Expert judgement in the processes of commercial property market forecasting

In this paper, we investigate the role of judgement in the formation of forecasts in commercial property markets. The investigation is based on interview surveys with the majority of UK forecast producers, who are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self‐censorship’ or are ‘censored’ following in‐house consultation. It is concluded that the forecasting process is significantly more complex than merely carrying out econometric modelling, forecasts are mediated and contested within organisations and that impacts can vary considerably across different organizational contexts.

Expert judgement in the processes of commercial property market forecasting

In this paper we investigate the role of judgement in the formation of forecasts in commercial real estate markets. Based on interview surveys with the majority of forecast producers, we find that real estate forecasters are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self-censorship’ or are ‘censored’ following in-house consultation. It is concluded that the forecasting process is more complex than merely carrying out econometric modelling and that the impact of the influences within this process vary considerably across different organizational contexts.

What is an expert? A systems perspective on expertise

1. Expert knowledge continues to gain recognition as a valuable source of information in a wide range of research applications. Despite recent advances in defining expert knowledge, comparatively little attention has been given to how to view expertise as a system of interacting contributory factors, and thereby, to quantify an individual’s expertise. 2. We present a systems approach to describing expertise that accounts for many contributing factors and their interrelationships, and allows quantification of an individual’s expertise. A Bayesian network (BN) was chosen for this purpose. For the purpose of illustration, we focused on taxonomic expertise. The model structure was developed in consultation with professional taxonomists. The relative importance of the factors within the network were determined by a second set of senior taxonomists. This second set of experts (i.e. supra-experts) also provided validation of the model structure. Model performance was then assessed by applying the model to hypothetical career states in the discipline of taxonomy. Hypothetical career states were used to incorporate the greatest possible differences in career states and provide an opportunity to test the model against known inputs. 3. The resulting BN model consisted of 18 primary nodes feeding through one to three higher-order nodes before converging on the target node (Taxonomic Expert). There was strong consistency among node weights provided by the supra-experts for some nodes, but not others. The higher order nodes, “Quality of work” and “Total productivity”, had the greatest weights. Sensitivity analysis indicated that although some factors had stronger influence in the outer nodes of the network, there was relatively equal influence of the factors leading directly into the target node. Despite differences in the node weights provided by our supra-experts, there was remarkably good agreement among assessments of our hypothetical experts that accurately reflected differences we had built into them. 4. This systems approach provides a novel way of assessing the overall level of expertise of individuals, accounting for multiple contributory factors, and their interactions. Our approach is adaptable to other situations where it is desirable to understand components of expertise.

Capturing expert knowledge for threatened species assessments: a case study using NatureServe conservation status ranks

Assessments for assigning the conservation status of threatened species that are based purely on subjective judgements become problematic because assessments can be influenced by hidden assumptions, personal biases and perceptions of risks, making the assessment process difficult to repeat. This can result in inconsistent assessments and misclassifications, which can lead to a lack of confidence in species assessments. It is almost impossible to Understand an expert's logic or visualise the underlying reasoning behind the many hidden assumptions used throughout the assessment process. In this paper, we formalise the decision making process of experts, by capturing their logical ordering of information, their assumptions and reasoning, and transferring them into a set of decisions rules. We illustrate this through the process used to evaluate the conservation status of species under the NatureServe system (Master, 1991). NatureServe status assessments have been used for over two decades to set conservation priorities for threatened species throughout North America. We develop a conditional point-scoring method, to reflect the current subjective process. In two test comparisons, 77% of species' assessments using the explicit NatureServe method matched the qualitative assessments done subjectively by NatureServe staff. Of those that differed, no rank varied by more than one rank level under the two methods. In general, the explicit NatureServe method tended to be more precautionary than the subjective assessments. The rank differences that emerged from the comparisons may be due, at least in part, to the flexibility of the qualitative system, which allows different factors to be weighted on a species-by-species basis according to expert judgement. The method outlined in this study is the first documented attempt to explicitly define a transparent process for weighting and combining factors under the NatureServe system. The process of eliciting expert knowledge identifies how information is combined and highlights any inconsistent logic that may not be obvious in Subjective decisions. The method provides a repeatable, transparent, and explicit benchmark for feedback, further development, and improvement. (C) 2004 Elsevier SAS. All rights reserved.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Marine biodiversity and ecosystem function relationships:the potential for practical monitoring applications

