Mediterranean forests have been degraded since the ancient time mainly by overgrazing and forest fires (Quezel & Medail, 2003). As a response to widespread forest loss and degradation, restoration of forest ecosystems is increasingly being implemented in many parts of the world (Lamb et al., 2005; Rey Benayas et al., 2009; Van Andel & Aronson, 2012). In this direction, forest degradation being increasingly considered in global policy processes that deal with biodiversity, climate change, and forest management (Thompson et al., 2013), and it is directly related to human well-being (depletion of water resources, spread of induced flooding, limitation of the forest resources use) (Mercurio, 2010). This is specifically true for two of the most interesting forest native species such as Quercus suber L. and Quercus petraea (Matt.) Liebl.

Moreover, the restoration of the degraded sites should represents one of the major target for the conservation of biological diversity in Mediterranean area. Nevertheless, still today one of the current scientific questions is focused on detecting a “degraded forest” (Holl & Aide, 2011). Assessing forest degradation is a very complex question, first because there is not an accepted definition of “forest degradation” and/or “degraded forest”. In fact, stakeholders differently perceive forest degradation in relation to their different cultural backgrounds (e.g., biodiversity conservation, carbon sequestration, wood production, soil conservation, etc.) (Simula, 2009; Lund, 2009; Sasaki & Putz, 2009; Putz & Redford, 2010; FAO, 2011). The definition proposed by FAO (2001) according to which “Forest degradation is changes within the forest which negatively affect the structure or function of the stand or site, and thereby lower the capacity to supply products and/or services” represents the start point of the present research. Following what stated in this definition, forest degradation must be expressed through indicators able to provide quantitative information, but to be of practical use they need to be easily measured, repeatable, cost-effective and of ecological significance. Lacking a holistic approach, single-indicators are selected to face single aspects. In this way, if “forest degradation” focuses on biological conservation, indicators such as species composition, stand structure and functional processes should be chosen (Larsson, 2001). On the other hand, if “forest degradation” is related to the global change mitigation, indicators should point out the loss of trees and their carbon stocks down (Sazaki et al., 2011). Synthetizing, a comprehensive index able to detect “forest degradation” and to support the prioritization of sites for forest restoration is needed (Wang et al., 2010; Ochoa-Gaona et al., 2010; Orsi et al., 2011; Thompson et al., 2013).

Generally speaking, to guarantee adequate goods and services for future generations and solve many conservation problems, forest policies should be addressed according to three main lines: managing the forest areas sustainably, protecting remnant natural forests with minimal human alteration that provide the baselines for scientific research, and restoring the degraded forest areas. Sustainable Forest Management (SFM) requires methods and approaches that recognize many variables and conflicting objectives and constraints. In more details, requires Decision-Making (DM) approaches that examine trade-offs between often competing/conflicting managing objectives (timber harvesting, biodiversity conservation, recreation, etc.), according to the economic, environmental, and social dimension of sustainability. Multi-Criteria Decision Analysis (MCDA) can support Decision Makers (DMs) in evaluating alternatives by taking into account multiple criteria in an explicit manner. The analysis of the specific literature shows that MCDA is a useful and widely used approach for suggesting solutions in the SFM. More specifically, MCDA methods and procedures have been widely applied over the last three decades in solving forest resource management problems (Ananda & Herath, 2009) and several scholars have previously made a comprehensive review: Mendoza & Martins (2006) reviewed the use of MCDA in natural resource management while with specific reference to the forest planning and management the works of Pukkala (2002), Kangas & Kangas (2005), Diaz-Balteiro & Romero (2008), Ananda & Herath (2009) provide the on-going state of the art. These reviews also highlight that there is an increasingly interest on MCDA by DMs and planners involved in forest planning and management, also outside the scientific community. To deal with numerous and often-conflicting objectives/alternatives, at least two critical issues must be faced in DM problems (Tzeng & Huang, 2011): defining the preference structure expressed by DMs and identifying the correct weights of criteria/alternatives matching their preferences. Over the last 50 years, an extensive literature has proposed several multi-criteria methods and techniques dealing with theoretical and practical issues on DM (Vizzari & Modica, 2013). Among these, the Analytic Hierarchy Process (AHP) (Saaty, 1977; Saaty, 1980) has been proposed to derive the relative criteria/alternatives weights according to the appropriate hierarchical system (Saaty, 1977; Saaty, 1980). Moreover, with specific reference to the objective of the present research, since its first application (Mendoza & Sprouse, 1989), AHP has been widely applied in forest planning and management.

