An index for the assessment of degraded Mediterranean forest ecosystems

  • Giuseppe Modica ‘Mediterranea’ University of Reggio Calabria, Department of Agricultural, Food, and Environmental Sciences. Reggio Calabria.
  • Angelo Merlino University of Tuscia, Department of Agriculture, Forests, Nature and Energy (DAFNE). Viterbo.
  • Francesco Solano University of Tuscia, Department of Agriculture, Forests, Nature and Energy (DAFNE). Viterbo.
  • Roberto Mercurio Italian Society of Forest Restoration (SIRF) c/o University of Tuscia, Department Department of Agriculture, Forests, Nature and Energy (DAFNE). Viterbo.

Abstract

Aim of study: Diagnosing the degradation degree of forest ecosystems is the basis for restoration strategies. However, there is no literature documenting how to quantify the forest degradation degree by using synthetic indicators, also because there is not a widely accepted definition for "forest degradation" and "degraded forest". Although there are many definitions of forest degradation that converge on the loss of ecosystem services, still today there are no largely accepted methods that give operational guidance to help in defining it. In the present research, with the aim to assess the degree of forest degradation, an integrated index - FDI, Forest Degradation Index - was developed.

Area of study: In this first application, the FDI was applied and validated at stand level in two different Mediterranean forest types in two different case studies: Madonie and Nedrodi regional Parks (Sicily, Italy). The first dominated by sessile oak [Quercus petraea (Matt.) Liebl. subsp. austrotyrrhenica Brullo, Guarino & Siracusa], the second dominated by cork oak (Quercus suber L.).

Material and methods: FDI is a synthetic index structured starting from representative and relatively easily detectable parameters. Here, we propose a set of six indicators that should be assessed to determine the forest degradation: Structural Index (SI), Canopy Cover (CC), Natural Regeneration Density (NRD), Focal Species of Degradation (FSD), Coarse Woody Debris (CWD), and Soil Depth (SD). FDI, here proposed and discussed, has been based on a MCDA (Multi-Criteria Decision Analysis) approach using the Analytic Hierarchy Process (AHP) technique, and implemented in order to contribute in finding simple indicators useful for forest restoration purposes that have an eco-functional basis.

Main results: An integrated index of forest degradation has been defined. FDI values are comprised in the closed interval [0, 10], ranging from class I (Higher ecological functionality) to class IV (Lower ecological functionality). A forest fallen in the FDI-IV class can be defined degraded. In this first application, degradation occurs in SA-4 and in SB-4 where the lowest values (qualitative and quantitative) of the indicators were recorded and the FDI reach the minimum value.

Research highlights: FDI has proved to be a useful tool at stand level in identifying a threshold value below which a forest can be termed as ‘degraded’. In turn, FDI assumes the meaning of descriptor of the ecological functionality. Future development of the FDI will provide an extension of the application at landscape scale exploiting the potential advantages in coupling MCDA and GIS (Geographical Information Systems) techniques.

Keywords: Forest Degradation Index (FDI); Sustainable Forest Management (SFM); Mediterranean Forest Landscape; Multi-Criteria Decision Analysis (MCDA) approach; Analytic Hierarchy Process (AHP). 

Downloads

Download data is not yet available.

Author Biographies

Giuseppe Modica, ‘Mediterranea’ University of Reggio Calabria, Department of Agricultural, Food, and Environmental Sciences. Reggio Calabria.
Department of Agraria
Angelo Merlino, University of Tuscia, Department of Agriculture, Forests, Nature and Energy (DAFNE). Viterbo.
Department DAFNE
Francesco Solano, University of Tuscia, Department of Agriculture, Forests, Nature and Energy (DAFNE). Viterbo.
Department DAFNE

References

References

Ádám R, Ódor P, Bölöni J, 2013. The effects of stand characteristics on the understory vegetation in Quercus petraea and Q. cerris dominated forests. Community Ecology 141: 101-109. http://dx.doi.org/10.1556/ComEc.14.2013.1.11

Agrimi M, Ciancio O, Portoghesi L, Pozzoli R, 1991. I querceti di cerro e farnetto di macchia grande di Manziana: struttura, trattamento e gestione. Cellul e Cart 5: 25-49.