There is an increasing demand for environmental assessments of the marine environment to include ecosystem function. However, existing schemes are predominantly based on taxonomic (i.e. structural) measures of biodiversity. Biodiversity and Ecosystem Function (BEF) relationships are suggested to provide a mechanism for converting taxonomic information into surrogates of ecosystem function. This review assesses the evidence for marine BEF relationships and their potential to be used in practical monitoring applications (i.e. operationalized). Five key requirements were identified for the practical application of BEF relationships: (1) a complete understanding of strength, direction and prevalence of marine BEF relationships, (2) an understanding of which biological components are influential within specific BEF relationships, (3) the biodiversity of the selected biological components can be measured easily, (4) the ecological mechanisms that are the most important for generating marine BEF relationships, i.e. identity effects or complementarity, are known and (5) the proportion of the overall functional variance is explained by biodiversity, and hence BEF relationships, has been established. Numerous positive and some negative BEF relationships were found within the literature, although many reproduced poorly the natural species richness, trophic structures or multiple functions of real ecosystems (requirement 1). Null relationships were also reported. The consistency of the positive and negative relationships was often low that compromised the ability to generalize BEF relationships and confident application of BEF within marine monitoring. Equally, some biological components and functions have received little or no investigation. Expert judgement was used to attribute biological components using spatial extent, presence and functional rate criteria (requirement 2). This approach highlighted the main biological components contributing the most to specific ecosystem functions, and that many of the particularly influential components were found to have received the least amount of research attention. The need for biodiversity to be measureable (requirement 3) is possible for most biological components although difficult within the functionally important microbes. Identity effects underpinned most marine BEF relationships (requirement 4). As such, processes that translated structural biodiversity measures into functional diversity were found to generate better BEF relationships. The analysis of the contribution made by biodiversity, over abiotic influences, to the total expression of a particular ecosystem function was rarely measured or considered (requirement 5). Hence it is not possible to determine the overall importance of BEF relationships within the total ecosystem functioning observed. In the few studies where abiotic factors had been considered, it was clear that these modified BEF relationships and have their own direct influence on functional rate. Based on the five requirements, the information required for immediate ‘operationalization’ of BEF relationships within marine functional monitoring is lacking. However, the concept of BEF inclusion within practical monitoring applications, supported by ecological modelling, shows promise for providing surrogate indicators of functioning.

Conceptual Ecological Modelling of Sublittoral Rock Habitats to Inform Indicator Selection

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 1 Report: Rationale and proposed ecological groupings for Level 5 biotopes against which sensitivity assessments would be best undertaken.

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

Tillin, H. & Tyler-Walters, H., 2014. Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 2 Report – Literature review and sensitivity assessments for ecological groups for circalittoral and offshore Level 5 biotopes. JNCC Report No. 512B, 260 pp.

