Skip to main content

Advertisement

Log in

Climate Change and Ecosystem Services Output Efficiency in Southern Loblolly Pine Forests

  • Published:
Environmental Management Aims and scope Submit manuscript

Abstract

Forests provide myriad ecosystem services that are vital to humanity. With climate change, we expect to see significant changes to forests that will alter the supply of these critical services and affect human well-being. To better understand the impacts of climate change on forest-based ecosystem services, we applied a data envelopment analysis method to assess plot-level efficiency in the provision of ecosystem services in Florida natural loblolly pine (Pinus taeda L.) forests. Using field data for n = 16 loblolly pine forest plots, including inputs such as site index, tree density, age, precipitation, and temperatures for each forest plot, we assessed the relative plot-level production of three ecosystem services: timber, carbon sequestered, and species richness. The results suggested that loblolly pine forests in Florida were largely inefficient in the provision of these ecosystem services under current climatic conditions. Climate change had a small negative impact on the loblolly pine forests efficiency in the provision of ecosystem services. In this context, we discussed the reduction of tree density that may not improve ecosystem services production.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. The FIA database assigned a dummy variable for each plot to determine if the forest plot had at least one of the silvicultural treatments mentioned in the manuscript. In the case of the selected loblolly pine plots, although all of them were naturally regenerated, they had some level of silvicultural management. However, the database did not specify which of the treatments were employed.

  2. The carbon in the above- and below-ground portion of the tree were measured in live trees with a diameter and dead trees with a diameter >2.54 cm dead trees with a diameter >12.5 cm; in case of the former, it was assumed to be one half of the value of the biomass in the tree (bole, stump, top, sapling, and woodland tree species); for the latter it is one half of the biomass of the roots (O’Connell et al. 2014).

  3. Although the PINEMAP project objective is to increase carbon sequestration by loblolly pine forests by 15 % by 2030, the 2030–2100 time period is also a time horizon analyzed by PINEMAP to evaluate carbon sequestration later in the 21st century.

  4. Site index at base age 25 years is expected to increase by 3–6 m on average by 2030, with a further 9 m increase by 2100 in the Southern U.S. (Teskey 2014; Bob Teskey, Warnell School of Forestry and Natural Resources, University of Georgia, personal communication, 26 March 2014). On average, an 8 % increase in total loblolly pine volume is obtained per 1 m increase in site index (with 1500 trees ha−1 and increasing site index from 20 to 25 m) (Carbon Resource Science Center 2014).

  5. Iverson and Prasad (2001) reported a decrease in the loblolly pine type (up to 11 %) for different climatic scenarios between 2070–2100, and Mcnab et al. (2014) reported, on average, a 66 % reduction in the range of 37 tree species in the Florida Peninsula by 2060, and, in the case of loblolly pine, a 90 % decrease.

References

  • Abatzoglou JT, Brown TJ (2012) A comparison of statistical downscaling methods suited for wildfire applications. Int J Climatol 32:772–780

    Article  Google Scholar 

  • Avkiran N (2013) Bank efficiency measurement and network DEA: a discussion of key issues and illustration of recent developments in the field. In: Pasiouras F (ed) Efficiency and productivity growth: modelling in the financial services industry, 1st edn. Wiley, Chichester, pp 171–214

    Chapter  Google Scholar 

  • Banker RD, Morey RC (1986) Efficiency analysis for exogenously fixed inputs and outputs. Oper Res 34:513–521

    Article  Google Scholar 

  • Banker RD, Cooper WW, Seiford LM, Zhu J (2011) Returns to scale in DEA. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis, 2nd edn. Springer, New York, pp 41–70

    Chapter  Google Scholar 

  • Bauhus J, Schmerbeck J (2010) Silvicultural options to enhance and use forest plantation biodiversity. In: Bauhus J, Schmerbeck J (eds) Ecosystem goods and services from plantation forests. Earthscan, Washington, DC, pp 96–139

