Conceptual framework: details

2012-09-05T11:35:30+00:00

Author: Eleni Briassoulis

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1. Aim of the LEDDRA conceptual framework

The principal aims of the LEDDRA conceptual framework are:

to offer a clear and concise presentation of the LEDDRA concept,
to demonstrate how research is organized to address the principal research question: to assess the fit of responses to LEDD and
to provide the basis for the synthesis of research findings.

A parallel aim of the framework is to serve as a general conceptual model for the systematic study of responses to LEDD.

The LEDDRA conceptual framework offers the broad context which coordinates all relevant and important research issues for the study of the socio-ecological fit of responses to LEDD and shows how they relate to one another. It helps identify how research in individual WPs and Tasks fits in the overall search for answers to the principal research question and how it relates to research in other WPs and Tasks. It is important to note that, because of the integrated approach of LEDDRA, research in an individual WP and/or Task may touch on more than one components of the LEDDRA conceptual framework and, thus, necessarily it has to be related to research in other WPs and/or Tasks.

Thus, the LEDDRA conceptual framework constitutes the basis for mapping the research activities undertaken in LEDDRA at all levels of detail and the basis for discussion, refinement, further elaboration of research issues during the course of the project and for the final synthesis of research findings. Eventually, it will show which research questions have been addressed in LEDDRA and which ones remain to be explored.

2. Basic approach and main structure of the LEDDRA conceptual framework

LEDDRA adopts the ecosystem approach and the CAS paradigm for the study of the socio-ecological fit of responses to LEDD (LEDDRA DoW 2010). This implies that (a) an integrated approach to the analysis of responses to LEDD is followed and (b) the study of responses to LEDD – description and explanation – focuses on the complex and multilevel relationships within and among the components of the biophysical and human system that interact within a particular socio-ecological system (SES) over time.

	Figure 1. LEDDRA conceptual framework; structure of the LEDDRA research process
	Figure 2. Schematic representation of a socio-ecological system (SES); the actual response assemblage (ARA) with capitals and critical functions

The LEDDRA conceptual framework comprises four main blocks that correspond to the four main stages of the research process. Stage A concerns the theory and assessment of the SES (or, of the ARA). More specifically, it provides an integrated description and explanation of the current state and of the evolution of the SES over time. Stage B concerns the assessment of system-level properties and of socio-ecological and community resilience. Stage C concerns the assessment and explanation of the fit of responses to LEDD in a SES while Stage D explores the design of Optimal Response Assemblages (ORA) and provides guidance in the form of policy and land management recommendations.

Stage A: Theory and Assessment of the SES (ARA)

The purpose of this stage is to provide a description and an explanation of the evolution and current state of a socio-ecological system (SES). The SES that is described represents essentially the Actual Response Assemblage (ARA) given the broad definition of ‘responses to LEDD’ adopted in LEDDRA. For every major state of the SES over time, the components of the biophysical and the human system (the three capitals), their relationships, the LEDD problems (biophysical and socio-economic aspects), and the responses to LEDD are described and explained. The emphasis is on the characteristics of those components of the three capitals that are important for the maintenance of the critical ecosystem and socio-economic functions (Figure 2). These are detailed in »Research framework.

The rationale underlying the conceptual scheme is as follows:

Human activities i.e. responses to LEDD sensu LEDDRA (including implementation of policies) produce desirable or unwanted environmental and socioeconomic impacts (LEDD)
These impacts modify the ‘capitals’ of the SES; more specifically, certain characteristics of the components of the natural, economic and social capital (Chapter 4)
In their turn, these changes may impact on critical ecosystem, economic and social functions, thus, either reducing or enhancing the ecosystem and human system services provided leading to desirable or unwanted changes in the properties of the SES and its socio-ecological resilience, and causing new rounds (of varying duration) of responses to LEDD

The maintenance of the integrity of these critical functions is essential for the smooth functioning of the system as a whole that secures its ability to deliver ecosystem and human system services. However, not all of these functions are similarly prone to change. According to the CAS literature and the Drylands Development Paradigm, a limited number of slow variables are responsible for bringing the system over the boundaries of its current domain of attraction that leads to degradation phenomena (Gunderson and Holling 2002, Stafford-Smith 2002, Reynolds et al. 2007). In this sense, the task ahead is to identify these slow variables in order to be able to manipulate the system so as to augment the domain of attraction with regard to these variables; in other words, to enhance its resilience. The task of this identification is not trivial. In the context of LEDDRA, it is proposed to proceed by defining the critical components of the natural, social and economic capitals and their characteristics that support the integrity of the functions of the SES under study. Once this is accomplished, the slow variables that affect the maintenance of these capitals can become apparent. A limited suite of these variables will show signs of change and these will be then examined with a view to whether they tend to approach critical thresholds that could destabilize the relevant functions and, through cascading effects, the SES as a whole.