Ajbilou R., Marañón T., Arroyo J, 2006. Ecological and biogeographical analyses of Mediterranean forests of northern Morocco. Acta Oecologica 29: 104–113. http://dx.doi.org/10.1016/j.actao.2005.08.006

Ananda J, Herath G, 2009. A critical review of multi-criteria decision making methods with special reference to forest management and planning. Ecol Econ 68: 2535–2548. http://dx.doi.org/10.1016/j.ecolecon.2009.05.010

Aronson J, Pereira JS, Pausas JG, 2009. Cork Oak Woodlands on the Edge: ecology, adaptive management and restoration. Island Press, Washington, D.C. USA. 315 pp.

Barbeito I, Cañellas I, Montes F, 2009. Evaluating the behaviour of vertical structure indices in Scots pine forests. Ann For Sci 66: 710–710. http://dx.doi.org/10.1051/forest/2009056

Barreca L, Marziliano P, Menguzzato G, Scuderi A, 2010. Stand structure and dead wood characterization in cork forest of Calabria region southern Italy. Forest@ 7: 158–168. http://dx.doi.org/10.3832/efor0628-007

Bergès L, Balandier P, 2009. Revisiting the use of soil water budget assessment to predict site productivity of sessile oak (Quercus petraea Liebl.) in the perspective of climate change. Eur J For Res 129: 199–208. http://dx.doi.org/10.1007/s10342-009-0315-1

Bergès L, Chevalier R, Dumas Y, Franc A, Gilbert JM, 2005. Sessile oak (Quercus petraea Liebl.) site index variations in relation to climate, topography and soil in even-aged high-forest stands in northern France. Ann For Sci 62: 391–402. http://dx.doi.org/10.1051/forest:2005035

Braun-Blanquet, J. 1964. Pflanzensoziologie. Grundzügeder Vegetationskunde. Ed. 3. Springer Verlag, Wien, AU. 865 pp.

Brullo S, 1984. Contributo alla conoscenza della vegetazione delle Madonie Sicilia Settentrionale. Boll Acc Gioenia Sci Nat 16: 351–420.

Brullo S, Scelsi F, Siracusa G, Spampinato G, 1999. Syntaxonomical and chorological considerations on the deciduous oak forest from Sicily and Calabria. Monti e Boschi 50: 16–29.

Campbell GS, 1985. Soil physics with BASIC: Transport models for soil-plant systems. Developments in Soil Science vol. 14. Elsevier, Amsterdam, New York, USA. 149 pp.

Carvalho JPF, 2011. Composition and structure of natural mixed-oak stands in northern and central Portugal. For Ecol Manage 262: 1928–1937.

Colles A, Liow LH, Prinzing A, 2009. Are specialists at risk under environmental change? Neoecological, paleoecological and phylogenetic approaches. Ecology Letters 12: 849–863. http://dx.doi.org/10.1111/j.1461-0248.2009.01336.x

Dezi S, Magnani F, 2007. Effects of soil characteristics on functionality and growth of forest stands: a sensitivity analysis of the model 3-PG. For - RivSelvic Ed Ecol For 4: 298–309.

Diaz-Balteiro L, Romero C, 2008. Making forestry decisions with multiple criteria: A review and an assessment. For Ecol Manage. 255, 3222–3241.

FAO, Food and Agriculture Organization of the United Nations, 2001. Global Forest Resources Assessment 2000. Main Report. FAO Forestry Paper 140, Rome, Italy.

FAO, Food and Agriculture Organization of the United Nations, 2011. Assessing forest degradation - Towards the development of globally applicable guidelines. Forest Resource Assessment Working paper 177, Rome, Italy.

