JS, Hanberry BB, Dijak WD (2015) Importance of succession, harvest, and climate change in determining future composition in U.S. central hardwood forests. Ecosphere 6(12):1–18

    Article  Google Scholar 

  • Wang WJ, He HS, Thompson FR III, Fraser JS, Dijak WD (2016) Changes in forest biomass and tree species distribution under climate change in the northeastern United States. Landscape Ecol. doi:10.1007/s10980-016-0429-z

    Google Scholar 

  • Way D, Montgomery R (2015) Photoperiod constraints on tree phenology, performance and migration in a warming world. Plant Cell Environ 38:1725–1736

    Article  PubMed  Google Scholar 

  • Wullschleger SD, Gunderson CA, Tharp ML, West DC, Post WM (2003) Simulated patterns of forest succession and productivity as a consequence of altered precipitation. In: Hanson PJ, Wullschleger SD (eds) North American temperate deciduous forest responses to changing precipitation regimes. Springer, New York, pp 433–446

    Chapter  Google Scholar 

  • Yukimoto S, Adachi Y, Hosaka M, Sakami T, Yoshimura H, Hirabara M, Tanaka TY, Shindo E, Tsu**o H, Deushi M, Mizuta R, Yabu S, Obata A, Nakano H, Koshiro T, Ose T, Kitoh A (2012) A new global climate model of the meteorological research institute: MRI-CGCM3—model description and basic performance. J Meterol Soc Japn 90A:23–64

    Article  Google Scholar 

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Acknowledgements

We thank Stanley Wullschleger and Wilfred Post for help in initializing LINKAGES v2.2 and Stephen Shifley, John Kabrick and Dan Dey for support and knowledge provided about forest ecology and forest soils. We thank Steve Pallardy and Oak Ridge National Laboratory for access to Ameriflux data. This project was funded by the U.S.D.A. Forest Service Northern Research Station, a cooperative agreement with the United States Geological Survey Northeast Climate Science Center, Department of Interior USGS Northeast Climate Science Center graduate and post-graduate fellowships, and the University of Missouri-Columbia. Its contents are solely the responsibility of the authors and do not necessarily represent views of the Northeast Climate Science Center or the USGS. This manuscript is submitted for publication with the understanding that the United States Government is authorized to reproduce and distribute reprints for Governmental purposes.

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Correspondence to William D. Dijak.

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Dijak, W.D., Hanberry, B.B., Fraser, J.S. et al. Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change. Landscape Ecol 32, 1365–1384 (2017). https://doi.org/10.1007/s10980-016-0473-8

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