The level of spatial and temporal scale at which the SES is described is discussed in Chapter 4 (LEDDRA methodological framework). The pertinent literature of the last 40+ years, at least, claims that the regional level is the most appropriate for the integrated analysis of a SES and for sustainable development planning and environmental policy making (Roberts 2001, CEC 2001). Nevertheless, the analysis of community-level SES provides deeper insights into the socio-cultural and institutional determinants of LEDD and of responses to LEDD. Thus, LEDDRA examines SES at two focal levels: the regional and the community (local). The analysis at both levels takes into account the links among the components of the biophysical and the human system at lower (local, household) and higher (national, EU, international) levels. Figures 2.2, 2.3, 2.6 and 2.7 do not show these cross-scale linkages for simplicity. The choice of the time frame of reference depends on the particular LEDD problem and the associated environmental and socio-economic impacts. In general, the SES should be described over a considerable time span to produce a satisfactory account of its evolution.

Finally, it is noted that research aims to identify commonalities and major differences among the three land themes (cropland, grazing land, forests/shrubland) that owe to different modes of production that characterize each theme.

Stage B: Assessment of system-level properties and of socio-ecological resilience

The integrated description and explanation of the SES offers the basis for the assessment of the Socio-Ecological Resilience (SER) of a SES. In LEDDRA, socio-ecological resilience is the term reserved for the regional level of analysis while community resilience refers to the local/community level of analysis.
One approach to assessing SER is to consider it as emerging from a hierarchy of properties of the SES where lower level properties shape higher, system-level properties. The assessment of the properties of the SES can be based on an analysis of its characteristics; more particularly, of the relationships among those characteristics of the components of the natural, economic and social capital of a SES that most importantly determine the maintenance of its critical ecosystem and socio-economic functions. These characteristics and their relationships should have been already identified and described in Stage A. Schematically the proposed assessment sequence is as follows:

Characteristics of the components of SES and their linkages
↓
System level properties
↓
Socio-Ecological Resilience (SER)

The contemporary ‘resilience thinking’ school suggests three principal system-level properties that characterize the ability of a SES to cope with various types of endogenous or exogenous disturbances and undergo transitions from one state to another; i.e. that determine their dynamics of change. These are: Resilience, Adaptability and Transformability – RAT (Walker et al., 2006; Folke et al., 2010) – and they are defined as follows:

Resilience: The capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same functions, structure, identity, and feedbacks (Walker et al. 2004)

Adaptability or adaptive capacity: The ability of a social-ecological system to cope with novel situations without losing options for the future (Folke et al. 2002)
Transformability: The capacity to create a fundamentally new system when the existing system is untenable (Walker et al. 2004)

The definition of resilience follows Holling’s (1973) definition of resilience as the amount of disturbance a system can absorb without shifting into an alternate regime. Social-ecological systems exhibit thresholds that, when exceeded, result in changed system feedbacks that lead to changes in function and structure. The system is said to have undergone a regime shift (e. g., Scheffer et al. 2001, Carpenter 2003) that may be reversible, irreversible, or effectively irreversible, i.e., not reversible on time scales of interest to society. The more resilient a system, the larger the disturbance it can absorb without shifting into an alternate regime. The resilience of a SES is a measure of its vulnerability to unexpected or unpredictable shocks. Nevertheless, the relationship between resilience and vulnerability is not straightforward; it is contingent and context-specific as recent analyses suggest (Miller et al. 2010, Gallopin 2006, van der Leeuw 2008).

