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1. An overview of the hydrology of non‐perennial rivers and streams

   https://doi.org/10.1002/wat2.1504  

   Shanafield, Margaret; Bourke, Sarah A.; Zimmer, Margaret A.; Costigan, Katie H. (February 2021, WIREs Water)

   Abstract Non‐perennial rivers and streams are ubiquitous on our planet. Although several metrics have been used to statistically group or compare streamflow characteristics, there is currently no widely used definition of how many days or over what reach length surface flow must cease in order to classify a river as non‐perennial. At the same time, the breadth of climate and geographic settings for non‐perennial rivers leads to diversity in their flow regimes, such as how often or how quickly they go dry. These rivers have a rich and expanding body of literature addressing their ecologic and geomorphic features, but are often said to be ignored by hydrologists. Yet there is much we do know about their hydrology in terms of streamflow generation processes, water losses, and variability in flow. We also know that while they are prevalent in arid regions, they occur across all climate types and experience a diverse set of natural and anthropogenic controls on streamflow. Furthermore, measuring and modeling the hydrology of these rivers presents a distinct set of challenges, and there are many research directions, which still require further attention. Therefore, we present an overview of the current understanding, methodologic challenges, knowledge gaps, and research directions for hydrologic understanding of non‐perennial rivers; critical topics in light of both growing global water scarcity and ever‐changing laws and policies that dictate whether and how much environmental protection these rivers receive. This article is categorized under:Science of Water > Science of Water 

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2. Building a bridge between adaptive capacity and adaptive potential to understand responses to environmental change

   https://doi.org/10.1111/gcb.15579  

   Seaborn, Travis; Griffith, David; Kliskey, Andrew; Caudill, Christopher C. (March 2021, Global Change Biology)

   Abstract Adaptive capacity is a topic at the forefront of environmental change research with roots in both social, ecological, and evolutionary science. It is closely related to the evolutionary biology concept of adaptive potential. In this systematic literature review, we: (1) summarize the history of these topics and related fields; (2) assess relationship(s) between the concepts among disciplines and the use of the terms in climate change research, and evaluate methodologies, metrics, taxa biases, and the geographic scale of studies; and (3) provide a synthetic conceptual framework to clarify concepts. Bibliometric analyses revealed the terms have been used most frequently in conservation and evolutionary biology journals, respectively. There has been a greater growth in studies of adaptive potential than adaptive capacity since 2001, but a greater geographical extent of adaptive capacity studies. Few studies include both, and use is often superficial. Our synthesis considers adaptive potential as one process contributing to adaptive capacity of complex systems, notes “sociological” adaptive capacity definitions include actions aimed at desired outcome (i.e., policies) as a system driver whereas “biological” definitions exclude such drivers, and suggests models of adaptive capacity require integration of evolutionary and social–ecological system components. 

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3. The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study

   https://doi.org/10.1145/3543507.3583354  

   Zhang, Yu; Jin, Bowen; Zhu, Qi; Meng, Yu; Han, Jiawei (April 2023, WWW '23: Proceedings of the ACM Web Conference 2023)

   Due to the exponential growth of scientific publications on the Web, there is a pressing need to tag each paper with fine-grained topics so that researchers can track their interested fields of study rather than drowning in the whole literature. Scientific literature tagging is beyond a pure multi-label text classification task because papers on the Web are prevalently accompanied by metadata information such as venues, authors, and references, which may serve as additional signals to infer relevant tags. Although there have been studies making use of metadata in academic paper classification, their focus is often restricted to one or two scientific fields (e.g., computer science and biomedicine) and to one specific model. In this work, we systematically study the effect of metadata on scientific literature tagging across 19 fields. We select three representative multi-label classifiers (i.e., a bag-of-words model, a sequence-based model, and a pre-trained language model) and explore their performance change in scientific literature tagging when metadata are fed to the classifiers as additional features. We observe some ubiquitous patterns of metadata’s effects across all fields (e.g., venues are consistently beneficial to paper tagging in almost all cases), as well as some unique patterns in fields other than computer science and biomedicine, which are not explored in previous studies. 

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4. A Review of Human Performance Models for Prediction of Driver Behavior and Interactions With In-Vehicle Technology

   https://doi.org/10.1177/00187208221132740  

   Park, Junho; Zahabi, Maryam (October 2022, Human Factors: The Journal of the Human Factors and Ergonomics Society)

   ObjectiveThis study investigated the use of human performance modeling (HPM) approach for prediction of driver behavior and interactions with in-vehicle technology. BackgroundHPM has been applied in numerous human factors domains such as surface transportation as it can quantify and predict human performance; however, there has been no integrated literature review for predicting driver behavior and interactions with in-vehicle technology in terms of the characteristics of methods used and variables explored. MethodA systematic literature review was conducted using Compendex, Web of Science, and Google Scholar. As a result, 100 studies met the inclusion criteria and were reviewed by the authors. Model characteristics and variables were summarized to identify the research gaps and to provide a lookup table to select an appropriate method. ResultsThe findings provided information on how to select an appropriate HPM based on a combination of independent and dependent variables. The review also summarized the characteristics, limitations, applications, modeling tools, and theoretical bases of the major HPMs. ConclusionThe study provided a summary of state-of-the-art on the use of HPM to model driver behavior and use of in-vehicle technology. We provided a table that can assist researchers to find an appropriate modeling approach based on the study independent and dependent variables. ApplicationThe findings of this study can facilitate the use of HPM in surface transportation and reduce the learning time for researchers especially those with limited modeling background. 

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5. Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles

   https://doi.org/10.1177/0272989X21996328  

   Bonner, Carissa; Trevena, Lyndal J.; Gaissmaier, Wolfgang; Han, Paul K.; Okan, Yasmina; Ozanne, Elissa; Peters, Ellen; Timmermans, Daniëlle; Zikmund-Fisher, Brian J. (October 2021, Medical Decision Making)

   null (Ed.)

   Background Shared decision making requires evidence to be conveyed to the patient in a way they can easily understand and compare. Patient decision aids facilitate this process. This article reviews the current evidence for how to present numerical probabilities within patient decision aids. Methods Following the 2013 review method, we assembled a group of 9 international experts on risk communication across Australia, Germany, the Netherlands, the United Kingdom, and the United States. We expanded the topics covered in the first review to reflect emerging areas of research. Groups of 2 to 3 authors reviewed the relevant literature based on their expertise and wrote each section before review by the full authorship team. Results Of 10 topics identified, we present 5 fundamental issues in this article. Although some topics resulted in clear guidance (presenting the chance an event will occur, addressing numerical skills), other topics (context/evaluative labels, conveying uncertainty, risk over time) continue to have evolving knowledge bases. We recommend presenting numbers over a set time period with a clear denominator, using consistent formats between outcomes and interventions to enable unbiased comparisons, and interpreting the numbers for the reader to meet the needs of varying numeracy. Discussion Understanding how different numerical formats can bias risk perception will help decision aid developers communicate risks in a balanced, comprehensible manner and avoid accidental “nudging” toward a particular option. Decisions between probability formats need to consider the available evidence and user skills. The review may be useful for other areas of science communication in which unbiased presentation of probabilities is important. 

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