Search

There is an important body of literature using multi-criteria distance function methods for the aggregation of a battery of sustainability indicators in order to obtain a composite index. This index is considered to be a proxy of the sustainability goodness of a natural system. Although this approach has been profusely used in the literature, it is not exempt from difficulties and potential pitfalls. Thus, in this paper, a significant number of critical issues have been identified showing different procedures capable of avoiding, or at least of mitigating, the inherent potential pitfalls associated with each one. The recommendations made in the paper could increase the theoretical soundness of the multi-criteria distance function methods when this type of approach is applied in the sustainability field, thus increasing the accuracy and realism of the sustainability measurements obtained. [ABSTRACT FROM AUTHOR]

Cumulative effects assessment (CEA) ― a type of environmental appraisal ― lacks effective methods for modeling cumulative effects, evaluating indicators of ecosystem condition, and exploring the likely outcomes of development scenarios. Random forests are an extension of classification and regression trees, which model response variables by recursive partitioning. Random forests were used to model a series of candidate ecological indicators that described lakes and rivers from a case study watershed (The Muskoka River Watershed, Canada). Suitability of the candidate indicators for use in cumulative effects assessment and watershed monitoring was assessed according to how well they could be predicted from natural habitat features and how sensitive they were to human land-use. The best models explained 75% of the variation in a multivariate descriptor of lake benthic-macroinvertebrate community structure, and 76% of the variation in the conductivity of river water. Similar results were obtained by cross-validation. Several candidate indicators detected a simulated doubling of urban land-use in their catchments, and a few were able to detect a simulated doubling of agricultural land-use. The paper demonstrates that random forests can be used to describe the combined and singular effects of multiple stressors and natural environmental factors, and furthermore, that random forests can be used to evaluate the performance of monitoring indicators. The numerical methods presented are applicable to any ecosystem and indicator type, and therefore represent a step forward for CEA. [ABSTRACT FROM AUTHOR]

One of the most relevant issues in discussion worldwide nowadays is the concept of sustainability. However, sustainability assessment is a difficult task due to the complexity of factors involved in the natural world added to the human interference. In order to assess the sustainability of beef ranching in complex and uncertain tropical environment systems this paper describes a decision support system based on fuzzy rule-approach, the Sustainable Pantanal Ranch (SPR). This tool was built by a set of measurements and indicators integrated by fuzzy logic to evaluate the attributes of the three dimensions of sustainability. Indicators and decision rules, as well as scenario evaluations, were obtained from workshops involving multi-disciplinary team of experts. A Fuzzy Rule-Based System (FRBS) was developed to each attribute, dimension and general index. The essential parts of the FRBS are the knowledge database, rules and the inference engine. The FuzzyGen and WebFuzzy tools were developed to support the FRBS and both showed efficiency and low cost for digital applications. The results of each attribute, dimension and index were presented as radar graphs, showing the individual value (0–10) of each indicator. In the validation process using the WebFuzzy, different combinations of indicators were made for each attribute index to show the corresponding output, and which confirm the feasibility and usability of the tool. [ABSTRACT FROM AUTHOR]

Marine Protected Areas (MPAs), marine areas in which human activities are restricted, are implemented worldwide to protect the marine environment. However, with a large proportion of these MPAs being no more than paper parks, it is important to be able to evaluate MPA success, determined by improvements to biophysical, socio-economic and governance conditions. In this study a systematic literature review was conducted to determine the most frequently used indicators of MPA success. These were then applied to a case study to demonstrate how success can be evaluated. The fifteen most frequently used indicators included species abundance, level of stakeholder participation and the existence of a decision-making and management body. Using the indicator framework with a traffic light system, we demonstrate how an MPA can be evaluated in terms of how well it performs against the indicators using secondary data from the literature. The framework can be used flexibly. For example, where no MPA data currently exist, the framework can be populated by qualitative data provided by local stakeholder knowledge. This system provides a cost-effective and straightforward method for managers and decision-makers to determine the level of success of any MPA and identify areas of weakness. However, given the variety of motivations for MPA establishment, this success needs to be determined in the context of the original management objectives of the MPA with greater weighting being placed on those objectives where appropriate. [ABSTRACT FROM AUTHOR]

By linking iterative learning and knowledge generation with power-sharing, adaptive co-management (ACM) provides a potential solution to resolving complex social-ecological problems. In this paper we evaluate ACM as a mechanism for resolving conservation conflict using a case study in Scotland, where seal and salmon fishery stakeholders have opposing and entrenched objectives. ACM emerged in 2002, successfully resolving this long-standing conflict. Applying evaluation approaches from the literature, in 2011 we interviewed stakeholders to characterise the evolution of ACM, and factors associated with its success over 10 years. In common with other ACM cases, triggers for the process were shifts in slow variables controlling the system (seal and salmon abundance, public perceptions of seal shooting), and exogenous shocks (changes in legal mandates, a seal disease outbreak). Also typical of ACM, three phases of evolution were evident: emerging local leadership preparing the system for change, a policy window of opportunity, and stakeholder partnerships building the resilience of the system. Parameters maintaining ACM were legal mechanisms and structures, legal power held by government, and the willingness of all stakeholders to reach a compromise and experiment with an alternative governance approach. Results highlighted the critical role of government power and support in resolving conservation conflict, which may constrain the extent of local stakeholder-driven ACM. The evaluation also demonstrated how, following perceived success, the trajectory of ACM has shifted to a ‘stakeholder apathy’ phase, with declining leadership, knowledge exchange, stakeholder engagement, and system resilience. We discuss remedial actions required to revive the process, and the importance of long term government resourcing and alternative financing schemes for successful conflict resolution. Based on the results we present a generic indicator framework and participatory method for the longitudinal evaluation of ACM applied to conservation conflict resolution. [ABSTRACT FROM AUTHOR]

