Ratios in Aquatic Sciences: Statistical Shortcomings with Mean Depth and the Morphoedaphic Index

1990 ◽  
Vol 47 (9) ◽  
pp. 1788-1795 ◽  
Author(s):  
Donald A. Jackson ◽  
Harold H. Harvey ◽  
Keith M. Somers
Keyword(s):  
Predictive Models ◽  
Null Models ◽  
Analysis Of Covariance ◽  
Future Research ◽  
Randomization Tests ◽  
Morphoedaphic Index ◽  
Cautious Interpretation ◽  
Aquatic Sciences ◽  
Analytical Approaches

Researchers in aquatic sciences frequently employ empirically derived models to predict productivity, yield, and abundance of fish. We demonstrate that predictive models employing ratios of standardized biomass and lake morphometric variables are biased by spurious correlations due to mathematical transformations and the use of inappropriate null models. Our findings emphasise that studies incorporating ratios like mean depth or the morphoedaphic index require cautious interpretation. Future research should focus on more appropriate analytical approaches such as regression-based models like the analysis of covariance. Alternatively, where ratios are employed and spurious correlations are likely, statistical evaluations must incorporate randomization tests to assess the significance of such results.

scholarly journals CANTARE: finding and visualizing network-based multi-omic predictive models

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Janet C. Siebert ◽  
Martine Saint-Cyr ◽  
Sarah J. Borengasser ◽  
Brandie D. Wagner ◽  
Catherine A. Lozupone ◽  
...  
Keyword(s):  
Random Forests ◽  
Predictive Models ◽  
Regression Models ◽  
Dynamic Range ◽  
P Value ◽  
Published Data ◽  
Logistic Regression Models ◽  
Pairwise Models ◽  
Biological Insight ◽  
Analytical Approaches

Abstract Background One goal of multi-omic studies is to identify interpretable predictive models for outcomes of interest, with analytes drawn from multiple omes. Such findings could support refined biological insight and hypothesis generation. However, standard analytical approaches are not designed to be “ome aware.” Thus, some researchers analyze data from one ome at a time, and then combine predictions across omes. Others resort to correlation studies, cataloging pairwise relationships, but lacking an obvious approach for cohesive and interpretable summaries of these catalogs. Methods We present a novel workflow for building predictive regression models from network neighborhoods in multi-omic networks. First, we generate pairwise regression models across all pairs of analytes from all omes, encoding the resulting “top table” of relationships in a network. Then, we build predictive logistic regression models using the analytes in network neighborhoods of interest. We call this method CANTARE (Consolidated Analysis of Network Topology And Regression Elements). Results We applied CANTARE to previously published data from healthy controls and patients with inflammatory bowel disease (IBD) consisting of three omes: gut microbiome, metabolomics, and microbial-derived enzymes. We identified 8 unique predictive models with AUC > 0.90. The number of predictors in these models ranged from 3 to 13. We compare the results of CANTARE to random forests and elastic-net penalized regressions, analyzing AUC, predictions, and predictors. CANTARE AUC values were competitive with those generated by random forests and  penalized regressions. The top 3 CANTARE models had a greater dynamic range of predicted probabilities than did random forests and penalized regressions (p-value = 1.35 × 10–5). CANTARE models were significantly more likely to prioritize predictors from multiple omes than were the alternatives (p-value = 0.005). We also showed that predictive models from a network based on pairwise models with an interaction term for IBD have higher AUC than predictive models built from a correlation network (p-value = 0.016). R scripts and a CANTARE User’s Guide are available at https://sourceforge.net/projects/cytomelodics/files/CANTARE/. Conclusion CANTARE offers a flexible approach for building parsimonious, interpretable multi-omic models. These models yield quantitative and directional effect sizes for predictors and support the generation of hypotheses for follow-up investigation.

scholarly journals Age, Sex and Cerebral Microbleed Effects On White Matter Degradation After Traumatic Brain Injury

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 886-887
Author(s):  
Andrei Irimia ◽  
Ammar Dharani ◽  
Van Ngo ◽  
David Robles ◽  
Kenneth Rostowsky
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
White Matter ◽  
Diffusion Tensor ◽  
Diffuse Axonal Injury ◽  
Principal Component ◽  
Older Age ◽  
Analysis Of Covariance ◽  
Future Research ◽  
Cerebral Microbleed