    Google Scholar 

  • Bogetoft P, Thorsen BJ, Strange N (2003) Efficiency and merger gains in the Danish forestry extension service. For Sci 49:585–595

    Google Scholar 

  • Bosetti V, Locatelli G (2006) A data envelopment analysis approach o the assessment of natural parks’ economic efficiency and sustainability. The case of Italian national parks. Sustain Dev 286:277–286

    Article  Google Scholar 

  • Bremer LL, Farley K (2010) Does plantation forestry restore biodiversity or create green deserts? A synthesis of the effects of land-use transitions on plant species richness. Biodivers Conserv 19:3893–3915

    Article  Google Scholar 

  • Burgess PJ, Moffat AJ, Matthews RB (2010) Assessing climate change causes, risks and opportunities in forestry. Outlook Agric 39:263–268

    Article  Google Scholar 

  • Cademus R, Escobedo F, McLaughlin D, Abd-Elrahman A (2014) Analyzing trade-offs, synergies, and drivers among timber production, carbon sequestration, and water yield in Pinus elliotii forests in southeastern USA. Forests 5:1409–1431

    Article  Google Scholar 

  • Cain MD, Shelton MG (2001) Natural loblolly and shortleaf pine productivity through 53 years of management under four reproduction cutting methods. South J Appl For 1:7–16

    Google Scholar 

  • Campbell JL, Alberti G, Martin J, Law B (2009) Carbon dynamics of a ponderosa pine plantation following a thinning treatment in the northern Sierra Nevada. For Ecol Manag 257:453–463

    Article  Google Scholar 

  • Carbon Resource Science Center (2014) Loblolly pine growth, yield and carbon balance model for planted Pinus taeda stands. http://carboncenter.ifas.ufl.edu/model_loblolly.shtml. Accessed 15 May 2105

  • Carnus J, Parrotta J, Brockerhoff E et al (2006) Planted forests and biodiversity. J For 104:65–77

    Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2:429–444

    Article  Google Scholar 

  • Collins M, Knutti R, Arblaster J et al (2013) Long-term climate change: projections, commitments and irreversibility. In: Stocker T, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Working group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 1029–1136

    Google Scholar 

  • Cooper WW, Seiford LM, Tone K (2006) Introduction to data envelopment analysis and its uses with DEA-solver software and references. Springer, New York

    Google Scholar 

  • Cooper WW, Seiford LM, Zhu J (2011) Data envelopment analysis: history, models, and interpretations. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis, 2nd edn. Springer, New York, pp 1–39

    Chapter  Google Scholar 

  • Coulston J, Wear DN, Vose JM (2015) Complex forest dynamics indicate potential for slowing carbon accumulation in the southeastern United States. Sci Rep. doi:10.1038/srep08002

    Google Scholar 

  • D’Amato AW, Bradford JB, Fraver S, Palik BJ (2011) Forest management for mitigation and adaptation to climate change: insights from long-term silviculture experiments. For Ecol Manag 262:803–816

    Article  Google Scholar 

  • Diaz-Balteiro L, Romero C (2008) Making forestry decisions with multiple criteria: a review and an assessment. For Ecol Manag 255:3222–3241

    Article  Google Scholar 

  • Domec J-C, Sun G, Noormets A et al (2012) A comparison of three methods to estimate evapotranspiration in two contrasting loblolly pine plantations: age-related changes in water use and drought sensitivity of evapotranspiration components. For Sci 58:497–512

    Google Scholar 

  • Duerr D, Mistretta P (2013) Invasive pests-insects and diseases. In: Wear D, Greis J (eds) The Southern Forest Futures project: technical report. U.S. Department of Agriculture Forest Service, General technical report SRS-178. Asheville, NC, pp 407–508

  • Dwivedi P, Bailis R, Khanna M (2014) Is use of both pulpwood and logging residues instead of only logging residues for bioenergy development a viable carbon mitigation strategy? BioEnergy Res 7:217–231