Human activities within the marine environment give rise to a number of pressures on seabed habitats. Improved understanding of the sensitivity of subtidal sedimentary habitats is required to underpin the management advice provided for Marine Protected Areas, as well as supporting other UK marine monitoring and assessment work. The sensitivity of marine sedimentary habitats to a range of pressures induced by human activities has previously been systematically assessed using approaches based on expert judgement for Defra Project MB0102 (Tillin et al. 2010). This previous work assessed sensitivity at the level of the broadscale habitat and therefore the scores were typically expressed as a range due to underlying variation in the sensitivity of the constituent biotopes. The objective of this project was to reduce the uncertainty around identifying the sensitivity of selected subtidal sedimentary habitats by assessing sensitivity, at a finer scale and incorporating information on the biological assemblage, for 33 Level 5 circalittoral and offshore biotopes taken from the Marine Habitat Classification of Britain and Ireland (Connor et al. 2004). Two Level 6 sub-biotopes were also included in this project as these contain distinctive characterising species that differentiate them from the Level 5 parent biotope. Littoral, infralittoral, reduced and variable salinity sedimentary habitats were excluded from this project as the scope was set for assessment of circalittoral and offshore sedimentary communities. This project consisted of three Phases. • Phase 1 - define ecological groups based on similarities in the sensitivity of characterising species from the Level 5 and two Level 6 biotopes described above. • Phase 2 - produce a literature review of information on the resilience and resistance of characterising species of the ecological groups to pressures associated with activities in the marine environment. • Phase 3 - to produce sensitivity assessment ‘proformas’ based on the findings of Phase 2 for each ecological group. This report outlines results of Phase 2. The Tillin et al., (2010) sensitivity assessment methodology was modified to use the best available scientific evidence that could be collated within the project timescale. An extensive literature review was compiled, for peer reviewed and grey literature, to examine current understanding about the effects of pressures from human activities on circalittoral and offshore sedimentary communities in UK continental shelf waters, together with information on factors that contribute to resilience (recovery) of marine species. This review formed the basis of an assessment of the sensitivity of the 16 ecological groups identified in Phase 1 of the project (Tillin & Tyler-Walters 2014). As a result: • the state of knowledge on the effects of each pressure on circalittoral and offshore benthos was reviewed; • the resistance, resilience and, hence, sensitivity of sixteen ecological groups, representing 96 characteristic species, were assessed for eight separate pressures; • each assessment was accompanied by a detailed review of the relevant evidence; Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with human activities • knowledge gaps and sources of uncertainty were identified for each group; • each assessment was accompanied by an assessment of the quality of the evidence, its applicability to the assessment and the degree of concordance (agreement) between the evidence, to highlight sources of uncertainty as an assessment of the overall confidence in the sensitivity assessment, and finally • limitations in the methodology and the application of sensitivity assessments were outlined. This process demonstrated that the ecological groups identified in Phase 1 (Tillin & Tyler-Walters 2014) were viable groups for sensitivity assessment, and could be used to represent the 33 circalittoral and offshore sediments biotopes identified at the beginning of the project. The results of the sensitivity assessments show: • the majority of species and hence ecological groups in sedimentary habitats are sensitive to physical change, especially loss of habitat and sediment extraction, and change in sediment type; • most sedimentary species are sensitive to physical damage, e.g. abrasion and penetration, although deep burrowing species (e.g. the Dublin Bay prawn - Nephrops norvegicus and the sea cucumber - Neopentadactyla mixta) are able to avoid damaging effects to varying degrees, depending on the depth of penetration and time of year; • changes in hydrography (wave climate, tidal streams and currents) can significantly affect sedimentary communities, depending on whether they are dominated by deposit, infaunal feeders or suspension feeders, and dependant on the nature of the sediment, which is itself modified by hydrography and depth; • sedentary species and ecological groups that dominate the top-layer of the sediment (either shallow burrowing or epifaunal) remain the most sensitive to physical damage; • mobile species (e.g. interstitial and burrowing amphipods, and perhaps cumaceans) are the least sensitive to physical change or damage, and hydrological change as they are already adapted to unstable, mobile substrata; • sensitivity to changes in organic enrichment and hence oxygen levels, is variable between species and ecological groups, depending on the exact habitat preferences of the species in question, although most species have at least a medium sensitivity to acute deoxygenation; • there is considerable evidence on the effects of bottom-contact fishing practices and aggregate dredging on sedimentary communities, although not all evidence is directly applicable to every ecological group; • there is lack of detailed information on the physiological tolerances (e.g. to oxygenation, salinity, and temperature), habitat preferences, life history and population dynamics of many species, so that inferences has been made from related species, families, or even the same phylum; • there was inadequate evidence to assess the effects of non-indigenous species on most ecological groups, and Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with human activities • there was inadequate evidence to assess the effects of electromagnetic fields and litter on any ecological group. The resultant report provides an up-to-date review of current knowledge about the effects of pressures resulting from human activities of circalittoral and offshore sedimentary communities. It provides an evidence base to facilitate and support the provision of management advice for Marine Protected Areas, development of UK marine monitoring and assessment, and conservation advice to offshore marine industries. However, such a review will require at least annual updates to take advantage of new evidence and new research as it becomes available. Also further work is required to test how ecological group assessments are best combined in practice to advise on the sensitivity of a range of sedimentary biotopes, including the 33 that were originally examined.

