Surrogate indicators for assessing community resilience

The importance of community resilience to natural disasters is being increasingly recognised. This paper presents an approach for the development of surrogate indicators for comprehensive assessment of community resilience, which is crucial in the context of predicted increase in natural disasters resulting from extreme weather events due to climate change. The use of surrogate indicators is advocated because a comprehensive assessment of community resilience across various thematic areas and associated key areas requires the measurement of a large number of resilience indicators which is not always feasible due to time and resource constraints, To overcome this, researchers tend to use secondary data sources, which are easily available but not always reliable. This highlights the need for surrogate indicators that are easy to measure from reliable primary data sources and are adequate to capture the resilience of a community. Firstly, the paper discusses the two approaches for defining and conceptualising community resilience and the need to account for the complex interrelationships between thematic areas, key areas and resilience indicators and their implications for research. Secondly, a comprehensive framework for the assessment of community resilience is proposed and the difficulties associated with the measurement of overall resilience of the community are discussed. Thirdly, the paper explains a two-step approach to develop surrogate indicators highlighting the necessity and challenges associated with it. Finally, the proposed approach is elaborated with a simple example for better understanding.

A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater

Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.

A systematic review of prescribing criteria to evaluate appropriateness of medications in frail older people

This study systematically reviews the published literature regarding inappropriate prescribing in frail individuals aged at least 65 years. Twenty-five of 466 identified studies met the inclusion criteria. All papers measured some surrogate indicators of frailty, such as performance-based tests, cognitive function and functional dependency. Beers criteria were used in 20 studies (74%) to evaluate inappropriate medication use and 36% (9/25) studies used more than one criterion. The prevalence of inappropriate medications ranged widely from 11 to 92%. Only a few studies reported the relationship between potentially inappropriate medication use and surrogate measures of frailty. These diverse findings indicate the need for a standardized measure for assessing appropriateness of medication in frail older individuals. Prescribing tools should address both medication and patient-related factors such as life expectancy and functional status to minimize inappropriate prescribing in frail individuals.

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.

Asthma control and exacerbations: two different sides of the same coin.

Purpose of review: Optimal asthma management includes both the control of asthma symptoms and reducing the risk of future asthma exacerbations. Traditionally, treatment has been adjusted largely on the basis of symptoms and lung function and for many patients, this approach delivers both excellent symptom control and reduced risk. However, the relationship between these two key components of the disease may vary between different asthmatic phenotypes and disease severities and there is increasing recognition of the need for more individualized treatment approaches.

Recent findings: A number of factors which predict exacerbation risk have been identified including demographic and behavioural features and specific inflammatory biomarkers. Type-2 cytokine-driven eosinophilic airways inflammation predisposes to frequent exacerbations and predicts response to corticosteroids, and the usefulness of sputum eosinophilia as both a marker of exacerbation risk and biomarker for adjustment of corticosteroid treatment has been established for some time. However, attempts to develop surrogate markers, which would be more straightforward to deliver in the clinic, have been challenging.

Summary: Some patients with asthma have persistent symptoms in the absence of type-2 cytokine driven-eosinophilic airways inflammation due to noncorticosteroid responsive mechanisms (T2-low disease). Composite biomarker strategies using easily measured surrogate indicators of type-2 inflammation (such as fractional exhaled nitric oxide, blood eosinophil count and serum periostin levels) may predict exacerbation risk better but it is unclear if they can be used to adjust corticosteroid treatment. Biomarkers will be used to target novel biologic treatments but additionally may be used to optimize corticosteroid treatment dose and act as prognostics for exacerbation risk and potentially other important longer term asthma outcomes.

Determining a set of surrogate parameters to evaluate urban stormwater quality

This thesis details methodology to estimate urban stormwater quality based on a set of easy to measure physico-chemical parameters. These parameters can be used as surrogate parameters to estimate other key water quality parameters. The key pollutants considered in this study are nitrogen compounds, phosphorus compounds and solids. The use of surrogate parameter relationships to evaluate urban stormwater quality will reduce the cost of monitoring and so that scientists will have added capability to generate a large amount of data for more rigorous analysis of key urban stormwater quality processes, namely, pollutant build-up and wash-off. This in turn will assist in the development of more stringent stormwater quality mitigation strategies. The research methodology was based on a series of field investigations, laboratory testing and data analysis. Field investigations were conducted to collect pollutant build-up and wash-off samples from residential roads and roof surfaces. Past research has identified that these impervious surfaces are the primary pollutant sources to urban stormwater runoff. A specially designed vacuum system and rainfall simulator were used in the collection of pollutant build-up and wash-off samples. The collected samples were tested for a range of physico-chemical parameters. Data analysis was conducted using both univariate and multivariate data analysis techniques. Analysis of build-up samples showed that pollutant loads accumulated on road surfaces are higher compared to the pollutant loads on roof surfaces. Furthermore, it was found that the fraction of solids smaller than 150 ìm is the most polluted particle size fraction in solids build-up on both roads and roof surfaces. The analysis of wash-off data confirmed that the simulated wash-off process adopted for this research agrees well with the general understanding of the wash-off process on urban impervious surfaces. The observed pollutant concentrations in wash-off from road surfaces were different to pollutant concentrations in wash-off from roof surfaces. Therefore, firstly, the identification of surrogate parameters was undertaken separately for roads and roof surfaces. Secondly, a common set of surrogate parameter relationships were identified for both surfaces together to evaluate urban stormwater quality. Surrogate parameters were identified for nitrogen, phosphorus and solids separately. Electrical conductivity (EC), total organic carbon (TOC), dissolved organic carbon (DOC), total suspended solids (TSS), total dissolved solids (TDS), total solids (TS) and turbidity (TTU) were selected as the relatively easy to measure parameters. Consequently, surrogate parameters for nitrogen and phosphorus were identified from the set of easy to measure parameters for both road surfaces and roof surfaces. Additionally, surrogate parameters for TSS, TDS and TS which are key indicators of solids were obtained from EC and TTU which can be direct field measurements. The regression relationships which were developed for surrogate parameters and key parameter of interest were of a similar format for road and roof surfaces, namely it was in the form of simple linear regression equations. The identified relationships for road surfaces were DTN-TDS:DOC, TP-TS:TOC, TSS-TTU, TDS-EC and TSTTU: EC. The identified relationships for roof surfaces were DTN-TDS and TSTTU: EC. Some of the relationships developed had a higher confidence interval whilst others had a relatively low confidence interval. The relationships obtained for DTN-TDS, DTN-DOC, TP-TS and TS-EC for road surfaces demonstrated good near site portability potential. Currently, best management practices are focussed on providing treatment measures for stormwater runoff at catchment outlets where separation of road and roof runoff is not found. In this context, it is important to find a common set of surrogate parameter relationships for road surfaces and roof surfaces to evaluate urban stormwater quality. Consequently DTN-TDS, TS-EC and TS-TTU relationships were identified as the common relationships which are capable of providing measurements of DTN and TS irrespective of the surface type.

