Trade-offs in the use of direct and indirect indicators of ecosystem degradation for risk assessment

Ecosystem risk assessments estimate the likelihood of major transformations (ecosystem collapse) over a specified time frame. They require an understanding of the biotic and abiotic processes that drive declines. Relative Severity and Extent of Decline quantify essential dimensions of ecosystem degradation as part of the International Union for the Conservation of Nature (IUCN) Red List of Ecosystems risk assessment protocol. These flexible and powerful concepts are operationalised through ecosystem-specific indicators of functional decline. Here, we examine trade-offs in risk assessment between direct, yet data-demanding indicators and indirect indicators that are more widely applicable with global data sets. Using a case study of multiple tropical glacier ecosystems, we compared estimates of risk based on a direct indicator of functional decline (ice mass) with those based on an indirect indicator (bioclimatic suitability). The direct estimate of Relative Severity was based on the projected changes in ice mass using a glacier ice mass balance and dynamics model, while the indirect estimate was calculated from the expected changes in suitability based on a correlative habitat suitability model parameterised with current occurrence records. For reference, we calculated probability of ecosystem collapse from simulations of the ice mass balance and dynamics model. We found that the indirect indicator systematically underestimated risks of ecosystem collapse compared to the direct indicator and returned a different rank order of risks across glaciers due to prominent discrepancies in some units. Small and isolated glaciers located outside the tropical Andes are uniformly exposed to high levels of degradation and have high probabilities of collapse before 2080, whereas tropical Andean glaciers exhibit different rates of degradation, but are expected to undergo very severe degradation before 2100. For these larger units a detailed analysis of spatial differences in future projections could inform regional and local strategies for future monitoring, management and conservation action that can benefit people and nature. Evaluating Relative Severity and Extent of Decline over time and with different ecosystem-specific indicators allowed us to describe trends across a group of functionally similar ecosystem types and compare their performance in assessment units of different size and risk of collapse. The methods could be applied to other ice or snow-dependent ecosystems, while the case study should be instructive for development of risk indicators in many other ecosystem types

The Effect of Krill Oil Supplementation on Exercise Performance and Markers of Immune Function

Date of Acceptance: 08/09/2015 Acknowledgments We thank the technical support of the Institute of Medical Sciences Musculoskeletal Programme and the Iain Fraser Cytometry Centre.Peer reviewedPublisher PD

Subtropical-temperate forested wetlands of coastal south-eastern Australia – an analysis of vegetation data to support ecosystem risk assessment at regional, national and global scales

Forested wetlands occurring on fluvial sediments are among the most threatened ecosystems in south-east Australia. The first quantitative diagnosis of forested wetland types in NSW was completed in 2005. Since then, there has been a three-fold increase in survey data on coastal floodplains, vegetation classification systems have been developed in New South Wales, Queensland and Victoria, and methods for the assessment of ecosystem conservation risks have been adopted by the International Union for the Conservation of Nature (IUCN). Aims. To ensure an evidence base that can support conservation decisions and national conservation assessments, there is a need to review and update the classification of forested wetlands and integrate classification schemes across jurisdictions. Methods. We evaluated the efficacy of a multi-stage clustering strategy, applied to data from different sources with largely unknown methodological idiosyncrasies, to retrieve ecologically meaningful clusters. We assessed the veracity and robustness of the 2005 classification of forest wetlands as a framework for national risk assessments over an expanded range. Key results. We derived a quantitative, cross- jurisdictional classification of forested wetlands based on a synthesis of 5173 plot samples drawn from three states and identified the status of our units in relation to IUCN's Global Ecosystem Typology. Conclusions. Our analyses support the retention of the five legacy types which are the basis for threatened ecosystem listings under the NSW Biodiversity Conservation Act 2016 and Commonwealth Environment Protection and Biodiversity Conservation Act 1999. Implications. Our results will support revised assessments of current listings and facilitate their integration at state, national and global scale

Morphological and volumetrical feature-based designer's intents

Features are claimed to be the carriers of Designer's Intents (DI's) which are seldom defined, identified and represented in Design-by-Features (DbF) systems. This paper presents an interpretation of Designer's Intents for the Feature-based Modelling (FBM) context and emphasis will be given to the Morphological Functional and Volumetrical Geometrical DI’s which express the basic behaviour of a DbF system. DI's are also an important part of a validation system capable of reasoning about the semantics of using features in a particular design. If features' characterisations via DI's are well established and measurable the representation could be assessed as to its conformity with feature's meaning and their semantics could be validated. It is considered that the better Designer's Intents are understood and specified, the more useful Feature-based Modelling will become