Care homes’ use of medicines study: prevalence, causes and potential harm of medication errors in care homes for older people

Introduction: Care home residents are at particular risk from medication errors, and our objective was to determine the prevalence and potential harm of prescribing, monitoring, dispensing and administration errors in UK care homes, and to identify their causes. Methods: A prospective study of a random sample of residents within a purposive sample of homes in three areas. Errors were identified by patient interview, note review, observation of practice and examination of dispensed items. Causes were understood by observation and from theoretically framed interviews with home staff, doctors and pharmacists. Potential harm from errors was assessed by expert judgement. Results: The 256 residents recruited in 55 homes were taking a mean of 8.0 medicines. One hundred and seventy-eight (69.5%) of residents had one or more errors. The mean number per resident was 1.9 errors. The mean potential harm from prescribing, monitoring, administration and dispensing errors was 2.6, 3.7, 2.1 and 2.0 (0 = no harm, 10 = death), respectively. Contributing factors from the 89 interviews included doctors who were not accessible, did not know the residents and lacked information in homes when prescribing; home staff’s high workload, lack of medicines training and drug round interruptions; lack of team work among home, practice and pharmacy; inefficient ordering systems; inaccurate medicine records and prevalence of verbal communication; and difficult to fill (and check) medication administration systems. Conclusions: That two thirds of residents were exposed to one or more medication errors is of concern. The will to improve exists, but there is a lack of overall responsibility. Action is required from all concerned.

Diseño y aplicación de una metodología prospectiva para la determinación de los condicionantes futuros del crecimiento de los grandes buques portacontenedores