Adaptability refers to the capacity of the actors in a system to manage resilience. Complex adaptive systems are generally characterized by self-organization without system-level intent or centralized control. Humans, however, are unique in having the capacity for foresight and deliberate action. Therefore, self-organization in complex social-ecological systems is somewhat different from that in ecological or physical systems (Westley et al. 2002). On the one hand, it can be argued that, although the dynamics and direction of change in such systems are influenced by individuals and groups that have intent, the system as a whole does not, as in the case of a market. However, because human actions dominate social-ecological systems, the adaptability of such systems is mainly a function of the individuals and groups managing them. Their actions influence resilience, either intentionally or unintentionally (Berkes et al. 2003). Their capacity to manage resilience with intent determines whether they can successfully avoid shifting into an undesirable system regime or succeed in shifting into a desirable one.

Social-ecological systems can sometimes get trapped in very resilient but undesirable regimes in which adaptation is not an option. Escape from such regimes may require large external interventions or internal restructuring to bring about change (Holling and Gunderson 2002). The transformation of a SES can occur in response to the recognition that past policies and actions have failed, or it can be triggered by a resource crisis, or it can be driven by shifts in social values (Gunderson et al. 1995). Although transformations generate novel system configurations, the pathways and mechanisms that drive transformations are not well understood and are one of the foci of the analysis of the study sites in LEDDRA.

The implications of these properties are schematically depicted in Figure 3.

Resilience and adaptability of a SES are usually treated as positive properties since they allow a SES to persist in its current state. This may be acceptable if, e.g., degradation processes threaten to bring the SES out of balance and eventually to a degraded state. However, a distinction has to be made between (undesirable) forced transitions to a new domain of attraction and intentional transitions in cases where remaining at a particular stability domain is no more possible or desirable. Transformability is exactly what allows a SES to smoothly move to a different stability domain while preserving much of its available capitals and critical functions. In such situations, resilience and adaptability attain a negative connotation causing either a prolonged stay in an unsustainable situation that inevitably ends up to a forced transition resulting in large capital losses or it preserves an undesirable equilibrium, referred to as a “trap”.

Scale issues are also important in this context. It should be taken into account that adaptability and transformability may be different sides of the same coin or, put differently, manifestations of the same process at different levels. Managing resilience under altered conditions may require changes at lower (than the SES under study) levels to cope with change in order to eventually be able to preserve the state of the SES at higher levels.

In addition to the system-level properties, there are several important properties that critically determine the values of the former; in a sense, they can be considered as constituents of the system-level properties. These have to do with the morphology, functioning and output of the SES. Gunderson and Holling (2002) as well as Ostrom, Berkes, Folke and many others mention several properties such as:

Diversity
The potential available for change, a function of the ‘amount’ of capitals available since this determines the range of options possible
The degree of connectedness between internal controlling variables and processes, a measure that reflects the degree of flexibility or rigidity of such controls – i.e., their sensitivity or not to external variation. Connectedness depends on the nature and strength of feedbacks
Modularity
Redundancy
Governance – the mode of governance in a SES greatly affects its resilience and adaptive capacity; ‘good governance’ , in particular, is considered essential for the well-being of a SES (Briassoulis 2010b, Folke et al. 2005, Lebel et al. 2006, Van Assche et al. 2011)
Learning
Social and ecological memory
Novelty, innovation

Alternative ways to operationalize SER and community resilience will be explored guided by the criterion that they must reflect the interlinkages of the natural, social and economic components of a SES.
A complementary approach would be to undertake analysis in the opposite direction. In this case, the higher level properties of a SES (current or historical) could be judged against empirical evidence showing the lack or the availability of the different capacities, e.g. persistence in time in spite of altered external or internal conditions is a strong sign of high resilience, and the exploration of the lower system properties that contributed to this outcome would follow.

Irrespective of assessment approach, multi-dimensional measures of socio-ecological resilience and of community resilience are expected to be developed in the context of LEDDRA.

Stage C: Assessment and explanation of the fit of responses to LEDD

This stage provides the final assessment of the fit of responses to LEDD that have been identified, assessed and explained in the previous stages. This assessment is basically an evaluation of the SER of the SES on the basis of specific evaluation-of-fit criteria.

The procedure followed at this stage comprises the following steps:

Identification of evaluation-of-fit criteria
assessment of the fit of responses to LEDD; i.e. evaluation of SER according to the criteria defined
explanation of the fit of responses.