    Article  CAS  Google Scholar 

  • Fahey TJ, Woodbury PB, Battles JJ et al (2010) Forest carbon storage: ecology, management, and policy. Front Ecol Environ 8:245–252

    Article  Google Scholar 

  • Flato G, Marotzke J, Abiodun B et al (2013) Evaluation of climate models. In: Stocker T, Qin D, Plattner G et al (eds) Climate change 2013: the physical science basis. Working group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 741–866

    Google Scholar 

  • Florida Department of Agriculture and Consumer Services (2013) 2013 Florida forestry economic highlights. http://floridaforest.org/wp-content/uploads/Media_Files_Florida-Forest-Service-Files_2013EconomicHighlights.pdf. Accessed 15 Aug 2015

  • Ford CR, Laseter SH, Swank WT, Vose JM (2011) Can forest management be used to sustain water-based ecosystem services in the face of climate change? Ecol Appl 21:2049–2067

    Article  Google Scholar 

  • Galik CS, Jackson RB (2009) Risks to forest carbon offset projects in a changing climate. For Ecol Manag 257:2209–2216

    Article  Google Scholar 

  • Gamfeldt L, Snäll T, Bagchi R et al (2013) Higher levels of multiple ecosystem services are found in forests with more tree species. Nat Commun 4:1340. doi:10.1038/ncomms2328

    Article  Google Scholar 

  • Golany B, Roll Y (1993) Some extensions of techniques to handle non-discretionary factors in data envelopment analysis. J Product Anal 4:419–432

    Article  Google Scholar 

  • Gonzalez-Benecke CA, Martin TA, Jokela EJ, La Torre RD (2011) A flexible hybrid model of life cycle carbon balance for loblolly pine (Pinus taeda L.) management systems. Forests 2:749–776

    Article  Google Scholar 

  • Gutiérrez E, Lozano S (2012) Avoidable damage assessment of forest fires in European countries: an efficient frontier approach. Eur J For Res 132:9–21

    Article  Google Scholar 

  • Halkos GE, Tzeremes NG (2010) Measuring biodiversity performance: a conditional efficiency measurement approach. Environ Model Softw 25:1866–1873

    Article  Google Scholar 

  • Han FX, Plodinec MJ, Su Y et al (2007) Terrestrial carbon pools in southeast and south-central United States. Clim Change 84:191–202

    Article  CAS  Google Scholar 

  • He H, Weng Q (2012) Ownership, autonomy, incentives and efficiency: evidence from the forest product processing industry in China. J For Econ 18:177–193

    Google Scholar 

  • Heller NE, Zavaleta ES (2009) Biodiversity management in the face of climate change: a review of 22 years of recommendations. Biol Conserv 142:14–32

    Article  Google Scholar 

  • Herault B, Bouxin G, Thoen D (2004) Comparison of the regeneration patterns of woody species between norway spruce plantations and deciduous forests on alluvial soils. Belg J Bot 137:36–46

    Google Scholar 

  • Hof J, Flather C, Baltic T, King R (2004) Forest and rangeland ecosystem condition indicators: identifying data envelopment analysis. For Sci 50:473–494

    Google Scholar 

  • Huang J, Abt B, Kindermann G, Ghosh S (2011) Empirical analysis of climate change impact on loblolly pine plantations in the southern United States. Nat Resour Model 24:445–476

    Article  Google Scholar 

  • IPCC (2013a) Summary for policymakers. In: Stocker T, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Working group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 3–29

    Google Scholar 

  • IPCC (2013b) Annex I: atlas of global and regional climate projections. In: Stocker T, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Working group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 1311–1393

    Google Scholar 

  • Iverson LR, Prasad AM (2001) Potential changes in tree species richness and forest community types following climate change. Ecosystems 4:186–199

    Article  CAS  Google Scholar 

  • Jackson RB, Jobbágy EG, Avissar R et al (2005) Trading water for carbon with biological carbon sequestration. Science 310:1944–1947