Determination of a set of surrogate parameters to assess urban stormwater quality

This paper presents the outcomes of a research project, which focused on developing a set of surrogate parameters to evaluate urban stormwater quality using simulated rainfall. Use of surrogate parameters has the potential to enhance the rapid generation of urban stormwater quality data based on on-site measurements and thereby reduce resource intensive laboratory analysis. The samples collected from rainfall simulations were tested for a range of physico-chemical parameters which are key indicators of nutrients, solids and organic matter. The analysis revealed that [total dissolved solids (TDS) and dissolved organic carbon (DOC)]; [total solids (TS) and total organic carbon (TOC)]; [turbidity (TTU)]; [electrical conductivity (EC)]; [TTU and EC] as appropriate surrogate parameters for dissolved total nitrogen (DTN), total phosphorus (TP), total suspended solids (TSS), TDS and TS respectively. Relationships obtained for DTN-TDS, DTN-DOC, and TP-TS demonstrated good portability potential. The portability of the relationship developed for TP and TOC was found to be unsatisfactory. The relationship developed for TDS-EC and TS-EC also demonstrated poor portability.

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Aerobic power and lean mass are indicators of competitive sprint performance among elite female cross-country skiers

The purpose of this study was to establish the optimal allometric models to predict International Ski Federation’s ski-ranking points for sprint competitions (FISsprint) among elite female cross-country skiers based on maximal oxygen uptake (V̇O2max) and lean mass (LM). Ten elite female cross-country skiers (age: 24.5±2.8 years [mean ± SD]) completed a treadmill roller-skiing test to determine V̇O2max (ie, aerobic power) using the diagonal stride technique, whereas LM (ie, a surrogate indicator of anaerobic capacity) was determined by dual-emission X-ray anthropometry. The subjects’ FISsprint were used as competitive performance measures. Power function modeling was used to predict the skiers’ FISsprint based on V̇O2max, LM, and body mass. The subjects’ test and performance data were as follows: V̇O2max, 4.0±0.3 L min-1; LM, 48.9±4.4 kg; body mass, 64.0±5.2 kg; and FISsprint, 116.4±59.6 points. The following power function models were established for the prediction of FISsprint: 3.91×105 ∙ VO -6.002maxand 6.95×1010 ∙ LM-5.25; these models explained 66% (P=0.0043) and 52% (P=0.019), respectively, of the variance in the FISsprint. Body mass failed to contribute to both models; hence, the models are based on V̇O2max and LM expressed absolutely. The results demonstrate that the physiological variables that reflect aerobic power and anaerobic capacity are important indicators of competitive sprint performance among elite female skiers. To accurately indicate performance capability among elite female skiers, the presented power function models should be used. Skiers whose V̇O2max differs by 1% will differ in their FISsprint by 5.8%, whereas the corresponding 1% difference in LM is related to an FISsprint difference of 5.1%, where both differences are in favor of the skier with higher V̇O2max or LM. It is recommended that coaches use the absolute expression of these variables to monitor skiers’ performance-related training adaptations linked to changes in aerobic power and anaerobic capacity.

Brucite Microbialites in Living Coral Skeletons: Indicators of Extreme Microenvironments in Shallow-Marine Settings

Brucite [Mg(OH)2] microbialites occur in vacated interseptal spaces of living scleractinian coral colonies (Acropora, Pocillopora, Porites) from subtidal and intertidal settings in the Great Barrier Reef, Australia, and subtidal Montastraea from the Florida Keys, United States. Brucite encrusts microbial filaments of endobionts (i.e., fungi, green algae, cyanobacteria) growing under organic biofilms; the brucite distribution is patchy both within interseptal spaces and within coralla. Although brucite is undersaturated in seawater, its precipitation was apparently induced in the corals by lowered pCO2 and increased pH within microenvironments protected by microbial biofilms. The occurrence of brucite in shallow-marine settings highlights the importance of microenvironments in the formation and early diagenesis of marine carbonates. Significantly, the brucite precipitates discovered in microenvironments in these corals show that early diagenetic products do not necessarily reflect ambient seawater chemistry. Errors in environmental interpretation may arise where unidentified precipitates occur in microenvironments in skeletal carbonates that are subsequently utilized as geochemical seawater proxies.