Durante las últimas décadas se observa una tendencia sostenida al crecimiento en las dimensiones de los grandes buques portacontenedores, que produce, que las infraestructuras portuarias y otras destinadas al tráfico de contenedores deban adaptarse para poder brindar los servicios correspondientes y mantenerse competitivas con otras para no perder el mercado. Esta situación implica importantes inversiones y modificaciones en los sistemas de transporte de contenedores por el gran volumen de carga que se debe mover en un corto periodo de tiempo, lo que genera la necesidad de tomar previsiones relacionadas con la probable evolución a futuro de las dimensiones que alcanzarán los grandes buques portacontenedores. En relación a los aspectos citados surge la inquietud de determinar los condicionantes futuros del crecimiento de los grandes buques portacontenedores, con una visión totalizadora de todos los factores que incidirán en los próximos años, ya sea como un freno o un impulso a la tendencia que se verifica en el pasado y en el presente. En consideración a que el tema a tratar y resolver se encuentra en el futuro, con un horizonte de predicción de veinte años, se diseña y se aplica una metodología prospectiva, que permite alcanzar conclusiones con mayor grado de objetividad sobre probables escenarios futuros. La metodología prospectiva diseñada, conjuga distintas herramientas metodológicas, cualitativas, semi-cuantitativas y cuantitativas que se validan entre sí. Sobre la base del pasado y el presente, las herramientas cuantitativas permiten encontrar relaciones entre variables y hacer proyecciones, sin embargo, estas metodologías pierden validez más allá de los tres a cuatro años, por los vertiginosos y dinámicos cambios que se producen actualmente, en las áreas política, social y económica. Las metodologías semi-cuantitativas y cualitativas, empleadas en forma conjunta e integradas, permiten el análisis de circunstancias del pasado y del presente, obteniendo resultados cuantitativos que se pueden proyectar hacia un futuro cercano, los que integrados en estudios cualitativos proporcionan resultados a largo plazo, facilitando considerar variables cualitativas como la creciente preocupación por la preservación del medio ambiente y la piratería. La presente tesis, tiene como objetivo principal “identificar los condicionantes futuros del crecimiento de los grandes buques portacontenedores y determinar sus escenarios”. Para lo cual, la misma se estructura en fases consecutivas y que se retroalimentan continuamente. Las tres primeras fases son un enfoque sobre el pasado y el presente, que establece el problema a resolver. Se estudian los antecedentes y el estado del conocimiento en relación a los factores y circunstancias que motivaron y facilitaron la tendencia al crecimiento de los grandes buques. También se estudia el estado del conocimiento de las metodologías para predecir el futuro y se diseña de una metodología prospectiva. La cuarta fase, denominada Resultados, se desarrolla en distintas etapas, fundamentadas en las fases anteriores, con el fin de resolver el problema dando respuestas a las preguntas que se formularon para alcanzar el objetivo fijado. En el proceso de esta fase, con el objeto de predecir probables futuros, se aplica la metodología prospectiva diseñada, que contempla el análisis del pasado y el presente, que determina los factores cuya influencia provocó el crecimiento en dimensiones de los grandes buques hasta la actualidad, y que constituye la base para emplear los métodos prospectivos que permiten determinar qué factores condicionarán en el futuro la evolución de los grandes buques. El probable escenario futuro formado por los factores determinados por el criterio experto, es validado mediante un modelo cuantitativo dinámico, que además de obtener el probable escenario futuro basado en las tendencias de comportamiento hasta el presente de los factores determinantes considerados, permite estudiar distintos probables escenarios futuros en función de considerar un cambio en la tendencia futura de los factores determinantes. El análisis del pasado indica que la tendencia al crecimiento de los grandes buques portacontenedores hasta el presente, se ha motivado por un crecimiento económico mundial que se tradujo en un aumento del comercio internacional, particularmente entre los países de Asia, con Europa y Estados Unidos. Esta tendencia se ha visto favorecida por el factor globalización y la acelerada evolución tecnológica que ha permitido superar los obstáculos que se presentaron. Es de destacar que aún en periodos de crisis económicas, con pronósticos de contracciones en el comercio, en los últimos años continuó la tendencia al crecimiento en dimensiones, en busca de una economía de escala para el transporte marítimo de contenedores, en las rutas transoceánicas. La investigación de la evolución de los grandes buques portacontenedores en el futuro, se efectúa mediante el empleo de una metodología prospectiva en la que el criterio experto se valida con un método cuantitativo dinámico, y además se fundamenta en una solida base pre-prospectiva. La metodología diseñada permite evaluar con un alto grado de objetividad cuales serán los condicionantes que incidirán en el crecimiento en tamaño de los grandes buques portacontenedores en el escenario con mayor probabilidad de acontecer en los próximos veinte años (2032), y también en otros escenarios que podrían presentarse en el caso de que los factores modifiquen su tendencia o bien se produzcan hechos aleatorios. El resultado se sintetiza en que la tendencia al crecimiento de los grandes buques portacontenedores en los próximos 20 años se verá condicionada por factores en relación a los conceptos de oferta (los que facilitan u obstaculizan la tendencia), demanda (los que motivan o impulsan la tendencia) y factores externos (los que desestabilizan el equilibrio entre oferta y demanda). La tendencia al crecimiento de los grandes buques portacontenedores se verá obstaculizada / limitada principalmente por factores relacionados a las infraestructuras, resultando los pasos y/o canales vinculados a las rutas marítimas, los limitantes futuros al crecimiento en dimensiones de los grandes buques portacontenedores; y la interacción buque / infraestructura (grúas) un factor que tenderá a obstaculizar esta tendencia de los grandes portacontenedores. El