Abstract Mild traumatic brain injury (mTBI) affects white matter (WM) integrity and accelerates neurodegeneration. This study assesses the effects of age, sex, and cerebral microbleed (CMB) load as predictors of WM integrity in 70 subjects aged 18-77 imaged acutely and ~6 months after mTBI using diffusion tensor imaging (DTI). Two-tensor unscented Kalman tractography was used to segment and cluster 73 WM structures and to map changes in their mean fractional anisotropy (FA), a surrogate measure of WM integrity. Dimensionality reduction of mean FA feature vectors was implemented using principal component (PC) analysis, and two prominent PCs were used as responses in a multivariate analysis of covariance. Acutely and chronically, older age was significantly associated with lower FA (F2,65 = 8.7, p < .001, η2 = 0.2; F2,65 = 12.3, p < .001, η2 = 0.3, respectively), notably in the corpus callosum and in dorsolateral temporal structures, confirming older adults’ WM vulnerability to mTBI. Chronically, sex was associated with mean FA (F2,65 = 5.0, p = 0.01, η2 = 0.1), indicating males’ greater susceptibility to WM degradation. Acutely, a significant association was observed between CMB load and mean FA (F2,65 = 5.1, p = 0.009, η2 = 0.1), suggesting that CMBs reflect the acute severity of diffuse axonal injury. Together, these findings indicate that older age, male sex, and CMB load are risk factors for WM degeneration. Future research should examine how sex- and age-mediated WM degradation lead to cognitive decline and connectome degeneration after mTBI.

scholarly journals Plant thermal tolerance: a global synthesis for future research

2020 ◽  
Author(s):  
Sonya Geange ◽  
Pieter Arnold ◽  
Alexandra Catling ◽  
Onoriode Coast ◽  
Alicia Cook ◽  
...  
Keyword(s):  
Cold Tolerance ◽  
Land Surface ◽  
Thermal Tolerance ◽  
Extreme Temperature ◽  
Critical Time ◽  
Functional Trait ◽  
The Body ◽  
Future Research ◽  
Biogeochemical Models ◽  
Analytical Approaches

<p>Extreme temperature events are increasing in frequency and intensity across the globe. These extremes, rather than averages, drive species evolution and determine survival by profoundly changing the structure and fluidity of cell membranes, altering enzyme function, and denaturing proteins. Given not only our dependence on agricultural crops and natural vegetation, but also the role of photosynthetic processes within the carbon and hydrological cycles, it is imperative to assess the state of our understanding of the potential impacts of extreme events on plants. Scaling responses from the molecular and organ level to ecosystem function is not without challenge however. There is vast literature on plant thermal tolerance research, but the body of literature is so large, the approaches so disparate and often siloed among disciplines, that research in this field risks floundering at a critical time. We conducted a systematic review of more than 21,500 studies spanning over 100 years of research that yielded almost 1,700 included studies on the tolerance of cultivated and wild land plants to both heat and cold. Our review indicates that most studies on thermal tolerance focus on the cold tolerance of cultivated species (52%) and only a trivial percentage of studies have considered both heat and cold tolerance of any given species (~5%). Combined heat and cold tolerance are important in areas where plants are exposed to extremes of both or may be in the future. This review illustrates the global distribution and concentrations of thermal tolerance studies and the diversity of thermal tolerance methods, ranging from molecular to biochemical, physiological and physical examinations, from transgenic model plants to agricultural and horticultural crops, to natural forest trees, shrubs, and grassland herbs. Critically, it also demonstrates that methods and metrics for assessing thermal tolerance are far from standardised, such that our potential to achieve mechanistic insight and compare across species and biomes is compromised. Without reconciling these issues, the scope for incorporating this critical ecological information into vegetation elements of land surface models may be limited. To aid this, we identify priorities for achieving efficient, reliable, and repeatable research across the spectrum of plant thermal tolerance. These priorities, including meta-analytical approaches and comparative experimental work, will not only further fundamental plant science, but will prove essential next steps if we are to integrate such diverse data on a critical plant functional trait into a usable metric within biogeochemical models.</p>

scholarly journals Socio-environmental extremes: rethinking extraordinary events as outcomes of interacting biophysical and social systems

2019 ◽  
Author(s):  
Jennifer Balch ◽  
Virginia Iglesias ◽  
Anna Braswell ◽  
Matthew Rossi ◽  
Maxwell B Joseph ◽  
...  
Keyword(s):  
Extreme Events ◽  
Social Impact ◽  
Heat Waves ◽  
Social Systems ◽  
The United States ◽  
Future Research ◽  
High Exposure ◽  
Mitigation And Adaptation ◽  
Environmental Extremes ◽  
Analytical Approaches