Practitioners appreciate AHP for its simplicity and flexibility, and because it allows relationships between factors – criteria and alternatives – to be established according to the DMs preferences expressed as ordinal language (judgments) and then converted into cardinal numbers. Considering its specific approach, AHP helps to capture both qualitative and quantitative aspects of a decision and provides a powerful yet simple way of weighting criteria, consequently reducing bias in DM. Indeed, most relevant criticism on the AHP concerns the lack of mathematical foundation of the scale used to convert ordinal judgments into cardinal numbers and the resulting limitation caused by this structure (Özcan et al., 2011). The use of a Pairwise Comparison Matrix (PCM) to obtain a ratio scale of measurement both for tangible and intangible factors is another recognized advantage of the AHP. In fact, the PCM effectively allows to overcome the human difficulty in simultaneously evaluating the importance of all the factors included in the evaluation. The AHP does not assume the complete transitivity of DM’s preferences and a certain degree of inconsistency is allowed, which is realistic in most decision scenarios. In this respect, one of the most important advantages is that AHP allows for checking the inconsistencies in judgments provided by experts reducing bias in DM.

In the general framework of MCDA methods applied in defining SFM, the aim of the present research is to propose a transparent, synthetic and adaptive index at stand level – i.e. the Forest Degradation Index (FDI) – focusing on forest ecological functionality. FDI is a holistic index developed through an AHP-MCDA approach and based on representative ecological and silvicultural parameters. Referring to the different nature of data and indicators considered for the FDI implementation, the AHP procedure is currently one of the most popular methods for obtaining criteria weights in MCDA from a large amount of heterogeneous data.

According to the overall priority rating obtained by the AHP, FDI are sensitive mainly to two indicators, FSD and CWD. For example, in SA-4 and SB-4, as it results from the findings, high values of FSD coupled with the absence of NR and with a shallow soil affect the possibilities of success in regeneration dynamics, leading to a final value of FDI, which reaches the lowest values. This dynamic leads to a loss of functionality in agreement with what was found also by Dezi & Magnani (2007), Simula (2009) and FAO (2011). High levels of FDI correspond to high levels of ecological function and therefore a good chance of perpetuation over time. A forest fallen in the FDI-IV class can be defined degraded. 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 (Class IV) (Figure 4).

Forest degradation is an arising topic issue in SFM. However, a rigorous evaluation to define the severity (especially at spatial large scales) (ITTO, 2002) is still lacking, also because of the different evaluations and the complexity characterizing these assessments. Although there are many definitions of forest degradation that converge on the loss of ecosystem services (Simula, 2009), still today there are no largely accepted methods that give operational guidance to help in assessing it.

With specific reference to forest management, MCDA methods have been applied to better meet the many challenges that forest management is facing in evolving towards sustainable management/adaptive management (Kangas & Kangas, 2005; Ananda & Herath, 2009). These techniques can usefully contribute in SFM by facilitating collaborative DM and conflict resolution and a large number of operational experiences can be found in literature. Among these, due to the ease of application coupled with flexibility and transparency in its implementation, applications based on AHP demonstrated an actual proliferation in the last two decades. Using an AHP-MCDA approach it was possible to consider more elements at the same time considering the functionality of a forest ecosystem from an ecological and silvicultural point of view and overcoming the problem of working with individual indicators, which do not permit a complete analysis of the variables that lead to degradation. The AHP has allowed both the interaction than the feedback within the set of variables (internal dependency) and among variables (external dependency). This feedback loop better reflects complex interaction effects in human society, especially when the risk and uncertainty are involved. The methodology has provided a way to combine evaluations and measurements to derive the scaling of the priorities for distribution of the influence of each parameter in the decision.

FDI here presented and discussed after its first application and validation in two Mediterranean forest types, has proved to be a useful tool at stand level in identifying a threshold value below which a forest subjected to a regime of continuous and repeated disturbances loses its ecological functionality and natural resilience, and therefore can be termed as ‘degraded’. Therefore it can be also useful in detecting the causes of degradation and the “tipping point” beyond which processes become irreversible if nothing is done. In addition, there is the possibility that the index can take a double biological meaning: as a Degradation Index (DI) for determining the threshold of ecological functionality and, in contrast, as a Restoration Index (RI) to evaluate increasing levels of functionality. In turn, the FDI assumes the meaning of descriptor of the ecological functionality. Furthermore, through the FDI it is possible re-defining a forest type joining, if necessary, the appropriate adjective “degraded”, thus identifying those which require forest restoration practices. In this direction, FDI can represent a useful tool in defining planning actions leading to an effective SFM.

The proposed index that will be further refined in other forest types applications as well as further monitoring the two study-sites, can be considered advantageous both for its ease of application and the relative simplicity of the surveys to be made for the establishment of each indicator considered in the FDI calculation. 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 in the DM process. Moreover, a WebGIS platform allowing accessing to data and maps of the project through the Web will be provided. One of the most recognized advantages of this methodology is in providing a very useful tool that improves land planning and decision making also by favoring the e-participation of citizen since the earlier stages of the planning process (Pollino & Modica, 2013). In this direction, another development direction will deal with the involvement of local communities in order to improve public participation in forest management and planning.