    Article  CAS  Google Scholar 

  • Jokela EJ, Martin TA, Vogel JG (2010) Twenty-five years of intensive forest management with southern Pines: important lessons learned. J For 10:338–347

    Google Scholar 

  • Kao C (2010) Malmquist productivity index based on common-weights DEA: the case of Taiwan forests after reorganization. Omega 38:484–491

    Article  Google Scholar 

  • Kirtman B, Power S, Adedoyin J et al (2013) Near-term climate change: projections and predictability. In: Stocker T, Qin D, Plattner G-K et al (eds) Climate change 2013: the physical science basis. Working group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 953–1028

    Google Scholar 

  • Kortelainen M, Kuosmanen T (2007) Eco-efficiency analysis of consumer durables using absolute shadow prices. J Product Anal 28:57–69

    Article  Google Scholar 

  • Kreye M, Adams D, Escobedo F (2014) The value of forest conservation for water quality protection. Forests 5:862–884

    Article  Google Scholar 

  • Kuosmanen T, Kortelainen M (2007) Valuing environmental factors in cost-benefit analysis using data envelopment analysis. Ecol Econ 62:56–65

    Article  Google Scholar 

  • Lal P, Alavalapati J (2014) Economics of forest biomass based-bioenergy. In: Kant S, Alavalapati JRR (eds) Handbook of forest resource economics. Routledge, New York, pp 275–289

    Google Scholar 

  • Landsberg J, Sands P (2010) Physiological ecology of forest production: Principles, processes and models. Academic Press Elsevier, Burlington

    Google Scholar 

  • Lockaby G, Nagy C, Vose J, et al (2013) Forests and water. In: Wear DN, Greis J (eds) The Southern Forest Futures project: technical report. U.S. Department of Agriculture Forest Service, General technical report SRS-178. Asheville, NC, pp 309–339

  • Mcnab WH, Spetich M, Perry R et al (2014) Climate-induced migration of native tree populations and consequences for forest composition. In: Vose JM, Klepzig K (eds) Climate change adaptation and mitigation management options: a guide for natural resource managers in southern Forest Ecosystems. CRC Press, Boca Raton, pp 307–378

    Google Scholar 

  • Mitchell R, Hiers JK, O’Brien JJ et al (2006) Silviculture that sustains: the nexus between silviculture, frequent prescribed fire, and conservation of biodiversity in longleaf pine forests of the southeastern United States. Can J For Res 36:2724–2736

    Article  Google Scholar 

  • Morin X, Fahse L, Scherer-Lorenzen M, Bugmann H (2011) Tree species richness promotes productivity in temperate forests through strong complementarity between species. Ecol Lett 14:1211–1219

    Article  Google Scholar 

  • Natural Capital Project (2014) InVEST Models. http://www.naturalcapitalproject.org/models/models.html

  • Nelson E, Mendoza G, Regetz J et al (2009) Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales. Front Ecol Environ 7:4–11

    Article  Google Scholar 

  • Newsmaster SG, Bell FW, Roosenboom CR et al (2006) Restoration of floral diversity through plantations on abandoned agricultural land. Can J For Res 36:1218–1235

    Article  Google Scholar 

  • NOAA (2014) National Climatic Data Center. http://www.ncdc.noaa.gov/. Accessed 10 May 2015

  • Norberg J, Urban MC, Vellend M et al (2012) Eco-evolutionary responses of biodiversity to climate change. Nat Clim Change 2:747–751

    Article  Google Scholar 

  • Noss R (1990) Indicators for monitoring biodiversity: a hierarchical approach. Conserv Biol 4:355–364

    Article  Google Scholar 

  • O’Connell BM, LaPoint EB, Turner JA, et al (2014) The forest inventory and analysis database: database description and user guide version 6.0 for phase 2. U.S. Department of Agriculture report, FIA program. http://www.fia.fs.fed.us/library/database-documentation/historic/ver6/FIADB_userguide_6-0_p2_5-6-. Accessed 10 Aug 2015