The identification of evaluation criteria is very important because:

(a) a ‘response’ is rarely a single, identifiable human action that can be isolated and studied individually (hence, the notion of a ‘response assemblage’); a response is multidimensional and multi-component (e.g. soil protection together with water conservation measures, choice of plants, special subsidies, …), a fact that importantly determines its impacts and fit;

(b) the fit of responses is not constant but variable over space, time and issue of concern due to the complexity of SES;

(c) the fit of responses to LEDD depends on the stakeholders’ view of the LEDD problems and their purpose to act on them. Cultural differences are expected to play an important role in assessing the ‘fit of responses to LEDD’. Differences in knowledge, understanding and perception of LEDD problems among scientists, administrators, interest groups and local users that reflect social concerns and priorities may reveal large disparities in the criteria used and, consequently, in the evaluation outcomes, i.e. the assessment of fit of responses to LEDD among these groups.

Alternative sets of ‘evaluation-of-fit’ criteria have to be developed in cooperation with stakeholders drawing on the definition of ‘fit’ (see LEDDRA Glossary) and the preceding discussion. The dimensions along which criteria will be determined need to be defined, such as environmental (fit in an environmental sense), socio-cultural (fit in a socio-cultural sense), economic (fit in an economic sense), and integrated. Differences in sets of criteria depending on the stakeholder group may be explored.

The application of alternative sets of evaluation-of-fit criteria to the multidimensional measures of SER obtained before will obviously produce alternative assessments of the fit of responses to LEDD in a SES. A given ARA may be fit according to some objective(s) but not universally, especially if future uncertainty is taken into account.

The final step will be to provide an integrated explanation of the assessment of fit obtained for each particular group of stakeholders, or evaluation criteria in general, following the CAS and related paradigms.

Stage D: Design of Optimal response Assemblages and Guidance for policy makers and stakeholders

This stage builds on the results of the evaluation of SER, i.e. on the assessment of fit of the SES/ARA, to identify those characteristics of the SES that should be fixed to improve the fit of responses to LEDD for different stakeholder groups. It is expected that certain improvements of the ARA may be commonly accepted by all stakeholder groups. Moreover, fixing the ARA for one stakeholder group may satisfy other stakeholder groups (win-win or partially win-win solutions).

Alternative methodologies to develop Optimal Response Assemblages will be developed. An important element in these methodologies is the specification of alternative future scenarios within which ORAs will materialize. Optimization of a SES/ARA depends on which SES components and their relationships are responsible for any ‘misfit’ observed according to particular stakeholders. It is, thus, impossible to predetermine a suitable optimization approach.

Guidance – in the form of policy and land management recommendations – will be offered for various types of stakeholders depending on their role in a SES and the influence of their actions on the determinants of SER. An important question/issue is whether current management practices and institutional arrangements as well as those proposed are/will be adequate to cope with future, uncertain disturbances that may threaten the current SER.

3. LEDDRA principal research questions

The principal research questions that the study of a SES addresses draw on the LEDDRA conceptual framework. These are summarized as follows:

What is the current state of the SES under study (i.e. the ARA); how did it evolve over time?
What are and what have been the main determinants (driving forces) of the past and the current LEDD issues?
Which human interventions (responses to LEDD sensu LEDDRA) are and have been associated with the past and the current LEDD issues?
How do human interventions (responses to LEDD sensu LEDDRA) and the associated LEDD problems affect and how are they affected by the socio-ecological resilience of the SES?
How did past interventions (responses to LEDD sensu LEDDRA) and the associated LEDD problems affect and how were they affected by the socio-ecological resilience of the SES?
What are the current ‘positive’ responses to LEDD in the SES and which are their main determinants?
How do these ‘positive’ responses to LEDD affect and are affected by the socio-ecological resilience of the SES?
What is the socio-ecological fit of current responses to LEDD for different groups of stakeholders?
What have been past ‘positive’ responses to LEDD and what have been their determinants?
How did these past ‘positive’ responses affect and how were they affected by the socio-ecological resilience of the SES?
What has been the socio-ecological fit of past responses?
What kinds of actions can be taken to improve the current situation, i.e. to design an optimal response assemblage (ORA) according to different groups of stakeholders?

The LEDDRA methodological framework that is presented in »Research framework has been designed to address these questions.

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