Multiple criteria optimization of contemporary logistics distribution network problems

In the contemporary customer-driven supply chain, maximization of customer service plays an equally important role as minimization of costs for a company to retain and increase its competitiveness. This article develops a multiple-criteria optimization approach, combining the analytic hierarchy process (AHP) and an integer linear programming (ILP) model, to aid the design of an optimal logistics distribution network. The proposed approach outperforms traditional cost-based optimization techniques because it considers both quantitative and qualitative factors and also aims at maximizing the benefits of deliverer and customers. In the approach, the AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to some critical customer-oriented criteria. The results of AHP prioritization are utilized as the input of the ILP model, the objective of which is to select the best warehouses at the lowest possible cost. In this article, two commercial packages are used: including Expert Choice and LINDO.

Quality-driven resource utilization methods for video streaming in wireless communication networks

This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots.

Making SENS:exploring the antecedents and impact of store environmental stewardship climate

Retailers increasingly recognize that environmental responsibility is a strategic imperative. However, little research has investigated or identified the factors that facilitate the successful implementation of environmentally responsible strategies across a network of customer-facing sales units (stores). We propose that a store manager’s ability to lead by example facilitates this process by fostering a supportive climate for store environmental stewardship (SENS-climate). By examining the influence of store managers’ actions on sales associates’ perceptions of the SENS-climate, as well as the subsequent impact on their performance—measured by margins, as well as sales of green and regular products—this study demonstrates that store managers can foster a SENS-climate by articulating their prioritization of environmental responsibility in their operational decisions. These positive effects are sustained by relational factors, such as the moderating effect of the store manager–sales associate dyadic tenure. In contrast, when store managers display high variability in their environmental orientation, it hinders the development of SENS-climate perceptions among sales associates. If sales associates perceive an enabling SENS-climate, they achieve higher margins and more green but fewer regular sales.

Performance of FRP-concrete bridges under blast loading

Catastrophic failure from intentional terrorist attacks on surface transportation infrastructure could he detrimental to the society. In order to minimize the vulnerabilities and to ensure a safe transportation system, the issue of security for transportation structures, primarily bridges, which are subjected to man-made hazards is investigated in this study. A procedure for identifying and prioritizing "critical bridges" using a screening and prioritization processes is established. For each of the "critical" bridges, a systematic risk-based assessment approach is proposed that takes into account the combination of threat occurrence likelihood, its consequences, and the socioeconomic importance of the bridge. A series of effective security countermeasures are compiled in the four categories of deterrence, detection, defense and mitigation to help reduce the vulnerability of critical bridges. The concepts of simplified equivalent I-shape cross section and virtual materials are proposed for integration into a nonlinear finite element model, which helps assess the performance of reinforced concrete structures with and without composite retrofit or hardening measures under blast loading. A series of parametric studies are conducted for single column and two-column pier frame systems as well as for an entire bridge. The parameters considered include column height, column type, concrete strength, longitudinal steel reinforcement ratio, thickness, fiber angle and tensile strength of the fiber reinforced polymer (FRP) tube, shape of the cross section, damping ratio and different bomb sizes. The study shows the benefits of hardening with composites against blast loading. The effect of steel reinforcement on blast resistance of the structure is more significant than the effect of concrete compressive strength. Moreover, multiple blasts do not necessarily lead to a more severe destruction than a single detonation at a strategically vulnerable location on the bridges.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Assessing Methods for Assigning SNPs to Genes in Gene-Based Tests of Association Using Common Variants

Gene-based tests of association are frequently applied to common SNPs (MAF>5%) as an alternative to single-marker tests. In this analysis we conduct a variety of simulation studies applied to five popular gene-based tests investigating general trends related to their performance in realistic situations. In particular, we focus on the impact of non-causal SNPs and a variety of LD structures on the behavior of these tests. Ultimately, we find that non-causal SNPs can significantly impact the power of all gene-based tests. On average, we find that the “noise” from 6–12 non-causal SNPs will cancel out the “signal” of one causal SNP across five popular gene-based tests. Furthermore, we find complex and differing behavior of the methods in the presence of LD within and between non-causal and causal SNPs. Ultimately, better approaches for a priori prioritization of potentially causal SNPs (e.g., predicting functionality of non-synonymous SNPs), application of these methods to sequenced or fully imputed datasets, and limited use of window-based methods for assigning inter-genic SNPs to genes will improve power. However, significant power loss from non-causal SNPs may remain unless alternative statistical approaches robust to the inclusion of non-causal SNPs are developed.

Improved Criteria for Estimating Calibration Factors for Highway Safety Manual (HSM) Applications

The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors. In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually. To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.