Forman E, Peniwati K, 1998. Aggregating individual judgments and priorities with the analytic hierarchy process. Eur J Oper Res 108: 165–169. http://dx.doi.org/10.1016/S0377-2217(97)00244-0

Holl KD, Aide TM, 2011. When and where to actively restore ecosystems? Forest Ecology and Management 261: 1558–1563. http://dx.doi.org/10.1016/j.foreco.2010.07.004

Humphrey JW, Sippola AL, Lempérière G, Dodelin B, Alexander KNA, Butler JE, 2004. Deadwood as an indicator of biodiversity in European forests: from theory to operational guidance. In: Monitoring and Indicators of Forest Biodiversity in Europe – From Ideas to Operationality. EFI Proceedings n. 51 (Marchetti M, ed). pp: 193–206.

ITTO International Tropical Timber Organization, 2002. ITTO guidelines for the restoration, management and rehabilitation of degraded and secondary tropical forests. Policy Development Series 13, 86 pp.

Kangas J, Kangas A, 2005. Multiple criteria decision support in forest management - the approach, methods applied, and experiences gained. For Ecol Manage 207: 133–143.

Kelly DL, 2002. The regeneration of Quercus petraea (sessile oak) in southwest Ireland: a 25-year experimental study. For Ecol and Manage, 166: 207–226.

Kimmins JP, 1997. Biodiversity and its relationship to ecosystem health and integrity. For Chron, 73: 229–232.

Lamb D, Erskine PD, Parrotta JA, 2005. Restoration of Degraded Tropical Forest Landscapes. Science 310:(5754) 1628–1632. http://dx.doi.org/10.1126/science.1111773

Larsson TB, 2001. Biodiversity evaluation tools for European forests. Ecological Bulletins, Vol. 50. Oxford, UK. Blackwell Science.

Latham PA, Zuuring HR, Coble DW, 1998. A method for quantifying vertical forest structure. For EcolManage 104: 157–170.

Lentini F, Vezzani L, 1974. Carta geologica delle Madonie Sicilia centro-settentrionale alla scala 1:50.000. L.A.C., Firenze.

Ligot G, Balandier P, Fayolle A, Lejeune P, Claessens H, 2013. Height competition between Quercus petraea and Fagus sylvatica natural regeneration in mixed and uneven-aged stands. For Ecol Manage, 304: 391–398.

Lindenmayer DB, Cunningham RB, Donnelly CF, Lesslie R, 2002a. On the use of landscape surrogates as ecological indicators in fragmented forests. For Ecol Manage, 159: 203–216.

Lindenmayer DB, Manning AD, Smith PL, Possingham HP, Fischer J, Oliver I, McCarthy MA 2002b. The Focal-Species Approach and Landscape Restoration: a Critique. Conservation Biology, 16: 338–345. http://dx.doi.org/10.1046/j.1523-1739.2002.00450.x

Lund GH, 2009. What is a degraded forest? Forest Information Services. Gainesville, VA, USA.

Macharis C, Springael J, De Brucker K, Verbeke A, 2004. PROMETHEE and AHP: The design of operational synergies in multicriteria analysis. Eur J Oper Res, 153: 307–317. http://dx.doi.org/10.1016/S0377-2217(03)00153-X

Manning AD, Cunningham RB, Lindenmayer DB, 2013. Bringing forward the benefits of coarse woody debris in ecosystem recovery under different levels of grazing and vegetation density. Biol Conserv, 157: 204–214. http://dx.doi.org/10.1016/j.biocon.2012.06.028

McComb W, Lindenmayer D, 2001. Dying, dead, and down trees. Maint. Biodivers. For. Ecosyst., Malcom L. Cambridge University Press, Cambridge, pp. 335–372.

McElhinny C, Gibbons P, Brack C, Bauhus J, 2005. Forest and woodland stand structural complexity: Its definition and measurement. For Ecol Manage, 218: 1–24.

MCPFE, 2007. State of Europe's forests 2007-The MCPFE report on sustainable forest management in Europe. Liaison Unit Warsaw. 263 pp.

Mendoza GA, Martins H, 2006. Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms. For Ecol Manage, 230: 1–22.

Mendoza GA, Sprouse W, 1989. Forest planning and decision making under fuzzy environments: an overview and illustration. For Sci, 35: 481–502.