  • Odeck J (2009) Statistical precision of DEA and Malmquist indices: a bootstrap application to Norwegian grain producers. Omega 37:1007–1017

    Article  Google Scholar 

  • Pawson SM, Brin A, Brockerhoff EG et al (2013) Plantation forests, climate change and biodiversity. Biodivers Conserv 22:1203–1227

    Article  Google Scholar 

  • Peterson DL, Wolken JM, Hollingsworth TN et al (2014) Regional highlights of climate change. In: Peterson DL, Vose JM, Patel-Weynand T (eds) Climate change and United States forests. Springer Science + Business Media, New York, pp 113–148

    Chapter  Google Scholar 

  • PINEMAP (2014) Pine integrated network: education, mitigation and adaptation project. http://www.pinemap.org/. Accessed 17 July 2015

  • Polasky S, Nelson E, Pennington D, Johnson KA (2010) The impact of land-use change on ecosystem services, biodiversity and returns to landowners: a case study in the state of Minnesota. Environ Resour Econ 48:219–242

    Article  Google Scholar 

  • Proença VM, Pereira HM, Guilherme J, Vicente L (2010) Plant and bird diversity in natural forests and in native and exotic plantations in NW Portugal. Acta Oecol 36:219–226

    Article  Google Scholar 

  • Raudsepp-Hearne C, Peterson GD, Bennett EM (2010) Ecosystem service bundles for analyzing tradeoffs in diverse landscapes. Proc Natl Acad Sci USA 107:5242–5247

    Article  CAS  Google Scholar 

  • Rosenzweig M (1995) Species diversity in space and time. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Ryan MG, Harmon ME, Birdsey RA et al (2010) A synthesis of the science on forests and carbon for U.S. forests. Issues Ecol 13:1–16

    Google Scholar 

  • Ryan MG, Vose JM, Hanson PJ et al (2014) Forests processes. In: Peterson DL, Vose JM, Patel-Weynand T (eds) Climate change and United States forests. Springer Science + Business Media, New York, pp 25–54

    Chapter  Google Scholar 

  • Saha S, Kuehne C, Bauhus J (2013) Tree species richness and stand productivity in low-density cluster plantings with oaks (Quercus robur L. and Q. petraea (Mattuschka) Liebl.). Forests 4:650–665

    Article  Google Scholar 

  • Samuelson LJ, Eberhardt TL, Bartkowiak SM, Johnson KH (2013) Relationships between climate, radial growth and wood properties of mature loblolly pine in Hawaii and a northern and southern site in the southeastern United States. For Ecol Manag 310:786–795

    Article  Google Scholar 

  • Sauer J, Abdallah JM (2007) Forest diversity, tobacco production and resource management in Tanzania. For Policy Econ 9:421–439

    Article  Google Scholar 

  • Schultz R (1997) Loblolly pine: the ecology and culture of loblolly pine (Pinus taeda L.). U.S. Department of Agriculture, Forest Service Handbook 713, Washington, DC

    Google Scholar 

  • Schwenk WS, Donovan TM, Keeton WS, Nunery JS (2012) Carbon storage, timber production, and biodiversity: comparing ecosystem services with multi-criteria decision analysis. Ecol Appl 22:1612–1627

    Article  Google Scholar 

  • Skog KE, Mckinley DC, Birdsey RA et al (2014) Managing carbon. In: Peterson DL, Vose JM, Patel-Weynand T (eds) Climate change and United States forests. Springer Science + Business Media, New York, pp 151–182

    Chapter  Google Scholar 

  • Smith W, Miles P, Perry C, Pugh S (2009) Forest resources of the United States, 2007. U.S. Department of Agriculture, Forest Service, General technical report WO-78, Washington, DC. p 336

  • Stern N (2007) The economics of climate change: the Stern review. Cambridge University Press, Cambridge, UK

    Book  Google Scholar 

  • Susaeta A, Carter DR, Adams DC (2014a) Impacts of climate change on economics of forestry and adaptation strategies in the southern United States. J Agric Appl Econ 2:257–272