Extreme droughts, heat waves, fires, hurricanes, floods, and landslides cause the largest losses in the United States, and globally, from natural hazards linked to weather and climate. There is evidence that the frequency of such extremes is increasing, particularly for heat waves, large fires, and intense precipitation, making better understanding of the probability and consequences of these events imperative. Further, these events are not isolated, but rather interact with each other, and with social and ecological vulnerability, to amplify impacts. Less is known about the nature and strength of these interactions. Natural and social science subfields frame extreme events with different definitions and analytical approaches, and most analyses neglect interactions and the subsequent novel extremes that can arise. Here we propose a framework for socio-environmental extremes, defined as extraordinary events that emerge from interactions among biophysical and social phenomena and have some degree of social impact. We review how different fields approach extremes as interacting phenomena and propose a synthetic framework for conceptualizing and defining extremes from both an environmental and social perspective. This approach recognizes multiple drivers and responses that yield extreme events and extreme outcomes, and reconciles the gap between understanding extremes as biophysical processes and their social underpinnings and impacts. We conclude with a future research agenda that adds clarity and direction to understanding the extreme events that matter to society. This agenda will help to identify where, when, and why communities may have high exposure and vulnerability to socio- environmental extremes—informing future mitigation and adaptation strategies.

Prediction and the aquatic sciences

2001 ◽  
Vol 58 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Michael L Pace
Keyword(s):  
Predictive Models ◽  
Probabilistic Models ◽  
Aquatic Systems ◽  
Environmental Concerns ◽  
Predictive Capability ◽  
Aquatic Science ◽  
Scientific Context ◽  
Key Features ◽  
Predictive Approaches ◽  
Aquatic Sciences

The need for prediction is now widely recognized and frequently articulated as an objective of research programs in aquatic science. This recognition is partly the legacy of earlier advocacy by the school of empirical limnologists. This school, however, presented prediction narrowly and failed to account for the diversity of predictive approaches as well to set prediction within the proper scientific context. Examples from time series analysis and probabilistic models oriented toward management provide an expanded view of approaches and prospects for prediction. The context and rationale for prediction is enhanced understanding. Thus, prediction is correctly viewed as an aid to building scientific knowledge with better understanding leading to improved predictions. Experience, however, suggests that the most effective predictive models represent condensed models of key features in aquatic systems. Prediction remains important for the future of aquatic sciences. Predictions are required in the assessment of environmental concerns and for testing scientific fundamentals. Technology is driving enormous advances in the ability to study aquatic systems. If these advances are not accompanied by improvements in predictive capability, aquatic research will have failed in delivering on promised objectives. This situation should spark discomfort in aquatic scientists and foster creative approaches toward prediction.

Ostrich Eggshell Beads in Later Stone Age Contexts

2021 ◽  
Author(s):  
Benjamin Collins
Keyword(s):  
Social Networks ◽  
Raw Material ◽  
Site Formation ◽  
Future Research ◽  
Stone Age ◽  
Later Stone Age ◽  
The Past ◽  
Eastern And Southern Africa ◽  
Analytical Approaches ◽  
Ostrich Eggshell

Ostrich eggshell (OES) beads are a common feature of Later Stone Age (LSA) archaeology throughout eastern and southern Africa and have the potential to inform on site use, cultural diversity, social networks, and site formation. However, too often OES bead assemblages have not been recorded or studied in the necessary detail to make meaningful contributions to these important questions. In this respect, and to aid future research focusing on the African LSA, OES and OES beads must be discussed in detail, beginning with a background to ostriches and their eggs and commenting on why OES is an important raw material. Then, one should consider OES beads in detail, specifically, the manufacturing process, the social context in which they were made, and how they may have been used in the past. Subsequently, the focus should be on how OES bead assemblages are analyzed, as well as archaeometric approaches to studying OES bead residues and OES bead provenance. The potential insights gained from these diverse and multidisciplinary analytical approaches, especially when combined, are then highlighted through discussing trends in OES bead research from African LSA contexts. These trends include the contribution of OES beads to understanding the complex transition from hunter-gatherers to herders, the identification of different cultural groups in the past, and identifying the presence and extent of past social networks. The final focus should be on future research directions that will benefit OES bead research, specifically more detailed approaches to understanding OES bead diversity and the expansion of experimentally derived taphonomic frameworks for identifying past human and nonhuman behaviors in OES bead assemblages. Future research should build on the growing body of detailed OES bead analyses, as they provide unique insight and a strong complement to traditional archaeological approaches to understanding past peoples, groups, and cultures during the African LSA.

scholarly journals The evolution of predictive models and tourism

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Najmeh Gharibi
Keyword(s):  
Technology Acceptance ◽  
Predictive Models ◽  
Future Research ◽  
Content Type ◽  
Technology Acceptance Models ◽  
New Directions ◽  
The Future ◽  
Future Outcomes ◽  
Tourism Services