Mercurio R, 2010. Restauro della foresta mediterranea. Clueb, Bologna (Italy), 368 pp.

Ochoa-Gaona S, Kampichler C, de Jong BHJ, Hernández S, Geissen V, Huerta E, 2010. A multi-criterion index for the evaluation of local tropical forest conditions in Mexico. For Ecol Manage 260: 618–627.

Orsi F, Geneletti D, Newton AC, 2011. Towards a common set of criteria and indicators to identify forest restoration priorities: An expert panel-based approach. Ecol Indic, 11: 337–347. http://dx.doi.org/10.1016/j.ecolind.2010.06.001

Özcan T, Çelebi N, Esnaf Ş, 2011. Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem. Expert Syst Appl, 38: 9773–9779. http://dx.doi.org/10.1016/j.eswa.2011.02.022

Petritan AM, Biris IA, Merce O, Turcu DO, Petritan IC, 2012. Structure and diversity of a natural temperate sessile oak (Quercus petraea L.) – European Beech (Fagus sylvatica L.) forest. For Ecol Manage, 280: 140–149.

Pollino M, Modica G, 2013. Free Web Mapping Tools to Characterise Landscape Dynamics and to Favour e-Participation. In: Murgante B, Misra S, Carlini M, et al. eds ICCSA 2013, Part III. LNCS, vol. 7973. Springer, Berlin, Heidelberg, pp 566–581. http://dx.doi.org/10.1007/978-3-642-39646-5_41

Portoghesi L, Agrimi M, Bollati S, Corona P, Ferrari B, Lamonaca A, Plutino M, 2005. Observations on a Turkey oak (Quercus cerris L.) forest and hypothesis of silvicultural treatment aiming at the diversification of stand structure and composition. Ital For e Mont, 4: 505–519.

Pukkala T, 2002. Multi-objective Forest Planning. Kluwer Academic Publishers. Springer Netherlands, Dordrecht. http://dx.doi.org/10.1007/978-94-015-9906-1

Putz FE, Redford KH, 2010. The Importance of Defining "Forest": Tropical Forest Degradation, Deforestation, Long-term Phase Shifts, and Further Transitions: Importance of Defining "Forest". Biotropica, 42: 10–20. http://dx.doi.org/10.1111/j.1744-7429.2009.00567.x

Quézel P, Médail F, 2003. Ecologie et biogéographie des forêts du bassinméditerranéen. Elsevier, Paris, 571 pp.

Rey Benayas JM, Newton AC, Diaz A, Bullock JM, 2009. Enhancement of biodiversity and ecosystem services by ecological restoration: a meta-analysis. Science, 325: 1121–4. http://dx.doi.org/10.1126/science.1172460

Rivas-Martınez S, 2008. Global bioclimatics Clasificaciòn Bioclimatica de la Tierra, version01-12-2008. Available in http://www.globalbioclimatics.org/book/bioc/global_bioclimatics-2008_00.htm.

Rives J, Fernandez-Rodriguez I, Rieradevall J, Gabarrell X, 2012. Environmental analysis of raw cork extraction in cork oak forests in southern Europe Catalonia – Spain. Journal of Environmental Management, 110: 236–245. http://dx.doi.org/10.1016/j.jenvman.2012.06.024

Romanyà J, Vallejo V, 2004. Productivity of Pinus radiata plantations in Spain in response to climate and soil. For Ecol Manage, 195: 177–189.

Saaty TL, 1977. A scaling method for priorities in hierarchical structures. J Math Psychol, 15: 234–281. http://dx.doi.org/10.1016/0022-2496(77)90033-5

Saaty TL, 1980. The analytic hierarchy process: planning, priority setting, resource allocation. McGraw-Hill International Book Co, New York.