    Article  Google Scholar 

  • Susaeta A, Carter DR, Adams DC (2014b) Sustainability of forest management under changing climatic conditions in the southern United States: adaptation strategies, economic rents and carbon sequestration. J Environ Manag 139:80–87

    Article  Google Scholar 

  • Teskey RO (2014) Developing scenarios to use in models simulations. PINEMAP Tear 3 annual report March 2013–February 2014. pp 10–11

  • Trani Griep M, Collins B (2013) Wildlife and Forest Communities. In: Wear DN, Greis J (eds) The Southern Forest Futures project: technical report. U.S. Department of Agriculture Forest Service, General technical report SRS-178. Asheville, NC, pp 341–396

  • University of Idaho (2013) Multivariate adaptive constructed analogs (MACA) statistical downscaling method. http://maca.northwestknowledge.net/. Accessed 12 March 2015

  • Upadhyay TP, Shahi C, Leitch M, Pulkki R (2012) An application of data envelopment analysis to investigate the efficiency of lumber industry in northwestern Ontario, Canada. J For Res 23:675–684

    Article  Google Scholar 

  • U.S. Department of Agriculture Forest Service (2014) Forest Inventory and Analysis National Program. www.fia.fs.fed.us. Accessed 18 June 2015

  • Verschuyl J, Riffell S, Miller D, Wigley TB (2011) Biodiversity response to intensive biomass production from forest thinning in North American forests—a meta-analysis. For Ecol Manag 261:221–232

    Article  Google Scholar 

  • Viitala E-J, Hanninen H (1998) Measuring the efficiency of public forestry organizations. For Sci 44:298–307

    Google Scholar 

  • Vuuren DP, Edmonds J, Kainuma M et al (2011) The representative concentration pathways: an overview. Clim Change 109:5–31

    Article  Google Scholar 

  • Wear DN, Greis J (2012) The Southern Forest Futures project: summary report. U.S. Department of Agriculture Forest Service General technical Report SRS-168. Ashville, NC, p 54

  • Wertin TM, Mcguire MA, Teskey RO (2010) The influence of elevated temperature, elevated atmospheric CO2 concentration and water stress on net photosynthesis of loblolly pine (Pinus taeda L.) at northern, central and southern sites in its native range. Glob Change Biol 16:2089–2103

    Article  Google Scholar 

  • Wertin TM, McGuire MA, Teskey RO (2012) Effects of predicted future and current atmospheric temperature and [CO2] and high and low soil moisture on gas exchange and growth of Pinus taeda seedlings at cool and warm sites in the species range. Tree Physiol 32:847–858

    Article  CAS  Google Scholar 

  • Will RE, Narahari NV, Shiver BD, Teskey RO (2005) Effects of planting density on canopy dynamics and stem growth for intensively managed loblolly pine stands. For Ecol Manag 205:29–41

    Article  Google Scholar 

  • Wilson D, Puettmann K (2007) Density management and biodiversity in young Douglas-fir forests: challenges of managing across scales. For Ecol Manage 246:123–134

    Article  Google Scholar 

  • Yang S, Feng J, Dong W, Chou J (2014) Analyses of extreme climate events over china based on CMIP5 historical and future simulations. Adv Atmos Sci 31:1209–1220

    Article  Google Scholar 

Download references

Acknowledgments

The authors acknowledge the funding support through the Pine Integrated Network: Education, Mitigation, and Adaptation Project (PINEMAP), a Coordinated Agricultural Project funded by the USDA National Institute of Food and Agriculture, award #2011-68002-30185.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andres Susaeta.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Susaeta, A., Adams, D.C., Carter, D.R. et al. Climate Change and Ecosystem Services Output Efficiency in Southern Loblolly Pine Forests. Environmental Management 58, 417–430 (2016). https://doi.org/10.1007/s00267-016-0717-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00267-016-0717-z

Keywords

Navigation