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1. Assessing Postural Instability and Cybersickness Through Linear and Angular Displacement

   https://doi.org/10.1177/0018720819881254  

   Widdowson, Christopher; Becerra, Israel; Merrill, Cameron; Wang, Ranxiao_Frances; LaValle, Steven (October 2019, Human Factors: The Journal of the Human Factors and Ergonomics Society)

   ObjectiveTo examine the hypothesis that constant speed is more comfortable than variable speed profiles and may minimize cybersickness. BackgroundCurrent best practices for virtual reality (VR) content creation suggest keeping any form of acceleration as short and infrequent as possible to mitigate cybersickness. MethodsIn Experiment 1, participants experienced repetitions of simulated linear motion, and in Experiment 2, they experienced repetitions of a circular motion. Three speed profiles were tested in each experiment. Each trial lasted 2 min while standing. Cybersickness was measured using the Simulator Sickness Questionnaire (SSQ) and operationally defined in terms of total severity scores. Postural stability was measured using a Wii Balance Board and operationally defined in terms of center of pressure (COP) path length. Postural measures were decomposed into anterior-posterior and medial-lateral axes and subjected to detrended fluctuation analysis. ResultsFor both experiments, no significant differences were observed between the three speed profiles in terms of cybersickness or postural stability, and none of the baseline postural measures could predict SSQ scores for the speed profile conditions. An axis effect was observed in both experiments such that normalized COP movement was significantly greater along the anterior-posterior axis than the medial-lateral axis. ConclusionResults showed no convincing evidence to support the common belief that constant speed is more comfortable than variable speed profiles for scenarios typical of VR applications. ApplicationThe present findings offer guidelines for the design of locomotion techniques involving traversal in VR environments. 

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2. The role of gender and ethnicity in perceived public support and sense of belonging among resource management professionals in Oregon and Washington, USA

   https://doi.org/10.1002/pan3.70066  

   Jost, Laura; Rapp, Claire; Nelson, Michael_Paul (July 2025, People and Nature)

   Abstract Federal and state land agencies lack diversity at the natural resource manager level, in turn limiting the agencies' capacity for creative problem solving needed for complex and wicked environmental problems. Diverse representation is imperative to increase public support and trust in natural resource management.We used an online survey method to examine the relationship and experiences between independent demographic variables (e.g. gender, ethnicity and years worked in natural resources) and two dependent variables: (1) perceived public support and (2) sense of belonging for resource management professionals in the Pacific Northwest, USA.We find in general, that gender is associated with how one progresses through a career in natural resource management. As years in natural resource management increases, sense of belonging decreases for women and remains constant for men. Similarly, as years in natural resource management increases, perceived public support increases for men and remains constant for women.Given that ample past research suggests strong links between sustainable management and diverse perspectives, this study has implications for addressing our current and future natural resource management challenges. Read the freePlain Language Summaryfor this article on the Journal blog. 

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3. ENMeval 2.0: Redesigned for customizable and reproducible modeling of species’ niches and distributions

   https://doi.org/10.1111/2041-210X.13628  

   Kass, Jamie M.; Muscarella, Robert; Galante, Peter J.; Bohl, Corentin L.; Pinilla‐Buitrago, Gonzalo E.; Boria, Robert A.; Soley‐Guardia, Mariano; Anderson, Robert P. (June 2021, Methods in Ecology and Evolution)

   Abstract Quantitative evaluations to optimize complexity have become standard for avoiding overfitting of ecological niche models (ENMs) that estimate species’ potential geographic distributions.ENMevalwas the first R package to make such evaluations (often termed model tuning) widely accessible for the Maxent algorithm. It also provided multiple methods for partitioning occurrence data and reported various performance metrics.Requests by users, recent developments in the field, and needs for software compatibility led to a major redesign and expansion. We additionally conducted a literature review to investigate trends inENMevaluse (2015–2019).ENMeval2.0 has a new object‐oriented structure for adding other algorithms, enables customizing algorithmic settings and performance metrics, generates extensive metadata, implements a null‐model approach to quantify significance and effect sizes, and includes features to increase the breadth of analyses and visualizations. In our literature review, we found insufficient reporting of model performance and parameterization, heavy reliance on model selection with AICc and low utilization of spatial cross‐validation; we explain howENMeval2.0 can help address these issues.This redesigned and expanded version can promote progress in the field and improve the information available for decision‐making. ​ 

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4. Intraspecific correlations between growth and defence vary with resource availability and differ within and among populations

   https://doi.org/10.1111/1365-2435.13878  

   Hahn, Philip G.; Keefover‐Ring, Ken; Nguyen, Linh M. N.; Maron, John L. (July 2021, Functional Ecology)

   Abstract A paradigm in the plant defence literature is that defending against herbivores comes at a cost to growth, resulting in a growth–defence trade‐off. However, while there is strong evidence for growth–defence trade‐offs across species, evidence is mixed within species.Several mechanisms can account for this equivocal support within species, but teasing them apart requires examining growth–defence relationships both within and among populations, an approach seldom employed.We examined correlations between plant biomass (growth) and terpene production (defence) within and among populations ofMonarda fistulosa, a perennial herb. We sampled populations from Montana and Wisconsin, regions that differ in resource availability characterized by different summer precipitation and associated abiotic conditions that influence plant productivity.We found negative, neutral and positive growth–defence correlations, depending on the scale examined. Negative correlations occurred across populations originating from divergent regions, positive correlations occurred across populations originating from within the high‐resource region and neutral correlations were found within single populations.Collectively, these results challenge the general expectation of ubiquitous trade‐offs and support emerging views that resource availability (as it affects productivity) shapes the evolution of defence at different scales. A freePlain Language Summarycan be found within the Supporting Information of this article. 

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5. Community- and data-driven homelessness prevention and service delivery: optimizing for equity

   https://doi.org/10.1093/jamia/ocad052  

   Kube, Amanda R.; Das, Sanmay; Fowler, Patrick J. (April 2023, Journal of the American Medical Informatics Association)

   Abstract ObjectiveThe study tests a community- and data-driven approach to homelessness prevention. Federal policies call for efficient and equitable local responses to homelessness. However, the overwhelming demand for limited homeless assistance is challenging without empirically supported decision-making tools and raises questions of whom to serve with scarce resources. Materials and MethodsSystem-wide administrative records capture the delivery of an array of homeless services (prevention, shelter, short-term housing, supportive housing) and whether households reenter the system within 2 years. Counterfactual machine learning identifies which service most likely prevents reentry for each household. Based on community input, predictions are aggregated for subpopulations of interest (race/ethnicity, gender, families, youth, and health conditions) to generate transparent prioritization rules for whom to serve first. Simulations of households entering the system during the study period evaluate whether reallocating services based on prioritization rules compared with services-as-usual. ResultsHomelessness prevention benefited households who could access it, while differential effects exist for homeless households that partially align with community interests. Households with comorbid health conditions avoid homelessness most when provided longer-term supportive housing, and families with children fare best in short-term rentals. No additional differential effects existed for intersectional subgroups. Prioritization rules reduce community-wide homelessness in simulations. Moreover, prioritization mitigated observed reentry disparities for female and unaccompanied youth without excluding Black and families with children. DiscussionLeveraging administrative records with machine learning supplements local decision-making and enables ongoing evaluation of data- and equity-driven homeless services. ConclusionsCommunity- and data-driven prioritization rules more equitably target scarce homeless resources. 

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