desarrollo económico mundial que estimula el comercio internacional y los factores precio del petróleo y condicionantes medioambientales impulsarán la tendencia al crecimiento de los grandes buques portacontenedores. Recent years have seen a sustained tendency towards the growth in the dimensions of large container ships. This has meant that port and other infrastructure used for container traffic has had to be adapted in order to provide the required services and to maintain a competitive position, so as not to lose market share. This situation implies the need for major investments in modifications to the container transport system, on account of the large volume of traffic to be handled in a short period of time. This in turn has generated a need to make provision for the probable future evolution of the ultimate dimensions that will be reached by large container ships. Such considerations give rise to the question of what are the future determinants for the growth of large container ships, requiring an overall vision of all the factors that will apply in future years, whether as a brake on or an incentive to the growth tendency which has been seen in the past and present In view of the fact that the theme to be dealt with and resolved relates to the future, with a forecasting horizon of some 20 years, a foresight methodology has been designed and applied so as to enable conclusions about probable future scenarios to be reached with a greater degree of objectivity. The designed methodology contains different methodological tools, both qualitative, semi-quantitative and quantitative, which are internally consistent. On the basis of past and present observations, the quantitative elements enable relationships to be established and forecasts to be made. Nevertheless such an approach loses validity more than three or four years into the future, on account of the very rapid and dynamic changes which may be seen at present in political, social and economic spheres. The semi-quantitative and qualitative methodologies are used coherently together and allow the analysis of past and present conditions, thus obtaining quantitative results which for short-term projections, which when integrated with the qualitative studies provide results for the long-term, facilitating the consideration of qualitative variables such as the increasing importance of environmental protection and the impact of piracy. The principal objective of the present thesis is "to identify the future conditions affecting the growth of large container ships and to determine possible scenarios". The thesis is structured in consecutive and related phases. The first three phases focus on the past and present in order to determine the problem to be resolved. The background is studied in order to establish the state of knowledge about the factors and circumstances which have motivated and facilitated the growth tendency for large container ships and the methodologies that have been used. In this way a specific foresight methodology is designed. The fourth phase, Results, is developed in distinct stages based on the previous phases, so as to resolve the problem posed and responding to the questions that arise. In this way the determined objective is reached. The fourth phase sees the application of the methodology that has been designed in order to predict posible futures. This includes analysis of the past and present factors which have caused the growth in the dimensions of large container ships up to the present. These provide the basis on which to apply the foresight methods which enable the future factors which will condition the development of such large container ships. The probable future scenarios are made up of the factors identified by expert judgement (using the Delphi technique) and validated by means of a dynamic quantitative model. This model both identifies the probable future scenarios based on past and present factors and enables the different future scenarios to be analysed as a function of future changes in the conditioning factors. Analysis of the past shows that the growth tendency up to the present for large container ships has been motivated by the growth of the world economy and the consequent increased international trade, especially between the countries of Asia with Europe and the United States. This tendency has been favoured by the trend towards globalization and by the rapid technical evolution in ship design, which has allowed the obstacles encountered to be overcome. It should be noted that even in periods of economic crisis, with an expectation for reduced trade, as experienced in recent years, the tendency towards increased ship dimensions has continued in search of economies of scale for the maritime transport of containers on transoceanic routes. The present investigation of the future evolution of large container ships has been done using a foresight methodology in which the expert judgement is validated by a dynamic quantitative methodology, founded on a firm pre-foresight analysis. The methodology that has been designed permits the evaluation, with a high degree of objectivity, of the future factors that will affect the growth of large container ships for the most probable scenario expected in the next 20 years (up to 2032). The evaluation applies also to other scenarios which may arise, in the event that their component factors are modified or indeed in the light of random events. In summary, the conclusión is that the tendency for growth in large container ships in the future 20 years will be determined by: factors related to supply, which slow or halt the tendency; factors related to demand, which encourage the tendency and finally, external factors which interrupt the equilibrium between supply and demand. The tendency for increasing growth in large container ships will be limited or even halted by factors related to infrastructure, including the natural and man-made straits and canals used by maritime transport. In addition the infrastructure required to serve such vessels both in port (including cranes and other equipment) and related transport, will tend to slow the growth tendency. The factors which will continue to encourage the tendency towards the growth of large container ships include world economic development, which stimulates international trade, and an increasing emphasis on environmental aspects.