Purpose This study aims to investigate the predictive technology acceptance models and their evolution in the tourism context. These predictive models make a knowledgeable decision about the possibility of future outcomes by analysing data. As futurists are interested in making a prediction about the likelihood of different behaviours over time, researchers of these predictive models have focussed on behaviour and predicting the intentions of users. This study proposes to demonstrate the revolution of these models and how are changed overtime. It also indicates the role of them in future studies. Design/methodology/approach By reviewing the predictive models and literature, this study looks in-depth in the process of alteration of these models. Findings This study explores the reasons of the evolution of predictive models and how they are changed. It shed light on the role of predictive models in future research and will suggest new directions for forthcoming studies. Research limitations/implications One of the main limitations of this study is that as the world is currently struggling with COVID-19 and predictability of these models will be changed. As the future is disruptive, it cannot be concluded that how these models will be altered in future. Practical implications Role of predictive behavioural models of tourists is fundamentally crucial in assessing the performance of planners and marketers of tourism services in the future. It will also vastly helps the successful development of tourism sectors, and it has practical value for all tourism stakeholders. Originality/value Few studies have focussed on the evaluation of these models and their role in future research.

Systematic Literature Review on Narratives in Organizations: Research Issues and Avenues for Future Research

2016 ◽  
Vol 20 (4) ◽  
pp. 368-379 ◽  
Author(s):  
Shalini Sahni ◽  
Chandranshu Sinha
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Narrative Analysis ◽  
Personal Narratives ◽  
Past Research ◽  
The Body ◽  
Future Research ◽  
Organization Studies ◽  
Research Issues ◽  
Analytical Approaches

Narrative as a method is an interpretive approach of sharing individual experiences and beliefs that facilitates knowledge and generates human responses. The purpose of this study is to review the body of literature available using narratology in organization studies. This article employs a systematic literature review of 186 research articles in 94 identified journals from the year 1995 to 2014 that were subsequently evaluated for analysis. The review identifies five different approaches used by the narrative researchers across disciplines—content analysis (case study method), structural analysis, oral narratives and personal narratives, their contribution and spread in organizations. This article attempts to reinforce the significance of taking narratives as a methodology in organizations by providing a systematic overview of past research works in organizational settings. The study also summarizes the analytical approaches of narrative analysis used in 186 articles, which might underpin the qualitative research and provide some practical advice for those who wish to use narrative analysis in future.

Career Goals and Internship Quality Among VET Students

2020 ◽  
pp. 089484532090226
Author(s):  
Vítor Gamboa ◽  
Maria Paula Paixão ◽  
José Tomás da Silva ◽  
Maria do Céu Taveira
Keyword(s):  
Repeated Measures ◽  
Longitudinal Design ◽  
Career Exploration ◽  
Analysis Of Covariance ◽  
Career Goals ◽  
Future Research ◽  
Career Interventions ◽  
12Th Grade ◽  
Exploration Behavior ◽  
The Relationship

Given the increased self-directedness of todays’ career environment, career goals represent to some extent the exercise of individual agency, particularly during ecological transitions (e.g., school to work). The main purpose of this study was to analyze the relationship between internship quality and career exploration behavior, considering students’ career goals content (labor market vs. higher education). Using a longitudinal design (pre- and post-internship), we conducted a study (12th grade; N = 191) that explores the relationship between perceived qualities of the internship and the different dimensions of career exploration. Analysis of variance and analysis of covariance, with repeated measures, were used to analyze the data. The results reinforce the importance of career goals, since they seem to have a differentiating effect on how the quality of the internship interacts with students’ career exploration behavior. Finally, the implications of these findings for career interventions and for future research in this area are discussed.

Needs and perspectives of odour research in the aquatic sciences

2007 ◽  
Vol 55 (5) ◽  
pp. 367-369
Author(s):  
F. Jüttner
Keyword(s):  
Secondary Metabolites ◽  
Food Web ◽  
Molecular Mechanisms ◽  
Temporal Distribution ◽  
Regulatory Mechanisms ◽  
Future Research ◽  
Spatial And Temporal Distribution ◽  
The Common ◽  
Aquatic Sciences

Over more than four decades odour research in the aquatic sciences has increasingly focused on cyanobacteria and the common odour-causing compounds, geosmin and 2-methylisoborneol. Success in future research requires a long-term perspective. Key areas for investigation are secondary metabolites and cyanobacteria, regulatory mechanisms for geosmin and other compounds' synthesis; understanding their spatial and temporal distribution (particularly relating to the food web in a habitat); and molecular mechanisms for liberation of geosmin by microorganisms.

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