The Environmental Performance Index (EPI) is a popular sustainability index. It is a composite index which ranks 180 countries based on their environmental performance in 32 indicators. Using the EPI data and stochastic dominance efficiency methodology, this paper examines the sensitivity to the subjective weights assigned to the indicators and categories of environmental performance. The findings show a remarkable variation in environmental performance based on alternative weights which are selected using Stochastic Dominance criteria. Except for 2020, the environmental health category in EPI gets relatively higher importance in the optimal scenario, and ecosystem vitality gets relatively higher weights in the inferior scenario, suggesting that the environmental health category achievements have been relatively higher for most countries over time. The ranking analysis also shows major variations in country rankings with alternative weights. Two countries, Maldives and Gabon, would have experienced more than 100 position changes in their rankings with alternative weights. Furthermore, 67 countries would have experienced 30 or more position changes in their rankings and 37 countries experienced an EPI score change of more than 50 (out of 100) with alternative weights. Overall, the results illustrate the importance of sensitivity analysis of composite indices to increase reliability and transparency. • Sensitivity of environmental performance index is tested using Stochastic dominance. • Choice of indicators and weights given to indicators dramatically alter performance. • EPI scores with the optimal (inferior) scenario have more (fewer) countries above any score. • 67 countries among 132 countries experience rank reversals more than 30 positions. • 37 countries experienced an EPI score change of more than 50 (out of 100) with alternative weights. [ABSTRACT FROM AUTHOR]

Abstract Decision triggers are defined thresholds in the status of monitored variables that indicate when to undertake management, and avoid undesirable ecosystem change. Decision triggers are frequently recommended to conservation practitioners as a tool to facilitate evidence-based management practices, but there has been limited attention paid to how practitioners are integrating decision triggers into existing monitoring programs. We sought to understand whether conservation practitioners' use of decision triggers was influenced by the type of variables in their monitoring programs. We investigated this question using a practitioner-focused workshop involving a structured discussion and review of eight monitoring programs. Among our case studies, direct measures of biodiversity (e.g. native species) were more commonly monitored, but less likely to be linked to decision triggers (10% with triggers) than measures being used as surrogates (54% with triggers) for program objectives. This was because decision triggers were associated with management of threatening processes, which were often monitored as a surrogate for a biodiversity asset of interest. By contrast, direct measures of biodiversity were more commonly associated with informal decision processes that led to activities such as management reviews or external consultation. Workshop participants were in favor of including more formalized decision triggers in their programs, but were limited by incomplete ecological knowledge, lack of appropriately skilled staff, funding constraints, and/or uncertainty regarding intervention effectiveness. We recommend that practitioners consider including decision triggers for discussion activities (such as external consultation) in their programs as more than just early warning points for future interventions, particularly for direct measures. Decision triggers for discussions should be recognized as a critical feature of monitoring programs where information and operational limitations inhibit the use of decision triggers for interventions. Highlights • There are challenges to integrating decision triggers into existing biodiversity monitoring programs. • Programs most frequently monitor direct measures of biodiversity assets (e.g. native species). • However, decision triggers are most frequently linked with measures of threats, monitored as surrogates for biodiversity. • Many operational barriers prevent practitioners from attaching decision triggers to direct measures. [ABSTRACT FROM AUTHOR]

Sustainable development is being reconsidered as a process with unknown endpoint. Outputs of sustainable urban water systems defined as 'policies, projects, laws, technologies, and consumption and reuse amounts associated with urban water sustainability goals' are therefore being viewed as inadequate monitoring instruments. I propose a new methodology for sustainability monitoring whereby normality of a system is diagnosed through normality of its supporting inputs in lieu of normality of its complex outputs. Supporting inputs are 'intents and behaviors that support system goals'. Supporting inputs follow a principle of self-organization to remain in the norm and behavior zone commonly associated with system goals. This implies that normality of supporting inputs can be inferred from their longitudinally normal or Gaussian distribution that can be explored by significance tests; in particular, the Shapiro-Wilk test which is most powerful for n < 50. We identify fourteen supporting inputs of sustainable urban water systems - such as internet searches, community campaigns, staff training, agent-principal reporting and legislation propositions about water sustainability – and define quantitative indicators for them. The Shapiro-Wilk test and Kolmogorov-Smirnov test (K–S) of these indicators and a subsequent Boxplot outlying examination of non-normal indicators are undertaken in Yazd – a desert city in central Iran with a historic record in water conservation – in the light of its complex wastewater speculation. Qualitative examination of non-normal supporting inputs confirms the ability of our statistical methodology to detect problems in the system. • This paper proposes a new methodology for monitoring sustainability of urban water systems. • Normality of the system is inferred from normality of its supporting inputs. • Supporting inputs are intents and behaviors that support system goals. • Normality of supporting inputs is inferred from their longitudinally normal distribution. • Fourteen supporting inputs and their quantitative indicators are identified for significance tests. [ABSTRACT FROM AUTHOR]