Feature-based interaction: an identification and classification methodology

Features are an established means of adding non-geometric information and extra geometric semantics to conventional computer aided design (CAD) systems. For some time it has been realized that, although feature-based modelling is necessary for the next generation of integrated design and manufacturing systems, the inherent feature interactions pose a difficulty in representing and manipulating geometric designs. This paper presents a structured geometric spatial feature interaction identification method based on a broad multilevel classification. Feature interaction definitions and classifications have been surveyed and it is evident that, although many feature interaction classifications have been proposed, there is a lack of a general framework. The classification presented here encompasses existing feature interference cases found in the literature and defines a singular framework that leads to a general classification structure. The framework is presented and applied at three different levels and each interaction case is defined by feature parameters rather than just geometric entities. The restrictions often found in other research concerning contact:non-contact and concave:convex situations are avoided. The resulting classification is easy to understand and implement because it uses simple rules based on commonly available Boolean operators. Finally, an example component is presented and the advantages, uses and applications of the classification scheme are discussed

Structured multi-level feature interaction identification

Features are an established means of adding non-geometric information and extra geometric semantics to conventional CAD systems. It has been already realised that although feature-based modelling is necessary for the next generation of integrated design and manufacturing systems, inherent feature interactions pose a difficulty in representing and manipulating geometric design. This paper presents a structured multi-level geometric feature interaction classification scheme implemented within a Design-by Feature (DbF) system for representation validation analysis. Various feature interaction definitions and classification methods are first surveyed. The elements and the tests used for the identification process are presented. The classification encompasses existing feature interference cases found in the literature, uses a clear structure for the classification and, is applied at three different levels

Feature modelling: a validation methodology and its evaluation

Geometric modelling techniques for computer-aided design are provided with formal validation methods to ensure that a valid model is made available to applications such as interference checking. A natural and popular extension to geometric modelling is to group geometric entities into features that provide some extra meaning for one or more aspects of design or manufacture. These extra meanings are typically loosely formulated, in which case it is not possible to validate the feature-based model to ensure that it provides a correct representation for a downstream activity such as process planning. This paper presents a methodology used to validate the feature-based representation which is based on the capture of designer’s intents related to functional, relational and volumetric aspects of the component geometry. The feature-based validation method has itself been validated through its application to a series of test parts which have been either drawn from the literature or created to demonstrate particular aspects. It is shown that the prototype system that has been developed is indeed capable of meaningful feature-based model validation and additionally provides extensive information that is potentially useful to a range of engineering and manufacturing analysis activities

Operating invalid feature-based models

A valid feature-based representation is one where instantiated features in a model agree with the features' expected behaviours, available and defined as a library. Invalid feature-based models happen when manipulations on the model change the interrelationship among features therefore changing the behaviour of an instantiated feature. Freedom of manipulation is an intrinsic advantage of using a CAD system and it is taken for granted. However, even the most basic manipulation, such as "adding" a feature to a model, is capable of disrupting the validity of a representation. Furthermore, invalid models could compromise the usefulness of any following analysis on it. Thus, identifying means to operate on an invalid model to make it valid, through "revalidation operations", is a necessity in Feature-based CAD systems. It allows conventional CAD systems (usually more preoccupied with representing and producing feature-like shapes within a geometrically constrained environment) to interface more easily for example with CAPP systems (usually more preoccupied with planning problems than with the correctness of the representation). The framework of a feature-based validation system, called FRIEND (Feature-based Reasoning system for Intent-driven Engineering Design), and a discussion on representation validity analysis is presented with emphasis on identifying and discussing "revalidation operations”

An intent-driven paradigm for feature-based design

A very important advantage of a feature-based modelling (FBM) system is claimed to be its ability to capture and carry designer’s intents (DI’s), although this last term is rarely clearly defined. Feature’s extra nongeometrical semantics, that are closely related to such designer’s intents, are used by many applications but never related back to designer’s intents. Therefore, adopting the approach of defining of designer’s intents helps define the role of features in the geometric design and, indeed, allows future feature-based modelling systems to better represent, store and reuse such information. Moreover, it allows a more formal approach for manipulating, verifying and maintaining DI’s throughout the design process, which is an invaluable support for really intelligent CAD systems. This paper presents Designer’s Intents in the feature-based modelling context and exposes a methodology used to effectivelly capture and manage and verify this extra information

Evaluation of a feature modelling validation method

Geometric modelling techniques for computer-aided design are provided with formal validation methods to ensure that a valid model is made available to applications such as interference checking. A natural and popular extension to geometric modelling is to group geometric entities into features that provide some extra meaning for one or more aspects of design or manufacture. These extra meanings are typically loosely formulated, in which case it is not possible to validate the feature-based model to ensure that it provides a correct representation for a downstream activity such as process planning. Earlier research established that validation methods can be based on the capture of designers' intents related to functional, relational and volumetric aspects of component geometry. This paper describes how this feature-based validation method has itself been validated through it's application to a series of test parts which have been either drawn from the literature or created to demonstrate particular aspects. It is shown that the prototype system that has been developed is indeed capable of meaningful featurebased model validation and additionally provides extensive information that is potentially useful to a range of engineering analysis activities