Saaty TL, 2013. On the Measurement of Intangibles. A Principal Eigenvector Approach to Relative Measurement Derived from Paired Comparisons. Not Am Math Soc, 60, 192. http://dx.doi.org/10.1090/noti944

Saaty TL, Shang JS, 2011. An innovative orders-of-magnitude approach to AHP-based mutli-criteria decision making: Prioritizing divergent intangible humane acts. Eur J Oper Res, 214, 703–715. http://dx.doi.org/10.1016/j.ejor.2011.05.019

Saaty TL, Vargas LG, 2011. The possibility of group choice: pairwise comparisons and merging functions. Soc Choice Welf, 38: 481–496. http://dx.doi.org/10.1007/s00355-011-0541-6

Sasaki N, Asner GP, Knorr W, Durst PB, Priyadi HR, Putz FE, 2011. Approaches to classifying and restoring degraded tropical forests for the anticipated REDD+ climate change mitigation mechanism. iForest - Biogeosciences and Forestry, 4: 1–6.

Sasaki N, Putz FE, 2009. Critical need for new definitions of "forest" and "forest degradation" in global climate change agreements. Conservation Letters, 2: 226–232. http://dx.doi.org/10.1111/j.1755-263X.2009.00067.x

Schnitzler A, Borlea F, 1998. Lessons from natural forests as keys for sustainable management and improvement of naturalness in managed broadleaved forests. For Ecol Manage, 109: 293–303.

Simula M, 2009. Towards defining forest degradation: comparative analysis of existing definitions. Forest Resources Assessment. FAO Rome. Working Paper 154.

Soil Survey Staff, 1999. Soil Taxonomy. USDA-NRCS Agric Handb n 436.

Terborgh J, Estes JA, 2010. Trophic cascades: predators, prey, and the changing dynamics of nature. Island Press, Washington [DC], 488pp.

Thompson ID, Guariguata MR, Okabe K, Bahamondez R, Nasi R, Heymell V, Sabogal C, 2013. An Operational Framework for Defining and Monitoring Forest Degradation. Ecol Soc 182, 20. http://dx.doi.org/10.5751/es-05443-180220

Tzeng GH, Huang J-J, 2011. Multiple attribute decision making: methods and applications. CRC Press, Boca Raton, FL.

Vallauri D, 2005. Le Bois dit mort, une lacune des forêts en France et en Europe. Bois mort à cavités, Tec & Doc. Lavoisierre, Paris, pp 9–17.

Van Andel J, Aronson J, 2012. Restoration Ecology: The New Frontier. Second edition. Wiley- Blackwell, Oxford, UK. http://dx.doi.org/10.1002/9781118223130

Van Wagner C, 1968. The line intersect method in forest fuel sampling. For Sci, 14: 26–27.

Vizzari M, Modica G, 2013. Environmental effectiveness of swine sewage management: a multicriteria AHP-based model for a reliable quick assessment. Environ Manage, 52(4): 1023-1039. http://dx.doi.org/10.1007/s00267-013-0149-y

Wang Z, Daun C, Yuan L, Rao J, Zhou Z, Li J, Yang C, Xu W, 2010. Assessment of the restoration of a degraded semi-humid evergreen broadleaf forest ecosystem by combined single-indicator and comprehensive model method. Ecol Eng, 36: 757–767. http://dx.doi.org/10.1016/j.ecoleng.2010.01.006

WDNR, 2011. Forest Soil Productivity. In: Wisconsin Forest Management Guidelines. WNDR, Madison, Wisconsin, 14 pp.

Wijdeven SMJ, 2004. Stand dynamics in Fontainebleu. Dynamics in beech forest structure and composition over 17 years in La Tillaie forest reserve, Fontainebleu, France. Aterra-rapport 1124.

Zhou L, Dai L, Gu H, Zhong L, 2007. Review on the decomposition and influence factors of coarse woody debris in forest ecosystem. J For Res, 18: 48–54. http://dx.doi.org/10.1007/s11676-007-0009-9

Published
2015-12-03
How to Cite
Modica, G., Merlino, A., Solano, F., & Mercurio, R. (2015). An index for the assessment of degraded Mediterranean forest ecosystems. Forest Systems, 24(3), e037. https://doi.org/10.5424/fs/2015243-07855
Section
Research Articles