Introduction
A plethora of international and national organizations have recognized that environmental and socio-economic indicators are playing an increasingly important role in supporting development policies for combating desertification. The necessity of elaborating indicators is one of the priorities identified by the United Nations Convention to Combat Desertification (UNCCD). The Convention has recognize the need for using indicators as the appropriate tool to provide operational support to a wide range of activities such as assessing and mapping the extent of desertification, as well as determining the causes, quantifying the impacts, justifying expenditure for mitigation measures and monitoring the efficiency of the measures undertaken. Furthermore, the implementation of Ten Year Strategy Plan for Combating Desertification formulated in COP8 (Madrid, 2007) has adopted specific indicators for assessing the performance and the impacts for the implementation of the Convention outcomes. In this context, the necessity for identifying a series of indicators of desertification based on scientific criteria in order to guarantee a close and real relationship between the indicator and the state or trend that it represents is more than evident.
The identification, evaluation and the effective use of indicators requires a series of characteristics that have been proposed by various authors (Stein et al., 2001). In 2001 the DESERTLINKS project was set up to assist the National Action Plans of the Annex IV countries with their indicator needs and this resulted in the state-of-the art DIS4ME indicator system that can be consulted on line by stakeholders. One core question about indicators is their feasibility and usefulness. The most appropriate indicator is not the one that provides the best information about the state and future trends for desertification, but the indicator that takes into account the available information and knowledge under low cost. For the identification and evaluation of indicators a series of characteristics have been proposed by various authors (Riley, 2001; Stein et al., 2001). The selected indicators have to be: (a) objectively and scientifically measurable, (b) preferentially quantitative, (c) easy and cost-effective to be measured, (d) sensitive to environmental changes, (e) simple in concept and accessible to both specialists and land managers, and (f) able to support policy decisions.
Several descriptions and definitions of the term "indicator" have been given by various agencies. The European Environmental Agency (EEA) has considered that an indicator can be defined as a parameter or value derived from parameters, which provides information about a phenomenon (OECD, 1993; EEA, 1998). In this essence, indicators should not be confused with raw data, from which they are derived. Indicators are quantified information which helps to explain how things are changing over time and space for decision making (EEA, 1998). Indicators generally simplify the reality in order to make complex phenomena quantifiable, so that information can be communicated (Department of Environment, UK, 1996; EEA, 1998). It should be point out that a complex process, such as soil erosion, can not be described using a single indicator but several indicators would be necessary, even if not many, but organized into a precise set. In particular, an environmental indicator is a parameter, which provides information about the situation or trends in the state of environment, in the human activities that affect or are affected by the environment, or about relationships among such variables (USA EPA, 1995; EEA, 1998).
A significant number of authors (O' Connor, 1994; Pieri et al., 1995; SCOPE, 1995; Dumanski & Pieri, 1996) considered that classification of indicators must take into account the linkages among; (a) pressures exerted on the environment by human activities, (b) changes in quality of the environmental components, and (c) societal responses to these changes that can be a useful and valuable tool for land-users and policy makers. In this sense, the DPSIR framework (Driving forces, Pressure, State, Impact, and Response) has been proposed (Fig. 1). In this scheme indicators can be briefly delineated as a chain reaction process starting from a developmental effort of natural resources, which applies Pressures and driving forces on the system, changing consequently the State of the system. Such a change produces Impacts, which leads to Responses that by a feed back loop interact with the Driving forces, the Pressures, the State and the Impacts. In this regard, the policy makers can have information for all the steps in the presented framework.
Fig. 1. DPSIR framework for system conditions used for classifying indicators (EEA, in Gentile, 1998).
In this context, driving forces indicators may delineate the economic, social and demographic conditions in a given time frame of a certain local. Such indicators also present the resulting changes in production, life styles and consumption. In this regard, the principal driving forces are population growth and the changes in economic and social modes. Such driving forces are creating the corresponding changes in consumption and production. Thus, according to the DPSIR chain these driving forces are applying pressure to the environment.
Pressure indicators usually express changes in the use of natural resources (water, land, minerals), biological and natural agents, emissions etc. Therefore, the pressures applied by the economic and social frame and practices to the physical system are resulting to the induced changes in the system elements.
State indicators demarcate the status of various parameters in a given local situation. They may present biological parameters (wildlife resources, etc.), chemical parameters (nitrogen, phosphorous concentrations in the soil or in water bodies etc.), or the quality and quantity of natural parameters (rain, temperature etc.).
Impacts indicators are describing the impacts provoked by the changes of the state of the system. Impacts are generated on resources availability, biodiversity, economic relationships, social functions etc. The impacts generate the willing of the people to face the problem by responding with certain measures.
Responses indicators are associated with and describe applied measures by societal groups or institutional organizations to confront, overcome, predict and prevent, compensate and adapt to the transformations of the state of the system. In addition responses indicators are delineating policy measures to preserve certain desirable system features.
In this project indicators have been considered in such a general framework and classified further to be easily used by the various stakeholders in the following categories: (a) physical and ecological environment including climate, soil, water, vegetation, water runoff, fires; (b) economics including agriculture, cultivation, husbandry, land management, land use, water use, tourism; (c) society; and (d) infrastructure. Finally, the objectives of this WP are to:
- Define a practical number of indicators based on a shortlist of indicators available from literature, previous and ongoing research programs.
- Document and develop a harmonized data base of indicators used or being used by different parties in the selected study areas by conducting field surveys on prevailing land use types affecting desertification in Mediterranean locales.
- Compare and link indicators and land management practices among the various studied hot study sites.
The data of the indicators defined in each study site are presented in the deliverable 2.1.3 in excel form, while the detailed description of the various indicators applied in the various land use types in each study area is presented in the current deliverable.
All in all, in deliverable 2.1.3, data for the various indicators have been collected from the following 17 study sites located along the Mediterranean Europe, Eastern Europe, Africa, Asia, and Latin America, namely:
- Rendina Basin Basilicata-Italy
- Nestos Basin Maggana-Greece
- Crete-Greece
- Mação- Portugal
- Gois - Portugal
- Guadalentin Basin Murcia-Spain
- Konya Karapinar plain-Turkey
- Eskisehir Plain, Turkey
- Novij Saratov-Russia
- Djanybek-Russia
- Zeuss Koutine-Tunisia
- Boteti Area-Botswana
- Santiago Island-Cape Verde
- Mamora Sehoul-Morocco
- Loess Plateau-China
- Secano Interior-Chile
- Cointzio catchment-Mexico.
In the following chapter a detailed analysis is undertaken of the identified in the study sites 72 indicators.