Regret theory-based scenario building using an interacttive process

This paper is an introduction of the regret theory-based scenario building approach combining with a modified Delphi method that uses an interactive process to design and assess four different TDM measures (i.e., cordon toll, parking charge, increased bus frequency and decreased bus fare). The case study of Madrid is used to present the analysis and provide policy recommendations. The new scenario building approach incorporates expert judgement and transport models in an interactive process. It consists of a two-round modified Delphi survey, which was answeared by a group of Spanish transport experts who were the participants of the Transport Engineering Congress (CIT 2012), and an integrated land-use and transport model (LUTI) for Madrid that is called MARS (Metropolitan Activity Relocation Simulator).

An analysis of fatal accidents in agriculture in Great Britain

The number of fatal accidents in the agricultural, horticultural and forestry industry in Great Britain has declined from an annual rate of about 135 in the 1960's to its current level of about 50. Changes to the size and makeup of the population at risk mean that there has been no real improvement in fatal injury incidence rates for farmers. The Health and Safety Executives' (HSE) current system of accident investigation, recording, and analysis is directed primarily at identifying fault, allocating blame, and punishing wrongdoers. Relatively little information is recorded about the personal and organisational factors that contributed to, or failed to prevent accidents. To develop effective preventive strategies, it is important to establish whether errors by the victims and others, occur at the skills, rules, or knowledge level of functioning: are violations of some rule or procedure; or stem from failures to correctly appraise, or control a hazard. A modified version of the Hale and Glendon accident causation model was used to study 230 fatal accidents. Inspectors' original reports were examined and expert judgement applied to identify and categorise the errors committed by each of the parties involved. The highest proportion of errors that led directly to accidents occurred whilst the victims were operating at the knowledge level. The mix and proportion of errors varied considerably between different classes of victim and kind of accident. Different preventive strategies will be needed to address the problem areas identified.

Ecological quality assessment of transitional waters based on fish assemblages in Portuguese estuaries: The Estuarine Fish Assessment Index (EFAI)

The assessment of water quality has changed markedly worldwide over the last years, especially in Europe due to the implementation of the Water Framework Directive. Fish was considered a key-element in this context and several fish-based multi-metric indices have been proposed. In this study, we propose a multi-metric index, the Estuarine Fish Assessment Index (EFAI), developed for Portuguese estuaries, designed for the overall assessment of transitional waters, which could also be applied at the water body level within an estuary. The EFAI integrates seven metrics: species richness, percentage of marine migrants, number of species and abundance of estuarine resident species, number of species and abundance of piscivorous species, status of diadromous species, status of introduced species and status of disturbance sensitive species. Fish sampling surveys were conducted in 2006, 2009 and 2010, using beam trawl, in 13 estuarine systems along the Portuguese coast. Most of the metrics presented a high variability among the transitional systems surveyed. According to the EFAI values, Portuguese estuaries presented a "Good" water quality status (except the Douro in a particular year). The assessments in different years were generally concordant, with a few exceptions. The relationship between the EFAI and the Anthropogenic Pressure Index (API) was not significant, but a negative and significant correlation was registered between the EFAI and the expert judgement pressure index, at both estuary and water body level. The ordination analysis performed to evaluate similarities among North-East Atlantic Geographical Intercalibration Group (NEAGIG) fish-based indices put in evidence four main groups: the French index, since it is substantially different from all the other indices (uses only four metrics based on densities); indices from Ireland, United Kingdom and Spain (Asturias and Cantabria); the Dutch and German indices; and the indices of Belgium. Portugal and Spain (Basque country). The need for detailed studies, including comparative approaches, on several aspects of these assessment tools, especially in what regards their response to anthropogenic pressures was stressed. (C) 2011 Elsevier Ltd. All rights reserved.

Fast and frugal models of clinical judgement in novice and expert physicians

Our objective was to study whether “compensatory” models provide better descriptions of clinical judgment than fast and frugal models, according to expertise and experience. Fifty practitioners appraised 60 vignettes describing a child with an exacerbation of asthma and rated their propensities to admit the child. Linear logistic (LL) models of their judgments were compared with a matching heuristic (MH) model that searched available cues in order of importance for a critical value indicating an admission decision. There was a small difference between the 2 models in the proportion of patients allocated correctly (admit or not-admit decisions), 91.2% and 87.8%, respectively. The proportion allocated correctly by the LL model was lower for consultants than juniors, whereas the MH model performed equally well for both. In this vignette study, neither model provided any better description of judgments made by consultants or by pediatricians compared to other grades and specialties.