Representações sociais de familiares sobre o atendimento das emergências psiquiátricas

The reformist movements in the field of mental health have pointed battle flags, among which the prioritization of production of mental health care out of the asylum environment should be highlighted, aiming the reduction of psychiatric beds, greater control over the hospitalization, family co-participation and the rescue of the citizenship of the social players involved. With the progressive reduction of asylum beds, associated with a lot of structural problems in the health services, the occurrence of crises outside the hospital environment has been increasingly frequent, thus giving the family an important therapeutic role. In face of this scenario, there is an urgent need to understand the social construction of the care for psychiatric emergencies, identifying the meanings assigned by family members to their constituent aspects. This study seeks to answer the following research question: what are the social representations of family members about the care of psychiatric emergencies in the city of Mossoró, Rio Grande do Norte? Therefore, the aim is to analyze the social representations of family members about the care of psychiatric emergencies in the city of Mossoró, Rio Grande do Norte. This is an exploratory and descriptive study, with a mixed approach, making use of multimethods: for collection, the semi-structured interview and the Technique of Free Association of Words; for data analysis, the Thematic Analysis of Bardin and its steps was used, with the informational support of the softwares ALCESTE (Analyse Lexicale par Contexte d'un Ensemble de Segments de Texte) and Iramuteq (Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires); and the theoretical support of social representations. The study participants totaled 72, and they were selected from the following criteria: older than18 years, with degree of kinship with users suffering from some mental and behavioral disorder, and who have already witnessed a situation of crisis, rescued by the SAMU or other means and taken to the psychiatric hospital or general emergency room. Preliminary results point out: 1.Previous note of the research project with the aim to disseminate it in the scientific community and ensure the intellectual property of the work; 2.The contextual analysis of the care for emergencies in the study place. Reflection about the phenomenon provide a name to the care for the psychiatric emergencies, which is called immediate context; the technical and operational aspects that influence the care, as a specific/ general context; and mental health policies in Brazil are identified as metacontext; 3. The systematic review from randomized clinical trials in the databases PubMed, COCHRANE, LILACS, SciELO and SCIRUS, with the use of the descriptors: ‘Physical restraint’, ‘Psychiatric emergency services’, ‘Restraint’, ‘Physical and Emergency Services’, ‘Psychiatric’. Only one work met the search protocol criteria: a short-term essay that records limited results about the proportion of people who are in restraint and seclusion. It does not show statistically significant results in relation to indications, contraindications and risks of the use of physical restraint; 4. The social representations of the care for psychiatric emergencies. The study results point to the presence of five thematic categories: 1. feeling in the face of the crisis/care; 2. thoughts and perspectives about the crisis/care; 3. centrality of care in the medical- medication-hospitalization triad; 4. the thinking/acting in the face of the use of physical restraint and police force; 5. periodicity of crises. The central core of the representation is in the first category, whilst the peripheral elements are in the third and fifth categories. The contrast zone is in the second and fourth categories. The sadness is the most prominent element of the structure. The social representations about the care for psychiatric crises are at a time of transition between the hegemonic and reformist models, with the traditional aspects being predominant, but already showing peripheral and contrast elements that point to a possible change in the representational field.

Prioritizing tropical habitats for long-distance migratory songbirds: an assessment of habitat quality at a stopover site in Colombia

Long-distance migratory birds are declining globally and migration has been identified as the primary source of mortality in this group. Despite this, our lack of knowledge of habitat use and quality at stopovers, i.e., sites where the energy for migration is accumulated, remains a barrier to designing appropriate conservation measures, especially in tropical regions. There is therefore an urgent need to assess stopover habitat quality and concurrently identify efficient and cost-effective methods for doing so. Given that fuel deposition rates directly influence stopover duration, departure fuel load, and subsequent speed of migration, they are expected to provide a direct measure of habitat quality and have the advantage of being measurable through body-mass changes. Here, we examined seven potential indicators of quality, including body-mass change, for two ecologically distinct Neotropical migratory landbirds on stopover in shade-coffee plantations and tropical humid premontane forest during spring migration in Colombia: (1) rate of body-mass change; (2) foraging rate; (3) recapture rate; (4) density; (5) flock size; (6) age and sex ratios; and (7) body-mass distribution. We found higher rates of mass change in premontane forest than in shade-coffee in Tennessee Warbler Oreothlypis peregrina, a difference that was mirrored in higher densities and body masses in forest. In Gray-cheeked Thrush Catharus minimus, a lack of recaptures in shade-coffee and higher densities in forest, also suggested that forest provided superior fueling conditions. For a reliable assessment of habitat quality, we therefore recommend using a suite of indicators, taking into account each species’ ecology and methodological considerations. Our results also imply that birds stopping over in lower quality habitats may spend a longer time migrating and require more stopovers, potentially leading to important carryover effects on reproductive fitness. Evaluating habitat quality is therefore imperative prior to defining the conservation value of newly identified stopover regions.

Interpreting Human Genetic Variation through Genomics and In Vivo Models

Improvements in genomic technology, both in the increased speed and reduced cost of sequencing, have expanded the appreciation of the abundance of human genetic variation. However the sheer amount of variation, as well as the varying type and genomic content of variation, poses a challenge in understanding the clinical consequence of a single mutation. This work uses several methodologies to interpret the observed variation in the human genome, and presents novel strategies for the prediction of allele pathogenicity.

Using the zebrafish model system as an in vivo assay of allele function, we identified a novel driver of Bardet-Biedl Syndrome (BBS) in CEP76. A combination of targeted sequencing of 785 cilia-associated genes in a cohort of BBS patients and subsequent in vivo functional assays recapitulating the human phenotype gave strong evidence for the role of CEP76 mutations in the pathology of an affected family. This portion of the work demonstrated the necessity of functional testing in validating disease-associated mutations, and added to the catalogue of known BBS disease genes.

Further study into the role of copy-number variations (CNVs) in a cohort of BBS patients showed the significant contribution of CNVs to disease pathology. Using high-density array comparative genomic hybridization (aCGH) we were able to identify pathogenic CNVs as small as several hundred bp. Dissection of constituent gene and in vivo experiments investigating epistatic interactions between affected genes allowed for an appreciation of several paradigms by which CNVs can contribute to disease. This study revealed that the contribution of CNVs to disease in BBS patients is much higher than previously expected, and demonstrated the necessity of consideration of CNV contribution in future (and retrospective) investigations of human genetic disease.

Finally, we used a combination of comparative genomics and in vivo complementation assays to identify second-site compensatory modification of pathogenic alleles. These pathogenic alleles, which are found compensated in other species (termed compensated pathogenic deviations [CPDs]), represent a significant fraction (from 3 – 10%) of human disease-associated alleles. In silico pathogenicity prediction algorithms, a valuable method of allele prioritization, often misrepresent these alleles as benign, leading to omission of possibly informative variants in studies of human genetic disease. We created a mathematical model that was able to predict CPDs and putative compensatory sites, and functionally showed in vivo that second-site mutation can mitigate the pathogenicity of disease alleles. Additionally, we made publically available an in silico module for the prediction of CPDs and modifier sites.

These studies have advanced the ability to interpret the pathogenicity of multiple types of human variation, as well as made available tools for others to do so as well.

Identifying the Structure and Fate of Wastewater Derived Organic Micropollutants by High-resolution Mass Spectrometry

Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.

The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.

In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.

I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.

Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.

Primary care physician decision making regarding severe obesity treatment and bariatric surgery: a qualitative study.

BACKGROUND: Less than 1% of severely obese US adults undergo bariatric surgery annually. It is critical to understand the factors that contribute to its utilization. OBJECTIVES: To understand how primary care physicians (PCPs) make decisions regarding severe obesity treatment and bariatric surgery referral. SETTING: Focus groups with PCPs practicing in small, medium, and large cities in Wisconsin. METHODS: PCPs were asked to discuss prioritization of treatment for a severely obese patient with multiple co-morbidities and considerations regarding bariatric surgery referral. Focus group sessions were analyzed by using a directed approach to content analysis. A taxonomy of consensus codes was developed. Code summaries were created and representative quotes identified. RESULTS: Sixteen PCPs participated in 3 focus groups. Four treatment prioritization approaches were identified: (1) treat the disease that is easiest to address; (2) treat the disease that is perceived as the most dangerous; (3) let the patient set the agenda; and (4) address obesity first because it is the common denominator underlying other co-morbid conditions. Only the latter approach placed emphasis on obesity treatment. Five factors made PCPs hesitate to refer patients for bariatric surgery: (1) wanting to "do no harm"; (2) questioning the long-term effectiveness of bariatric surgery; (3) limited knowledge about bariatric surgery; (4) not wanting to recommend bariatric surgery too early; and (5) not knowing if insurance would cover bariatric surgery. CONCLUSION: Decision making by PCPs for severely obese patients seems to underprioritize obesity treatment and overestimate bariatric surgery risks. This could be addressed with PCP education and improvements in communication between PCPs and bariatric surgeons.

La incertidumbre amorosa contemporánea. Estrategias de los jóvenes

Este artículo explora las fuentes de incertidumbre en la experiencia contemporánea del amor y las estrategias que los jóvenes españoles ponen en práctica para afrontarla. Para ello, se utiliza el material empírico obtenido a través de la realización de 31 entrevistas en profundidad a adultos jóvenes entre 25 y 35 años de edad, residentes en Madrid. Su análisis ha permitido identificar una serie de estrategias que apuntan hacia la extensión de cierta “normatividad de la cautela” en la experiencia de los vínculos amorosos: a) La “disciplina emocional” para controlar la imagen que se otorga de los propios sentimientos, b) la concatenación de emparejamientos, c) la priorización del propio “yo” en las expectativas y d) la búsqueda de fórmulas alternativas al modelo de pareja monógama tradicional. Se analiza, además, cómo cada una de estas estrategias se hace plausible en función de determinados contextos y posiciones de clase y género.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.